Invention Application
- Patent Title: SIMULATING FLUID FLOW WITH NEURAL NETWORKS
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Application No.: US17581452Application Date: 2022-01-21
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Publication No.: US20220237350A1Publication Date: 2022-07-28
- Inventor: Bryce D. CONDUIT , Jian Cheng WONG , Anthony B. PHIPPS , Piotr ZACHARZEWSKI , Chin Chun OOI , Qi QI , Yi WANG , My Ha DAO , Pao-Hsiung CHIU
- Applicant: ROLLS-ROYCE plc
- Applicant Address: GB London
- Assignee: ROLLS-ROYCE plc
- Current Assignee: ROLLS-ROYCE plc
- Current Assignee Address: GB London
- Priority: GB2101096.2 20210127
- Main IPC: G06F30/28
- IPC: G06F30/28 ; G06F30/15

Abstract:
A neural network is trained for, and may be used in, the simulation of the fluid flow through a domain around an object geometry. A first training process for the neural network includes training (902) the network on a first set of encodings of pre-computed computational fluid dynamics (CFD) simulations for object geometries and associated boundary conditions. The first training process uses a first loss function that evaluates an error between the network output and the pre-computed CFD simulations. A second training process is then carried out which includes training (905) the network on a second set of encodings of object geometries and associated boundary conditions. The second training process uses a second loss function that evaluates an error between the network output and a set of fluid dynamics conditions.
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