Cukier, R., Fortuin, C., Shuler, K., Petschek, A.,Schaibly, J.H.: Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients I. Theory. J. Chem. Phys. 59, 3873-3878 (1973)

Cukier, R.I., Levine, H.B., Shuler, K.E.: Nonlinear sensitivity analysis of multiparameter model systems. J. Phys. Chem. 81, 2365-2366 (1977)

Cukier, R.I., Levine, H.B., Shuler, K.E.: Nonlinear sensitivity analysis of multi-parameter model systems. J. Comput. Phys. 26, 1-42 (1978)

Cukier, R.I., Schaibly, J.H., Shuler, K.E.: Study of sensitivity of coupled reaction systems to uncertainties in rate coefficients 3. Analysis of approximations. J. Chem. Phys. 63, 1140-1149 (1975)

Cunha Jr, A., da Silva, L.F.F.: Assessment of a transient homogeneous reactor through in situ adaptive tabulation. J Braz. Soc. Mech. Sci. Eng. 36, 377–391 (2014)

Cuoci, A., Frassoldati, A., Faravelli, T., Ranzi, E.: A computational tool for the detailed kinetic modeling of laminar flames: application to C₂H₄/CH₄ coflow flames. Combust. Flame 160, 870–886 (2013a)

Cuoci, A., Frassoldati, A., Faravelli, T., Ranzi, E.: Numerical modeling of laminar flames with detailed kinetics based on the operator-splitting method. Energy Fuels 27, 7730–7753 (2013b)

Császár, A.G., Furtenbacher, T.: From a network of computed reaction enthalpies to atom-based thermochemistry (NEAT). Chem. Eur. J. 16, 4826-4835 (2010)

Daescu, D., Sandu, A., Carmichael, G.R.: Direct and adjoint sensitivity analysis of chemical kinetic systems with KPP: Part II - Validation and numerical experiments. Atm. Environm. 37, 5097-5114 (2003)

Dagaut, P., Cathonnet, M.: The ignition, oxidation, and combustion of kerosene: A review of experimental and kinetic modeling. Prog. Energy Combust. Sci. 32, 48-92 (2006)

Dagaut, P., Gail, S.: Chemical kinetic study of the effect of a biofuel additive on Jet-A1 combustion. J. Phys. Chem. A 111, 3992-4000 (2007)

DAKOTA: Design Analysis Kit for Optimization and Terascale Applications. In: http://www.cs.sandia.gov/DAKOTA/.

Damian, V., Sandu, A., Damian, M., Potra, F., Carmichael, G.R.: The Kinetic PreProcessor KPP - A software environment for solving chemical kinetics. Comp. Chem. Eng. 26, 1567-1579 (2002)

Danby, S.J., Echekki, T.: Proper orthogonal decomposition analysis of autoignition simulation data of nonhomogeneous hydrogen-air mixtures. Combust. Flame 144, 126-138 (2006)

Danis, J., Turányi, T.: Sensitivity analysis of bacterial chemotaxis models. Procedia Computer Science 7, 233-234 (2011)

Dano, S., Madsen, M.F., Schmidt, H., Cedersund, G.: Reduction of a biochemical model with preservation of its basic dynamic properties. Febs J. 273, 4862-4877 (2006)

Davis, M.J.: Low-dimensional manifolds in reaction−diffusion equations. 1. Fundamental aspects. J. Phys. Chem. A 110, 5235-5256 (2006a)

Davis, M.J.: Low-dimensional manifolds in reaction−diffusion equations. 2. Numerical analysis and method development. J. Phys. Chem. A 110, 5257-5272 (2006b)

Davis, M.J., Skodje, R.T.: Geometric investigation of low-dimensional manifolds in systems approaching equilibrium. J. Chem. Phys. 111, 859-874 (1999)

Davis, M.J., Skodje, R.T., Tomlin, A.S.: Global sensitivity analysis of chemical-kinetic reaction mechanisms: Construction and deconstruction of the probability density function. J. Phys. Chem. A 115, 1556-1578 (2011)

Davis, M.J., Tomlin, A.S.: Spatial dynamics of steady flames 1. Phase space structure and the dynamics of individual trajectories. J. Phys. Chem. A 112, 7768-7783 (2008a)

Davis, M.J., Tomlin, A.S.: Spatial dynamics of steady flames 2. Low-dimensional manifolds and the role of transport processes. J. Phys. Chem. A 112, 7784-7805 (2008b)

Davis, S.G., Mhadeshwar, A.B., Vlachos, D.G., Wang, H.: A new approach to response surface development for detailed gas-phase and surface reaction kinetic model optimization. Int. J. Chem. Kinet. 36, 94-106 (2004)

De Avillez Pereira, R., Baulch, D., Pilling, M.J., Robertson, S.H., Zeng, G.: Temperature and pressure dependence of the multichannel rate coefficients for the CH₃ + OH system. J. Phys. Chem. A 101, 9681-9693 (1997)

de Goey, L.P.H., van Oijen, J.A., H., B., Groot, G.R.A.: New flamelet based reduction methods: the bridge between chemical reduction techniques and flamelet methods. In: Proc. ECM 2003

de Jong, H.: Modeling and simulation of genetic regulatory systems: A literature review. J. Comput. Biol. 9, 67-103 (2002)

Degasperi, A., Gilmore, S.: Sensitivity analysis of stochastic models of bistable biochemical reactions. Lect. Notes Comput. Sci. 5016, 1-20 (2008)

Derwent, R., Hov, Ø.: Application of sensitivity and uncertainty analysis techniques to a photochemical ozone model. J. Geophys. Res. Atm. 93, 5185–5199 (1988)

Derwent, R.G.: Treating uncertainty in models of the atmospheric chemistry of nitrogen compounds. Atmos. Environ. 21, 1445-1454 (1987)

Di Carlo, P., Brune, W.H., Martinez, M., Harder, H., Lesher, R., Ren, X.R., Thornberry, T., Carroll, M.A., Young, V., Shepson, P.B., Riemer, D., Apel, E., Campbell, C.: Missing OH reactivity in a forest: Evidence for unknown reactive biogenic VOCs. Science 304(5671), 722-725 (2004)

Dickinson, R.P., Gelinas, R.J.: Sensitivity analysis of ordinary differential equation systems - Direct Method. J. Comput. Phys. 21, 123-143 (1976)

Djouad, R., Audiffren, N., Sportisse, B.: A sensitivity analysis study for RADM2 mechanism using automatic differentiation. Atmos. Environ. 37, 3029-3038 (2003a)

Djouad, R., Sportisse, B.: Partitioning techniques for reduction in chemical kinetics. APLA: an Automatic Partitioning and Lumping Algorithm. Appl. Numeric. Math. 43, 383-398 (2002)

Djouad, R., Sportisse, B., Audiffren, N.: Reduction of multiphase atmospheric chemistry. J. Atm. Chem. 46, 131-157 (2003b)

Dobrijevic, M., Carrasco, N., Hébrard, E., Pernot, P.: Epistemic bimodality and kinetic hypersensitivity in photochemical models of Titan's atmosphere. Planetary and Space Science 56, 1630-1643 (2008)

Dobrijevic, M., Hébrard, E., Plessis, S., Carrasco, N., Pernot, P., Bruno-Claeys, M.: Comparison of methods for the determination of key reactions in chemical systems: Application to Titan’s atmosphere. Adv. Space Res. 45, 77-91 (2010)

Dokoumetzidis, A., Aarons, L.: A method for robust model order reduction in pharmacokinetics. J. Pharmacokinet. Pharmacodyn. 36, 613-628 (2009a)

Dokoumetzidis, A., Aarons, L.: Proper lumping in systems biology models. IET Syst Biol. 3, 40-51 (2009b)

Douglass, A.R., Kawa, S.R.: Contrast between 1992 and 1997 high-latitude spring Halogen Occultation Experiment observations of lower stratospheric HCl. J. Geophys. Res.-Atmos. 104(D15), 18739-18754 (1999)

Drake, G.W.F. (ed.) Springer Handbook of Atomic, Molecular, and Optical Physics

Springer, (2005)

Dresch, J.M., Liu, X.Z., Arnosti, D.N., Ay, A.: Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects. BMC Systems Biology 4 (2010)

Dunker, A.M.: Efficient calculation of sensitivity coefficients for complex atmospheric models. Atm. Environ. 15, 1155-1161 (1981)

Dunker, A.M.: The Decoupled Direct Method for calculating sensitivity coefficients in chemical kinetics. J. Chem. Phys. 81, 2385-2393 (1984)

Dunker, A.M.: The reduction and parameterization of chemical mechanisms for inclusion in atmospheric reaction-transport models. Atm. Environ. 20, 479-486 (1986)

Dyer, R.S., Korakianitis, T.: Pre-integrated response map for inviscid propane-air detonation. Combust Sci Technol 179, 1327–1347 (2007)

Edelson, D.: On the solution of differential equations arising in chemical kinetics. J. Comput. Phys. 11, 455-457 (1973)

Edelson, D., Allara, D.L.: A computational analysis of the alkane pyrolysis mechanism: Sensitivity analysis of individual reaction steps. Int. J. Chem. Kinet. 12, 605–621 (1980)

Edelson, D., Thomas, V.M.: Sensitivity analysis of oscillating reactions. J. Phys. Chem. 85, 1555-1558 (1981)

Edwards, K., Edgar, T.F., Manousiouthakis, V.I.: Kinetic model reduction using genetic algorithms. Comput. Chem. Eng. 22, 239-246 (1998)

Edwards, K., Edgar, T.F., Manousiouthakis, V.I.: Reaction mechanism simplification using mixed-integer nonlinear programming. Comput. Chem. Eng. 24, 67-79 (2000)

Eggels, R.L.G.M., de Goey, L.P.H.: Mathematically reduced reaction mechanisms applied to adiabatic flat hydrogen/air flames. Combust. Flame 100, 559-570 (1995)

Elliott, L., Ingham, D.B., Kyne, A.G., Mera, N.S., Pourkashanian, M., Wilson, C.W.: Genetic algorithms for optimisation of chemical kinetics reaction mechanisms. Prog. Energy Combust. Sci. 30, 297-328 (2004)

Elliott, L., Ingham, D.B., Kyne, A.G., Mera, N.S., Pourkashanian, M., Wilson, C.W.: Reaction mechanism reduction and optimization using genetic algorithms. Indust. & Eng. Chem. Res. 44, 658-667 (2005)

Elliott, L., Ingham, D.B., Kyne, A.G., Merab, N.S., Pourkashanian, M., Whittaker, S.: Reaction mechanism reduction and optimisation for modelling aviation fuel oxidation using standard and hybrid genetic algorithms. Comput. Chem. Eng. 30, 889–900 (2006)

Elliott, S., Shen, M., Kao, C.Y.J., Turco, R.P., Jacobson, M.Z.: A streamlined family photochemistry module reproduces major nonlinearities in the global tropospheric ozone system. Comput. Chem. 20, 235-259 (1996)

Elliott, S., Turco, R.P., Jacobson, M.Z.: Tests on combined projection forward differencing integration for stiff photochemical family systems at long-time step. Comput. Chem. 17, 91-102 (1993)

Enjalbert, N., Domingo, P., Vervisch, L.: Mixing time-history effects in Large Eddy Simulation of non-premixed turbulent flames: Flow-Controlled Chemistry Tabulation. Combust. Flame 159, 336-352 (2012)

Érdi, P., Lente, G.: Stochastic chemical kinetics: Theory and (mostly) systems biological applications. Springer, Heidelberg (2014)

Érdi, P., Sipos, T., Tóth, J.: Összetett kémiai reakciók sztochasztikus szimulálása számítógéppel (Stochiastic simulation of complex chemical reactions using computer). Magyar Kémiai Folyóirat 79, 97-108 (1973)

Érdi, P., Tóth, J.: A kémiai reakció termodinamikájának sztochasztikus formulázásáról (On the stochiastic formulation of the thermodynamics of chemical reactions), vol. 41. A kémia újabb eredményei. Akadémiai Kiadó, Budapest (1976)

Érdi, P., Tóth, J.: Mathematical models of chemical reactions. Princeton Univ. Press, Princeton (1989)

Esposito, G., Chelliah, H.K.: Effect of binary diffusion and chemical kinetic parameter uncertainties in simulations of premixed and non-premixed laminar hydrogen flames. Combust. Flame 159, 3522–3529 (2012)

Everitt, B.S., Landau, S., Leese, M.: Cluster analysis. Oxford Univ. Press., (2001)

Fall, C.P., Marland, E.S., Wagner, J.M., Tyson, J.J.: Computational cell biology. Springer, (2005)

Farkas, G.: Kinetic lumping schemes. Chem. Eng. Sci. 54, 3909–3915 (1999)

Farrow, L.A., Edelson, D.: Steady-state approximation - Fact or fiction? Int. J. Chem. Kinet. 6, 787-800 (1974)

Faure, C.: An automatic differentiation platform: Odyssée. Fut. Gen. Comput. Sys. 21, 1391-1400 (2005)

Faure, H.: Good permutations for extreme discrepancy. J. Num. Theor. 42, 47-56 (1992)

Feeley, R., Frenklach, M., Onsum, M., Russi, T., Arkin, A., Packard, A.: Model discrimination using data collaboration. J. Phys. Chem. A 110, 6803-6813 (2006)

Feeley, R., Seiler, P., Packard, A., Frenklach, M.: Consistency of a reaction dataset. J. Phys. Chem. A 108, 9573-9583 (2004)

Feil, B., Kucherenko, S., Shah, N., Ieee: Comparison of Monte Carlo and Quasi Monte Carlo Sampling Methods in High Dimensional Model Representation. Simul: 2009 First International Conference on Advances in System Simulation. Ieee, New York (2009)

Feng, X.-J., Hooshangi, S., Chen, D., Li, G., Weiss, R., Rabitz, H.: Optimizing genetic circuits by global sensitivity analysis. Biophys. J. 87, 2195–2202 (2004)

Fenichel, N.: Geometric singular perturbation theory for ordinary differential equations. J. Diff. Equations 31, 53–98 (1979)

Field, R.J., Kőrös, E., Noyes, R.M.: Oscillations in chemical systems II. Thorough analysis of temporal oscillation in the bromate-cerium-malonic acid system. J. Am. Chem. Soc. 94, 8649-8664 (1972)

Field, R.J., Noyes, R.M.: Oscillations in chemical systems. IV. Limit cycle behavior in a model of a real reaction. J. Chem. Phys. 60, 1877-1884 (1974)

Fiorina, B., Gicquel, O., Vervisch, L., Carpentier, S., Darabiha, N.: Approximating the chemical structure of partially premixed and diffusion counterflow flames using FPI flamelet tabulation. Combust. Flame 140, 147-160 (2005)

Fischer, M., Riedel, U.: Combustion chemistry and parameter estimation. In: Bock, H.G., Carraro, T., Jäger, W., Körkel, S., Rannacher, R., Schlöder, J.P. (eds.) Model based parameter estimation. Theory and applications., vol. 4. pp. 207-226. Springer, Berlin Heidelberg (2013)

Fish, D.J.: The automatic generation of reduced mechanisms for tropospheric chemistry modelling. Atm. Environ. 34, 1563-1574 (2000)

Fishtik, I., Callaghan, C.A., Datta, R.: Wiring diagrams for complex reaction networks. Ind. Eng. Chem. Res. 45, 6468-6476 (2006)

Flach, E.H., Schnell, S.: Use and abuse of the quasi-steady-state approximation. IEE Proc. Syst. Biol. 153, 187–191 (2006)

FlameMaster: In: http://www.stanford.edu/group/pitsch/FlameMaster.htm http://www.itv.rwth-aachen.de/downloads/flamemaster/. (2014)

Flemming, F., Sadiki, A., Janicka, J.: LES using artificial neural networks for chemistry representation. Prog. Comput. Fluid Dynamics 5, 375-385 (2000)

FluxViewer: Visualisation tool for element fluxes. In: http://garfield.chem.elte.hu/Combustion/fluxviewer.htm.

Fotache, C.G., Kreutz, T.G., Law, C.K.: Ignition of counterflowing methane versus heated air under reduced and elevated pressures. Combust. Flame 108, 442-470 (1997)

Fournet, R., Warth, V., Glaude, P.A., Battin-Leclerc, F., Scacchi, G., Côme, G.M.: Automatic reduction of detailed mechanisms of combustion of alkanes by chemical lumping. Int. J. Chem. Kinet. 32, 36-51 (2000)

Frank-Kamenetskii, D.A.: Условия примениности метода Боденштейна в химической кинетике (Conditions for the applicability of the Bodenstein method in chemical kinetics) Ж. Физ. Хим. 14, 695-700 (1940)

Fraser, S.J.: The steady state and equilibrium approximations: a geometrical picture. J. Chem. Phys. 88, 4732–4738 (1988)

Fraser, S.J., Roussel, M.R.: Phase-plane geometries in enzyme-kinetics. Canadian Journal of Chemistry-Revue Canadienne De Chimie 72, 800-812 (1994)

Frenklach, M.: Computer modeling of infinite reaction sequences - a chemical lumping. Chem. Eng. Sci. 40, 1843-1849 (1985)

Frenklach, M.: Reduction of chemical reaction models. In: Oran, E.S., Boris, J.P. (eds.) Numerical approaches to combustion modeling. pp. 129-154. American Institute of Aeronautics and Astronautics, Inc., Washington, DC (1991)

Frenklach, M.: Transforming data into knowledge - process informatics for combustion chemistry. Proc. Combust. Inst. 31, 125-140 (2007)

Frenklach, M., Harris, S.J.: Aerosol dynamics modeling using the method of moments. J. Colloid Interface Sci. 118, 252-261 (1987)

Frenklach, M., Kailasanath, K., Oran, E.S.: Systematic development of reduced mechanisms for dynamic modeling. Prog. Astronaut. Aeronautics 105, 365-376 (1986)

Frenklach, M., Packard, A., Seiler, P., Feeley, R.: Collaborative data processing in developing predictive models of complex reaction systems. Int. J. Chem. Kinet. 36, 57-66 (2004)

Frenklach, M., Wang, H., Rabinowitz, M.J.: Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method - combustion of methane. Prog. Energy Combust. Sci. 18, 47-73 (1992)

Frouzakis, C.E., Boulouchos, K.: Analysis and reduction of the CH₄-air mechanism at lean conditions. Comb. Sci. Tech. 159, 281-303 (2000)

Frouzakis, C.E., Kevrekidis, Y.G., Lee, J., Boulouchos, K., Alonso, A.A.: Proper orthogonal decomposition of direct numerical simulation data: Data reduction and observer construction. Proc. Comb. Inst. 28, 75-81 (2000)

Fürbringer, J.-M., Roulet, C.-A.: Confidence of simulation results: put a sensitivity analysis module in your MODEL. The IEA-ECBCS Annex 23 experience of model evaluation. Energy and Buildings 30, 61-71 (1999)

Gadewar, S.B., Doherty, M.F., Malone, M.F.: A systematic method for reaction invariants and mole balances for complex chemistries. Comput. Chem. Eng. 25, 1199-1217 (2001)

Galanti, S., Jung, A.: Low-discrepancy sequences: Monte Carlo simulation of option prices. J. Deriv. 5, 63–83 (1997)

Gao, D., Stockwell, W.R., Milford, J.B.: First-order sensitivity and uncertainty analysis for a regional-scale gas-phase chemical mechanism. J. Geophys. Res. Atm. 100, 23153–23166 (1995)

Gao, D.F., Stockwell, W.R., Milford, J.B.: Global uncertainty analysis of a regional-scale gas-phase chemical mechanism. J. Geophys. Res. Atm. 101, 9107-9119 (1996)

García-Ybarra, P.L., Treviño, C.: Asymptotic analysis of the boundary layer H₂ ignition by a hot flat plate with thermal diffusion. Combust. Flame 96, 293-303 (1994)

Gear, C.W.: The automatic integration of ordinary differential equations. Numerical Mathematics 14, 176-190 (1971)

Gear, C.W., Petzold, L.R.: ODE methods for the solution of differential algebraic systems. SIAM J. Numer. Anal. 21, 716-728 (1984)

Georgakis, C., Aris, R.: Diffusion, reaction and the pseudo-steady-state hypothesis. Math. Biochem 25, 237-258 (1975)

GEPASI: http://www.gepasi.org/. In.

