The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 29, 2022

Filed:

Jun. 25, 2019
Applicants:

GM Global Technology Operations Llc, Detroit, MI (US);

Ut-battelle, Llc, Oak Ridge, TN (US);

Inventors:

Jian Chen, Oak Ridge, TN (US);

Hui Huang, Oak Ridge, TN (US);

Zhili Feng, Oak Ridge, TN (US);

Blair Carlson, Ann Arbor, MI (US);

Hui-Ping Wang, Warren, MI (US);

Wayne Cai, Troy, MI (US);

Assignees:

GM Global Technology Operations LLC, Detroit, MI (US);

UT-Battelle, LLC, Oak Ridge, TN (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 30/23 (2020.01); G06F 17/11 (2006.01); G06T 19/00 (2011.01); G06T 15/00 (2011.01);
U.S. Cl.
CPC ...
G06F 30/23 (2020.01); G06F 17/11 (2013.01); G06T 15/005 (2013.01); G06T 19/00 (2013.01);
Abstract

A method for accelerating an explicit finite element analysis (FEA) simulation of a modeled system or process includes performing an initial iteration of the FEA simulation according to a baseline time interval via an FEA computing network, and calculating a criteria ratio of a predetermined set of scaling criteria for the modeled system or process. The method includes determining a time-scaling factor using the criteria ratio via the FEA computing network as a function of the criteria ratio, and then applying the time-scaling factor to the baseline time interval to generate a scaled time interval. The scaled time interval accelerates simulation time of the FEA simulation. The method includes performing a subsequent iteration of the explicit FEA simulation at the scaled time interval using the FEA computing network. The process continues for subsequent iterations, with the time-scaling factor adapting with each iteration.


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