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Enhancing Crashworthiness Optimization at BMW with Altair HyperWorks AI Solutions

Overview

BMW faces complex body in white crash design challenges that require a high degree of engineering expertise. With the help of Altair's machine learning (ML)-driven predictive surrogate modeling, BMW can emulate human expertise to accelerate development cycles and gain new insights for crashworthiness optimization. The challenges include handling opposing load cases and design criteria, while ensuring passenger safety through precise judgments on crash kinematics, event timings, and performance indicators like energy absorption, peak force levels, displacements, and weight.

BMW's Challenge

The intricate process of ensuring passenger safety during a crash event, including coordinating various factors and judgments, poses a significant challenge for BMW's crash engineers. Balancing crash kinematics with performance indicators such as energy absorption and peak force levels can lead to highly constrained optimization problems. This complexity can hinder the validation process within BMW's fast-paced product development environment.

BMW's Solution with Altair

BMW leverages Altair's integrated Machine Learning solutions within HyperWorks to create optimization constraints that mimic expert engineering decisions. Using clustering algorithms, engineers gain insights into how crash kinematics impact key performance indicators, enabling the enforcement of favorable crash scenarios during the optimization process. Through the use of classifiers, BMW can emulate human decision-making processes throughout structural optimization.

Impact and Value

Altair's Machine Learning solutions enable BMW to target specific crash kinematics accurately during structural optimization. By incorporating machine learning constraints that mirror expert engineering knowledge, BMW simplifies the optimization problem formulation and reduces the number of design iterations needed to develop advanced automotive crash structures. This leads to more efficient resource allocation and enhanced simulation, analysis, and validation efforts.

Future Outlook

The implementation of machine learning-powered workflows has extended BMW's engineering capabilities, allowing for better utilization of computing and human resources for high-value tasks. BMW plans to explore additional applications of Altair's Machine Learning technologies across their design processes, enhancing efficiency and innovation in their engineering practices.


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