We are pleased to highlight the work of Enrico Benso, whose thesis at the University of Rome Tor Vergata explores an innovative workflow for the optimization of internal combustion engine (ICE) exhaust ports in a flow bench scenario.

This research integrates Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) in an automated Design of Experiment (DOE) approach, leveraging a Python-based framework to generate and evaluate multiple geometric variants. The mesh morphing methodology, powered by Radial Basis Functions (RBF), allows for precise shape modifications using strategically placed virtual control points.

Key findings include:
🔹 A 10% increase in flow rate
🔹 A 15% reduction in maximum stress

The developed workflow employs RBF Morph software to generate shape variants, which are then analyzed in CONVERGE CFD for fluid dynamics assessment. The resulting temperature and pressure fields serve as input for structural analysis in ANSYS Mechanical, ensuring a comprehensive multiphysics evaluation.

This work represents an important advancement in CAE-driven optimization, demonstrating a methodology that, while developed for automotive applications, is broadly applicable to multiphysics engineering challenges.

We invite you to read the presentation and the full thesis.