Gery, M.W., Whitten, G.Z., Killus, J.P., Dodge, M.C.: A photochemical kinetics mechanism for urban and regional scale computer modeling. J. Geophys. Res. D94, 12925-12956 (1989)

Gicquel, O., Darabiha, N., Thevenin, D.: Laminar premixed hydrogen/air counterflow flame simulations using Flame Prolongation of ILDM with differential diffusion. Proc. Comb. Inst. 28, 1901-1908 (2000)

Gicquel, O., Ribert, O., Ribert, G., Gicquel, O., Darabiha, N., Veynante, D.: Tabulation of complex chemistry based on self-similar behavior of laminar premixed flames. Combust. Flame 146, 649-664 (2006)

Gicquel, O., Thévenien, D., Hilka, M., Darabiha, N.: Direct numerical simulation of turbulent premixed flames using intrinsic low-dimensional manifolds. Combust. Theory Modell. 3, 479-502 (1999)

Gilbert, R.G., Luther, K., Troe, J.: Theory of thermal unimolecular reactions in the fall-off range. II. Weak collision rate constants. Berichte Bunsenges. phys. Chem. 87, 169-177 (1983)

Gillespie, D.T.: A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys. 22, 403-434 (1976)

Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81, 2340-2361 (1977)

Gillespie, D.T.: Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58, 35-55 (2007)

Glaude, P.A., Battin-LeClerc, F., Fournet, R., Warth, V., Côme, G.M., Scacchi, G.: Construction and simplification of a model for the oxidation of alkanes. Combust. Flame 122, 451-462 (2000)

Glaude, P.A., Herbinet, O., Bax, S., Biet, J., Warth, V., Battin-Leclerc, F.: Modeling of the oxidation of methyl esters-Validation for methyl hexanoate, methyl heptanoate, and methyl decanoate in a jet-stirred reactor. Combust. Flame 157, 2035-2050 (2010)

Godel, G., Domingo, P., Vervisch, L.: Tabulation of NOx chemistry for Large-Eddy Simulation of non-premixed turbulent flames. Proc. Combust. Inst. 32, 1555-1561 (2009)

Gokulakrishnan, P., Joklik, R., Viehe, D., Trettel, A., E, G.-J., Klassen, M.: Optimization of reduced kinetic models for reactive flow simulations. J. Eng. Gas Turbines Power 136, 011503 (2013)

Gokulakrishnan, P., Lawrence, A.D., McLellan, P.J., Grandmaison, E.W.: A functional-PCA approach for analyzing and reducing complex chemical mechanisms. Comput. Chem. Eng. 30, 1093-1101 (2006)

Goldsmith, C.F., Tomlin, A.S., Klippenstein, S.J.: Uncertainty propagation in the derivation of phenomenological rate coefficients from theory: A case study of n-propyl radical oxidation. Proc. Combust. Inst. 34, 177-185 (2013)

Golub, G.H., Van Loan, C.F.: Matrix computations, second ed. John Hopkins, Baltimore (1983)

Gomez, M.C., Tchijov, V.: The FEOM technique applied to a three-dimensional model of diffusion/advection of pollutants. Environ. Modell. Softw. 25, 602-606 (2010)

Goos, E., Lendvay, G.: Calculation of molecular thermochemical data and their availability in databases. In: Battin-Leclerc, F., Simmie, J.M., Blurock, E. (eds.) Cleaner combustion: Developing detailed chemical kinetic models. pp. 515-547. Springer, London (2013)

Gorban, A., Karlin, I., Zinovyev, A.: Invariant grids: method of complexity reduction in reaction networks. ComPlexUs 2, 110–127 (2004a)

Gorban, A., Karlin, I.V.: Invariant manifolds for physical and chemical kinetics. Springer, Berlin (2005)

Gorban, A.N., Karlin, I.V.: Method of invariant manifold for chemical kinetics. Chem. Eng. Sci. 58, 4751–4768 (2003)

Gorban, A.N., Karlin, I.V., Zinovyev, A.Y.: Constructive methods of invariant manifolds for kinetic problems. Phys. Rep. 396, 197-403 (2004b)

Gorban, A.N., Karlin, I.V., Zinovyev, A.Y.: Invariant grids for reaction kinetics. Physica A 333, 106-154 (2004c)

Gou, X., Chen, Z., Sun, W., Ju, Y.: A dynamic adaptive chemistry scheme with error control for combustion modeling with a large detailed mechanism. Combust. Flame 160, 225–231 (2013)

Goussis, D.A.: On the construction and use of reduced chemical kinetic mechanisms produced on the basis of given algebraic relations. J. Comput. Phys. 128, 261-273 (1996)

Goussis, D.A.: Quasi steady state and partial equilibrium approximations: their relation and their validity. Combust. Theory Modell. 16, 869-926 (2012)

Goussis, D.A., Lam, S.H.: A study of homogeneous methanol oxidation kinetics using CSP. Proc. Comb. Inst. 24, 113-120 (1992)

Goussis, D.A., Maas, U.: Model reduction for combustion chemistry. In: Echekki, T., Mastorakos, E. (eds.) Turbulent Combustion Modeling. pp. 193-220. Springer, (2011)

Goussis, D.A., Najm, H.N.: Model reduction and physical understanding of slowly oscillating processes: the circadian cycle. SIAM Multiscale Model. Simul., 5, 1297-1332 (2006)

Goussis, D.A., Skevis, G.: Nitrogen chemistry controlling steps in methane-air premixed flames. In: Bathe, K.J. (ed.) Computational Fluid and Solid Mechanics. pp. 650-653. Elsevier, Amsterdam (2005)

Goussis, D.A., Skevis, G., Mastorakos, E.: Transport-chemistry interactions in laminar premixed hydrogen-air flames near flammability limits. Proc. ECM (2005a)

Goussis, D.A., Valorani, M.: An efficient iterative algorithm for the approximation of the fast and slow dynamics of stiff systems. J. Comput. Phys. 214, 316-346 (2006)

Goussis, D.A., Valorani, M., Creta, F., Najm, H.N.: In: Bathe, K. (ed.) Computational Fluid and Solid Mechanics, vol. 2. pp. 1951-1954. Elsevier, Amsterdam (2003)

Goussis, D.A., Valorani, M., Creta, F., Najm, H.N.: Reactive and reactive-diffusive time scales in stiff reaction-diffusion systems. Progress in Computational Fluid Dynamics 5, 316-326 (2005b)

Granata, S., Faravelli, T., Ranzi, E.: A wide range kinetic modeling study of the pyrolysis and combustion of naphthenes. Combust Flame 132, 533-544 (2003)

Green, W.H.: Predictive Kinetics: A New Approach for the 21st Century. In: Guy, B.M. (ed.) Advances in Chemical Engineering, vol. 32. pp. 1-50. Academic Press, (2007)

Green, W.H., Allen, J.W., Buesser, B.A., Ashcraft, R.W., Beran, G.J., Class, C.A., Gao, C., Goldsmith, C.F., Harper, M.R., Murat Keceli, A.J., Magoon, G.R., Matheu, D.M., Merchant, S.S., Mo, J.D., Petway, S., Raman, S., Sharma, S., Song, J., Suleymanov, Y., Van Geem, K.M., Wen, J., West, R.H., Wong, A., Wong, H.-W., Yelvington, P.E., Yee, N., Yu, J.: RMG - Reaction Mechanism Generator v4.0.1. http://rmg.sourceforge.net/ (2013). Accessed March, 2014

Green, W.H., Barton, P.I., Bhattacharjee, B., Matheu, D.M., Schwer, D.A., Song, J., Sumathi, R., Carstensen, H.H., Dean, A.M., Grenda, J.M.: Computer construction of detailed chemical kinetic models for gas-phase reactors. Ind Eng Chem Res 40, 5362–5370 (2001)

Grenda, J.M., Androulakis, I.P., Dean, A.M., Green, W.H.: Application of computational kinetic mechanism generation to model the autocatalytic pyrolysis of methane. Ind. Eng. Chem. Res. 42, 1000-1010 (2003)

Griffiths, J.F.: Reduced kinetic-models and their application to practical combustion systems. Prog. Energy Combust. Sci. 21, 25-107 (1995)

GUI-HDMR: http://www.gui-hdmr.de/. In.

Gunawan, R., Cao, Y., Petzold, L., Doyle, F.J.: Sensitivity analysis of discrete stochastic systems. Biophys. J. 88, 2530-2540 (2005)

Gupta, S., Im, H.G., Valorani, M.: Classification of ignition regimes in HCCI combustion using computational singular perturbation. Proc. Combust. Inst. 33, 2991-2999 (2011)

Gutenkunst, R.N., Waterfall, J.J., Casey, F.P., Brown, K.S., Myers, C.R., Sethna, J.P.: Universally sloppy parameter sensitivities in systems biology models. PLoS Comput. Biol. 3, e189 (2007)

Hadjinicolaou, M., Goussis, D.A.: Asymptotic solution of stiff PDEs with the CSP method: The reaction diffusion equation. SIAM J. Sci. Comput. 20, 781-810 (1998)

Hakka, M.H., Bennadji, H., Biet, J., Yahyaoui, M., Sirjean, B., Warth, V., Coniglio, L., Herbinet, O., Glaude, P.A., Billaud, F., Battin-Leclerc, F.: Oxidation of methyl and ethyl butanoates. Int. J. Chem. Kinet. 42, 226-252 (2010)

Halton, J.H.: On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals. Numerische Mathematik 2, 84-90 (1960)

Hannemann-Tamás, R., Gábor, A., Szederkényi, G., Hangos, K.M.: Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming. Comput. Math. Appl. (2014)

Hansen, N., Harper, M.R., Green, W.H.: High-temperature oxidation chemistry of n-butanol – experiments in low-pressure premixed flames and detailed kinetic modeling. PCCP 13, 20262–20274 (2011)

Hansen, N., Merchant, S.S., Harper, M.R., Green, W.H.: The predictive capability of an automatically generated combustion chemistry mechanism: Chemical structures of premixed iso-butanol flames. Combust. Flame 160, 2343-2351 (2013)

Happel, J., Sellers, P.H.: Multiple reaction mechanisms in catalysis. Ind. Eng. Chem. Fundam. 21, 67–76 (1982)

Harper, M.R., Van Geem, K.M., Pyl, S.P., Marin, G.B., Green, W.H.: Comprehensive reaction mechanism for n-butanol pyrolysis and combustion. Combust. Flame 158, 16–41 (2011)

Harris, S.D., Elliott, L., Ingham, D.B., Pourkashanian, M., Wilson, C.W.: The optimisation of reaction rate parameters for chemical kinetic modelling of combustion using genetic algorithms. Computer Methods in Applied Mechanics and Engineering 190, 1065-1090 (2000)

Harstad, K., Bellan, J.: A model of reduced oxidation kinetics using constituents and species: Iso-octane and its mixtures with n-pentane, iso-hexane and n-heptane. Combust. Flame 157, 2184-2197 (2010a)

Harstad, K.G., Bellan, J.: A model of reduced kinetics for alkane oxidation using constituents and species: Proof of concept for n-heptane. Combust. Flame 157, 1594–1609 (2010b)

He, K., Androulakis, I.P., Ierapetritou, M.G.: On-the-fly reduction of kinetic mechanisms using element flux analysis. Chem. Eng. Sci. 65, 1173–1184 (2010)

He, K., Ierapetritou, M.G., Androulakis, I.P.: A graph-based approach to developing adaptive representations of complex reaction mechanisms. Combust. Flame 155, 585-604 (2008)

He, S., Carmichael, G.R., Sandu, A., Hotchkiss, B., Damian-Iordache, V.: Application of ADIFOR for air pollution model sensitivity studies. Environ. Model. Soft. 15, 549-557 (2000)

Heard, A.C., Pilling, M.J., Tomlin, A.S.: Mechanism reduction techniques applied to tropospheric chemistry. Atm. Environ. 32, 1059-1073 (1998)

Hébrard, E., Dobrijevic, M., Pernot, P., Carrasco, N., Bergeat, A., Hickson, K.M., Canosa, A., Le Picard, S.D., Sims, I.R.: How measurements of rate coefficients at low temperature increase the predictivity of photochemical models of Titan’s atmosphere. . J. Phys. Chem. A 113, 11227–11237 (2009)

Heineken, F.G., Tsuchiya, H.M., Aris, R.: On the mathematical status of the pseudo-steady-state hypothesis of biochemical kinetics. Math. Biosci. 1, 95-113 (1967)

Helton, J.C., Davis, F.J.: Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliab. Engng Syst. Safety 81, 23–69 (2003)

Helton, J.C., Johnson, J.D., Sallaberry, C.J., Storlie, C.B.: Survey of sampling-based methods for uncertainty and sensitivity analysis. Reliab. Eng. Syst. Saf. 91, 1175-1209 (2006)

Herbinet, O., Pitz, W., Westbrook, C.K.: Detailed chemical kinetic mechanism for the oxidation of biodiesel fuels blend surrogate. Combust. Flame 157, 893-908 (2010)

Herbinet, O., Pitz, W.J., Westbrook, C.K.: Detailed chemical kinetic oxidation mechanism for a biodiesel surrogate Combust. Flame 154, 507-528 ( 2008)

Hernández, J.J., Ballesteros, R., Sanz-Argent, J.: Reduction of kinetic mechanisms for fuel oxidation through genetic algorithms. Math. Comput. Modelling 52, 1185-1193 (2010)

Hessler, J.P., Ogren, P.J.: Correlation analysis of complex kinetic systems: A new scheme for utilizing sensitivity coefficients. J. Chem. Phys. 97, 6249 (1992)

Hesstvedt, E., Hov, O., Isaksen, I.S.A.: Quasi-steady-state approximations in air-pollution modeling - comparison of two numerical schemes for oxidant prediction. Int. J. Chem. Kinet. 10, 971-994 (1978)

Higham, N.J.: Accuracy and Stability of Numerical Algorithms. SIAM, Philadelphia (1996)

Hiremath, V., Pope, S.B.: A study of the rate-controlled constrained-equilibrium dimension reduction method and its different implementations. Combust. Theory Model. 17, 260-293 (2013)

Hiremath, V., Ren, Z.Y., Pope, S.B.: A greedy algorithm for species selection in dimension reduction of combustion chemistry. Combust. Theory Model. 14, 619-652 (2010)

Hiremath, V., Ren, Z.Y., Pope, S.B.: Combined dimension reduction and tabulation strategy using ISAT-RCCE-GALI for the efficient implementation of combustion chemistry. Combust. Flame 158, 2113-2127 (2011)

Ho, T.C., Aris, R.: On apparent second-order kinetics. AIChE J. 33, 1050-1051 (1987)

Hoare, A., Regan, D.G., Wilson, D.P.: Sampling and sensitivity analyses tools (SaSAT) for computational modelling. Theor. Biol. Med. Modelling 5, 4 (2008)

Homma, T., Saltelli, A.: Importance measures in global sensitivity analysis of nonlinear models. Reliability Engineering Syst. Safety 52, 1–17 (1996)

Hong, Z., Davidson, D.F., Hanson, R.K.: An improved H₂/O₂ mechanism based on recent shock tube/laser absorption measurements Combust. Flame 158, 633-644 (2011)

Honnet, S., Seshadri, K., Niemann, U., Peters, N.: A surrogate fuel for kerosene. Proc. Combust. Inst. 32, 485-492 (2009)

Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P., Kummer, U.: COPASI — a COmplex PAthway SImulator. Bioinformatics 22, 3067-3074 (2006)

Horiuti, J.: Theory of reaction rates as based on the stoichiometric number concept. Annals New York Acad. Sci. 213, 5-30 (1973)

Hovland, P.D., Norris, B., Mills Strout, M., Bhowmick, S., Utke, J.: Sensitivity analysis and design optimization through automatic differentiation. J. Phys. Conf. Ser. 16, 466-470 (2005)

Hu, D., Braun-Unkhoff, M., Frank, P.: Modeling study on soot formation at high pressures. Combust. Sci. Technol. 149, 79-94 (1999)

Huang, H., Fairweather, M., Griffiths, J.F., Tomlin, A.S., Brad, R.B.: A systematic lumping approach for the reduction of comprehensive kinetic models. Proc. Combust. Inst. 30, 1309-1316 (2005)

Hughes, K.J., Fairweather, M., Griffiths, J.F., Porter, R., Tomlin, A.S.: The application of the QSSA via reaction lumping for the reduction of complex hydrocarbon oxidation mechanisms. Proc. Combust. Inst. 32, 543-551 (2009)

Hughes, K.J., Griffiths, J.F., Fairweather, M., Tomlin, A.S.: Evaluation of models for the low temperature combustion of alkanes through interpretation of pressure-temperature ignition diagrams. PCCP 8, 3197-3210 (2006)

Hughes, K.J., Tomlin, A.S., Hampartsoumian, E., Nimmo, W., Zsély, I.G., Ujvári, M., Turányi, T., Clague, A.R., Pilling, M.J.: An investigation of important gas-phase reactions of nitrogenous species from the simulation of experimental measurements in combustion systems. Combust. Flame 124, 573-589 (2001a)

Hughes, K.J., Turányi, T., Clague, A.R., Pilling, M.J.: Development and testing of a comprehensive chemical mechanism for the oxidation of methane. Int. J. Chem. Kinet. 33, 513-538 (2001b)

Hwang, J.T.: Nonlinear sensitivity analysis in chemical kinetics. Proc. Natl. Sci. Council B. ROC 6, 20-29 (1982)

Hwang, J.T., Dougherty, E.P., Rabitz, S., Rabitz, H.: Greens Function Method of sensitivity analysis in chemical kinetics. J. Chem. Phys. 69, 5180-5191 (1978)

Ihekwaba, A.E., Broomhead, D.S., Grimley, R.L., Benson, N., Kell, D.B.: Sensitivity analysis of parameters controlling oscillatory signalling in the NF-kB pathway: the roles of IKK and IkBa. Syst Biol 1, 93-103 (2004)

Ihme, M., Marsden, A.L., Pitsch, H.: Generation of optimal artificial neural networks using a pattern search algorithm: Application to approximation of chemical systems. Neural Computation 20, 573-601 (2008)

Ihme, M., Schmitt, C., Pitsch, H.: Optimal artificial neural networks and tabulation methods for chemistry representation in LES of a bluff-body swirl-stabilized flame. Proc. Combust. Inst. 32, 1527-1535 (2009)

Imbert, B., Lafosse, F., Catoire, L., Paillard, C.-É., Khasainov, B.: Formulation reproducing the ignition delays simulated by a detailed mechanism: Application to n-heptane combustion. Combust. Flame 155, 380-408 (2008)

Ingalls, B.P.: Autonomously oscillating biochemical systems: Parametric sensitivities of extrema and period. IEE Systems Biology 1, 62–70 (2004)

Ingber, L., Rosen, B.: Genetic algorithms and very fast simulated re-annealing - A comparison. Math. Comput. Modell. 16, 87-100 (1992)

Ingham, T., Goddard, A., Whalley, L.K., Furneaux, K.L., Edwards, P.M., Seal, C.P., Self, D.E., Johnson, G.P., Read, K.A., Lee, J.D., Heard, D.E.: A flow-tube based laser-induced fluorescence instrument to measure OH reactivity in the troposphere. Atmospheric Measurement Techniques 2, 465-477 (2009)

Ishmurzin, A., Schramm, B., Lebiedz, D., Warnatz, J.: Reduction of detailed reaction mechanisms for large hydrocarbons combustion by the ILDM method. In: Proc. ECM 2003

Ismail, H.M., Ng, H.K., Gan, S., Lucchini, T., Angelo Onorati, A.: Development of a reduced biodiesel combustion kinetics mechanism for CFD modelling of a light-duty diesel engine. Fuel 106, 388–400 (2013)

Isukapalli, S.S., Roy, A., Georgopoulos, P.G.: Efficient sensitivity/uncertainty analysis using the combined stochastic response surface method and automated differentiation: application to environmental and biological systems. Risk Anal. 20, 591-602 (2000)

Jacobson, M.Z.: Fundamentals of atmospheric modeling 2nd edition ed. Cambridge University Press, (2005)

Jakeman, A.J., Letcher, R.A., Norton, J.P.: Ten iterative steps in development and evaluation of environmental models. Environ. Modell. Softw. 21, 602-614 (2006)

Jalan, A., West, R.H., H., G.W.: An extensible framework for capturing solvent effects in computer generated kinetic models. J Phys Chem B 117, 2955-2970 (2013)

James, S., Anand, M.S., Razdan, M.K., Pope, S.B.: In situ detailed chemistry calculations in combustor flow analyses. J. Eng. Gas. Turbines Power-Trans. ASME 123, 747-756 (2001)

Jasper, A.W., Klippenstein, S.J., Harding, L.B., Ruscic, B.: Kinetics of the reaction of methyl radical with hydroxyl radical and methanol decomposition. J. Phys. Chem. A 111, 3932−3950 (2007)

Jay, L.O., Sandu, A., Potra, F.A., Carmichael, G.R.: Improved quasi-steady-state-approximation methods for atmospheric chemistry integration. SIAM J. Sci. Comput. 18, 182-202 (1997)

Jay, S., Colin, O.: A variable volume approach of tabulated detailed chemistry and its applications to multidimensional engine simulations. Proc. Combust. Inst. 33, 3065-3072 (2011)

