Case Study: Satven accelerates crush can crash prediction with Hexagon’s ODYSSEE CAE

AI/ML-based prediction of crash parameters using ODYSSEE CAE

Satven, a leading automotive engineering bureau, sought to leverage AI and Machine Learning to gain a competitive advantage. Their challenge was to drastically reduce the time required to predict the effects of different materials and thicknesses on crash parameters for a vehicle crush can, a process that was slow and resource-intensive using traditional CAE simulation methods.

Hexagon addressed this with its ODYSSEE CAE software, which uses machine learning and reduced order modeling. By training the model with data from just 20 CAE runs, Satven could predict results for new material and thickness combinations in seconds instead of hours. This solution from Hexagon eliminated the need for simulation software for initial predictions and significantly accelerated the product development cycle.

Satven