Adjoint methods for car aerodynamics

• Published in: Journal of mathematics in industry Vol. 4; no. 1; p. 6
• Main Author: Othmer, Carsten
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2014; Springer Nature B.V
• Subjects: Applications of Mathematics; Automobile industry; Design; ECMI2012-Selected papers on Mathematics in Industry; Math. Appl. in Environmental Science; Mathematical and Computational Biology; Mathematical and Computational Engineering; Mathematical Methods in Physics; Mathematical Modeling and Industrial Mathematics; Mathematics; Mathematics and Statistics; Methods; Navier-Stokes equations; Permeability; Software; Ventilation; Viscosity; Drag Reduction; Adjoint Method; Computational Fluid Dynamics; Topology Optimisation; Shape Optimisation
• ISSN: 2190-5983; 2190-5983
• DOI: 10.1186/2190-5983-4-6

The adjoint method has long been considered as the tool of choice for gradient-based optimisation in computational fluid dynamics (CFD). It is the independence of the computational cost from the number of design variables that makes it particularly attractive for problems with large design spaces. Originally developed by Lions and Pironneau in the 70’s, the adjoint method has evolved towards a standard tool within the development processes of the aeronautical industries. Its uptake in the automotive industry, however, lags behind. The first systematic applications of adjoint methods in automotive CFD have interestingly not taken place in the classical shape design arena, but in a relatively young discipline of sensitivity-based optimisation: fluid dynamic topology optimisation. While being an established concept in structure mechanics for decades already, its transfer to fluid dynamics took place just ten years ago. We demonstrate that specifically for ducted flow applications, like airducts for cabin ventilation or engine intake ports, it constitutes a very powerful tool and has matured over the last years to a level that allows its systematic usage for various automotive applications. To drive adjoint-based shape optimisation to the same degree of maturity and robustness for car applications is the subject of ongoing research collaborations between academia and the car industry. Achievements and challenges encountered during these efforts are presented.