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In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.

Learning impact of CAD geometry change on finite element analysis results

Devdikar, Gaurav (1); Pohl, Thorsten (1); Strang, Daniel (1); Schleich, Benjamin (2)

Type:
Papers
DS 145: Proceedings of the DESIGN2026 19th International Design Conference
Year:
2026
Editor:
Štorga, M.; Škec, S.; Martinec, T.; Marjanović, D.; Pavković, N.
Author:
Devdikar, Gaurav (1); Pohl, Thorsten (1); Strang, Daniel (1); Schleich, Benjamin (2)
Series:
DESIGN
Institution:
1: Stellantis, Germany; 2: Technical University of Darmstadt, Germany
Page(s):
3235-3244
DOI number:
10.1017/pds.2026.10681
ISSN:
2732-527X (Online)
Abstract:
This study examines how CAD geometry variations affect finite element (FE) crash simulations for automotive front rail assembly and motivate the use of combined impact measures that better reflect the physical response. Based on these insights, we outline a machine learning formulation that links geometric modifications to their simulation effects. The study centers on geometric representation, employing UV‑based graph encodings to capture local shape changes and provide the basis for advancing and validating the full prediction pipeline.
Keywords:
computer-aided design (CAD), computer-aided engineering (CAE), artificial intelligence (AI), geometric deep learning, UV map
DESIGN2026 - The 19th International Design Conference
Conferences

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