JCGM: International vocabulary of metrology - Basic and general concepts and associated terms (VIM). In: http://www.bipm.org/. (2008)

Jenkin, M.E., Watson, L.A., Utembe, S.R., Shallcross, D.E.: A Common Representative Intermediates (CRI) mechanism for VOC degradation. Part 1: Gas phase mechanism development. Atmospheric Environment 42, 7185-7195 (2008)

Jiang, Y., Qiu, R.: Reduction of large kinetic mechanisms of hydrocarbon fuels with directed relation graph. Acta Physico-Chimica Sinica 25, 1019-1025 (2009)

Johnson, B.G., Corio, P.L.: Computer construction of reaction mechnisms. J. Phys. Chem. 97, 12100–12105 (1993)

Johnston, H., Kinnison, D.: Methane photooxidation in the atmosphere: Contrast between two methods of analysis. J. Geophys. Res. 103, 21967–21984 (1998)

Jones, W.P., Rigopoulos, S.: Rate-controlled constrained equilibrium: Formulation and application to nonpremixed laminar flames. Combust. Flame 142, 223-234 (2005a)

Jones, W.P., Rigopoulos, S.: Reduction of comprehensive chemistry via constraint potentials. Proc. Combust. Inst. 30, 1325-1331 (2005b)

Jones, W.P., Rigopoulos, S.: Reduced chemistry for hydrogen and methanol premixed flames via RCCE. Combust. Theory Model. 11, 755-780 (2007)

Kalachev, L.V., Field, R.J.: Reduction of a model describing ozone oscillations in the troposphere: Example of an algorithmic approach to model reduction in atmospheric chemistry. J. Atm. Chem. 39, 65-93 (2001)

Kanehisa, M., Goto, S.: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 28, 27-30 (2000)

Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., Hirakawa, M.: KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Research 38(suppl 1), D355-D360 (2010)

Karp, P.D., Riley, M., Saier, M., Paulsen, I.T., Paley, S.M., Pellegrini-Toole, A.: The EcoCyc and MetaCyc databases. Nucleic Acids Research 28, 56-59 (2000)

Katare, S., Bhan, A., Caruthers, J.M., Delgass, W.N., Venkatasubramanian, V.: A hybrid genetic algorithm for efficient parameter estimation of large kinetic models. Comput. Chem. Eng. 28, 2569–2581 (2004)

Kazakov, A., Frenklach, M.: Dynamic modeling of soot particle coagulation and aggregation: Implementation with the method of moments and application to high-pressure laminar premixed flames. Combust. Flame 114, 484-501 (1998)

Keating, S.M., Bornstein, B.J., Finney, A., Hucka, M.: SBMLToolbox: an SBML toolbox for MATLAB users. Bioinformatics 22, 1275–1277 (2006)

Keck, J.C.: Rate-controlled constrained-equilibrium theory of chemical-reactions in complex-systems. Prog. Energy Combust. Sci. 16, 125-154 (1990)

Keck, J.C., Gillespie, D.: Rate-controlled partial-equilibrium method for treating reacting gas-mixtures. Combust. Flame 17, 237–248 (1971)

Kee, R.J., Grcar, J.F., Smooke, M.D., Miller, J.A.: PREMIX: A FORTRAN program for modeling steady laminar one-dimensional premixed flames. In. Sandia National Laboratories, (1985)

Kee, R.J., Rupley, F.M., Miller, J.A.: CHEMKIN-II: A FORTRAN chemical kinetics package for the analysis of gas-phase chemical kinetics. In. Sandia National Laboratories, (1989)

Kelley, A.P., Liu, W., Xin, Y.X., Smallbone, A.J., Law, C.K.: Laminar flame speeds, non-premixed stagnation ignition, and reduced mechanisms in the oxidation of iso-octane. Proc. Combust. Inst. 33, 501-508 (2011)

Kent, E., Neumann, S., Kummer, U., Mendes, P.: What can we learn from global sensitivity analysis of biochemical systems? PLoS ONE 8 (2013)

Kerdouci, J., Picquet-Varrault, B., Doussin, J.F.: Structure-activity relationship for the gas-phase reactions of NO3 radical with organic compounds: Update and extension to aldehydes. Atmos. Environ. 84, 363-372 (2014)

KINAL: program package for the simulation and analysis of reaction mechanisms. In: http://garfield.chem.elte.hu/Combustion/kinal.htm.

KINALC: CHEMKIN based program for KInetic aNALysis. In: http://garfield.chem.elte.hu/Combustion/kinalc.htm.

Kintecus: http://www.kintecus.com/. In. (2014)

Kiparissides, A., Kucherenko, S.S., Mantalaris, A., Pistikopoulos, E.N.: Global sensitivity analysis challenges in biological systems modeling. Ind. Eng. Chem. Res. 48, 7168-7180 (2009)

Kiparissides, A., Rodriguez-Fernandez, M., Kucherenko, S., Mantalaris, A., Pistikopoulos, E.: Application of global sensitivity analysis to biological models. In: Braunschweig, B., Joulia, X. (eds.) 18th European Symposium on Computer Aided Process Engineering, vol. 25. Computer-Aided Chemical Engineering, pp. 689-694. Elsevier Science Bv, Amsterdam (2008)

Kirchner, F.: The chemical mechanism generation programme CHEMATA--Part 1: The programme and first applications. Atm. Environ. 39, 1143-1159 (2005)

Kirkpatrick, S.: Optimization by simulated annealing. Science 220, 671-681 (1983)

Klamt, S., Stelling, J., Ginkel, M., Gilles, E.D.: FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics 19, 261-269 (2003)

Klipp, E., Herwig, R., Kowald, A., Wierling, C., Lehrach, H.: Systems biology in practice. Wiley-VCH, Weinheim (2005)

Klipp, E., Liebermeister, W., Wierling, C., Kowland, A., Lehrach, H., Herwig, R.: Systems biology: a textbook. Wiley-VCH Verlag, (2009)

Klippenstein, S.J., Harding, L.B., Davis, M.J., Tomlin, A.S., Skodje, R.T.: Uncertainty driven theoretical kinetics studies for CH₃OH ignition: HO₂+CH₃OH and O₂+CH₃OH. Proc. Combust. Inst. 33, 351-357 (2011)

Klonowski, W.: Simplifying principles for chemical and enzyme reaction kinetics. Biophys. Chem. 18, 73-87 (1983)

Knio, O.M., Najm, H.N., Wyckoff, P.S.: A semi-implicit numerical scheme for reacting flow II. Stiff, operator-split formulation. J. Comput. Phys. 154, 428-467 (1999)

Konnov, A.A.: Remaining uncertainties in the kinetic mechanism of hydrogen combustion. Combust. Flame 152, 507-528 (2008)

Kooshkbaghi, M., Frouzakis, C.E., Boulouchos, K., Karlin, I.V.: Entropy production analysis for mechanism reduction. Combust. Flame 161, 1507–1515 (2014)

Kourdis, P.D., Bellan, J.: Heavy-alkane oxidation kinetic-mechanism reduction using dominant dynamic variables, self similarity and chemistry tabulation. Combust. Flame 161, 1196–1223 (2014)

Kourdis, P.D., Goussis, D.A.: Glycolysis in saccharomyces cerevisiae: Algorithmic exploration of robustness and origin of oscillations. Math. Biosci. 243, 190–214 (2013)

Kourdis, P.D., Steuer, R., Goussis, D.A.: Physical understanding of complex multiscale biochemical models via algorithmic simplification: Glycolysis in Saccharomyces cerevisiae. Physica D 239, 1798-1817 (2010)

Kouri, T.M., Crabtree, J.D., Huynh, L., Dean, A.M., Mehta, D.P.: RCARM: Reaction classification using automated reaction mapping. Int J Chem Kinet 45, 125–139 (2013)

Kovács, K., Vízvári, B., Riedel, M., Tóth, J.: Decomposition of the permanganate/oxalic acid overall reaction to elementary steps based on integer programming theory. PCCP 6, 1236-1242 (2004)

Kovacs, T.A., Brune, W.H.: Total OH loss rate measurement. J. Atmos. Chem. 39, 105-122 (2001)

König, K., Maas, U.: On-demand generation of reduced mechanisms based on hierarchically extended intrinsic low-dimensional manifolds in generalized coordinates. Proc Combust Inst. 32, 553-560 (2009)

Könnyű, B., Sadiq, S.K., Turányi, T., Hírmondó, R., Müller, B., Kräusslich, H.G., Coveney, P.V., Müller, V.: Gag-Pol Processing during HIV-1 virion maturation: a systems biology approach. PLoS Comput. Biol. 9, e1003103 (2013)

KPP: Kinetic Preprocessor. In: http://people.cs.vt.edu/~asandu/Software/Kpp/.

Kraft, M., Wagner, W.: An improved stochastic algorithm for temperature-dependent homogeneous gas phase reactions. J. Comput. Phys. 185, 139-157 (2003)

Kramer, M.A., Calo, J.M., Rabitz, H.: An improved computational method for sensitivity analysis - Greens Function Method with AIM. Appl. Math. Modell. 5, 432-441 (1981)

Kramer, M.A., Rabitz, H., Calo, J.M., Kee, R.J.: Sensitivity analysis in chemical kinetics - recent developments and computational comparisons. Int. J. Chem. Kinet. 16, 559-578 (1984)

Kremling, A., Fischer, S., Sauter, T., Bettenbrock, K., Gilles, E.D.: Time hierarchies in the Escherichia coli carbohydrate uptake and metabolism. . Biosystems 73, 57-71 (2004)

Kucherenko, S.: Application of global sensitivity indices for measuring the effectiveness of quasi-Monte Carlo methods and parameter estimation. . In: Fifth International Conference on Sensitivity Analysis of Model Output, Budapest 2007, pp. 35–36

Kucherenko, S.: SOBOLHDMR: A general-purpose modeling software. In: Polizzi, K.M., Kontoravdi, C. (eds.) Synthetic Biology, vol. 1073. Methods in Molecular Biology, pp. 191-224. Humana Press Inc, Totowa (2013)

Kucherenko, S., Tarantola, S., Annoni, P.: Estimation of global sensitivity indices for models with dependent variables. Comput. Phys. Commun. 183, 937-946 (2012)

Kumar, A., Mazumder, S.: Adaptation and application of the in situ Adaptive Tabulation (ISAT) procedure to reacting flow calculations with complex surface chemistry. Comput. Chem. Eng. 35, 1317-1327 (2011)

Kumar, K., Sung, C.J.: Autoignition of methanol: Experiments and computations. Int. J. Chem. Kinet. 43, 175-184 (2011)

Kurtz, T.G.: The relationship between stochastic and deterministic models of chemical reactions. J. Chem. Phys. 57, 2976-2978 (1972)

Kwok, E.S.C., Atkinson, R.: Estimation of hydroxyl radical reaction rate constants for gas-phase organic compounds using a structure-reactivity relationship: An update. Atmos. Environ. 29, 1685-1695 (1995)

Lam, S.H.: Using CSP to understand complex chemical kinetics. Combust. Sci. Technol. 89, 375-404 (1993)

Lam, S.H.: Reduced chemistry-diffusion coupling. Combust. Sci. Technol. 179, 767–786 (2006)

Lam, S.H.: Model reductions with special CSP data. Combust. Flame 160, 2707–2711 (2013)

Lam, S.H., Goussis, D.A.: Understanding complex chemical kinetics with computational singular perturbation. Proc. Combust. Inst. 22, 931-941 (1988)

Lam, S.H., Goussis, D.A.: Conventional asymptotics and computational singular perturbation for simplified kinetics modeling. In: Smooke, M.O. (ed.) Reduced kinetic mechanisms and asymptotic approximations for methane-air flames, vol. 384. Springer Lecture Notes, pp. 227–242. Springer, Berlin (1991)

Lam, S.H., Goussis, D.A.: The CSP method for simplifying kinetics. Int. J. Chem. Kinet. 26, 461-486 (1994)

laminarSMOKE web site. http://www.opensmoke.polimi.it/ (2014).

Lamouroux, J., Ihme, M., Fiorina, B., Gicquel, O.: Tabulated chemistry approach for diluted combustion regimes with internal recirculation and heat losses. Combust. Flame 161, 2120–2136 (2014)

Larter, R.: Sensitivity analysis of autonomous oscillators. Separation of secular terms and determination of structural stability. J. Phys. Chem. 87, 3114-3121 (1983)

Law, C.K.: Combustion at a crossroads: Status and prospects. Proc. Combust Inst. 31, 1-29 (2007)

Law, C.K., Sung, C.J., Wang, H., Lu, T.F.: Development of comprehensive detailed and reduced reaction mechanisms for combustion modeling. AIAA Journal 41, 1629-1646 (2003)

Laxminarasimhan, C.S., Verma, R.P., Ramachandran, P.A.: Continuous lumping model for simulation of hydrocracking. AIChE J. 42, 2645-2653. (1996)

Lebiedz, D.: Computing minimal entropy production trajectories: An approach to model reduction in chemical kinetics. J. Chem. Phys. 120, 6890–6897 (2004)

Lee, C.H., Othmer, H.G.: A multi-time-scale analysis of chemical reaction networks: I. Deterministic systems. J. Math. Biol. 60, 387–450 (2010)

Lee, J.C., Najm, H.N., Lefantzi, S., Ray, J., Frenklach, M., Valorani, M., Goussis, D.: On chain branching and its role in homogeneous ignition and premixed flame propagation. In: Bathe, K. (ed.) Computational Fluid and Solid Mechanics. pp. 717–720. Elsevier Science, (2005)

Lee, J.C., Najm, H.N., Lefantzi, S., Ray, J., Frenklach, M., Valorani, M., Goussis, D.: A CSP and tabulation-based adaptive chemistry model. Combust. Theory Model. 11, 73–102. (2007)

Lee, J.D., Young, J.C., Read, K.A., Hamilton, J.F., Hopkins, J.R., Lewis, A.C., Bandy, B.J., Davey, J., Edwards, P., Ingham, T., Self, D.E., Smith, S.C., Pilling, M.J., Heard, D.E.: Measurement and calculation of OH reactivity at a United Kingdom coastal site. J. Atm. Chem. 64, 53-76 (2009)

Lee, J.M., Gianchandani, E.P., Papin, J.A.: Flux balance analysis in the era of metabolomics. Briefings in Bioinformatics 7, 140-150 (2006)

Lehmann, R.: Determination of dominant pathways in chemical reaction systems: An algorithm and its application to stratospheric chemistry. J. Atmos. Chem. 41, 297–314 (2002)

Lehmann, R.: An algorithm for the determination of all significant pathways in chemical reaction systems. J. Atm. Chem. 47, 45-78 (2004)

Leloup, J.-C., Goldbeter, A.: Modeling the mammmalian circadian clock: Sensitivity analysis and multiplicity of oscillatory mechanisms. . J Theor. Biol. 230, 541–562 (2004)

Li, B., Li, B.: Quasi-Steady-State Laws in reversible model of enzyme kinetics. J Math Chem 51, 2668–2686 (2013)

Li, B., Shen, Y., Li, B.: Quasi-Steady State Laws in enzyme kinetics. J. Phys. Chem. A 112, 2311–2321 (2008a)

Li, G., Rabitz, H.: A general analysis of exact lumping in chemical kinetics. Chem. Eng. Sci. 44, 1413-1430 (1989)

Li, G., Rabitz, H.: Determination of constrained lumping schemes for nonisothermal first-order reaction systems. Chem. Eng. Sci. 46, 583-596 (1991)

Li, G., Rabitz, H.: A special singular perturbation methods for kinetic model reduction: With application to an H₂/O₂ oxidation model. J. Chem. Phys. 105, 4065-4075 (1996a)

Li, G., Rabitz, H.: Reduced kinetic equations of a CO/H₂/air oxidation model by a special perturbation method. Chem. Eng. Sci. 52, 4317-4327 (1997)

Li, G., Rabitz, H., Tóth, J.: A general analysis of exact nonlinear lumping in chemical kinetics. Chem. Eng. Sci. 49, 343-361 (1994a)

Li, G., Rosenthal, C., Rabitz, H.: High dimensional model representations. J. Phys. Chem. A 105, 7765 -7777. (2001)

Li, G., Tomlin, A.S., Rabitz, H., Tóth, J.: Determination of approximate lumping schemes by a singular perturbation method. J. Chem. Phys. 99, 3562-3574 (1993)

Li, G., Tomlin, A.S., Rabitz, H., Tóth, J.: A general analysis of approximate nonlinear lumping in chemical kinetics. I. Unconstrained lumping. J. Chem. Phys. 101, 1172-1187 (1994b)

Li, G., Tomlin, A.S., Rabitz, H., Tóth, J.: A general analysis of approximate nonlinear lumping in chemical kinetics. II. Constrained lumping. J. Chem. Phys. 101, 1188-1201 (1994c)

Li, G., Wang, S.-W., Rabitz, H.: Practical approaches to construct RS-HDMR component functions. J. Phys. Chem. A 106, 8721-8733 (2002a)

Li, G., Wang, S.-W., Rabitz, H., Wang, S., Jaffé, P.: Global uncertainty assessments by high dimensional model representations (HDMR). Chem. Eng. Sci. 57, 4445-4460 (2002b)

Li, G.Y., Rabitz, H.: A lumped model for H₂/O₂ oxidation in the oscillatory regime. J. Chem. Phys. 102, 7006-7016 (1995)

Li, G.Y., Rabitz, H.: Combined symbolic and numerical approach to constrained nonlinear lumping - With application to an H₂/O₂ oxidation model. Chem. Eng. Sci. 51, 4801-4816 (1996b)

Li, G.Y., Rabitz, H.: General formulation of HDMR component functions with independent and correlated variables. J. Math. Chem. 50, 99-130 (2012)

Li, G.Y., Rabitz, H., Hu, J.S., Chen, Z., Ju, Y.: Regularized random-sampling high dimensional model representation (RS-HDMR). J. Math. Chem. 43, 1207–1232 (2008b)

Li, G.Y., Rabitz, H., Yelvington, P.E., Oluwole, O.O., Bacon, F., Kolb, C.E., Schoendorf, J.: Global sensitivity analysis for systems with independent and/or correlated inputs. J. Phys. Chem. A 114, 6022-6032 (2010)

Li, H., Cao, Y., Petzold, L.R., Gillespie, D.T.: Algorithms and software for stochastic simulation of biochemical reacting systems. Biotechnol Prog. 24, 56-61 (2008c)

Li, K., Crittenden, J.: Computerized pathway elucidation for hydroxyl radical-induced chain reaction mechanisms in aqueous phase advanced oxidation processes. Environm. Sci. Technol. 43, 2831-2837 (2009)

Liang, L., Stevens, J.G., Farrell, J.T.: A dynamic adaptive chemistry scheme for reactive flow computations. Proc. Combust. Inst. 32, 527-534 (2009a)

Liang, L., Stevens, J.G., Raman, S., Farrell, J.T.: The use of dynamic adaptive chemistry in combustion simulation of gasoline surrogate fuels. Combust. Flame 156, 1493-1502 (2009b)

Liao, J.C., Lightfoot, E.N.: Lumping analysis of biochemical reaction systems with time scale separation. Biotechnol. Bioeng. 31, 869-879 (1988)

Libby, P.A., Bray, K.N.C.: Implications of the laminar flamelet model in premixed turbulent combustion. Combust. Flame 39, 33-41 (1980)

Liew, S.K., Bray, K.N.C., Moss, J.B.: A flamelet model of turbulent non-premixed combustion. Combust. Sci. Technol. 27, 69-73 (1981)

Lindemann, F.A., Arrhenius, S., Langmuir, I., Dhar, N.R., Perrin, J., McC. Lewis, W.C.: Discussion on “the radiation theory of chemical action”. Trans. Faraday Soc. 17, 598-606 (1922)

Liu, B.J.D., Pope, S.B.: The performance of in situ adaptive tabulation in computations of turbulent flames. Combust. Theory Model. 9, 549-568 (2005)

Liu, G., Swihart, M.T., Neelamegham, S.: Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling. Bioinformatics 21, 1194–1202 (2005)

Liu, J.-W., Xiong, S.-W., Ma, X.-S., Li, P., Li, X.-Y.: Development and reduction of n-decane detailed combustion reaction mechanism Tuijin Jishu/Journal of Propulsion Technology 33, 64-68 (2012)

Lodier, G., Vervisch, L., Moureau, V., Domingo, P.: Composition-space premixed flamelet solution with differential diffusion for in situ flamelet-generated manifolds. Combust. Flame(158), 2009-2016 (2011)

LOGE: LOGEsoft v. 1.02. In: Engineering, L.C. (ed.). http://www.loge.se/Products/LOGE_Products.html, (2014)

