화학공학소재연구정보센터
Combustion and Flame, Vol.168, 342-364, 2016
Degree of Disequilibrium analysis for automatic selection of kinetic constraints in the Rate-Controlled Constrained-Equilibrium method
The Rate-Controlled Constrained-Equilibrium (RCCE) model reduction scheme for chemical kinetics provides acceptable accuracies with a number of differential equations much lower than the number of species in the underlying Detailed Kinetic Model (DKM). To yield good approximations, however, the method requires accurate identification of the rate controlling constraints. So far, a drawback of the RCCE scheme has been the absence of a fully automatable and systematic procedure that is capable of identifying the best constraints for a given range of thermodynamic conditions and a required level of approximation. In this paper, we propose a new methodology for such identification based on a simple algebraic analysis of the results of a preliminary simulation of the underlying DKM, which is focused on the behaviour of the degrees of disequilibrium (DoD) of the individual chemical reactions. The new methodology is based on computing an Approximate Reduced Row Echelon Form of the Actual Degrees of Disequilibrium (ARREFADD) with respect to a preset tolerance level. An alternative variant is to select an Approximate Singular Value Decomposition of the Actual Degrees of Disequilibrium (ASVDADD). Either procedure identifies a low dimensional subspace in the DoD space, from which the actual DoD traces do not depart beyond a fixed distance related to the preset tolerance (ARREFADD methodology) or to the first neglected singular value of the matrix of DoD traces (ASVDADD methodology). The effectiveness and robustness of the method is demonstrated for the case of a very rapid supersonic nozzle expansion of the products of hydrogen and methane oxycombustion and for the case of methane/oxygen ignition. The results are in excellent agreement with DKM predictions. For both variants of the method, we provide a simple Matlab code implementing the proposed constraint selection algorithm. (C) 2016 The Combustion Institute. Published by Elsevier Inc. All rights reserved.