Why Impact Assessment Needs to Scale

Impact performance depends on multiple interacting variables — impact angle, energy, ground condition, and unavoidable real-world uncertainties.
Yet traditional FEM-based approaches allow engineers to evaluate only a limited number of scenarios due to time and computational cost.
As a result, critical risks may only be identified late in the design cycle – or not at all.

Scaling Impact Assessment with TE Connectivity

In collaboration with TE Connectivity, this webinar presents an initial exploration of how impact studies can move beyond isolated drop-test simulations toward continuous, risk-aware assessment.
The current work is based on a simplified demonstrator developed to illustrate the methodology. Starting from a finite number of high-fidelity FEM simulations, ODYSSEE is used to:

   
Extend simulation results across the full design space   Identify critical impact scenarios early   Quantify probability of failure under real-world variability

 

From Hours of Computation to Seconds of Prediction with ODYSSEE

ODYSSEE enables scalable machine-learning workflows that extend the value of high-fidelity FEM simulations. Through automated model training and large-scale scenario evolution, engineers can transform hours of computation into seconds of prediction, supporting faster and more confident decisions early in development.

  • How ODYSSEE accelerates impact simulations by orders of magnitude
  • How to convert sparse FEM results into dense design-space evaluations
  • How probability of failure supports risk-based engineering decisions
  • How ODYSSEE integrates into existing CAE workflows
  • Practical considerations, current limitations, and the path
    toward validation on real industrial components

Register for individual sessions or attend the full series for a complete overview of how AI and machine learning enabled engineering is reshaping the industry.

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