Accelerating Fluid Flow Prediction 1000X with Deep Learning - A Case Study
AI/Machine Learning/Deep Learning
Clouds and Distributed Computing
TimeTuesday, June 18th2:30pm - 2:52pm CEST
DescriptionSolving fluid flow problems using computational fluid dynamics (CFD, here OpenFOAM) is demanding both in terms of computing power and simulation time, and requires deep expertise in CFD. In this project, together with partners Renumics and Advania Data Centers, an Artificial Neural Network (ANN) has been applied to predicting the fluid flow given only the shape of the object that is to be simulated. The goal is to apply an ANN to solve fluid flow problems to significantly decrease time-to-solution while preserving much of the accuracy of a traditional CFD solver. Creating a large number of simulation samples is paramount to let the neural network learn the dependencies between simulated design and the flow field around it.
President of TheUberCloud