Altair > Case Studies > Improving Crash Simulations with High-Performance Computing: A Case Study of PSA Peugeot Citroën

Improving Crash Simulations with High-Performance Computing: A Case Study of PSA Peugeot Citroën

Technology Category

Analytics & Modeling - Digital Twin / Simulation
Analytics & Modeling - Predictive Analytics

Applicable Industries

Automotive
Life Sciences

Applicable Functions

Product Research & Development
Sales & Marketing

Use Cases

Digital Twin
Virtual Reality

Services

System Integration
Testing & Certification

About The Customer

PSA Peugeot Citroën is the second largest carmaker in Europe, recording sales and revenue of €54 billion in 2013. With its world-renowned brands, DS, Peugeot and Citroën, PSA sold 2.8 million vehicles worldwide in 2013, of which 42% were sold outside Europe. PSA is a European leader in terms of CO2 emissions, with an average of 115.9 grams of CO2/km in 2013. The company has sales operations in 160 countries and is also involved in financing activities (Banque PSA Finance) and automotive equipment (Faurecia).

The Challenge

PSA Peugeot Citroën, the second largest carmaker in Europe, faced a significant challenge in meeting increasingly stringent automotive regulations that demanded lower CO2 emission levels. This required the carmaker to decrease the design structure mass by using materials with a higher strength-to-weight ratio. However, introducing new materials into the design process was complex; design rules and numerical tools had to evolve to understand the characteristics of these materials and evaluate potential failures. There was a risk of delaying production awaiting reliable design direction from simulation, or having to redesign a part late in the design cycle. Furthermore, due to the large, nonlinear deformations involved in simulating crash or rupture events, proper material failure criteria were essential to results accuracy. To improve its knowledge in assessing predictive rupture models, and to identify a viable solution for testing ruptures on a massive scale, PSA collaborated with Altair, Ecole Polytechnique Laboratoire de Mécanique des Solides (LMS) and PRACE.

The Solution

Altair engineers ported RADIOSS, the market-leading analysis solver for crash simulation in Altair’s HyperWorks CAE software suite, to Bullxmpi for the Curie supercomputer allocated to the study. This porting included the optimization of the setup of RADIOSS under Bullxmpi to obtain ideal performance. The efficiency of the solution was evaluated and improved using industrial car crash models ranging from 1 to 10 million elements. Two specific models were developed to study rupture of a B-pillar component with mesh size requirement of 75µm element length. Altair had to optimize the code to handle the large simulation models, especially contact treatments inside the very fine mesh part; the project also required optimizing several I/O treatments. In addition, Altair engineers implemented a specific material law and a rupture model in RADIOSS, which was developed through an “Industrial Fracture Consortium” including MIT, Ecole Polytechnique and industrial partners like PSA.

Operational Impact

PSA was pleased with the outcome of the study. Without access to this type of large scale supercomputer system, it would have been impossible to consider running such a large simulation problem in a reasonable amount of time. The achievements obtained during this project help companies like PSA to be ready to handle increasingly complex simulations and to evaluate future needs more precisely in terms of computational resources for evolving rupture simulation projects. The organizations involved plan to continue this work via a regular PRACE project to study the behavior of the rupture of this B-pillar component as well as some other components through a full vehicle crash simulation.

Quantitative Benefit

Validated readiness of the RADIOSS code to handle very large models of several millions of solid elements
Proved scalability of the code up to 8,192 cores and beyond -- tested up to 16,384 cores for the very first time
Implemented and validated a new material law and rupture model representing the state of the art for fracture modeling