Logist, F., Saucez, P., Van Impe, J., Wouwer, A.V.: Simulation of (bio)chemical processes with distributed parameters using Matlab (R). Chem. Eng. J. 155, 603-616 (2009)

Lotka, A.J.: Contribution to the theory of periodic reaction. J. Phys. Chem. 14, 271–274 (1910)

Lotka, A.J.: Analytical note on certain rhythmic relations in organic systems. Proc. Natl. Acad. Sci. U.S. 6, 410-415 (1920)

Løvås, T.: Automatic generation of skeletal mechanisms for ignition combustion based on level of importance analysis. Combust. Flame 156, 1348-1358 (2009)

Løvås, T., Amneus, P., Mauss, F., Mastorakos, E.: Comparison of automatic reduction procedures for ignition chemistry. Proc. Combust. Inst. 29, 1387-1393 (2002a)

Løvås, T., Houshfar, E., Bugge, M., Skreiberg, Ø.: Automatic generation of kinetic skeletal mechanisms for biomass combustion. Energy Fuels 27, 6979−6991 (2013)

Løvås, T., Mastorakos, E., Goussis, D.A.: Reduction of the RACM scheme using computational singular perturbation analysis. J. Geophys. Res.-Atmos. 111, D13302 (2006)

Løvås, T., Mauss, F., Hasse, C., Peters, N.: Development of adaptive kinetics for application in combustion systems. Proc. Comb. Inst. 29, 1403-1410 (2002b)

Løvås, T., Navarro-Martinez, S., Rigopoulos, S.: On adaptively reduced chemistry in large eddy simulations. Proc. Combust. Inst. 33, 1339-1346 (2011)

Løvås, T., Nilsson, D., Mauss, F.: Automatic reduction procedure for chemical mechanisms applied to premixed methane/air flames. Proc. Combust. Inst. 28, 1809-1815 (2000)

Lovrics, A., Csikász-Nagy, A., Zsély, I.G., Zádor, J., Turányi, T., Novák, B.: Time scale and dimension analysis of a budding yeast cell cycle model. BMC Bioinformatics 7, 494 (2006)

Lovrics, A., Zsély, I.G., Csikász-Nagy, A., Zádor, J., Turányi, T., Novák, B.: Analysis of a budding yeast cell cycle model using the shapes of local sensitivity functions. Int. J. Chem. Kinet. 40, 710–720 (2008)

Lowe, R., Tomlin, A.: Low-dimensional manifolds and reduced chemical models for tropospheric chemistry simulations. Atm. Environ. 34, 2425-2436 (2000a)

Lowe, R.M., Tomlin, A.S.: The application of repro-modelling to a tropospheric chemical model. Env. Modell. Soft. 15, 611-618 (2000b)

Lu, B., Yue, H.: Sensitivity analysis of oscillatory biological systems with a SVD-based algorithm. Systemics and Informatics World Network 10, 37-47 (2010)

Lu, L.Y., Pope, S.B.: An improved algorithm for in situ adaptive tabulation. J. Comput. Phys. 228, 361-386 (2009)

Lu, T., Ju, Y., Law, C.K.: Complex CSP for chemistry reduction and analysis. Combust. Flame 126, 1445-1455 (2001)

Lu, T., Law, C.: Linear time reduction of large kinetic mechanisms with directed relation graph: n-heptane and iso-octane. Combust. Flame 144, 24-36 (2006a)

Lu, T., Law, C.K.: A directed relation graph method for mechanism reduction. Proc. Comb. Inst. 30, 1333–1341 (2005)

Lu, T., Law, C.K.: On the applicability of directed relation graphs to the reduction of reaction mechanisms. Combust. Flame 146, 472–483 (2006b)

Lu , T., Law, C.K.: Systematic approach to obtain analytic solutions of quasi steady state species in reduced mechanisms. J. Phys. Chem. A 110, 13202-13208 (2006)

Lu, T., Law, C.K.: A criterion based on computational singular perturbation for the identification of quasi steady state species: A reduced mechanism for methane oxidation with NO chemistry. Combust. Flame 154, 761-774 (2008a)

Lu, T., Law, C.K.: Strategies for mechanism reduction for large hydrocarbons: n-heptane. Combust. Flame 154, 153–163 (2008b)

Lu, T., Law, C.K.: Toward accommodating realistic fuel chemistry in large-scale computations. Prog. Energy Combust. Sci. 35, 192-215 (2009)

Lu, T., Law, C.K., Yoo, C.S., Chen, J.H.: Dynamic stiffness removal for direct numerical simulations. Combust. Flame 156, 1542–1551 (2009)

Lu, T.F., Yoo, C.S., Chen, J.H., Law, C.K.: Three-dimensional direct numerical simulation of a turbulent lifted hydrogen jet flame in heated coflow: a chemical explosive mode analysis J. Fluid Mechanics 652, 45-64 (2010)

Luche, J., Reuillon, M., Boettner, J.-C., Cathonnet, M.: Reduction of large detailed kinetic mechanisms: Application to kerosene/air combustion. Combust. Sci. Tech. 176, 1935–1963 (2004)

Luo, Z., Plomer, M., Lu, T.F., Som, S., Longman, D.E.: A reduced mechanism for biodiesel surrogates with low temperature chemistry for compression ignition engine application. Combust. Theory Model. 16, 369–385 (2012a)

Luo, Z., Plomer, M., Lu, T.F., Som, S., Longman, D.E., Sarathy, S.M., Pitz, W.J.: A reduced mechanism for biodiesel surrogates for compression ignition engine applications. Fuel 99, 143–153 (2012b)

Luo, Z., Som, S., Sarathy, S.M., Plomer, M., Pitz, W.J., Longman, D.E., Lu, T.F.: Development and validation of an n-dodecane skeletal mechanism for Diesel spray-combustion applications. Combust. Theory Model. 18, 187-203 (2014)

Luo, Z., Yoo, C.S., Richardson, E.S., Chen, J.H., Law, C.K., Lu, T.F.: Chemical explosive mode analysis for a turbulent lifted ethylene jet flame in highly-heated coflow. Combust. Flame 159, 265-274 (2012c)

Luo, Z.Y., Lu, T.F., Liu, J.W.: A reduced mechanism for ethylene/methane mixtures with excessive NO enrichment. Combustion and Flame 158, 1245-1254 (2011)

Luo, Z.Y., Lu, T.F., Maciaszek, M.J., Som, S., Longman, D.E.: A reduced mechanism for high-temperature oxidation of biodiesel surrogates. Energy Fuels 24, 6283-6293 (2010a)

Luo, Z.Y., Lu, T.F., Som, S., Longman, D.E., Asme: Numerical study on combustion characteristics of biodiesel using a new reduced mechanism for methyl decanoate as surrogate. Proceedings of the ASME Internal Combustion Engine Division Fall Technical Conference, 873-884 (2010b)

Luong, M.B., Luo, Z., Lu, T.F., Chung, S.H., Yoo, C.S.: Direct numerical simulations of the ignition of lean primary reference fuel/air mixtures under HCCI condition. Combust. Flame 160, 2038–2047 (2013)

Lüdtke, N., Panzeri, S., Brown, M., Broomhead, D.S., Knowles, J., Montemurro, M.A., Kell, D.B.: Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks. J R Soc Interface. 26 (2007)

Lv, Y., Wang, Z.H., Zhou, J.H., Cen, K.F.: Reduced mechanism for hybrid NOx control process. Energy Fuels 23, 5920-5928 (2009)

Maas, U.: Coupling of chemical reaction with flow and molecular transport. Appl. Math. 40, 249-266 (1995)

Maas, U.: Efficient calculation of intrinsic low-dimensional manifolds for the simplification of chemical kinetics. Computing and Visualization in Science 1, 69-81 (1998)

Maas, U.: Mathematical modeling of the coupling of chemical kinetics with flow and molecular transport. In: Keil, F., Mackens, W., Voss, H., Werther, J. (eds.) Scientific Computing in Chemical Engineering II. pp. 26-56. (1999)

Maas, U., Bykov, V.: The extension of the reaction/diffusion manifold concept to systems with detailed transport models. Proc. Combust. Inst. 33, 1253-1259 (2011)

Maas, U., Pope, S.B.: Implementation of simplified chemical kinetics based on intrinsic low-dimensional manifolds. Proc. Combust. Inst. 24, 103-112 (1992a)

Maas, U., Pope, S.B.: Simplifying chemical kinetics:Intrinsic low-dimensional manifolds in composition space. Combust. Flame 88, 239-264 (1992b)

Maas, U., Pope, S.B.: Laminar flame calculations using simplified chemical kinetics based on intrinsic low-dimensional manifolds. Proc. Combust. Inst. 25, 1349-1356 (1994)

Maas, U., Thévenin, D.: Correlation analysis of direct numerical simulation data of turbulent non-premixed flames. Proc. Combust. Inst. 27, 1183-1189 (1998)

Maas, U., Tomlin, A.S.: Time-scale splitting-based mechanism reduction. In: Battin-Leclerc, F., Blurock, E., Simmie, J. (eds.) Development of detailed chemical kinetic models for cleaner combustion. pp. 467-484. Springer, Heidelberg (2013)

Maas, U., Warnatz, J.: Ignition processes in hydrogen-oxigen mixtures. Combust. Flame 74, 53-69 (1988)

Machrafi, H., Lombaert, K., Cavadias, S., Guibert, P., Amouroux, J.: Reduced chemical reaction mechanisms: experimental and HCCI modelling investigations of autoignition processes of iso-octane in internal combustion engines. Fuel 84, 2330-2340 (2005)

Macken, K.V., Sidebottom, H.W.: The reactions of methyl radicals with chloromethanes. Int. J. Chem. Kinet. 11, 511–527 (1979)

Maiwald, T., Timmer, J.: Dynamical modeling and multi-experiment fitting with PottersWheel. Bioinformatics 24, 2037-2043 (2008)

Malik, A., Schramm, J., Nielsen, C., Løvås, T.: Development of surrogate for Fischer-Tropsch biofuel and reduced mechanism for combustion in Diesel engine. SAE Technical Paper 2013-2001-2599 (2013)

Maly, T., Petzold, L.R.: Numerical methods and software for sensitivity analysis of differential-algebraic systems. Appl. Numer. Math. 20, 57-79 (1996)

Manion, J.A., Huie, R.E., Levin, R.D., Burgess Jr., D.R., Orkin, V.L., Tsang, W., McGivern, W.S., Hudgens, J.W., Knyazev, V.D., Atkinson, D.B., Chai, E., Tereza, A.M., Lin, C.-Y., Allison, T.C., Mallard, W.G., Westley, F., Herron, J.T., Hampson, R.F., Frizzell, D.H.: NIST Chemical Kinetics Database, NIST Standard Reference Database 17, Version 7.0 (Web Version), Release 1.6.7, Data Version 2013.03, National Institute of Standards and Technology, Gaithersburg, Maryland, 20899-8320. . http://kinetics.nist.gov/ (2013).

Mao, J., Ren, X., Brune, W.H., Olson, J.R., Crawford, J.H., Fried, A., Huey, L.G., Cohen, R.C., Heikes, B., Singh, H.B., Blake, D.R., Sachse, G.W., Diskin, G.S., Hall, S.R., Shetter, R.E.: Airborne measurement of OH reactivity during INTEX-B. Atmos. Chem. Phys. 9, 163-173 (2009)

Maple. http://www.maplesoft.com/.

Mara, T.A., Tarantola, S.: Variance-based sensitivity indices for models with dependent inputs. Reliab. Eng. Syst. Saf. 107, 115-121 (2012)

Maria, G.: A review of algorithms and trends in kinetic model identification for chemical and biochemical systems. Chem. Biochem. Eng. Q. 18, 195-222 (2004)

Maria, G.: Application of lumping analysis in modelling the living systems - A trade-off between simplicity and model quality. Chem. Biochem. Eng. Q. 20, 353-373 (2006)

Maria, G.: Reduced modular representations applied to simulate some genetic regulatory circuits. Rev. Chim. 59, 318-324 (2008)

Maria, G.: Lumped dynamic model for a bistable genetic regulatory circuit within a variable-volume whole-cell modelling framework. Asia-Pac. J. Chem. Eng. 4, 916-928 (2009)

Marinov, N.M., Pitz, W.J., Westbrook, C.K., Castaldi, M.J., Senkan, S.M.: Modeling of aromatic and polycyclic aromatic hydrocarbon formation in premixed methane and ethane flames. Combust. Sci. Technol. 116, 211-287 (1996)

Marsden, A.R., Frenklach, M., Reible, D.D.: Increasing the computational feasibility of urban air-quality models that employ complex chemical mechanisms. JAPCA 37, 370-376 (1987)

Masri, A.R., Cao, R., Pope, S.B., Goldin, G.M.: PDF calculations of turbulent lifted flames of H₂/N₂ fuel issuing into a vitiated co-flow. Combust. Theory Model. 8, 1-22 (2004)

Massias, A., Diamantis, D., Mastorakos, E., Goussis, D.A.: An algorithm for the construction of global reduced mechanisms with CSP data. Combust. Flame 117, 685-708 (1999a)

Massias, A., Diamantis, D., Mastorakos, E., Goussis, D.A.: Global reduced mechanisms for methane and hydrogen combustion with nitric oxide formation constructed with CSP data. Combust. Theory Modell. 3, 233-257 (1999b)

Matheu, D.M., Dean, A.M., Grenda, J.M., Green, W.H.: Mechanism generation with integrated pressure dependence: A new model for methane pyrolysis. J. Phys. Chem. A 107, 8552-8565 (2003)

Matheu, D.M., Grenda, J.M.: A systematically generated, pressure-dependent mechanism for high-conversion ethane pyrolysis. 1. Pathways to the minor products. J. Phys. Chem. A 109, 5332–5342 (2005a)

Matheu, D.M., Grenda, J.M.: A systematically generated, pressure-dependent mechanism for high-conversion ethane pyrolysis. 2. Radical disproportionations, missing reaction families, and the consequences of pressure dependence. J. Phys. Chem. A 109, 5343–5351 (2005b)

Mauersberger, G.: ISSA (iterative screening and structure analysis)—a new reduction method and its application to the tropospheric cloud chemical mechanism RACM/CAPRAM 2.4. Atm. Environm. 39, 4341-4350 (2005)

Maurya, M.R., Bornheimer, S.J., Venkatasubramanian, V., Subramaniam, S.: Mixed-integer nonlinear optimisation approach to coarse-graining biochemical networks. IET Syst. Biol. 3, 24-39 (2009)

Mauryaa, M.R., Katare, S., Patkar, P.R., Rundell, A.E., Venkatasubramanian, V.: A systematic framework for the design of reduced-order models for signal transduction pathways from a control theoretic perspective. Comput. Chem. Eng. 30, 437–452 (2006)

Mavrovouniotis, M.L.: Synthesis of reaction mechanisms consisting of reversible and irreversible steps. 2. Formalization and analysis of the synthesis algorithm. Ind. Eng. Chem. Res. 31, 1637–1653 (1992)

Mavrovouniotis, M.L., Stephanopoulos, G., Stephanopoulos, G.: Computer-aided synthesis of biochemical pathways. Biotechnol. Bioeng. 36, 1119–1132 (1990)

Mazumder, S.: Adaptation of the in situ adaptive tabulation (ISAT) procedure for efficient computation of surface reactions. Comput. Chem. Eng. 30, 115-124 (2005)

McKay, M.D., Beckman, R.J., Conover, W.J.: A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42, 55-61 (2000)

MECHMOD: Modification of CHEMKIN-format mechanisms. In: http://garfield.chem.elte.hu/Combustion/mechmod.htm.

Meisel, W.S., Collins, D.C.: Repro-modeling: An approach to efficient model utilization and interpretation. IEEE Trans. SMC-3/4, 349-358 (1973)

Mendes, P.: GEPASI: A software package for modelling the dynamics, steady states and control of biochemical and other systems. Comput. Applic. Biosci. 9, 563-571 (1993)

Mendes, P.: Biochemistry by numbers: simulation of biochemical pathways with Gepasi 3. Trends Biochem. Sci. 22, 361-363 (1997)

Mendes, P., Kell, D.B.: Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation. Bioinformatics 14, 869-883 (1998)

Mendiara, T., Alzueta, M., Millera, A., Bilbao, R.: An augmented reduced mechanism for methane combustion. Energy Fuels 18, 619-627 (2004)

Mengers, J.D., Powers, J.M.: One-dimensional slow invariant manifolds for fully coupled reaction and micro-scale diffusion. SIAM J. Appl. Dyn. Syst. 12, 560-595 (2013)

Mersin, I.E., Blurock, E.S., Soyhan, H.S., Konnov, A.A.: Hexadecane mechanisms: Comparison of hand-generated and automatically generated with pathways. Fuel 115, 132–144 (2014)

Metcalfe, W.K., Burke, S.M., Ahmed, S.S., Curran, H.J.: A hierarchical and comparative kinetic modeling study of C1−C2 hydrocarbon and oxygenated fuels. Int. J. Chem. Kinet. 45, 638–675 (2013)

Michael, J.V., Kumaran, S.S., Su, M.C., Lim, K.P.: Thermal rate constants over thirty orders of magnitude for the I + H₂ reaction. Chem. Phys. Lett. 319, 99-106 (2000)

Michaelis, L., Menten, M.: Die Kinetik der Invertinwirkung. Biochem. Z. 49, 333-369 (1913)

Michel, J.-B., Colin, O., Angelberger, C.: On the formulation of species reaction rates in the context of multi-species CFD codes using complex chemistry tabulation techniques. Combust Flame 157, 701-714 (2010)

Michel, J.-B., Colin, O., Angelberger, C., Veynanteb, D.: Using the tabulated diffusion flamelet model ADF-PCM to simulate a lifted methane-air jet flame. Combust Flame 156, 1318-1331 (2009)

Michel, J.-B., Colin, O., Veynante, D.: Modeling ignition and chemical structure of partially premixed turbulent flames using tabulated chemistry. Combust Flame 152, 80-99 (2008)

Miki, K., Prudencio, E.E., Cheung, S.H., Terejanu, G.: Using Bayesian analysis to quantify uncertainties in the H+O₂→OH+O reaction. Combust Flame. 160, 861-869 (2013)

Miller, J.A., Pilling, M.J., Troe, J.: Unravelling combustion mechanisms through a quantitative understanding of elementary reactions. Proc. Combust. Inst. 30, 43-88 (2005)

Miller, W.G., Alberty, R.A.: Kinetics of the reversible Michaelis–Menten mechanism and the applicability of the Steady-state Approximation. J. Am. Chem. Soc. 80, 5146-5151 (1958)

Milner, P.C.: The possible mechanisms of complex reactions involving consecutive steps. J. Electrochem. Soc. 111, 228–232 (1964)

Mirgolbabaei, H., Echekki, T.: A novel principal component analysis-based acceleration scheme for LES–ODT: An a priori study. Combust. Flame 160, 898–908 (2013)

Mirgolbabaei, H., Echekki, T.: Nonlinear reduction of combustion composition space with kernel principal component analysis. Combust. Flame 161, 118–126 (2014)

Mirgolbabaei, H., Echekki, T., Smaoui, N.: A nonlinear principal component analysis approach for turbulent combustion composition space. Int. J. Hydrogen Energy 39, 4622-4633 (2014)

Mishra, M.K., Yetter, R.A., Reuven, Y., Rabitz, H.: On the role of transport in the combustion kinetics of a steady-state premixed laminar CO+H₂+O₂ flame. Int. J. Chem. Kinet. 26, 437-453 (1994)

Mitsos, A., Oxberry, G.M., Barton, P.I., Green, W.H.: Optimal automatic reaction and species elimination in kinetic mechanisms. Combust. Flame 155, 118–132 (2008)

Mittal, G., Chaos, M., Sung, C.J., Dryer, F.L.: Dimethyl ether autoignition in a rapid compression machine: Experiments and chemical kinetic modeling. Fuel Process. Technol. 89, 1244-1254 (2008)

Mittal, G., Sung, C.J., Fairweather, M., Tomlin, A.S., Griffiths, J.F., Hughes, K.J.: Significance of the HO₂+CO reaction during the combustion of CO+H₂ mixtures at high pressures. Proc. Combust. Inst. 31, 419-427 (2007)

Montgomery, C.J., Yang, C., Parkinson, A.R., Chen, J.-Y.: Selecting the optimum quasi-steady-state species for reduced chemical kinetic mechanisms using a genetic algorithm. Combust. Flame 144, 37-52 (2006)

Mora-Ramirez, M.A., Velasco, R.M.: Reduction of CB05 mechanism according to the CSP method. Atmos. Environ. 45, 235-243 (2011)

Moreac, G., Blurock, E.S., Mauss, F.: Automatic generation of a detailed mechanism for the oxidation of n-decane. Combust Sci Technol 178, 2025–2038 (2006)

Morokoff, W., Caflisch, R.: Quasi-Monte Carlo Integration. J. Comput. Phys. 122, 218-230 (1995)

Morris, M.D.: Factorial sampling plans for preliminary computational experiments. Technometrics 33, 161-174 (1991)

Morris, M.D.: Input screening: Finding the important model inputs on a budget. Reliab. Eng. Syst. Safety 91, 1252-1256 (2006)

Mosbach, S., Aldawood, A.M., Kraft, M.: Real-time evaluation of a detailed chemistry HCCI engine model using a tabulation technique. Combust. Sci. Technol. 180, 1263-1277 (2008)

Mosbach, S., Hong, J.H., Brownbridge, G.P.E., Kraft, M., Gudiyella, S., Brezinsky, K.: Bayesian error propagation for a kinetic model of n-propylbenzene oxidation in a shock tube. Int. J. Chem. Kinet. 46, 389-404 (2014)

Moulik, M.D., Milford, J.B.: Factors influencing ozone chemistry in subsonic aircraft plumes. Atmos. Environ. 33, 869-880 (1999)

Muller, C., Michel, V., Scacchi, G., Côme, G.M.: THERGAS: a computer program for the evaluation of thermochemical data of molecules and free radicals in the gas phase. Journal De Chimie Physique Et De Physico-chimie Biologique 92, 1154-1178 (1995)

Nafe, J., Maas, U.: A general algorithm for improving ILDMs. Combust. Theory Modell. 6, 697-709 (2002)

Nafe, J., Maas, U.: Hierarchical generation of ILDMs of higher hydrocarbons. Combust. Flame 135, 17–26 (2003)

NAG: Numerical Algorithms Group www.nag.co.uk. (2014).

