Artificial Neural Networks for Chemistry Representation in Numerical Simulation of the Flamelet-Based Models for Turbulent Combustion

Zhixun Xia,Likun Ma,Honglan Huang,Yifan Duan,Jincai Huang,Yanghe Feng,Jiarui Zhang

doi:10.1109/access.2020.2990943

Zhixun Xia, Likun Ma + Show 5 more

Open Access

https://doi.org/10.1109/access.2020.2990943

Copy DOI

Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 8	License type: CC BY 4.0

Affiliation: National University of Defense Technology

Abstract

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.

Highlights

Combustion system is widely used in the field of energy, transportation industries and aerospace, which has brought rapid socio-economic development
Based on how to address the challenge posed by the coupling between chemical reactions and molecular diffusion, the current mainstream combustion models can be divided into Transported probability function (TPDF) models and Flamelet-based models [4]
At the position where x/d = 20, the temperature prediction error is shortened to 40%. The season for this improvement may be that the Artificial neural network (ANN) is able to provide more accurate chemical reaction results over the linear interpolation method used in tabulation techniques, and this advantage is more significant in the flame ignition position where the gradients of scalar properties are relatively large

Summary

Introduction

Combustion system is widely used in the field of energy, transportation industries and aerospace, which has brought rapid socio-economic development. It triggered a series of serious environmental issues, such as resources and pollution problems. The flamelet models assume that all chemical reactions happen on a thin layer, for which only the changes perpendicular to the flame front is important, the other two dimensions are negligible.

Methods

Results

Conclusion