International Business Machines Corporation
Machine learning based fluid simulation

Last updated:

Abstract:

Fluid motion is simulated by performing a first fluid simulation without reflecting all of a plurality of forces acting on a fluid, to obtain a first velocity of the fluid at a current time step; estimating a velocity residue at the current time step by inputting a calculated velocity from the previous time step into a regression model. The regression model is trained to relate velocity obtained by performing a second fluid simulation reflecting the plurality of forces acting on the fluid to a difference between the velocity obtained by performing the first fluid simulation and the velocity obtained by performing the second fluid simulation; and calculating a velocity of the fluid at the current time step by adding the first velocity at the current time step and the velocity residue at the current time step.

Status:
Grant
Type:

Utility

Filling date:

11 Jan 2019

Issue date:

8 Mar 2022