On-Demand Webinar - Predicting Aerodynamic Flow Around Automotive Vehicles

  On-demand. Register only once to get access to all Cadence on-demand webinars.

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Predicting aerodynamic flow physics around automotive vehicles is a complex endeavor, often leaving the engineer with the need to balance cost and accuracy. While steady-state approaches (such as RANS) are attractive for their low computational cost, they usually fail to predict all flow phenomena correctly. More fidelity can be achieved by using unsteady scale-resolving models such as DES or wall-modeled LES, of course at a significantly higher cost.

An ideal model would offer an accurate solution within a small turnaround time, therefore being applicable across the board and allowing for a faster, more consistent, decision making.

In this webinar, we present a comparison between standard RANS models, Stress-Omega RSM implementation, and unsteady scale resolving approaches on several representative test cases including Windsor body and DrivAer.

Learning benefits:

• Demonstration of the full CFD simulation workflow for car external aerodynamics
• Comparison of speed and accuracy for different turbulence modeling approaches
• Application to multiple reference car models

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  On-demand. Register only once to get access to all Cadence on-demand webinars.

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