Nagy, A.L., Papp, D., Tóth, J.: ReactionKinetics — A Mathematica package with applications. Chem. Eng. Sci. 83, 12–23 (2012)

Nagy, T.: SEM: mechanism reduction based on simulation error minimization. http://garfield.chem.elte.hu/Combustion/sem.htm (2009).

Nagy, T., Turányi, T.: Reduction of very large reaction mechanisms using methods based on simulation error minimization. Combust. Flame 156, 417–428 (2009a)

Nagy, T., Turányi, T.: Relaxation of concentration perturbation in chemical kinetic systems. Reac. Kinet. Catal. Letters 96, 269-278 (2009b)

Nagy, T., Turányi, T.: Uncertainty of Arrhenius parameters. Int.J.Chem.Kinet. 43, 359-378 (2011)

Nagy, T., Turányi, T.: Determination of the uncertainty domain of the Arrhenius parameters needed for the investigation of combustion kinetic models. Reliability Engineering Syst. Safety 107, 29-34 (2012)

Naik, C.V., Puduppakkam, K.V., Modak, A., Wang, C., Meeks, E.: Validated F-T fuel surrogate model for simulation of jet-engine combustion. Proceedings of the ASME Turbo Expo 2, 1301-1308 (2010)

Najafi-Yazdi, A., Cuenot, B., Mongeau, L.: Systematic definition of progress variables and Intrinsically Low-Dimensional, Flamelet Generated Manifolds for chemistry tabulation. Combust. Flame 159, 1197-1204 (2012)

Najm, H., Debusschere, B.J., Marzouk, Y.M., Widmer, S., Le Maître, O.P.: Uncertainty quantification in chemical systems. Int. J. Numer. Meth. Eng. 80, 789-814 (2009)

Najm, H.N., Malorani, M.: Enforcing positivity in intrusive PC-UQ methods for reactive ODE systems. J. Comp. Phys. 270, 544-569 (2014)

Németh, A., Vidóczy, T., Héberger, K., Kúti, Z., Wágner, J.: MECHGEN: Computer aided generation and reduction of reaction mechanisms. J. Chem. Inf. Comput. Sci. 42, 208-214 (2002)

Neophytou, M.K., Goussis, D.A., van Loon, M., Mastorakos, E.: Reduced chemical mechanisms for atmospheric pollution using Computational Singular Perturbation analysis. Atm. Environ. 38, 3661-3673 (2004)

Nicolini, P., Frezzato, D.: Features in chemical kinetics. I. Signatures of self-emerging dimensional reduction from a general format of the evolution law. J. Chem. Phys. 138, 234101 (2013a)

Nicolini, P., Frezzato, D.: Features in chemical kinetics. II. A self-emerging definition of slow manifolds. J. Chem. Phys. 138, 234102 (2013b)

Niederreiter, H.: Low-discrepancy and low-dispersion sequences. J. Num. Theor. 30, 51-70 (1988)

Niemann, H., Schmidt, D., Maas, U.: An efficient storage scheme for reduced chemical kinetics based on orthogonal polynomials. J. Eng. Math. 31, 131-142 (1997)

Niemeyer, K.E., Sung, C.J., Raju, M.P.: Skeletal mechanism generation for surrogate fuels using directed relation graph with error propagation and sensitivity analysis. Combust. Flame 157, 1760-1770 (2010)

Niemeyer, K.E., Sung, C.J.: On the importance of graph search algorithms for DRGEP-based mechanism reduction methods, Combust. Flame 158, 1439–1443 (2011)

Niemeyer, K.E., Sung, C.J.: Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels. Combust. Flame 161, 2752–2764 (2014)

Nikolaev, E.V., Atlas, J.C., Shuler, M.L.: Sensitivity and control analysis of periodically forced reaction networks using the Green’s function method. J. Theor. Biol. 247, 442-461 (2007)

Nilsson, D., Løvås, T., Amneus, P., Mauss, F.: Reduction of complex fuel chemistry for simulation of combustion in an HCCI engine. VDI-Berichte 1492, 511-516 (1999)

Niu, Y.-S., Vervisch, L., Tao, P.D.: An optimization-based approach to detailed chemistry tabulation: Automated progress variable definition. Combust. Flame 160, 776-785 (2013)

Novák, B., Pataki, Z., A, C., Tyson, J.J.: Mathematical model of the cell division cycle of fission yeast. Chaos 11, 277-286 (2001)

Ó Conaire, M., Curran, H.J., Simmie, J.M., Pitz, W.J., Westbrook, C.K.: A comprehensive modeling study of hydrogen oxidation. Int. J. Chem. Kinet. 36, 603-622 (2004)

Oakley, J., O'Hagan, A.: Bayesian inference for the uncertainty distribution of computer model outputs. Biometrika 89, 769-784 (2002)

Oakley, J.E., O'Hagan, A.: Probabilistic sensitivity analysis of complex models: A Bayesian approach. Journal of the Royal Statistical Society. Series B (Statistical Methodology) 66, 751-769 (2004)

Ocone, R., Astarita, G.: Lumping nonlinear kinetics in porous catalysts: Diffusion-reaction lumping strategy. AIChE J. 39, 288-293 (1993)

Ogren, P.J., Hessler, J.P.: Sensitivity and correlation analysis of the physical parameters in absorption, four-wave mixing, and Schlieren experiments. Int. J. Chem. Kinet. 27, 719–738 (1995)

Okino, M.S., Mavrovouniotis, M.L.: Simplification of mathematical models of chemical reaction systems. Chem. Rev. 98, 391–408 (1998)

Olm, C., Zsély, I.G., Pálvölgyi, R., Varga, T., Nagy, T., Curran, H.J., Turányi, T.: Comparison of the performance of several recent hydrogen combustion mechanisms. Combust. Flame 161, 2219-2234 (2014)

Oluwole, O.O., Bhattacharjee, B., Tolsma, J.E., Barton, P.I., H., G.W.: Rigorous valid ranges for optimally reduced kinetic models. Combust. Flame 146, 348-365 (2006)

Oluwole, O.O., Shi, Y., Wong, H.W., Green, W.H.: An Exact-Steady-state Adaptive Chemistry method for combustion simulations: Combining the efficiency of reduced models and the accuracy of the full model. Combust. Flame 159, 2352–2362 (2012)

Orth, J.D., Thiele, I., Palsson, B.O.: What is flux balance analysis? Nat Biotech 28, 245-248 (2010)

Paczko, G., Lefdal, P.M., Peters, N.: Reduced reaction schemes for methane, methanol and propane flames. Proc. Combust. Inst. 21, 739–748 (1986)

Panesi, M., Miki, K., Prudhomme, S., Brandis, A.: On the assessment of a Bayesian validation methodology for data reduction models relevant to shock tube experiments. Comput Methods Appl Mech. Eng. 213–216, 383-398 (2012)

Pantazis, Y., Katsoulakis, M.A., Vlachos, D.G.: Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory. BMC Bioinformatics 14, 311 (2013)

Pantea, C., Gupta, A., Rawlings, J.B., Craciun, G.: The QSSA in chemical kinetics: As taught and as practiced. In: Jonoska, N., Saito, M. (eds.) Discrete and topological models in molecular biology. pp. 419-442. Springer, Berlin, Heidelberg (2014)

Papin, J.A., Stelling, J., Price, N.D., Klamt, S., Schuster, S., Palsson, B.O.: Comparison of network-based pathway analysis methods. Trends in Biotechnology 22, 400-405 (2004)

Parente, A., Sutherland, J.C., Dally, B.B., Tognotti, L., Smith, P.J.: Investigation of the MILD combustion regime via Principal Component Analysis. Proc. Combust. Inst. 33, 3333–3341 (2011)

Parente, A., Sutherland, J.C., Tognotti, L., Smith, P.J.: Identification of low-dimensional manifolds in turbulent flames. Proc. Combust. Inst. 32, 1579–1586 (2009)

Peng, Z., Dobrijevic, M., Hébrard, E., Carrasco, N., Pernot, P.: Photochemical modeling of Titan atmosphere at the “10 percent uncertainty horizon”. Faraday Discussions 147, 137-153 (2010)

Pepiot-Desjardins, P., Pitsch, H.: An efficient error-propagation-based reduction method for large chemical kinetic mechanisms. Combust. Flame 154, 67-81 (2008)

Pepiot, P., Pitsch, H.: Systematic reduction of large chemical mechanisms. In: 4th Joint Meeting of the U.S. Sections of the Combustion Institute, Philadelphia 2005

Pera, C., Colin, O., Jay, S.: Development of a FPI detailed chemistry tabulation methodology for internal combustion engines. Oil & Gas Science and Technology Rev IFP 64:243-258 (2009)

Perger, T., Kovács, T., Turányi, T., Treviño, C.: Determination of adsorption and desorption parameters from ignition temperature measurements in catalytic combustion systems. J. Phys. Chem. B 107, 2262-2274 (2003)

Perini, F., Brakora, L.J., Reitz, D.R., Cantore, G.: Development of reduced and optimized reaction mechanisms based on genetic algorithms and element flux analysis. Combust. Flame 159, 103–119 (2012)

Perumal, T.M., Gunawan, R.: Understanding dynamics using sensitivity analysis: caveat and solution. BMC Systems Biol. 5, 41 (2011)

Perumal, T.M., Gunawan, R.: pathPSA: A dynamical pathway-based parametric sensitivity analysis. Ind. Eng. Chem. Res. 53, 9149–9157 (2014)

Perumal, T.M., Krishna, S.M., Tallam, S.S., Gunawan, R.: Reduction of kinetic models using dynamic sensitivities. Comput. Chem. Eng. 56, 37– 45 (2013)

Perumal, T.M., Wu, Y., Gunawan, R.: Dynamical analysis of cellular networks based on the Green’s function matrix. J. Theor. Biol. 261, 248–259 (2009)

Peters, N.: Numerical and asymptotic analysis of systematically reduced reaction schemes for hydrocarbon flames. Lecture Notes in Physics 241, 90-109 (1985)

Peters, N., Kee, R.J.: The computation of stretched laminar methane-air diffusion flames using a reduced four-step mechanism. Combust. Flame 68, 17–29 (1987)

Peters, N., Paczko, G., Seiser, R., Seshadri, K.: Temperature cross-over and non-thermal runaway at two-stage ignition of n-heptane. Combust. Flame 128, 38-59 (2002)

Peters, N., Rogg, B. (eds.): Reduced kinetic mechanisms for applications in combustion systems. Springer, Berlin (1993)

Peters, N., Williams, F.A.: The asymptotic structure of stoichiometric methane-air flames. Combust. Flame 68, 185-207 (1987)

Petzold, L., Zhu, W.: Model reduction for chemical kinetics: An optimization approach. AIChE Journal 45, 869-886 (1999)

Pierucci, S., Ranzi, E.: A review of features in current automatic generation software for hydrocarbon oxidation mechanisms. Comp. Chem. Eng. 32, 805-826 (2008)

Pilling, M.J.: From elementary reactions to evaluated chemical mechanisms for combustion models. Proc. Combust. Inst. 32, 27-44 (2009)

Pilling, M.J., Seakins, P.W.: Reaction Kinetics. Oxford University Press, Oxford (1995)

Plessis, S., Carrasco, N., Pernot, P.: Knowledge-based probabilistic representations of branching ratios in chemical networks: The case of dissociative recombinations. J. Chem. Phys. 133, 134110 (2010)

Polifke, W., Geng, W., Döbbeling, K.: Optimization of rate coefficients for simplified reaction mechanisms with genetic algorithms. Combust. Flame 113, 119-135 (1998)

Pontryagin, L.S.: Ordinary differential equations. Elsevier, Amsterdam (1962)

Poon, H., Ng, H., Gan, S., Pang, K., Schramm, J.: Evaluation and development of chemical kinetic mechanism reduction scheme for biodiesel and Diesel fuel surrogates. SAE Int. J. Fuels Lubr. 6, 729-744 (2013)

Pope, S.B.: Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation. Combust. Theory Modell. 1, 41-63 (1997)

Pope, S.B.: Small scales, many species and the manifold challenges of turbulent combustion. Proc. Combust.Inst. 34, 1–31 (2013)

Pope, S.B., Ren, Z.: Efficient implementation of chemistry in computational combustion. Flow Turbulence Combust. 82, 437–453 (2009)

PottersWheel: Multi-experiment fitting. In: http://www.potterswheel.de/.

Prager, J., Najm, H.N., Sargsyan, K., Safta, C., Pitz, W.J.: Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters. Combust. Flame 160, 1583–1593 (2013)

Prager, J., Najm, H.N., Valorani, M., Goussis, D.A.: Skeletal mechanism generation with CSP and validation for premixed n-heptane flames. Proc. Combust. Inst. 32, 509-517 (2009)

Prasad, G.N., Agnew, J.B., Sridhar, T.: Continuous reaction mixture for coal liquefaction. Theory. AIChE J. 32, 1277-1287 (1986)

Prasolov, V.V.: Problems and theorems in linear algebra, vol. 134. Translations of Mathematical Monographs. American Mathematical Society, (1994)

PrIMe: Process Informatics Model. In: http://www.primekinetics.org/.

Prüfert, U., Hunger, F., Hasse, C.: The analysis of chemical time scales in a partial oxidation flame. Combust. Flame 161, 416–426 (2014)

Puszyński, K., Lachor, P., Kardyńska, M., Śmieja, J.: Sensitivity analysis of deterministic signaling pathways models. Bull. Pol. Ac.: Tech. 60, 471-479 (2012)

Rabitz, H., Aliş, O.F.: Managing the tyranny of parameters in mathematical modelling of physical systems. In: Saltelli, A., Chan, K., Scott, E. (eds.) Sensitivity Analysis. pp. 199-224. John Wiley & Sons, (2000)

Rabitz, H., Aliş, Ö.F., Shorter, J., Shim, K.: Efficient input-output model representations. Comput. Phys. Commun. 117, 11-20 (1999)

Rabitz, H., Kramer, M., Dacol, D.: Sensitivity analysis in chemical-kinetics. Ann. Rev. Phys. Chem. 34, 419-461 (1983)

Rabitz, H., Smooke, M.D.: Scaling relations and self-similarity conditions in strongly coupled dynamical systems. J. Phys. Chem. 92, 1110-1119 (1988)

Radulescu, O., Gorban, A.N., Zinovyev, A., Lilienbaum, A.: Robust simplifications of multiscale biochemical networks. BMC Systems Biol. 2, 86 (2008)

Raj, G.: Chemical Kinetics. Krishna Prakashan Media P Ltd, Meerut (2010)

Ramaroson, R., Pirre, M., Cariolle, D.: A box model for online computations of diurnal-variations in a 1-d model - potential for application in multidimensional cases. Ann. Geophys.-Atmos. Hydrospheres Space Sci. 10, 416-428 (1992)

Ramirez, H.P., Hadj-Ali, K., Dievart, P., Dayma, G., Togbe, C., Moreac, G., Dagaut, P.: Oxidation of commercial and surrogate bio-Diesel fuels (B30) in a jet-stirred reactor at elevated pressure: Experimental and modeling kinetic study. Proc. Combust. Inst. 33, 375-382 (2011)

Rangarajan, S., Bhan, A., Daoutidis, P.: Rule-based generation of thermochemical routes to biomass conversion. Ind. Eng. Chem. Res. 49, 10459-10470 (2010)

Ranzi, E., Dente, M., Goldaniga, A., Bozzano, G., Faravelli, T.: Lumping procedures in detailed kinetic modeling of gasification, pyrolysis, partial oxidation and combustion of hydrocarbon mixtures. Prog. Energy Combust. Sci. 27, 99-139 (2001)

Ranzi, E., Faravelli, T., Gaffuri, P., Sogaro, A.: Low-temperature combustion: Automatic generation of primary oxidation reactions and lumping procedures. Combust. Flame 102, 179-192 (1995)

Ranzi, E., Faravelli, T., Gaffuri, P., Sogaro, A., D'Anna, A., Ciajolo, A.: A wide-range modeling study of iso-octane oxidation. Combust. Flame 108, 24-42 (1997)

Ranzi, E., Frassoldati, A., Granata, S., Faravelli, T.: Wide-range kinetic modeling study of the pyrolysis, partial oxidation, and combustion of heavy n-alkanes. Ind. Eng. Chem. Res. 44, 5170-5183 (2004)

Rao, C.V., Frenklach, M., Arkin, A.P.: An allosteric model for transmembrane signaling in bacterial chemotaxis. J. Mol. Biol. 343, 291–303 (2004)

Rappoport, D., Galvin, C.J., Zubarev, D.Y., Aspuru-Guzik, A.n.: Complex chemical reaction networks from heuristics-aided quantum chemistry. J. Chem. Theory Comput. 10, 897–907 (2014)

Ratto, M., Pagano, A., Young, P.: State dependent parameter metamodelling and sensitivity analysis. Comput. Phys. Commun. 177, 863-876 (2007)

Ratto, M., Pagano, A., Young, P.C.: Non-parametric estimation of conditional moments for sensitivity analysis. Reliab. Eng. Syst. Saf. 94, 237-243 (2009)

Ratto, M., Paladino, O.: Analysis of controlled CSTR models with fluctuating parameters and uncertain parameters. Chem. Eng. J. 79, 13-21 (2000)

Reaction-Design: Chemkin-Pro. In. http://www.reactiondesign.com/products/chemkin/chemkin-pro/, (2014)

Reaction-Engineering-International: CARM (Computer Assisted Reduction Method). In. http://www.reaction-eng.com/modeling_tools/carm.html, (2014)

REACTION\ANALYSIS: Software system for the manipulation of chemical information through statistics and machine learning. In: http://esblurock.info.

ReactionDesign: www.reactiondesign.com.

