As detailed chemical mechanisms are becoming viable for large scale simulations, knowledge and control of the uncertainty correlated to the kinetic parameters are becoming crucial to ensure accurate numerical predictions. A flexible toolbox for the optimization of chemical kinetics has therefore been developed in this work. The toolbox is able to use different optimization methodologies, as well as it can handle a large amount of uncertain parameters simultaneously. It can also handle experimental targets from different sources: Batch reactors, Plug Flow Reactors, Perfectly Stirred Reactors, Rapid Compression Machines and Laminar Flame Speeds. This work presents the different features of this toolbox together with five different test cases which exemplifies these features. Program summary: Program Title: OptiSMOKE++ CPC Library link to program files: https://doi.org/10.17632/tvjky2n8md.1 Licensing provisions: GPLv3 Programming language: C++ Nature of problem: Optimization of uncertain kinetic parameters with respect to experimental data. Solution method: Using the optimization capabilities of DAKOTA [1], and solving reacting systems with OpenSMOKE++ [2], OptiSMOKE++ determines the optimal combination of specified kinetic parameters, within their uncertainty, and with respect to the experimental data. References [1] B. M. Adams, M. S. Ebeida, M. S. Eldred, G. Geraci, J. D. Jakeman, K. A. Maupin, J. A. Monoscheke, L. P. Swiler, J. A. Stephens, D. M. Vigil, T. M. Wildey, W. J. Bohno, K. R. Dalbey, J. P. Eddy, R. W. Hooper, K. T. Hu, P. D. Hough, E. M. Ridgwat, A. Rushdi, Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.5 User's Manual (2014). [2] A. Cuoci, A. Frassoldati, T. Faravelli, E. Ranzi, OpenSMOKE++: An object-oriented framework for the numerical modeling of reactive systems with detailed kinetic mechanisms, Computer Physics Communications 192 (2015) 237-264. doi:10.1016/j.cpc.2015.02.014.

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

Bertolino A.;Cuoci A.;Faravelli T.;Frassoldati A.;
2021-01-01

Abstract

As detailed chemical mechanisms are becoming viable for large scale simulations, knowledge and control of the uncertainty correlated to the kinetic parameters are becoming crucial to ensure accurate numerical predictions. A flexible toolbox for the optimization of chemical kinetics has therefore been developed in this work. The toolbox is able to use different optimization methodologies, as well as it can handle a large amount of uncertain parameters simultaneously. It can also handle experimental targets from different sources: Batch reactors, Plug Flow Reactors, Perfectly Stirred Reactors, Rapid Compression Machines and Laminar Flame Speeds. This work presents the different features of this toolbox together with five different test cases which exemplifies these features. Program summary: Program Title: OptiSMOKE++ CPC Library link to program files: https://doi.org/10.17632/tvjky2n8md.1 Licensing provisions: GPLv3 Programming language: C++ Nature of problem: Optimization of uncertain kinetic parameters with respect to experimental data. Solution method: Using the optimization capabilities of DAKOTA [1], and solving reacting systems with OpenSMOKE++ [2], OptiSMOKE++ determines the optimal combination of specified kinetic parameters, within their uncertainty, and with respect to the experimental data. References [1] B. M. Adams, M. S. Ebeida, M. S. Eldred, G. Geraci, J. D. Jakeman, K. A. Maupin, J. A. Monoscheke, L. P. Swiler, J. A. Stephens, D. M. Vigil, T. M. Wildey, W. J. Bohno, K. R. Dalbey, J. P. Eddy, R. W. Hooper, K. T. Hu, P. D. Hough, E. M. Ridgwat, A. Rushdi, Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.5 User's Manual (2014). [2] A. Cuoci, A. Frassoldati, T. Faravelli, E. Ranzi, OpenSMOKE++: An object-oriented framework for the numerical modeling of reactive systems with detailed kinetic mechanisms, Computer Physics Communications 192 (2015) 237-264. doi:10.1016/j.cpc.2015.02.014.
2021
Chemical kinetics
Combustion
Optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1168925
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