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An Efficient Chemical Kinetics Solver Using High Dimensional Model Representation

机译:使用高维模型表示的高效化学动力学求解器

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A high dimensional model representation (HDMR) technique is introduced to capture the input-output behavior of chemical kinetic models. The HDMR expresses the output chemical species concentrations as a rapidly convergent hierarchical correlated function expansion in the input variables. In this paper, the input variables are taken as the species concentrations at time t_i and the output is the concentrations at time t_i + #delta#, where #delta# can be much larger than conventional integration time steps. A specially designed set of model runs is performed to determine the correlated functions making up the HDMR. The resultant HDMR can be used to (i) identify the key input variables acting independently or cooperatively on the output, and (ii) create a high speed fully equivalent operational model (FEOM) serving to replace the original kinetic model and its differential equation solver. A demonstration of the HDMR technique is presented for stratospheric chemical kinetics. The FEOM proved to give accurate accurate and stable chemical concentrations out to long times of many years. In addition, the FEOM was found to be orders of magnitude faster than a conventional stiff equation solver. This computational acceleration should have significance in many chemical kinetic applications.
机译:引入了高维模型表示(HDMR)技术来捕获化学动力学模型的输入输出行为。 HDMR将输出化学物质浓度表示为输入变量中快速收敛的层次相关函数扩展。在本文中,将输入变量作为时间t_i处的物种浓度,输出为时间t_i +#delta#处的浓度,其中#delta#可能比常规积分时间步长大得多。执行一组专门设计的模型运行,以确定组成HDMR的相关功能。生成的HDMR可用于(i)识别独立或协同作用于输出的关键输入变量,以及(ii)创建一个高速完全等效操作模型(FEOM),以代替原始动力学模型及其微分方程求解器。对平流层化学动力学的HDMR技术进行了演示。经证明,FEOM可以长期提供准确,准确和稳定的化学浓度。此外,发现FEOM比常规的刚性方程求解器快几个数量级。这种计算上的加速度在许多化学动力学应用中应具有重要意义。

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