CAE Performance Prediction Using Machine Learning Model Based On Historical Data 2021-26-0401
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.
Citation: Tangudu, S. and Rongali, P., "CAE Performance Prediction Using Machine Learning Model Based On Historical Data," SAE Technical Paper 2021-26-0401, 2021, https://doi.org/10.4271/2021-26-0401. Download Citation
Author(s):
Srinivas Patro Tangudu, Praveen Rongali
Affiliated:
Altair Engineering, Altair Engineering India Pvt Ltd
Pages: 9
Event:
Symposium on International Automotive Technology
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Design processes
Machine learning
CAD, CAM, and CAE
Materials properties
Simulation and modeling
Optimization
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