Projektinformation
Projekttitel:
Wind Noise Shape Optimization Enhanced by Machine Learning
Koordinator:
Volvo Personvagnar Aktiebolag
Diarienummer:
2023-204401
Projektnummer:
P2023-00985
Projektstart:
2023-12-01
Projektslut:
2027-11-30
Budget:
| År | Beviljat |
|---|---|
| 2023 | 552 739 kr |
| 2024 | 250 875 kr |
| 2025 | 763 692 kr |
| 2026 | 757 883 kr |
| 2027 | 718 101 kr |
| Total: | 3 043 290 kr |
Program:
FFI Nollutsläpp
Programområde:
Transporter, forskningsprogram
Projektsammanfattning:
The project's primary objective is to apply scientific machine learning techniques to develop reduced-order models for turbulent flows that effectively predict wind noise (aerodynamic noise). These models are expected to substantially reduce lead time by more than tenfold, expediting the early stages of car development. The project's value lies in its potential to provide near-real-time predictions of wind noise and aerodynamic performance, enabling rapid design iterations and effective shape optimization. Intended users include automotive engineers and designers who can seamlessly integrate these models into numerical simulations for turbulent flows. Furthermore, the new knowledge generated through this research can also be directly applied in the aerospace and wind turbine industries.
Energimyndighetens andel:
45 %
