In this work, several novel algorithms for the numerical simulation of homogeneous gas-phase combustion chemistry are introduced and investigated. In the first instance, stochastic methods for the numerical solution of systems of ordinary differential equations (ODEs) are developed based on the theory of Markov pure-jump processes. By establishing a correspondence principle between stochastic and deterministic schemes, further algorithms of both types are obtained. In particular, a scheme for the deterministic direct simulation of chemical reactions is devised. All methods under consideration have in common that they are explicit, and hence conceptually very simple and easy to implement.For three of the proposed algorithms, detailed numerical studies of some of their properties such as efficiency and convergence are performed for the high-temperature isobaric homogeneous gas-phase combustion of various hydrocarbon fuels. In addition, the new algorithms are compared in terms of performance to each other and to some widespread conventional ODE-solver packages for stiff systems.
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In this work, several novel algorithms for the numerical simulation of homogeneous gas-phase combustion chemistry are introduced and investigated. In the first instance, stochastic methods for the numerical solution of systems of ordinary differential equations (ODEs) are developed based on the theory of Markov pure-jump processes. By establishing a correspondence principle between stochastic and deterministic schemes, further algorithms of both types are obtained. In particular, a scheme for the deterministic direct simulation of chemical reactions is devised. All methods under consideration have in common that they are explicit, and hence conceptually very simple and easy to implement. For three of the proposed algorithms, detailed numerical studies of some of their properties such as efficiency and convergence are performed for the high-temperature isobaric homogeneous gas-phase combustion of various hydrocarbon fuels. In addition, the new algorithms are compared in terms of performance to each other and to some widespread conventional ODE-solver packages for stiff systems.
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Kartoniert / Broschiert. Condición: New. In this work, several novel algorithms for thenumerical simulation of homogeneous gas-phasecombustion chemistry are introduced andinvestigated. In the first instance, stochasticmethods for the numerical solution of systems ofordinary differential equations . Nº de ref. del artículo: 4954868
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this work, several novel algorithms for thenumerical simulation of homogeneous gas-phasecombustion chemistry are introduced andinvestigated. In the first instance, stochasticmethods for the numerical solution of systems ofordinary differential equations (ODEs) are developedbased on the theory of Markov pure-jump processes.By establishing a correspondence principle betweenstochastic and deterministic schemes, furtheralgorithms of both types are obtained. Inparticular, a scheme for the deterministic directsimulation of chemical reactions is devised. Allmethods under consideration have in common that theyare explicit, and hence conceptually very simple andeasy to implement. For three of the proposedalgorithms, detailed numerical studies of some oftheir properties such as efficiency and convergenceare performed for the high-temperature isobarichomogeneous gas-phase combustion of varioushydrocarbon fuels. In addition, the new algorithmsare compared in terms of performance to each otherand to some widespread conventional ODE-solverpackages for stiff systems. Nº de ref. del artículo: 9783639072921
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Taschenbuch. Condición: Neu. Explicit Simulation Methods for Combustion Chemistry | Stochastic and Deterministic Numerical Algorithms and their Relationship | Sebastian Mosbach | Taschenbuch | Kartoniert / Broschiert | Englisch | 2013 | VDM Verlag Dr. Müller | EAN 9783639072921 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Nº de ref. del artículo: 101752950
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