...
首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >The optimisation of reaction rate parameters for chemical kinetic modelling of combustion using genetic algorithms
【24h】

The optimisation of reaction rate parameters for chemical kinetic modelling of combustion using genetic algorithms

机译:基于遗传算法的燃烧化学动力学模型反应速率参数优化

获取原文
获取原文并翻译 | 示例
           

摘要

A general inversion procedure for determining the optimum rate coefficients for chemical kinetic schemes based upon limited net species production data is presented. The objective of the optimisation process is to derive rate parameters such that the given net species production rates at various conditions are simultaneously achieved by searching the parameter space of the rate coefficients in the generalised Arrhenius form of the reaction rate mechanisms. Thus, the goal is to both match the given net species production rates and subsequently ensure the accurate prediction of net species production rates over a wide range of conditions. We have retrieved the reaction rate data using an inversion technique whose minimisation process is based on the Darwinian principle of survival of the fittest which has inspired a class of algorithms known as genetic algorithms. The excellent results presented here from our initial study are based upon the recovery of reaction rate coefficients for hydrogenitrogen/oxygen flames. The successful identification of the reaction rate parameters which correspond to product species measurement data from a sequence of such experiments clearly suggests that the progression onto other chemical kinetic schemes and the optimisation of higher-order hydrocarbon schemes can now be realised. The results of this study therefore demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behaviour for fuels where the reaction rate coefficients are not known with any confidence and, subsequently, accurately predict emission characteristics, stable species concentrations and flame characterisation. Such predictive capabilities are of paramount im- portance in a wide variety of industries.
机译:介绍了基于有限的净物种生产数据确定化学动力学方案最佳速率系数的通用反演程序。优化过程的目的是得出速率参数,以便通过以反应速率机制的广义Arrhenius形式搜索速率系数的参数空间,从而同时实现各种条件下给定的净物种生产速率。因此,目标是既要匹配给定的净物种生产率,又要确保在广泛的条件下准确预测净物种生产率。我们已经使用一种反演技术检索了反应速率数据,该技术的最小化过程基于优胜劣汰的达尔文主义生存原理,这激发了一类称为遗传算法的算法。从我们的初步研究中得出的出色结果是基于氢/氮/氧火焰反应速率系数的恢复。从一系列此类实验中成功鉴定出与产物种类测量数据相对应的反应速率参数,清楚地表明,现在可以实现向其他化学动力学方案的发展以及高级烃方案的优化。因此,这项研究的结果表明,遗传算法的反演过程具有评估燃料燃烧行为的能力,其中反应速率系数没有任何可信度,因此可以准确地预测排放特性,稳定的物种浓度和火焰表征。在许多行业中,这种预测能力至关重要。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号