Artificial Neural Networks for Chemistry Representation in Numerical Simulation of the Flamelet-Based Models for Turbulent Combustion
Artificial Neural Networks for Chemistry Representation in Numerical Simulation of the Flamelet-Based Models for Turbulent Combustion
复制标题
基于小火焰的湍流燃烧模型数值模拟中化学表示的人工神经网络
DOI：
10.1109/access.2020.2990943
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
Huang Jincai
中科院分区：
文献类型：
--
作者：
Zhang Jiarui;Huang Honglan;Xia Zhixun;Ma Likun;Duan Yifan;Feng Yanghe;Huang Jincai
湍流燃烧是现代生活中许多能量转换系统的关键过程之一。为了提高燃烧效率和抑制污染物的排放，学者们对湍流火焰进行了大量的研究。首次将人工神经网络（ANN）用于火焰面生成流形（FGM）模型中火焰面库的存储和插值，其中采用欧拉随机场（ESF）模型直接考虑控制变量的概率密度函数。该模型已在OpenFOAM中实现，并通过Sandia Flame D的模拟进行了验证，考虑了详细的化学反应机理。通过对温度和主要组分质量分数的数值模拟结果与实验测量结果的对比，验证了所提出的ANN-ESFFGM模型的准确性。通过使用人工神经网络来表征化学反应，新模型的火焰模拟精度高于原ESFFGM模型，特别是在点火位置的预测。随着随机场数目的增加，新湍流燃烧模型的模拟精度不断提高，直到随机场数目达到一定值。此外，过高的FGM工作台分辨率限制了数值模拟精度的提高。
Turbulent combustion is one of the key processes in many energy conversion systems in modern life. In order to improve combustion efficiency and suppress emission of pollutants, many efforts have been made by scholars to investigate turbulent flames. In the present study, Artificial neural network (ANN) was first employed for the storage and interpolation of the flamelet library in flamelet generated manifolds (FGM) model, in which Eulerian stochastic field (ESF) model was used to directly consider the probability density function of the control variables. This new model had been implemented in OpenFOAM and was validated by simulation of the Sandia Flame D under consideration of the detailed chemical reaction mechanism. By comparing the results of numerical simulations and experimental measurements of the temperature and the mass fraction of main components, the accuracy of the proposed ANN-ESFFGM model was verified. Through the use of ANNs to characterize the chemical reactions, the flame simulation accuracy of the new model is higher than that of the original ESFFGM model, especially in the prediction of the ignition position. With the increase in the number of stochastic fields, the simulation accuracy of the new turbulent combustion model is continuously improved until a certain value of stochastic fields was reached. Moreover, excessively high FGM table resolution has limited improvement in numerical simulation accuracy.