Article ID Journal Published Year Pages File Type
768950 Computers & Fluids 2011 14 Pages PDF
Abstract

Numerical solutions of the unsteady Reynolds-averaged Navier–Stokes equations using a parallel implicit flow solver are given to investigate unsteady aerodynamic flows affecting the fuel economy of Class 8 trucks. Both compressible and incompressible forms of the equations are solved using a finite-volume discretization for unstructured grids and using Riemann-based interfacial fluxes and characteristic-variable numerical boundary conditions. A preconditioned primitive-variable formulation is used for compressible solutions, and the incompressible solutions employ artificial compressibility. Detached eddy simulation (DES) versions of the one-equation Menter SAS and the two-equation k − ϵ/k − ω hybrid turbulence models are used. A fully nonlinear implicit backward-time approximation is solved using a parallel Newton-iterative algorithm with numerically computed flux Jacobians. Unsteady three-dimensional aerodynamic simulations with grids of 18–20 million points and 50,000 time steps are given for the Generic Conventional Model (GCM), a 1:8 scale tractor–trailer model that was tested in the NASA Ames 7 × 10 tunnel. Computed pressure coefficients and drag force are in good agreement with measurements for a zero-incidence case. Similar computations for a case with 10° yaw gave reasonable agreement for drag force, while the pressure distributions suggested the need for tighter grid resolution or possibly improved turbulence models. Unsteady incompressible flow simulations were performed for a modified full scale version of the GCM geometry to evaluate drag reduction devices. All of these simulations were performed with a moving ground plane and rotating rear wheels. A simulation with trailer base flaps is compared with drag reduction data from wind tunnels and track and road tests. A front spoiler and three mud-flap designs with modest drag reduction potential are also evaluated.

Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics
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