CAE Performance Prediction Using Machine Learning Model Based On Historical Data

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CAE Performance Prediction Using Machine Learning Model Based On Historical Data

CAE Performance Prediction Using Machine Learning Model Based On Historical Data

Rongali, Praveen / Tangudu, Srinivas Patro

Machine Learning applications are developed to disrupt product design methodology across all industries. Every design engineer would like to optimize his design at the concept stage only considering a few critical and essential load cases. The major challenge for the design engineer has not much simulation expertise required to prepare the CAE model, apply material properties, load case, solve and post-process to understand the CAE performance. Even, when the engineer has CAE expertise, it will take a considerable amount of time to prepare the CAE model, solve and post-process it.

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Title :

CAE Performance Prediction Using Machine Learning Model Based On Historical Data

Additional title:

Sae Technical Papers

Contributors:

Rongali, Praveen (author) / Tangudu, Srinivas Patro (author)

Conference:

Symposium on International Automotive Technology ; 2021

Published in:

Sae Technical Paper Series

Publication date :

2021-09-22

ISSN :

2688-3627 , 0148-7191

DOI :

https://doi.org/10.4271/2021-26-0401

Type of media :

Conference paper

Type of material :

Print

Language :

English

Keywords :

CAD, CAM, and CAE , Optimization , Simulation and modeling , Materials properties , Design processes , Machine learning

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