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Fast approximations of exponential and logarithm functions combined with efficient storage/retrieval for combustion kinetics calculations

机译:指数和对数函数的快速逼近,结合有效的存储/检索,可进行燃烧动力学计算

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We developed two approaches to speed up combustion chemistry simulations by reducing the amount of time spent computing exponentials, logarithms, and complex temperature-dependent kinetics functions that heavily rely on them. The evaluation of these functions is very accurate in 64-bit arithmetic, but also slow. Since these functions span several orders of magnitude in temperature space, some of this accuracy can be traded with greater solution speed, provided that the governing ordinary differential equation (ODE) solver still grants user-defined solution convergence properties. The first approach tackled the exp() and log() functions, and replaced them with fast approximations which perform bit and integer operations on the exponential-based IEEE-754 floating point number machine representation. The second approach addresses complex temperature-dependent kinetics functions via storage/retrieval. We developed a function-independent piecewise polynomial approximation method with the following features: it minimizes table storage requirements, it is not subject to ill-conditioning over the whole variable range, it is of arbitrarily high order n 0, and is fully vectorized. Formulations for both approaches are presented; and their performance assessed against zero-dimensional reactor simulations of hydrocarbon fuel ignition delay, with reaction mechanisms ranging from 10 to 10(4) species. The results show that, when used concurrently, both methods allow global speed-ups of about one order of magnitude even with an already highly-optimized sparse analytical Jacobian solver. The methods also demonstrate that global error is within the integrator's requested accuracy, and that the solver's performance is slightly positively affected, i.e., a slight reduction in the number of timesteps per integration is seen. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:我们开发了两种方法,通过减少花费在指数,对数和高度依赖它们的复杂温度相关动力学函数上的计算时间来加快燃烧化学模拟。这些功能的评估在64位算术中非常准确,但也很慢。由于这些函数在温度空间上跨越几个数量级,因此只要控制型微分方程(ODE)求解器仍具有用户定义的解决方案收敛性,就可以以更高的求解速度来交换某些精度。第一种方法解决了exp()和log()函数,并用快速逼近代替了它们,它们在基于指数的IEEE-754浮点数机器表示上执行位和整数运算。第二种方法是通过存储/检索解决复杂的温度相关动力学函数。我们开发了一种与函数无关的分段多项式逼近方法,该方法具有以下特征:最大限度地减少了表存储需求,在整个变量范围内均不受不良影响,其n> 0任意高,并且已完全矢量化。介绍了两种方法的配方;并根据碳氢燃料点火延迟的零维反应堆模拟评估了它们的性能,反应机理范围从10到10(4)种。结果表明,当同时使用时,即使使用已经高度优化的稀疏解析雅可比解算器,这两种方法也可以使全局速度提高约一个数量级。这些方法还证明了全局误差在积分器要求的精度之内,并且求解器的性能受到了一些积极的影响,即,每次积分的时间步数有所减少。 (C)2018年燃烧研究所。由Elsevier Inc.出版。保留所有权利。

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