A Novel Approach for Efficient Storage and Retrieval of Tabulated Chemistry in Reactive Flow Simulations

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• 关键词：Memory management ; Tabulated chemistry ; Flamelet ; CFD ; Polynomial
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10164
• 期：1
• 页码：82-95
• 丛书名：High-Performance Scientific Computing
• ISBN：978-3-319-53862-4
• 卷排序：10164

文摘

Turbulent combustion is a typical example of a multi-scale problem, coupling different ranges of time and length scales of the flow field and the chemical reactions. Due to scale separation and the availability of suitable coupling procedures, tabulated chemistry approaches have emerged as an effective method for describing turbulence-chemistry interaction (TCI). However, different flame configurations, complex fuels and multiphase flows, among other things, increase both the number of tabulated variables and the dimension of the database, and thus the overall size. With larger database sizes, the requirements for computing time and memory management have become a crucial issue for CFD applications. In the present study, the novel flatkernel approach for efficient memory management at reduced computational cost is developed. This new software-library-based approach uses polynomial fitting to represent the database. The resulting functions are generated as source code and compiled in a shared library, taking advantage of automatic compiler optimization. Since the shared library is also memory managed by the operating system, the flatkernel approach leads to reduced memory and computing time requirements in the coupled CFD application. The approach developed is applied for scale-resolving Large Eddy Simulations (LES), coupled with the flamelet-progress variable approach (LES-FPV) for combustion modeling of a reactive jet in a cross flow configuration. The evaluation of the simulations is focused on a comparison between the novel method and an existing approach, with respect to memory and computing time requirements.