Senior Crash CAE Engineer — BiW Simulation & Dataset Lead

Full Time 3 months ago Durban, South Africa

Employment Information

About the Role

A senior-level role for someone who can own crash simulation methodology end-to-end. You'll define the simulation strategy, validate FE models against known test data, and set the quality bar for a large synthetic crash dataset powering machine learning surrogate models.

What You'll Do

  • Own FE model development and validation strategy for parametric BiW crash simulations
  • Lead conversion and adaptation of existing LS-DYNA models (CCSA Camry-class vehicles) into OpenRadioss-compatible decks via ANSA
  • Take a parametrically designed BiW and automate the setup in ANSA
  • Define simulation protocols across multiple load cases: frontal rigid wall, MPDB, small overlap oblique, side pole, and roof crush
  • Establish spot weld and structural connection modeling standards across the full BiW assembly (pattern, failure criteria, element formulation)
  • Ensure energy balance, mass scaling, and hourglassing are within acceptable bounds across every run
  • Build or supervise automated META post-processing pipelines to extract structured, ML-ready outputs
  • Act as technical bridge between the simulation team and the ML engineering team

Requirements

  • Deep expertise in vehicle crash CAE, structural impact, or explicit dynamics simulation
  • Deep expertise in LS-DYNA and/or OpenRadioss / AltairRadioss — fluent in at least one, willing to bridge both
  • Expert-level ANSA pre-processing: connections, mesh morphing, load case setup, model validation
  • Expert-level META post-processing: automated results extraction, force-displacement curves, intrusion measurements
  • Proven track record validating FE models against physical crash test data
  • Deep understanding of vehicle crash physics: crush zone behavior, load path management, energy absorption, occupant cell integrity

Nice to Have

  • Direct experience generating simulation datasets for ML or surrogate modeling applications
  • Python scripting for pre/post-processing automation
  • Understanding of how parametric CAD variation affects simulation setup
  • Experience with NHTSA, IIHS, or Euro NCAP testing protocols
  • Prior work with NCAC / CCSA open-source vehicle FE models

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