Reagan, M.T., Najm, H.N., Debusschere, B.J., Le Maitre, O.P., Knio, O.M., Ghanem, R.G.: Spectral stochastic uncertainty quantification in chemical systems. Combust. Theor. Model. 8, 607-632 (2004)

Reagan, M.T., Najm, H.N., Ghanem, R.G., Knio, O.M.: Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection. Combust. Flame 132(3), 545-555 (2003)

Reagan, M.T., Najm, H.N., Pebay, P.P., Knio, O.M., Ghanem, R.G.: Quantifying uncertainty in chemical systems modeling. Int. J. Chem. Kinet. 37, 368-382 (2005)

Ren, Z., Liu, Y., Lu, T., Lu, L., Oluwole, O.O., Goldin, G.M.: The use of dynamic adaptive chemistry and tabulation in reactive flow simulations. Combust. Flame 161, 127–137 (2014a)

Ren, Z., Pope, S.B.: Species reconstruction using pre-image curves. Proc. Combust. Inst. 30, 1293-1300 (2005)

Ren, Z., Pope, S.B.: The geometry of reaction trajectories and attracting manifolds in composition space. Combust. Theory Modell. 10, 361-388 (2006a)

Ren, Z., Pope, S.B.: The use of slow manifolds in reactive flows. Combust. Flame 147, 243-261 (2006b)

Ren, Z., Pope, S.B.: Reduced description of complex dynamics in reactive systems. J. Phys. Chem. A 111, 8464-8474 (2007a)

Ren, Z., Pope, S.B.: Transport-chemistry coupling in the reduced description of reactive flows. Combust. Theory Modell. 11, 715-739 (2007b)

Ren, Z., Pope, S.B., Vladimirsky, A., Guckenheimer, J.M.: The invariant constrained equilibrium edge preimage curve method for the dimension reduction of chemical kinetics. J. Chem. Phys., 124, 114111 (2006)

Ren, Z., Pope, S.B., Vladimirsky, A., Guckenheimer, J.M., John, M.: Application of the ICE-PIC method for the dimension reduction of chemical kinetics coupled with transport. Proc. Comb. Inst. 31, 473–481 (2007)

Ren, Z., Xu, C., Lu, T., Singer, M.A.: Dynamic adaptive chemistry with operator splitting schemes for reactive flow simulations. J. Comput. Phys. 263, 19–36 (2014b)

Ren, Z.Y., Pope, S.B.: Second-order splitting schemes for a class of reactive systems. J. Comput. Phys. 227, 8165-8176 (2008)

Reonhardt, V., Winckler, M., Lebiedz, D.: Approximation of slow attracting manifolds in chemical kinetics by trajectory-based optimization approaches. J. Phys. Chem. A 112, 1712–1718 (2008)

Reuven, Y., Smooke, M.D., Rabitz, H.: Sensitivity analysis of boundary value problems: Application to nonlinear reaction-diffusion systems. J. Comput. Phys. 64, 27-55 (1986)

Revel, J., Boettner, J.C., Cathonnet, M., Bachman, J.S.: Derivation of a global chemical kinetic mechanism for methane ignition and combustion. J. Chim. Phys. 91, 365-382 (1994)

Rhodes, C., Morari, M., Wiggins, S.: Identification of low order manifolds: Validating the algorithm of Maas and Pope. Chaos 9, 108-123 (1999)

Rice, O.K.: Conditions for a steady state in chemical kinetics. J. Phys. Chem. 64, 1851-1857 (1960)

Riedel, U., Schmidt, D., Maas, U., Warnatz, J.: Laminar flame calculations based on automatically simplified chemical kinetics. In: Proc. Eutherm. Seminar #35, Compact Fired Heating Systems, Leuven, Belgium 1994

Rigopoulos, S.: The rate-controlled constrained equilibrium (RCCE) method for reducing chemical kinetics in systems with time-scale separation. Int. J. Multiscale Comput. Eng. 5, 11-18 (2007)

Rigopoulos, S., Løvås, T.: A LOI-RCCE methodology for reducing chemical kinetics, with application to laminar premixed flames. Proc. Combust. Inst. 32, 569-576 (2009)

Ritter, E.R., Bozzelli, J.W.: THERM: Thermodynamic property estimation for gas phase radicals and molecules. Int. J. Chem. Kinet. 23, 767-778 (1991)

Rodiguin, N.M., Rodiguina, E.N.: Consecutive chemical reactions. Mathematical analysis and development. . D. van Nostrand, Princeton (1964)

Ross, J.: Determination of complex reaction mechanisms. Analysis of chemical, biological and genetic networks. J. Phys. Chem. A 112, 2134-2143 (2008)

Ross, J., Vlad, M.O.: Nonlinear kinetics and new approaches to complex reaction mechanisms. Ann. Rev. Phys. Chem. 50, 51-78 (1999)

Roussel, M.R., Fraser, S.J.: Geometry of the steady-state approximation: perturbation and accelerated convergence methods. J. Chem. Phys. 93, 1072–1081 (1990)

Roussel, M.R., Fraser, S.J.: Accurate steady-state approximation: Implications for kinetics experiments and mechanism. J. Chem. Phys. 94, 7106-7113 (1991a)

Roussel, M.R., Fraser, S.J.: On the geometry of transient relaxation. J. Chem. Phys. 94, 7106-7113 (1991b)

Roussel, M.R., Fraser, S.J.: Invariant manifold methods for metabolic model reduction. Chaos 11, 196-206 (2001)

Roussel, M.R., Tang, T.: The functional equation truncation method for approximating slow invariant manifolds: A rapid method for computing intrinsic low-dimensional manifolds. J. Chem. Phys. 125, 214103 (2006)

Ruscic, B.: Active Thermochemical Tables (ATcT) http://atct.anl.gov/.

Ruscic, B.: Active thermochemical tables: Water and water dimer. J. Phys. Chem. A 117, 11940-11953 (2013)

Ruscic, B.: Uncertainty quantification in thermochemistry, benchmarking electronic structure computations, and Active Thermochemical Tables. Int. J. Quantum Chem. 114, 1097-1101 (2014)

Ruscic, B., Boggs, J.E., Burcat, A., Császár, A.G., Demaison, J., Janoschek, R., Martin, J.M.L., Morton, M.L., Rossi, M.J., Stanton, J.F., Szalay, P.G., Westmoreland, P.R., Zabel, F., Bérces, T.: IUPAC Critical Evaluation of Thermochemical Properties of Selected Radicals. Part I. J. Phys. Chem. Ref. Data 34, 573-656 (2003)

Ruscic, B., Feller, D., Peterson, K.A.: Active thermochemical tables: Dissociation energies of several homonuclear first-row diatomics and related thermochemical values. Theor. Chem. Acc. 133, 1415/1411-1412 (2014)

Ruscic, B., Pinzon, R.E., Morton, M.L., Srinivasan, N.K., Su, M.C., Sutherland, J.W., Michael, J.V.: Active Thermochemical Tables: Accurate enthalpy of formation of hydroperoxyl radical, HO₂. J. Phys. Chem. A 110, 6592-6601 (2006)

Ruscic, B., Pinzon, R.E., Morton, M.L., von Laszevski, G., Bittner, S.J., Nijsure, S.G., Amin, K.A., Minkoff, M., Wagner, A.F.: Introduction to Active Thermochemical Tables: Several "Key" Enthalpies of Formation Revisited. J. Phys. Chem. A 108, 9979-9997 (2004)

Ruscic, B., Pinzon, R.E., von Laszewski, G., Kodeboyina, D., Burcat, A., Leahy, D., Montoya, D., Wagner, A.F.: Active Thermochemical Tables: Thermochemistry for the 21st Century. J. Phys. Conf. Ser. 16, 561-570 (2005)

Russi, T., Packard, A., Feeley, R., Frenklach, M.: Sensitivity analysis of uncertainty in model prediction. J. Phys. Chem. A 112, 2579-2588 (2008)

Russi, T., Packard, A., Frenklach, M.: Uncertainty quantification: Making predictions of complex reaction systems reliable. Chem. Phys. Lett. 499, 1-8 (2010)

Rzhetsky, A., Iossifov, I., Koike, T., Krauthammer, M., Kra, P., Morris, M., Yu, H., Duboué, P.A., Weng, W., Wilbur, W.J., Hatzivassiloglou, V., Friedman, C.: GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data. J. Biomed. Inf. 37, 43-53 (2004)

Saltelli, A.: Making best use of model evaluations to compute sensitivity indices. Comput. Phys. Commun. 145, 280-297 (2002)

Saltelli, A., Annoni, P.: How to avoid a perfunctory sensitivity analysis. Environ. Model. Softw. 25, 1508-1517 (2010)

Saltelli, A., Annoni, P., Azzini, I., Campolongo, F., Ratto, M., Tarantola, S.: Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index. Comp. Phys. Commun. 181, 259–270 (2010)

Saltelli, A., Bolado, R.: An alternative way to compute Fourier Amplitude Sensitivity Test (FAST). Comput. Stat. Data Anal. 26, 445-460 (1998)

Saltelli, A., Funtowicz, S.: When all models are wrong: More stringent quality criteria are needed for models used at the science-policy interface. Issues in Science and Technology Winter, 79-85 (2014)

Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S.: Global Sensitivity Analysis: The Primer. Wiley, (2008)

Saltelli, A., Ratto, M., Tarantola, S., Campolongo, F.: Sensitivity analysis for chemical models. Chem. Reviews 105, 2811-2828 (2005)

Saltelli, A., Ratto, M., Tarantola, S., Campolongo, F.: Sensitivity analysis practices: Strategies for model-based inference. Reliab. Engng Syst. Safety 91, 1109-1125 (2006)

Saltelli, A., Ratto, M., Tarantola, S., Campolongo, F.: Update 1 of: Sensitivity Analysis for Chemical Models. Chem. Rev. 112, PR1-PR21 (2012)

Saltelli, A., Scott, M., Chen, K. (eds.): Sensitivity analysis. Wiley, Chichester (2000)

Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M.: Sensitivity analysis in practice. A guide to assessing scientific models. Wiley (2004)

Saltelli, A., Tarantola, S., Chan, K.: A quantitative model-independent method for global sensitivity analysis of model output. Technometrics 41, 39 (1999)

Sander, S.P., Abbatt, J., Barker, J.R., Burkholder, J.B., Friedl, R.R., Golden, D.M., Huie, R.E., Kolb, C.E., Kurylo, M.J., Moortgat, G.K., Orkin, V.L., Wine, P.H.: Chemical kinetics and photochemical data for use in atmospheric studies, Evaluation No. 17. In: JPL Publication, vol. 10-6. Jet Propulsion Laboratory, Pasadena, (2011)

Sandu, A., Daescu, D.N., Carmichael, G.R.: Direct and adjoint sensitivity analysis ofchemical kinetic systems with KPP: Part I - theory and software tools. Atm. Environm. 37, 5083–5096 (2003)

Sandu, A., Verwer, J.G., Blom, J.G., Spee, E.J., Carmichael, G.R., Potra, F.A.: Benchmarking stiff ODE solvers for atmospheric chemistry problems II: Rosenbrock solvers. Atm. Environ. 31, 3459-3472 (1997a)

Sandu, A., Verwer, J.G., Van Loon, M., Carmichael, G.R., Potra, F.A., Dabdub, D., Seinfeld, J.H.: Benchmarking stiff ODE solvers for atmospheric chemistry problems I. implicit vs. explicit. Atm. Environ. 31, 3151-3166 (1997b)

Sankaran, R., Hawkes, E.R., Chen, J.H., Lu, T., Law, C.K.: Structure of a spatially developing turbulent lean methane–air Bunsen flame. Proc. Combust. Inst. 31, 1291-1298 (2007)

SaSAT: Sampling and sensitivity analyses tools. In: http://www.nchecr.unsw.edu.au/NCHECRweb.nsf/page/BioModInfectDis.

Saunders, S.M., Jenkin, M.E., Derwent, R.G., Pilling, M.J.: Protocol for the development of the Master Chemical Mechanism, MCM V3: tropospheric degradation of non-aromatic VOC. Atmospheric Chemistry and Physics 3, 161-180 (2003a)

Saunders, S.M., Pascoe, S., Johnson, A.P., Pilling, M.J., Jenkin, M.E.: Development and preliminary test results of an expert system for the automatic generation of tropospheric VOC degradation mechanisms. Atm. Environ. 37, 1723-1735 (2003b)

Savage, P.E.: Pyrolysis of a binary mixture of complex hydrocarbons - reaction modeling. Chem. Eng. Sci. 45, 859-873 (1990)

Saxena, V., Pope, S.B.: PDF simulations of turbulent combustion incorporating detailed chemistry. Combust. Flame 117, 340-350 (1999)

Sayasov, Y.S., Vasil'eva, A.B.: Обоснование и условия применимости метода квазистационарных концентраций Семенова–Боденштейна. Ж. Физ. Хим. 29, 802-810 (1955)

SBML-SAT: SBML based Sensitivity Analysis Tool. In: http://sysbio.molgen.mpg.de/SBML-SAT/.

SBML: Systems Biology Markup Language. In: http://sbml.org/.

SBMLToolbox: an SBML toolbox for MATLAB users. In: http://sbml.org/Software/SBMLToolbox.

sbtoolbox2. http://www.sbtoolbox2.org.

SBtoolbox: Systems Biology Toolbox for MATLAB. In: http://www.sbtoolbox.org/.

SBW: Systems Biology Workbench. In: http://www.sys-bio.org.

Schaibly, J.H., Shuler, K.E.: Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients II. Applications. J. Chem. Phys. 59, 3879-3888 (1973)

Schilling, C.H., Letscher, D., Palsson, B.Ø.: Theory for the systematic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J. Theor. Biol. 203, 229–248 (2000)

Schilling, C.H., Schuster, S., Palsson, B.O., Heinrich, R.: Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol. Prog. 15, 296–303 (1999)

Schmidt, H., Jirstrand, M.: Systems Biology Toolbox for MATLAB: a computational platform for research in systems biology. Bioinf. Appl. Note 22, 514–515 (2006)

Schuchardt, K., Oluwole, O., Pitz, W., Rahn, L.A., Green, W.H., Leahy, D., Pancerella, C., Sjöberg, M., Dec, J.: Development of the RIOT web service and information technologies to enable mechanism reduction for HCCI simulations. J. Phys. Conf. Ser. 16, 107-112 (2005)

Schuchardt, K., Pancerella, C., Rahn, L.A., Didier, B., Kodeboyina, D., Leahy, D., Myers, J.D., Oluwole, O.O., Pitz, W., Ruscic, B., Song, J., von Laszewski, G., Yang, C.: Portal-based knowledge environment for collaborative science. Concurrency and Computation: Practice and Experience 19, 1703 - 1716 (2007)

Schuster, R., Schuster, S.: Refined algorithm and computer program for calculating all nonnegative fluxes admissible in steady states of biochemical reaction systems with or without some flux rates fixed. Comp. Appl. Biosci. 9, 79–85 (1993)

Schuster, S., Danekar, T., Fell, D.A.: Detection of elementary flux modes in biochemical networks: A promising tool for pathway analysis and metabolic engineering. Trends Biotechnol. 17, 53–60 (1999)

Schuster, S., Hilgetag, C.: On elementary flux modes in biochemical reaction systems at steady state. J. Biol. Syst. 2, 165–182 (1994)

Schuster, S., Hilgetag, C., Woods, J.H., Fell, D.A.: Reaction routes in biochemical reaction systems: Algebraic properties, validated calculation procedure and example from nucleotide metabolism. J. Math. Biol. 45, 153–181 (2002)

Schwer, D.A., Lu, P., Green, W.H.: An adaptive chemistry approach to modeling complex kinetics in reacting flows. Combust. Flame 133, 451-465 (2003a)

Schwer, D.A., Lu, P., Green, W.H., Semiao, V.: A consistent-splitting approach to computing stiff steady-state reacting flows with adaptive chemistry. Combust. Theory Modell. 7, 383-399 (2003b)

Scire, J.J., Dryer, F.L., Yetter, R.A.: Comparison of global and local sensitivity techniques for rate constants determined using complex reaction mechanisms. Int. J. Chem. Kinet. 33, 784-802 (2001)

Scott, S.K.: Chemical Chaos, vol. 24. International Series of Monographs on Chemistry. Clarendon Press, Oxford (1990)

Sedaghat, A.R., Sherman, A., Quon, M.J.: A mathematical model of metabolic insulin signaling pathways. Am J Physiol Endocrinol Metab. 283, E1084-E1101 (2002)

Segel, L.A.: On the validity of the steady-state assumption of enzyme kinetics. Bull. Math. Biol. 50, 579–593 (1988)

Segel, L.A., Slemrod, M.: The quasi-steady-state assumption: a case study in perturbation. SIAM Rev. 31, 446–477 (1989)

Seiler, P., Frenklach, M., Packard, A., Feeley, R.: Numerical approaches for collaborative data processing. Optim. Eng. 7, 459-478 (2006)

Semenoff, N.: On the kinetics of complex reactions. J. Chem. Phys. 7, 683-699 (1939)

Semenov, N.N.: Кинетика сложных гомогенных реакции. Ж. Физ. Хим. 17, 187-214 (1943)

Seressiotis, A., Bailey, J.E.: MPS: An artificially intelligent software system for the analysis and synthesis of metabolic pathways. Biotechnol. Bioeng. 31, 587–602 (1988)

Seshadri, K., Lu, T.F., Herbinet, O., Humer, S.B., Niemann, U., Pitz, W.J., Seiser, R., Law, C.K.: Experimental and kinetic modeling study of extinction and ignition of methyl decanoate in laminar non-premixed flows. Proc. Combust. Inst. 32, 1067-1074 (2009)

Shanks, D.: Non-linear transformations of divergent and slowly convergent sequences and an example from hydrodynamics. Phys. Review 76, 876-876 (1949)

Sheen, D., Wang, H.: Combustion kinetic modeling using multispecies time histories in shock-tube oxidation of heptane. Combust. Flame 158, 645-656 (2011a)

Sheen, D.A., Rosado-Reyes, C.M., Tsang, W.: Kinetics of H atom attack on unsaturated hydrocarbons using spectral uncertainty propagation and minimization techniques. Proc. Combust. Inst. 34, 527-536 (2013)

Sheen, D.A., Wang, H.: The method of uncertainty quantification and minimization using polynomial chaos expansions. Combust. Flame 158, 2358–2374 (2011b)

Sheen, D.A., You, X., Wang, H., Løvås, T.: Spectral uncertainty quantification, propagation and optimization of a detailed kinetic model for ethylene combustion. Proc. Combust. Inst. 32, 535-542 (2009)

Sheen, D.A., Manion, J.A.: Kinetics of the reactions of H and CH3 radicals with n-butane: An experimental design study using reaction network analysis J. Phys. Chem. A, 118, 4929-4941 (2014)

Shenvi, N., Geremia, J., Rabitz, H.: Efficient chemical kinetic modeling through neural network maps J. Chem. Phys. 120, 9942-9951 (2004)

Shi, Y., Ge, H.W., Brakora, J.L., Reitz, R.D.: Automatic chemistry mechanism reduction of hydrocarbon fuels for HCCI engines based on DRGEP and PCA methods with error control. Energy Fuels 24, 1646-1654 (2010a)

Shi, Y., Liang, L., Ge, H.W., Reitz, R.D.: Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes. Combust. Theory Model. 14, 69-89 (2010b)

Shorter, J.A., Ip, P.C., Rabitz, H.A.: An efficient chemical kinetics solver using high dimensional model representation. J. Phys. Chem. A 103, 7192-7198 (1999)

Sikalo, N., Hasemann, O., Schulz, C., Kempf, A., Wlokas, I.: A genetic algorithm-based method for the automatic reduction of reaction mechanisms. Int J Chem. Kinet. 46, 41–59 (2014)

SimBiology: Model, simulate, and analyze biological systems. In: http://www.mathworks.com/products/simbiology/.

Simlab: Software package for uncertainty and sensitivity analysis. Joint Research Centre of the European Commission. http://simlab.jrc.ec.europa.eu (2011).

