A stoichiometric method for reducing simulation cost of chemical kinetic models

Mathematical models for chemically reacting systems have high degrees of freedom (very large) and are computationally expensive to analyse. In this discussion, we present and analyse a model reduction method that is based on stoichiometry and mass balances. This method can significantly reduce the high degrees of freedom of such systems. Numerical simulations are undertaken to validate and establish efficiency of the method. A practical example of acid mine drainage is used as a test case to demonstrate the efficacy of the procedure. Analytical results show that the stoichiometrically-reduced model is consistent with the original large model, and numerical simulations demonstrate that the method can accelerate convergence of the numerical schemes in some cases.AEA acknowledges support from the Pilot Bursary of the University of Pretoria, the African Institute of Mathematical Sciences and University of Stellenbosch. MKB is grateful to the African Institute for Mathematical Sciences (AIMS) for hosting him while finalising this work. This work is also supported in part by the National Research Foundation of South Africa (Grant number: 93099 and 93476).http://www.elsevier.com/locate/com/pchemeng2019-04-06hj2018Mathematics and Applied Mathematic

A stoichiometric method for reducing simulation cost of chemical kinetic models

Mathematical models for chemically reacting systems have high degrees of freedom (very large) and are computationally expensive to analyse. In this discussion, we present and analyse a model reduction method that is based on stoichiometry and mass balances. This method can significantly reduce the high degrees of freedom of such systems. Numerical simulations are undertaken to validate and establish efficiency of the method. A practical example of acid mine drainage is used as a test case to demonstrate the efficacy of the procedure. Analytical results show that the stoichiometrically-reduced model is consistent with the original large model, and numerical simulations demonstrate that the method can accelerate convergence of the numerical schemes in some cases.AEA acknowledges support from the Pilot Bursary of the University of Pretoria, the African Institute of Mathematical Sciences and University of Stellenbosch. MKB is grateful to the African Institute for Mathematical Sciences (AIMS) for hosting him while finalising this work. This work is also supported in part by the National Research Foundation of South Africa (Grant number: 93099 and 93476).http://www.elsevier.com/locate/com/pchemeng2019-04-06hj2018Mathematics and Applied Mathematic