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Dynamic adaptive acceleration of chemical kinetics with consistent error control

机译:具有恒定误差控制的化学动力学动态自适应加速

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The incorporation of detailed chemistry in combustion simulations is challenging due to the large number of chemical species and the wide range of chemical timescales. The performance of acceleration methods such as tabulation/retrieval strategies may deteriorate dramatically when large variation in the accessed composition space is present. In this study, a dynamic adaptive acceleration method (DAAM) is proposed, in which in situ adaptive tabulation (ISAT) or dynamic adaptive chemistry (DAC) is dynamically selected for chemistry integration based on the encountered composition inhomogeneity. The principle component analysis (PCA) of instantaneous representative compositions is employed to identify a low-dimensional subspace, in which the composition inhomogeneity of the computational cells is quantified through reconstructing the histogram of composition. ISAT is invoked for cells being in composition regions with high cell/particle numbers to avoid unnecessary tabulations and DAC is employed for the remaining ones by invoking on-the-fly reduction to generate small skeletal mechanisms for local thermo-chemical conditions and therefore accelerates the chemistry integration. A heuristic approach that dynamically adjusts the DAC reduction threshold based on the user-defined ISAT error tolerance has been proposed for DAAM, which enables a single, intuitive error control parameter for the combined use of these two methods and more importantly enables rigorous local error control. DAAM have been demonstrated in internal combustion engine (ICE) model simulations and premixed charge compression ignition (PCCI) engine simulations of n-heptane/air mixture, respectively. DAAM can improve the acceleration performance up to 50% compared to standalone ISAT while maintaining the same level of accuracy in temperature and species. It also shows advantage in speedup performance over the fixed ISAT-DAC method at the same level of accuracy. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:由于大量的化学种类和广泛的化学时间表,将详细的化学方法纳入燃烧模拟具有挑战性。当所访问的构图空间存在较大变化时,诸如制表/检索策略之类的加速方法的性能可能会急剧下降。在这项研究中,提出了一种动态自适应加速方法(DAAM),其中根据遇到的成分不均匀性,动态选择就地自适应制表法(ISAT)或动态自适应化学方法(DAC)进行化学整合。瞬时代表性成分的主成分分析(PCA)用于识别低维子空间,在该空间中,通过重建成分直方图来量化计算单元的成分不均匀性。对处于高细胞/粒子数的组成区域中的细胞调用ISAT,以避免不必要的列表,并通过动态减少以生成局部热化学条件的小骨架机制,将DAC用于剩余的列表。化学整合。已针对DAAM提出了一种启发式方法,该方法可根据用户定义的ISAT误差容限动态调整DAC降低阈值,该方法可为组合使用这两种方法提供单个直观的误差控制参数,更重要的是,可进行严格的局部误差控制。 DAAM已分别在正庚烷/空气混合物的内燃机(ICE)模型仿真和预混合充气压缩点火(PCCI)发动机仿真中得到证明。与独立的ISAT相比,DAAM可以将加速性能提高多达50%,同时保持相同水平的温度和物种精度。与固定的ISAT-DAC方法相比,它还显示出在相同精度水平上的加速性能优势。 (C)2018年燃烧研究所。由Elsevier Inc.出版。保留所有权利。

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