Singer, M.A., Pope, S.B.: Exploiting ISAT to solve the reaction-diffusion equation. Combust Theory Model 8, 361–383 (2004)

Singer, M.A., Pope, S.B., Najm, H.N.: Operator-splitting with ISAT to model reacting flow with detailed chemistry. Combust. Theory Model. 10, 199-217 (2006)

Singh, S., Powers, J.M., Paolucci, S.: On slow manifolds of chemically reactive systems. J. Chem. Phys. 117, 1482-1496 (2002)

Skodje, R.T., Davis, M.J.: Geometrical simplification of complex kinetic systems. J. Phys. Chem. A 105, 10356-10365 (2001)

Skodje, R.T., Tomlin, A.S., Klippenstein, S.J., Harding, L.B., Davis, M.J.: Theoretical validation of chemical kinetic mechanisms: Combustion of methanol. J. Phys. Chem. A 114, 8286-8301 (2010)

Smallbone, A.J., Bhave, A., Kraft, M., A, D., McDavid, R.: Moving toward establishing more robust and systematic model development for IC engines using process informatics. SAE Paper, 01-0572 (2010)

Smooke, M.D., Rabitz, H., Reuven, Y., Dryer, F.L.: Application of sensitivity analysis to premixed hydrogen-air flames. Combust. Sci. Technol. 59, 295-319 (1988)

Snow, R.M.: A chemical kinetics computer program for homogeneous and free-radical systems of reactions. J. Phys. Chem. 70, 2780-2786 (1966)

Sobol', I.M.: Sensitivity estimates for nonlinear mathematical models. Mat. Model 2, 112-118 (1990)

Sobol', I.M.: Sensitivity analysis for non-linear mathematical models. Math. Model. Comp. Exp. 1, 407-414 (1995)

Sobol', I.M., Kucherenko, S.S.: On global sensitivity analysis of quasi-Monte Carlo algorithms. Monte Carlo Meth. Appl. 11, 83-92 (2005)

Sobol, I.M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math. Comput. Sim. 55, 271-280 (2001)

Sobol, I.M., Kucherenko, S.: Derivative based global sensitivity measures and their link with global sensitivity indices. Math. Comput. Simul. 79, 3009-3017 (2009)

Sobol’, I.M.: On the distribution of points in a cube and the approximate evaluation of integrals. USSR Comput. Math. Math. Phys. 7, 86-112 (1967)

Soyhan, H., Mauss, F., Sorusbay, C.: Chemical kinetic modeling of combustion in internal combustion engines using reduced chemistry. Combust. Sci. Tech. 174, 73–91 (2002)

Sportisse, B.: An analysis of operator splitting techniques in the stiff case. J. Comput. Phys. 161, 140-168 (2000)

Sportisse, B., Djouad, R.: Reduction of chemical kinetics in air pollution modelling. J. Comp. Phys. 164, 354-376 (2000)

Sportisse, B., Djouad, R.: Use of proper Orthogonal Decompositions for the reduction of atmospheric chemistry. J. Geophys. Res. - Atmos. 112, D06303 (2007)

Stagni, A., Cuoci, A., Frassoldati, A., Faravelli, T., Ranzi, E.: Lumping and reduction of detailed kinetic schemes: an effective coupling. Ind. Eng. Chem. Res. 53, 9004–9016 (2014)

Stanford, N.J., Lubitz, T., Smallbone, K., Klipp, E., Mendes, P., Liebermeister, W.: Systematic construction of kinetic models from genome-scale metabolic networks. PLoS ONE 8 (2013)

Stelling, J., Gilles, E.D., Doyle III, F.J.: Robustness properties of the circadian clock architectures. Proc Natl Acad Sci U S A 101, 13210–13125 (2004)

Stevens, W.R., Ruscic, B., Baer, T.: The heats of formation of C₆H₅, C₆H₅⁺, and C₆H₅NO by TPEPICO and active thermochemical tables analysis. J. Phys. Chem. A 114, 13134–13145 (2010)

Stewart, P.H., Larson, C.W., Golden, D.M.: Pressure and temperature dependence of reactions proceeding via a bound complex. 2. Application to 2CH₃ → C₂H₅ + H. Combust. Flame 75, 25-31 (1989)

Stockmayer, W.H.: The steady-state approximation in polymerization kinetics. J. Chem. Phys. 12, 143-144 (1944)

Stolarski, R.S., Butler, D.M., Rundel, R.D.: Uncertainty propagation in a stratospheric model 2. Monte Carlo analysis of imprecisions due to reaction rates. J. Geophys. Res. Oceans 83, 3074–3078 (1978)

Stolarski, R.S., Douglass, A.R.: Sensitivity of an atmospheric photochemistry model to chlorine perturbations including consideration of uncertainty propagation. J. Geophys. Res. Atm. 91, 7853–7864 (1986)

Storlie, C.B., Helton, J.C.: Multiple predictor smoothing methods for sensitivity analysis: Description of techniques. Reliab. Eng. Syst. Safety 93, 28-54 (2008)

Strang, G.: On construction and comparison of difference schemes. SIAM J. Numer. Anal. 5, 506-517 (1968)

Straube, R., Flockerzi, D., Müller, S.C., Hauser, M.J.B.: Reduction of chemical reaction networks using quasi-integrals. J. Phys. Chem. A 109, 441-450 (2005)

Ströhle, J., Myhrvold, T.: Reduction of a detailed reaction mechanism for hydrogen combustion under gas turbine conditions. Combust. Flame 144, 545-557 (2006)

Sun, W.T., Chen, Z., Gou, X.L., Ju, Y.G.: A path flux analysis method for the reduction of detailed chemical kinetic mechanisms Combust. Flame 157, 1298-1307 (2010)

Sundaram, K.M., Froment, G.F.: Accuracy of pseudo-steady-state approximation for radicals in thermal-cracking. Int. J. Chem. Kinet. 10(11), 1189-1193 (1978)

SUNDIALS: SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. In: https://computation.llnl.gov/casc/sundials/.

Sung, C.J., Law, C.K., Chen, J.Y.: Augmented reduced mechanisms for NO emission in methane oxidation. Combust. Flame 125, 906-919 (2001)

Sunnaker, M., Cedersund, G., Jirstrand, M.: A method for zooming of nonlinear models of biochemical systems. BMC Syst. Biol. 5 (2011)

Sunnaker, M., Schmidt, H., Jirstrand, M., Cedersund, G.: Zooming of states and parameters using a lumping approach including back-translation. BMC Syst. Biol. 4 (2010)

Surovtsova, I., Simus, N., Lorenz, T., König, A., Sahle, S., Kumme, U.: Accessible methods for the dynamic time-scale decomposition of biochemical systems. Bioinformatics 25, 2816–2823 (2009)

Sutherland, J.C., Parente, A.: Combustion modeling using principal component analysis. Proc. Combust. Inst. 32, 1563-1570 (2009)

Szabó, Z.G.: Kinetic characterization of complex reaction systems. In: Bamford, C.H., Tipper, C.F.H. (eds.) Comprehensive Chemical Kinetics, vol. 2. Comprehensive chemical kinetics, vol. , pp. 1-80. (1969)

Taing, S., Masri, A.R., Pope, S.B.: pdf calculations of turbulent nonpremixed flames of H₂/CO₂ using reduced chemical mechanisms. Combust. Flame 95, 133-150 (1993)

Tang, Q., Pope, S.B.: Implementation of combustion chemistry by in situ adaptive tabulation of rate-controlled constrained equilibrium manifolds. Proc. Combust. Inst. 29, 1411-1417 (2002)

Tang, Q., Pope, S.B.: A more accurate projection in the rate-controlled constrained-equilibrium method for dimension reduction of combustion chemistry. Combust. Theory Model. 8, 255-279 (2004)

Tang, Q., Xu, J., Pope, S.B.: Probability density function calculations of local extinction and no production in piloted-jet turbulent methane/air flames. Proceedings of the Combustion Institute 28, 133-139 (2000)

Taylor, S.R., Doyle III, F.J., Petzold, L.R.: Oscillator model reduction preserving the phase response: application to the circadian clock. Biophys. J. 95, 1658-1673 (2008)

Tebes-Stevens, C.L., Valocchi, A.J.: Calculation of reaction parameter sensitivity coefficients in multicomponent subsurface transport models. Adv. Water Res. 23, 591-611 (2000)

Temkin, M.I.: The kinetics of some industrial heterogeneous catalytic reactions. Adv Catal. 26, 173-291 (1979)

Tenua: the kinetics simulator for Java. In: http://bililite.com/tenua/.

Tihonov, A.N.: Системы дифференциальных уравнений, содержащие малые параметры при производных. Мат. Сборник 31, 575-586 (1952)

Tomita, M., Hashimoto, K., Takahashi, K., Shimizu T, Matsuzaki Y, Miyoshi F, Saito K, Tanida S, Yugi K, Venter JC, CA., H.: E-CELL: Software Environment for Whole Cell Simulation. Bioinformatics 15, 72-84 (1999)

Tomlin, A., Berzins, M., Ware, J., Smith, J., Pilling, M.J.: On the use of adaptive gridding methods for modelling chemical transport from multi-scale sources. Atmos. Environ. 31, 2945-2959 (1997a)

Tomlin, A.S.: The use of global uncertainty methods for the evaluation of combustion mechanisms. Reliab. Eng. Syst. Safety 91, 1219-1231 (2006)

Tomlin, A.S.: The role of sensitivity and uncertainty analysis in combustion modelling. Proc. Combust. Inst. 34, 159-176 (2013)

Tomlin, A.S., Li, G.Y., Rabitz, H., Tóth, J.: A general-analysis of approximate nonlinear lumping in chemical-kinetics 2. Constrained lumping. J. Chem. Phys. 101, 1188-1201 (1994)

Tomlin, A.S., Pilling, M.J., Turányi, T., Merkin, J.H., Brindley, J.: Mechanism reduction for the oscillatory oxidation of hydrogen: Sensitivity and quasi-steady-state analyses. Combust. Flame 91, 107-130 (1992)

Tomlin, A.S., Turányi, T.: Investigation and improvement of reaction mechanisms using sensitivity analysis and optimization. In: Battin-Leclerc, F., Blurock, E., Simmie, J. (eds.) Development of detailed chemical kinetic models for cleaner combustion. pp. 411-445. Springer, Heidelberg (2013a)

Tomlin, A.S., Turányi, T.: Mechanism reduction to skeletal form and species lumping. In: Battin-Leclerc, F., Blurock, E., Simmie, J. (eds.) Development of detailed chemical kinetic models for cleaner combustion. pp. 447-466. Springer, Heidelberg (2013b)

Tomlin, A.S., Turányi, T., Pilling, M.J.: Mathematical tools for the construction, investigation and reduction of combustion mechanisms. In: Pilling, M.J., Hancock, G. (eds.) Low-temperature combustion and autoignition, vol. 35. Comprehensive chemical kinetics, pp. 293-437. Elsevier, Amsterdam (1997b)

Tomlin, A.S., Whitehouse, L., Lowe, R., Pilling, M.J.: Low-dimensional manifolds in tropospheric chemical systems. Faraday Discussions 120, 125-146 (2001)

Tomlin, A.S., Ziehn, T.: The use of global sensitivity methods for the analysis, evaluation and improvement of complex modelling systems. In: Gorban, A.N., Roose, D. (eds.) Coping with complexity: Model reduction and data analysis, vol. 75. Lecture Notes in Computational Science and Engineering, pp. 9-36. Springer, Berlin Heidelberg (2011)

Tonse, S.R., Moriarty, N.W., Brown, N.J., Frenklach, M.: PRISM: Piece-wise reusable implementation of solution mapping. An economical strategy for chemical kinetics. Israel J. Chem. 39, 97–106 (1999)

Tonse, S.R., Moriarty, N.W., Frenklach, M., Brown, N.J.: Computational economy improvements in PRISM. Int J Chem Kinet. 35, 438-452 (2003)

Tosatto, L., Bennett, B.A.V., Smooke, M.D.: A transport-flux-based directed relation graph method for the spatially inhomogeneous instantaneous reduction of chemical kinetic mechanisms. Combust. Flame 158, 820–835 (2011)

Tosatto, L., Bennett, B.A.V., Smooke, M.D.: Comparison of different DRG-based methods for the skeletal reduction of JP-8 surrogate mechanisms. Combust. Flame 160, 1572-1582 (2013)

Tóth, J., Érdi, P.: A formális reakciókinetika modelljei, problémái és alkalmazásai (The models, problems and applications of formal reaction kinetics), vol. 41. A kémia újabb eredményei. Akadémiai Kiadó, Budapest (1978)

Toth, J., Li, G.Y., Rabitz, H., Tomlin, A.S.: Effect of lumping and expanding on kinetic differential equations. SIAM J. Appl. Math. 57(6), 1531-1556 (1997)

Treviño, C.: Ignition phenomena in H₂/O₂ mixtures. Prog. Astronaut. Aeronautics 131, 19-43 (1991)

Treviño, C., Liñan, A.: Numerical and asymptotic analysis of ignition processes. In: Buckmaster, J., Jackson, T.L., Kumar, A. (eds.) Combustion in high-speed flows. pp. 477-490. Kluwer Academic Publishers, Dordrecht (1994)

Treviño, C., Liñan, A.: Mixing layer ignition of hydrogen. Combust. Flame 103, 129-141 (1995)

Treviño, C., Mendez, F.: Asymptotic analysis of the ignition of hydrogen by a hot plate in a boundary layer flow. Combust. Sci. Technol. 78, 197-216 (1991)

Treviño, C., Mendez, F.: Reduced kinetic mechanism for methane ignition. Proc. Combust. Inst. 24, 121-127 (1992)

Treviño, C., Solorio, F.: Asymptotic analysis of high temperature ignition of CO/H₂/O₂ mixtures. Combust. Flame 86, 285-295 (1991)

Troe, J.: The thermal dissociation/recombination reaction of hydrogen peroxide H₂O₂(+M)=2OH(+M) III. Analysis and representation of the temperature and pressure dependence over wide ranges. Combust. Flame 158, 594–601 (2011)

Tsang, W.: Chemical kinetic data base for propellant combustion. II. Reactions involving CN, NCO, and HNCO. J. Phys. Chem. Ref. Data 21, 753-791 (1992)

Tsang, W., Hampson, R.F.: Chemical kinetic database for combustion chemistry 1. Methane and related compounds. J. Phys. Chem. Ref. Data 15, 1087-1279 (1986)

Turányi, T.: KINAL - A program package for kinetic-analysis of reaction-mechanisms. Comput. Chem. 14, 253-254 (1990a)

Turányi, T.: Reduction of large reaction mechanisms. New J. Chem. 14, 795-803 (1990b)

Turányi, T.: Sensitivity analysis of complex kinetic systems. Tools and applications. J. Math. Chem. 5, 203-248 (1990c)

Turányi, T.: Parametrization of reaction mechanisms using orthonormal polynomials. Comput. Chem. 18, 45-54 (1994)

Turányi, T.: Application of repro-modelling for the reduction of combustion mechanisms. Proc. Combust. Inst. 25, 948-955 (1995)

Turányi, T.: Applications of sensitivity analysis to combustion chemistry. Reliab. Engng Syst. Saf. 57, 41-48 (1997)

Turányi, T., Bérces, T., Vajda, S.: Reaction rate analysis of complex kinetic systems. Int. J. Chem. Kinet. 21, 83-99 (1989)

Turányi, T., Györgyi, L., Field, R.J.: Analysis and simplification of the GTF model of the Belousov-Zhabotinsky reaction. J. Phys. Chem. 97, 1931-1941 (1993a)

Turányi, T., Nagy, T., Zsély, I.G., Cserháti, M., Varga, T., Szabó, B.T., Sedyó, I., Kiss, P.T., Zempléni, A., J., C.H.: Determination of rate parameters based on both direct and indirect measurements. Int. J. Chem. Kinet. 44, 284-302 (2012)

Turányi, T., Rabitz, H.: Local methods In: Saltelli, A., Chan, K., Scott, E.M. (eds.) Sensitivity analysis. pp. 81-99. Wiley, Chichester (2000)

Turányi, T., Tomlin, A.S.: Storage of chemical kinetic information. In: Battin-Leclerc, F., Blurock, E., Simmie, J. (eds.) Development of detailed chemical kinetic models for cleaner combustion. pp. 485-512. Springer, Heidelberg (2013)

Turányi, T., Tomlin, A.S., Pilling, M.J.: On the error of the quasi-steady-state approximation. J. Phys. Chem. 97, 163-172 (1993b)

Turányi, T., Tóth, J.: Comments to an article of Frank-Kamenetskii on the quasi-steady-state approximation. Acta Chim. Hung. - Models In Chemistry 129(6), 903-907 (1992)

Turányi, T., Zalotai, L., Dóbé, S., Bérces, T.: Effect of the uncertainty of kinetic and thermodynamic data on methane flame simulation results Phys. Chem. Chem. Phys 4, 2568-2578 (2002)

Turco, R.P., Whitten, R.C.: Comparison of several computational techniques for solving some common aeronomic problems. J. Geophys. Res. 79, 3179-3185 (1974)

Turns, S.R.: An introduction to combustion. Concepts and applications, second ed. McGraw-Hill, Boston (2000)

Tzafriri, A.R., Edelman, E.R.: The total quasi-steady-state approximation is valid for reversible enzyme kinetics. J. Theor. Biol. 226, 303–313 (2004)

Tzafriri, A.R., Edelman, E.R.: On the validity of the quasi-steady state approximation of bimolecular reactions in solution. J. Theor. Biol. 233, 343-350 (2005)

Ugarte, S., Gao, Y., Metghalchi, H.: Application of the maximum entropy principle in the analysis of a non-equilibrium chemically reacting mixture. Int. J. Thermodynamics 8, 43–53 (2005)

Vajda, S., Rabitz, H.: Parametric sensitivity and self-similarity in thermal explosion theory. Chem. Engng Sci. 47, 1063-1078 (1992)

Vajda, S., Rabitz, H., Yetter, R.A.: Effects of thermal coupling and diffusion on the mechanism of H₂ oxidation in steady premixed laminar flames. Combust. Flame 82, 270-297 (1990)

Vajda, S., Turányi, T.: Principal component analysis for reducing the Edelson-Field-Noyes model of the Belousov-Zhabotinsky reaction. J. Phys. Chem. 90, 1664-1670 (1986)

Vajda, S., Valkó, P., Turányi, T.: Principal component analysis of kinetic models. Int. J. Chem. Kinet. 17, 55-81 (1985)

Vallabhajosyula, R.R., Chickarmane, V., Sauro, H.M.: Conservation analysis of large biochemical networks. Bioinformatics 22, 346-353 (2006)

Valorani, M., Creta, F., Donato, F., Najm, H.N., Goussis, D.A.: Skeletal mechanism generation and analysis for n-heptane with CSP. Proc. Combust. Inst. 31, 483-490 (2007)

Valorani, M., Creta, F., Goussis, D., Lee, J., Najm, H.: An automatic procedure for the simplification of chemical kinetic mechanisms based on CSP. Combust. Flame 146, 29–51 (2006)

Valorani, M., Creta, F., Goussis, D.A., Najm, H.N., Lee, J.C.: Chemical kinetics mechanism simplification via CSP. In: Bathe, K.J. (ed.) Computational Fluid and Solid Mechanics 2005a, pp. 900-904

Valorani, M., Goussis, D.A.: Explicit time-scale splitting algorithm for stiff problems: auto-ignition of gaseous mixtures behind a steady shock. J. Comput. Phys. 169, 44–79 (2001)

Valorani, M., Goussis, D.A., Creta, F., Najm, H.N.: Higher order corrections in the approximation of low dimensional manifolds and the construction of simplified problems with the CSP method. J.Comput. Phys. 209, 754-786 (2005b)

Valorani, M., Najm, H.N., Goussis, D.A.: CSP analysis of a transient flame-vortex interaction: time scales and manifolds. Combust. Flame 134, 35-53 (2003)

Van Delden, H., Seppelt, R., White, R., Jakeman, A.J.: A methodology for the design and development of integrated models for policy support. Environ. Model. Softw. 26, 266-279 (2011)

Van Geem, K.M., Pyl, S.P., Marin, G.B., Harper, M.R., Green, W.H.: Accurate high-temperature reaction networks for alternative fuels: Butanol isomers. Ind. Eng. Chem. Res. 49, 10399-10420 (2010)

Van Geem, K.M., Reyniers, M.-F., Marin, G.B., Song, J., Green, W.H., Matheu, D.M.: Automatic reaction network generation using RMG for steam cracking of n-hexane. AIChE Journal 52, 718-730 (2006)

Van Oijen, J.A., Bastlaans, R.J.M., De Goey, L.P.H.: Low-dimensional manifolds in direct numerical simulations of premixed turbulent flames. Proc. Combust. Inst. 31, 1377-1384 (2007)

Van Oijen, J.A., de Goey, L.P.H.: Modelling of premixed laminar flames using Flamelet Generated Manifolds. Comb. Sci.Tech. 161, 113-137 (2000)

Van Oijen, J.A., de Goey, L.P.H.: Modelling of premixed counterflow flames using the flamelet-generated manifold method. Combust. Theory Modell. 6, 463-478 (2002)

Van Oijen, J.A., Lammers, F.A., de Goey, L.P.H.: Modeling of complex premixed burner systems by using flamelet-generated manifolds. Combust. Flame 127, 2124-2134 (2001)

Varga, L., Szabó, B., Zsély, I.G., Zempléni, A., Turányi, T.: Numerical investigation of the uncertainty of Arrhenius parameters. J. Math. Chem. 49, 1798-1809 (2011)

Varga, T., Nagy, T., Olm, C., Zsély, I.G., Pálvölgyi, R., Valkó, É., Vincze, G., Cserháti, M., Curran, H.J., Turányi, T.: Optimization of a hydrogen combustion mechanism using both direct and indirect measurements. Proc. Combust. Inst. in press (2015)

Varga, T., Zsély, I.G., Turányi, T., Bentz, T., Olzmann, M.: Kinetic analysis of ethyl iodide pyrolysis based on shock tube measurements. Int. J. Chem. Kinet. 46, 295–304 (2014)

Venkatech, P.K., Chang, A.Y., Dean, A.M., Cohen, M.H., Carr, R.W.: Parameterization of pressure- and temperature-dependent kinetics in multiple well reactions. AIChE J. 43, 1331-1340 (1997)

Verhoeven, L.M., Ramaekers, W.J.S., van Oijen, J.A., de Goey, L.P.H.: Modeling non-premixed laminar co-flow flames using flamelet-generated manifolds. Combust. Flame 159, 230-241 (2012)

Vervisch, P.E., Colin, O., Michel, J.-B., Darabiha, N.: NO Relaxation Approach (NORA) to predict thermal NO in combustion chambers. Combust. Flame 158, 1480-1490 (2011)

Vol'pert, A.I.: Дифференциальные уравнения на графах. Мат. Сборник 88, 578-588 (1972)

