使用TensorFlow在OpenFOAM中部署深度学习
Deploying deep learning in OpenFOAM with TensorFlow
摘要：
我们概述了OpenFOAM中数据科学模块的开发，该模块允许在现场部署经过训练的深度学习架构，用于通用预测任务。该模块使用TensorFlow C API构建，并作为可在运行时链接的应用程序集成到OpenFOAM中。值得注意的是，我们的公式排除了与神经网络架构类型相关的任何限制（即，卷积的、全连接的等等）。这使得复杂的神经架构的实际CFD问题的潜在研究。此外，拟议的模块概述了一条通往计算流体动力学和机器学习的开源、统一和透明框架的道路。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
