Computational and Multi-scale Mechanics Group

Crash, Defense, Aerospace, Healthcare, HPC

CFD, Multiphysics, EM, MetalForming, DropTest

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Automotive industry is experiencing a transformative change in car research and engineering, from a traditional mechanical world to digital assimilation and reinvention. A lot of emerging technologies such as machine learning, 3D printing, multi-scale and reduced-order modeling, interactive safety systems and autonomous driving are targeting the automotive industry for this digital transformation. On the other hand, the reinforcement in regulations with respect to environmental and crashworthiness standards will continue to raise car costs as well as increase design complexity when modern automobiles such as electric and self-driving cars effectively come to dominate the market.

An advanced CAE tool integrating the data in the linkage of process-structure-property-assembly-performance is a time and cost effective enabler, a means for facilitating this digital transformation while boosting the energy economy and improving safety and performance in modern automobile design and analysis.

The Process-Structure-Property-Assembly-Performance chain

in the multi-scale and multi-physics car manufacturing and safety simulation

Provide advanced CAE tools to help customers meet design goal

Environmental and safety regulations: new material and manufacturing
Electric vehicle, autonomous driving: integration of multi-physics

Crashworthiness, Model reduction, User interface, Digital twins

Design optimization

Corrosion, Fatigue, ...

Meso-macro concurrent modeling

Design optimization

Simulation data

Design optimization

Residual stress/strain, defect, ...

Deformation and failure analysis

Joints
Base materials
Solids and shells

High performance
Light-weighted

Metal alloy, CFRP, 3D printing

Material characterization and design

Mechanistic machine learning
Training data
Efficient solver

Micro-meso linking

RVE / SVE database

Mapping data / AI