Case Study: École Centrale de Lyon improves jet noise prediction with Hexagon Actran

Researchers extend Actran to perform advanced research

École Centrale de Lyon, a leading research institution, partnered with Hexagon to tackle the challenge of accurately predicting complex jet engine noise, particularly for engines installed on aircraft wings. The highly rotational and complex flow made this difficult for existing finite element models, and calculating the required Green's functions was computationally expensive for each new geometry.

Using the Python API within Hexagon's Actran software, the research team implemented the Pierce equation to model the high-speed flow. This solution, developed in collaboration with Hexagon's experts, dramatically reduced memory requirements from 43 GB to just 1.7 GB while maintaining accuracy. This allowed the researchers to successfully calculate the necessary adjoint Green's functions, resulting in a new model that accurately predicts the peak frequency of the noise spectrum.

École Centrale de Lyon

Etienne Spieser

Postdoctoral Researcher