Turbulence and Near-Wall Modeling for Commercial Vehicle Aerodynamics: A Comparative Study of Scale Resolving Approaches

Sammanfattning

This thesis presents a comparative study of turbulence and near-wall modeling for aerodynamicsimulations of commercial vehicles. The work addresses a central challenge in industrialcomputational fluid dynamics, namely how to obtain reliable flow predictions without theprohibitive cost of high-fidelity scale-resolving methods. Two geometries were investigated: asimplified truck model and a detailed production-scale Volvo truck. The simplified case was usedto evaluate wall-modeled LES, hybrid RANS–LES methods, Scale-Resolving Hybrid methods,and selected RANS formulations against a wall-resolved LES reference and experimental data.The production truck case was used to assess model behavior under full-scale wind-tunnelconditions. Additional simulations investigated model sensitivity to numerical choices such astime step, inner iterations, and prism-layer design.Across both configurations, the turbulence model had a strong influence on predicted separationbehavior, wake structure, and drag. For the simplified truck, DDES Elliptic Blending k-ε andwall-modeled LES showed the best overall agreement with the wall-resolved LES. For thefull-scale truck, DDES Elliptic Blending k-ε gave the most accurate absolute drag predictionsand the best agreement for yaw-weighted drag. However, DDES k-ω SST captured the relativedrag differences between geometry variations more accurately. The sensitivity studies showedthat the current numerical setup is generally robust. Timestep reduction and prism–layervariation showed only limited effects in aerodynamic drag. Furthermore, it was shown that 6 to8 inner iterations generally resulted in convergence within each timestep. Overall, the resultsshow that no single turbulence model is optimal for all purposes, and that model selection inindustrial vehicle aerodynamics should be guided by the specific engineering objective.