Computational fluid dynamics acceleration method and device, equipment and storage medium

Abstract

The invention provides a computational fluid dynamics acceleration method and device, equipment, a storage medium and a program product, and relates to the field of artificial intelligence, in particular to a deep learning technology. The implementation mode of the variational Bayesian neural network training method comprises the following steps: inputting a real solution of a partial differential equation of computational fluid dynamics (CFD) at a t moment into a variational Bayesian neural network to obtain an interpolation coefficient vector at the t moment; calculating a k-order partial derivative at the t moment based on the interpolation coefficient vector at the t moment; based on the k-order partial derivative at the t moment, solving a prediction solution of the partial differential equation of the CFD at the t + [delta]t moment; calculating the loss based on the predicted solution at the t + [delta]t moment and the true solution at the t + [delta]t moment; and adjusting parameters of the variational Bayesian neural network based on the loss. The variational Bayesian neural network trained by the implementation mode can be used for learning interpolation coefficient vectors in CFD calculation, and required high-precision training sets are reduced based on prior knowledge, so that the effect of accelerating CFD calculation under a small data volume is achieved.

Description

technical field [0001] The present disclosure relates to the field of artificial intelligence, in particular to deep learning technology. Background technique [0002] FCC (Fluid Catalytic Cracking, Fluid Catalytic Cracking) process is an important conversion process in petroleum refining, used to produce important chemical raw materials such as gasoline, diesel oil, and light olefins. The CFD (Computational Fluid Dynamics, Computational Fluid Dynamics) simulation of the FCC reaction process helps to understand the flow and reaction behavior in the FCC reactor, assists in the design and optimization of FCC process equipment, and ultimately guides industrial production and realizes virtual regulation and amplification. [0003] However, although the CFD simulation can better reveal the flow and reaction behavior in the industrial FCC riser reactor, there is a lack of examples of using the same method to realize the simulation scale-up from the small laboratory to the industri...

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Problems solved by technology

[0003] However, although the CFD simulation can better reveal the flow and reaction behavior in the industrial FCC riser reactor, there is a lack of examples of using the same method to realize the simulation scale-up from the small laboratory to the industrial reactor, which reflects the current FCC theoretical model and Simulation technology is far from being able to replace experiments

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