- 期刊
Research on Turbulence Calculation Model based on Machine Learning
摘要
With the continuous development of the information age, machine learning technology has been continuously improved and applied in various aspects. Especially in the petroleum industry, it has become common to use computational fluid dynamics (CFD) technology to study multiphase flow problems. Due to the great development of machine learning, the fitting speed and accuracy of this technology are accelerated in the process of modeling and analysis. CFD technology consists of pre-processing, solver and post-processing. The solver stage is the core of CFD technology, and turbulence model analysis is the most valuable part in this stage, which has great room for improvement. This paper starts from turbulence analysis, based on machine learning, adds filters before iterative values are introduced into turbulence model, extracts similar features, and removes redundancy, and also puts forward the prospect of machine learning and turbulence model research.
參考文獻
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