Vol'pert, A.I., Hudjaev, S.I.: Analysis in classes of discontinuous functions and equations of mathematical physics. Martinus Nijhoff, Dordrecht (1985)

Volterra, V.: Variazioni e fluttuazioni del numero d’individui in specie animali conviventi. Mem. Acad. Lincei Roma 2, 31-113 (1926)

von Hohenbalken, B., Clarke, B.L., Lewis, J.E.: Least distance methods for the frame of homogeneous equation systems. J. Comp. Appl. Math. 19, 231–241 (1987)

Vora, N., Daoutidis, P.: Nonlinear model reduction of chemical reaction systems. AIChE Journal 47, 2320–2332 (2001)

Waage, P., Guldberg, C.M.: Studies concerning affinity. Forhandlinger: Videnskabs-Selskabet i Christiana 35 (1864)

Wagner, A.: Robustness and evolvability in living systems. Princeton studies in complexity. Princeton University Press, (2013)

Wang, H., Frenklach, M.: Detailed reduction of reaction mechanisms for combustion modeling. Combust. Flame 87, 365-370 (1991)

Wang, H., Sheen, D.A.: Combustion kinetic model uncertainty quantification, propagation and minimization. Prog. Energy Combust. Sci. 47, 1–31 (2015)

Wang, H., Yao, M., Reitz, R.D.: Development of a reduced primary reference fuel mechanism for internal combustion engine combustion simulations. Energy Fuels 27, 7843−7853 (2013)

Wang, H., You, X., Joshi, A.V.D., S G, Laskin, A., Egolfopoulos, F., Law, C.K.: USC Mech Version II. High-temperature combustion reaction model of H₂/CO/C1-C4 compounds. http://ignis.usc.edu/USC_Mech_II.htm. (2007)

Wang, L., Milford, J.B., Carter, W.P.L.: Reactivity estimates for aromatic compounds. Part 2. Uncertainty in incremental reactivities. Atmos. Environ. 34, 4349-4360 (2000a)

Wang, L., Milford, J.B., Carter, W.P.L.: Reactivity estimates for aromatic compounds. Part I. Uncertainty in chamber-derived parameters. Atm. Environm. 34, 4337-4348 (2000b)

Wang, L.G., Fox, R.O.: Application of in situ adaptive tabulation to CFD simulation of nano-particle formation by reactive precipitation. Chem. Eng. Sci. 58, 4387-4401 (2003)

Wang, Q.-D.: Skeletal mechanism generation for high-temperature combustion of H₂/CO/C₁−C₄ hydrocarbons. Energy Fuels 27, 4021−4030 (2013)

Wang, S.W., Balakrishnan, S., Georgopoulos, P.: Fast equivalent operational model of tropospheric alkane photochemistry. AIChE Journal 51, 1297-1303 (2005)

Wang, S.W., Georgopoulos, P.G., Li, G., Rabitz, H.: Computationally efficient atmospheric chemical kinetic modeling by means of high dimensional model representation (HDMR). Lect. Note Comput. Sci. 2179, 326-333 (2001)

Wang, W., Rogg, B.: Premixed ethylene/air and ethane/air flames: Reduced mechanisms based on inner iteration. In: Peters, N., Rogg, B. (eds.) Reduced kinetic mechanisms for applications in combustion systems, vol. Monograph 15. Lecture Notes in Physics Monographs, pp. 82-107. Springer-Verlag, New York (1993)

Warnatz, J.: Rate coefficients in the C/H/O system. In: Gardiner, W.C. (ed.) Combustion chemistry. pp. 197-361. Springer, New York (1984)

Warnatz, J.: Resolution of gas phase and surface combustion chemistry into elementary reactions. Proc. Combust. Inst. 24, 553-579 (1992)

Warnatz, J., Maas, U., Dibble, R.W.: Combustion. Physical and chemical fundamentals, modeling and simulation, experiments, pollutant formation, 4th ed. Springer, Berlin Heidelberg (2006)

Warth, V., Battin-Leclerc, F., Fournet, R., Glaude, P.A., Côme, G.M., Scacchi, G.: Computer based generation of reaction mechanisms for gas-phase oxidation. Comput. Chem. 24, 541-560 (2000)

Watson, L.A., Shallcross, D.E., Utembe, S.R., Jenkin, M.E.: A Common Representative Intermediates (CRI) mechanism for VOC degradation. Part 2: Gas phase mechanism reduction. Atmos. Environment 42, 7196-7204 (2008)

Weekman, V.W., Jr.: Lumps, models, and kinetics in practice. AIChE Monogr. Ser. 11 75, 3-29 (1979)

Wei, J., Kuo, J.C.W.: A lumping analysis in monomolecular reaction systems. Ind. Eng. Chem.Fundam. 8, 114–123 (1969)

Westbrook, C.K., Naik, C.V., Herbinet, O., Pitz, W.J., Mehl, M., Sarathy, S.M., Curran, H.J.: Detailed chemical kinetic reaction mechanisms for soy and rapeseed biodiesel fuels. Combust. Flame 158, 742-755 (2011)

Westbrook, C.K., Pitz, W.J., Curran, H.J.: Chemical kinetic modeling study of the effects of oxygenated hydrocarbons on soot emissions from diesel engines. J. Phys. Chem. A 110, 6912-6922 (2006)

Whitehouse, L.E., Tomlin, A.S., Pilling, M.J.: Systematic reduction of complex tropospheric chemical mechanisms using sensitivity and time-scale analyses. Atmos. Chem. Phys. Discuss. 4, 3721-3783 (2004a)

Whitehouse, L.E., Tomlin, A.S., Pilling, M.J.: Systematic reduction of complex tropospheric chemical mechanisms, Part I: sensitivity and time-scale analyses. Atmos. Chem. Phys. 4, 2025-2056 (2004b)

Whitehouse, L.E., Tomlin, A.S., Pilling, M.J.: Systematic reduction of complex tropospheric chemical mechanisms, Part II: Lumping using a time-scale based approach. Atmos. Chem. Phys. 4, 2057-2081 (2004c)

Whitten, G.Z., Hogo, H., Killus, J.P.: The Carbon Bond Mechanism: A condensed kinetic mechanism for photochemical smog analysis techniques to a photochemical ozone model. Env. Sci. Technol. 14, 690-700 (1980)

Wiechert, W.: Modeling and simulation: tools for metabolic engineering. Journal of Biotechnology 94, 37-63 (2002)

Wilkins, A.K., Barton, P.I., Tidor, B.: The Per2 negative feedback loop sets the period in the mammalian circadian clock mechanism. PLoS Comput. Biol. 3, 2476-2486 (2007)

Wilkinson, S.J., Benson, N., Kell, D.B.: Proximate parameter tuning for biochemical networks with uncertain kinetic parameters. Mol. Biosyst. 4, 74-97 (2008)

WINPP/XPP: In: http://www.math.pitt.edu/~bard/classes/wppdoc/readme.htm.

Wolfram, S.: Mathematica Language. http://www.wolfram.com/mathematica/. Accessed April, 2014

Wu, Z., Qiao, X., Huang, Z.: A criterion based on computational singular perturbation for the construction of a reduced mechanism for dimethyl ether oxidation. J. Serb. Chem. Soc. 78, 1177–1188 (2013)

Wyss, G., Jorgensen, K.: A user’s guide to LHS: Sandia’s Latin hypercube sampling software. In. US Department of Energy, Sandia National Laboratories, (1998)

Xia, A.G., Michelangeli, D.V., Makar, P.A.: Mechanism reduction for the formation of secondary organic aerosol for integration into a 3-dimensional regional air quality model: alpha-pinene oxidation system. Atmos. Chem. Phys. 9, 4341-4362 (2009)

Xia, J., Wishart, D.S.: MetPA: a web-based metabolomics tool for pathway analysis and visualization. Bioinformatics 26, 2342-2344 (2010)

Xie, N., Battaglia, F., Fox, R.O.: Simulations of multiphase reactive flows in fluidized beds using in situ adaptive tabulation. Combust. Theory Model. 8, 195-209 (2004)

Xu, J., Pope, S.B.: PDF calculations of turbulent nonpremixed flames with local extinction. Combust. Flame 123, 281-307 (2000)

Xu, M., Fan, Y., Yuan, J.: Simplification of the mechanims of NO_x formation in a CH₄/air combustion system. Int. J. Energy Res. 23, 1267-1276 (1999)

Xuan, Y., Blanquart, G.: A flamelet-based a priori analysis on the chemistry tabulation of polycyclic aromatic hydrocarbons in non-premixed flames. Combust Flame 161, 1516–1525 (2014)

Yang, B., Pope, S.B.: An investigation of the accuracy of manifold methods and splitting schemes in the computational implementation of combustion chemistry. Combust. Flame 112, 16-32 (1998a)

Yang, B., Pope, S.B.: Treating chemistry in combustion with detailed mechanisms -In situ adaptive tabulation in principal directions - premixed combustion. Combust. Flame 112, 85-112 (1998b)

Yang , H., Ren, Z., Lu, T., Goldin, G.M.: Dynamic adaptive chemistry for turbulent flame simulations. Combust. Theory Modelling 17, 167-183 (2013)

Yannacopoulos, A.N., Tomlin, A.S., Brindley, J., Merkin, J.H., Pilling, M.J.: The use of algebraic sets in the approximation of inertial manifolds and lumping in chemical kinetic systems. Physica D 83, 421-449 (1995)

Yannacopoulos, A.N., Tomlin, A.S., Brindley, J., Merkin, J.H., Pilling, M.J.: The error of the quasi steady-state approximation in spatially distributed systems. Chem. Phys. Lett. 248, 63-70 (1996a)

Yannacopoulos, A.N., Tomlin, A.S., Brindley, J., Merkin, J.H., Pilling, M.J.: Error propagation in approximations to reaction-diffusion-advection equations. Phys. Lett. A 223, 82-90 (1996b)

Yarwood, G., Rao, S., Yocke, M., Whitten, G.: Updates to the Carbon Bond chemical mechanism: CB05. In. Final Report to the US EPA, RT-0400675, (2005)

Yoneda, Y.: A computer program for the analysis, creation and estimation of generalised reactions: GRACE. Bulletin of the Chemical Society of Japan 52, 8-14 (1979)

Yoo, C.S., Lu, T.F., Chen, J.H., Law, C.K.: Direct numerical simulations of ignition of a lean n-heptane/air mixture with temperature inhomogeneities at constant volume: Parametric study. Combust. Flame 158, 1727–1741 (2011)

Yoo, C.S., Luo, Z., Lu, T.F., Kim, H., Chen, J.H.: DNS study of the ignition of a lean iso-octane/air mixture under HCCI and SACI conditions. Proc. Combust. Inst. 34, 2985–2993 (2012)

You, X.Q., Packard, A., Frenklach, M.: Process informatics tools for predictive modeling: Hydrogen combustion. Int. J. Chem. Kinet. 44, 101-116 (2012)

You, X.Q., Russi, T., Packard, A., Frenklach, M.: Optimization of combustion kinetic models on a feasible set. Proc. Combust. Inst. 33, 509-516 (2011)

Yue, H., Brown, M., He, F., Jia, J., Kell, D.B.: Sensitivity analysis and robust experimental design of a signal transduction pathway system. Int. J. Chem. Kinet. 40, 730-741 (2008)

Yuryev, A., Mulyukov, Z., Kotelnikova, E., Maslov, S., Egorov, S., Nikitin, A., Daraselia, N., Mazo, I.: Automatic pathway building in biological association networks. BMC Bioinformatics 7, 171 (2006)

Zádor, J.: Uncertainty analysis of reaction kinetic models. PhD Thesis. (2006)

Zádor, J., Taatjes, C.A., Fernandes, R.X.: Kinetics of elementary reactions in autoignition chemistry. Prog. Energy Combust. Sci. 37, 371 (2011)

Zádor, J., Turányi, T., Wirtz, K., Pilling, M.J.: Uncertainty analysis backed investigation of chamber radical sources in the European Photoreactor (EUPHORE). J. Atmos. Chem. 55, 147-166 (2006a)

Zádor, J., Wagner, V., Wirtz, K., Pilling, M.J.: Quantitative assessment of uncertainties for a model of tropospheric ethene oxidation using the European Photoreactor (EUPHORE). Atmos. Environ. 39, 2805-2817 (2005a)

Zádor, J., Zsély, I.G., Turányi, T.: Investigation of the correlation of sensitivity vectors of hydrogen combustion models. Int. J. Chem. Kinet. 36, 238-252 (2004)

Zádor, J., Zsély, I.G., Turányi, T.: Local and global uncertainty analysis of complex chemical kinetic systems. Reliab. Eng. Syst. Saf. 91, 1232-1240 (2006b)

Zádor, J., Zsély, I.G., Turányi, T., Ratto, M., Tarantola, S., Saltelli, A.: Local and global uncertainty analyses of a methane flame model. J. Phys. Chem. A 109, 9795-9807 (2005b)

Zagaris, A., Kaper, H.G., Kaper, T.J.: Analysis of the computational singular perturbation reduction method for chemical kinetics. J. Nonlinear Sci. 14, 59-91 (2004)

Zak, D.E., Stelling, J., Doyle III, F.J.: Sensitivity analysis of oscillatory (bio)chemical systems. Comput. Chem. Eng. 29, 663-673 (2005)

Zambon, A.C., Chelliah, H.K.: Explicit reduced reaction models for ignition, flame propagation, and extinction of C₂H₄/CH₄/H₂ and air systems. Combust. Flame 150, 71-91 (2007)

Zhabotinsky, A.M.: Периодический процесс окисления малоновой кислоты растворе (исследование кинетики реакции Белоусова). Биофизика 9, 306-311 (1964)

Zhang, H.X., Dempsey, J., W P , Goutsias, J.: Probabilistic sensitivity analysis of biochemical reaction systems. J. Chem. Phys. 131, 094101 (2009)

Zhang, P., Law, C.K.: A fitting formula for the falloff curves of unimolecular reactions. Int.J.Chem. Kinet. 41, 727-734 (2009)

Zhang, P., Law, C.K.: A fitting formula for the falloff curves of unimolecular reactions, II: Tunneling effects. Int.J.Chem. Kinet. 43, 31-42 (2011)

Zhang, S., Androulakis, I.P., Ierapetritou, M.G.: A hybrid kinetic mechanism reduction scheme based on the on-the-fly reduction and quasi-steady-state approximation. Chem. Eng. Sci. 93, 150–162 (2013)

Zhang, S., Broadbelt, L.J., Androulakis, I.P., Ierapetritou, M.G.: Reactive flow simulation based on the integration of automated mechanism generation and on-the-fly reduction. Energy Fuels 28, 4801-4811 (2014)

Zhang, Y., Bischof, C., Easter, R., Wu, P.: Sensitivity analysis of a mixed-phase chemical mechanism using automatic differentiation. . J. Geophys. Res. 103 953-979. (1998)

Zhao, S., Ovadia, J., Liu, X., Zhang, Y.-T., Nie, Q.: Operator splitting implicit integration factor methods for stiff reaction-diffusion-advection systems. J. Comput. Phys. 230, 5996–6009 (2011)

Zhao, W., Chen, D., Hu, S.: Differential fraction-based kinetic model for simulating hydrodesulfurization process of petroleum fraction. Comput. Chem. 26, 141-148 (2002)

Zheng, X.L., Lu, T.F., Law, C.K.: Experimental counterflow ignition temperatures and reaction mechanisms of 1,3-butadiene. Proc. Combust. Inst. 31, 367–375 (2007)

Zhou, D.D.Y., Davis, M.J., Skodje, R.T.: Multitarget global sensitivity analysis of n‑butanol combustion. J. Phys. Chem. A 117, 3569−3584 (2013a)

Zhou, Z.J., Lü, Y., Wang, Z.H., Xu, Y.W., Zhou, J.H., Cen, K.F.: Systematic method of applying ANN for chemical kinetics reduction in turbulent premixed combustion modeling. Chin. Sci. Bull. 58, 486-492 (2013b)

Zhu, J., Zhang, Y.-T., Newman, S., Alber, M.: Application of discontinuous Galerkin methods for reaction-diffusion systems in developmental biology. J. Sci. Comput. 40, 391-418 (2009)

Zi, Z.: SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models. Bioinformatics 27, 1028–1029 (2011a)

Zi, Z.: Sensitivity analysis approaches applied to systems biology models. IET Systems Biology 5, 336-346 (2011b)

Zi, Z., Klipp, E.: SBML-PET: a Systems Biology Markup Language-based parameter estimation tool. Bioinformatics 22, 2704–2705 (2006)

Zi, Z., Zheng, Y., Rundell, A.E., Klipp, E.: SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool. BMC Bioinf. 9, 342 (2008)

Ziehn, T.: Development and application of global sensitivity analysis methods in environmental and safety engineering. University of Leeds (2008)

Ziehn, T., Dixon, N.S., Tomlin, A.S.: The effects of parametric uncertainties in simulations of a reactive plume using a Lagrangian stochastic model. Atmos. Environ. 43, 5978-5988 (2009a)

Ziehn, T., Hughes, K.J., Griffiths, J.F., Porter, R., Tomlin, A.S.: A global sensitivity study of cyclohexane oxidation under low temperature fuel-rich conditions using HDMR methods. Combust. Theor. Model. 13, 589-605 (2009b)

Ziehn, T., Tomlin, A.S.: Global sensitivity analysis of a 3D street canyon model - part I: the development of high dimensional model representations. Atm. Environ. 42, 1857-1873 (2008a)

Ziehn, T., Tomlin, A.S.: A global sensitivity study of sulphur chemistry in a premixed methane flame model using HDMR. Int. J. Chem. Kinet. 40, 742-753 (2008b)

Ziehn, T., Tomlin, A.S.: GUI-HDMR - A software tool for global sensitivity analysis of complex models. Environ. Model. Soft. 24, 775-785 (2009)

Zuniga, M.M., Kucherenko, S., Shah, N.: Metamodelling with independent and dependent inputs. Computer Physics Communications 184(6), 1570-1580 (2013). doi:10.1016/j.cpc.2013.02.005

Zsély, I.G., Nagy, T., Simmie, J.M., Curran, H.J.: Reduction of a detailed kinetic model for the ignition of methane/propane mixtures at gas turbine conditions using simulation error minimization methods. Combust. Flame 158, 1469-1479 (2011)

Zsély, I.G., Turányi, T.: Investigation and reduction of two methane combustion mechanisms. Archivum Combustionis 21, 173-177 (2001)

Zsély, I.G., Turányi, T.: The influence of thermal coupling and diffusion on the importance of reactions: The case study of hydrogen-air combustion. PCCP 5, 3622-3631 (2003)

Zsély, I.G., Varga, T., Nagy, T., Cserháti, M., Turányi, T., Peukert, S., Braun-Unkhoff, M., Naumann, C., Riedel, U.: Determination of rate parameters of cyclohexane and 1-hexene decomposition reactions. Energy 43, 85-93 (2012)

Zsély, I.G., Zádor, J., Turányi, T.: Similarity of sensitivity functions of reaction kinetic models. J. Phys. Chem. A 107, 2216-2238 (2003)

Zsély, I.G., Zádor, J., Turányi, T.: On the similarity of the sensitivity functions of methane combustion models. Combust. Theory Modell. 9, 721-738 (2005a)

Zsély, I.G., Zádor, J., Turányi, T.: Uncertainty analysis backed development of combustion mechanisms. Proc. Combust. Inst. 30, 1273-1281 (2005b)

Zsély, I.G., Zádor, J., Turányi, T.: Uncertainty analysis of NO production during methane combustion. Int. J. Chem. Kinet. 40, 754-768 (2008)

Typo found:

p.52
original: Ranzi, E., Frassoldati, A., Granata, S., Faravelli, T.: Wide-range kinetic modeling study of the pyrolysis, partial oxidation, and combustion of heavy n-alkanes. Ind. Eng. Chem. Res. 44, 5170-5183 (2004)
corrected: Ranzi, E., Frassoldati, A., Granata, S., Faravelli, T.: Wide-range kinetic modeling study of the pyrolysis, partial oxidation, and combustion of heavy n-alkanes. Ind. Eng. Chem. Res. 44, 5170-5183 (2004)

p. 293
original: Bilger, R.W.: On reduced mechanisms
corrected: Bilger, R.W., Stårner, S.H., Kee, R.J.: On reduced mechanisms

p. 297
original: Gicquel, O., Ribert, O., Darabiha, N., Veynante, D.: Tabulation of complex chemistry based on self-similar behavior of laminar premixed flames. Combust. Flame 146, 649–664 (2006)
corrected: Ribert, G., Gicquel, O., Darabiha, N., Veynante, D.: Tabulation of complex chemistry based on self-similar behavior of laminar premixed flames. Combust. Flame 146, 649–664 (2006)

Content

Index

References