论文标题
用TensorFlow在OpenFOAM中部署深度学习
Deploying deep learning in OpenFOAM with TensorFlow
论文作者
论文摘要
我们概述了OpenFOAM中数据科学模块的开发，该模块允许对训练有素的深度学习架构进行通用预测任务的现场部署。该模块是用TensorFlow C API构建的，并将其集成到OpenFOAM中作为可以在运行时链接的应用程序。值得注意的是，我们的公式排除了与神经网络体系结构类型（即卷积，完全连接等）相关的任何限制。这允许对实际CFD问题进行复杂的神经体系结构的潜在研究。此外，提议的模块概述了通往计算流体动力学和机器学习的开源，统一和透明框架的路径。
We outline the development of a data science module within OpenFOAM which allows for the in-situ deployment of trained deep learning architectures for general-purpose predictive tasks. This module is constructed with the TensorFlow C API and is integrated into OpenFOAM as an application that may be linked at run time. Notably, our formulation precludes any restrictions related to the type of neural network architecture (i.e., convolutional, fully-connected, etc.). This allows for potential studies of complicated neural architectures for practical CFD problems. In addition, the proposed module outlines a path towards an open-source, unified and transparent framework for computational fluid dynamics and machine learning.
