A procedure for code Verification by the Method of Manufactured Solutions (MMS) is presented. Although the procedure requires a certain amount of creativity and skill, we show that MMS can be applied to a variety of engineering codes which numerically solve partial differential equations. This is illustrated by detailed examples from computational fluid dynamics. The strength of the MMS procedure is that it can identify any coding mistake that affects the order-of-accuracy of the numerical method. A set of examples which use a blind-test protocol demonstrates the kinds of coding mistakes that can (and cannot) be exposed via the MMS code Verification procedure. The principle advantage of the MMS procedure over traditional methods of code Verification is that code capabilities are tested in full generality. The procedure thus results in a high degree of confidence that all coding mistakes which prevent the equations from being solved correctly have been identified.

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At 70 miles per hour, overcoming aerodynamic drag represents about 65% of the total energy expenditure for a typical heavy truck vehicle. The goal of this US Department of Energy supported consortium is to establish a clear understanding of the drag producing flow phenomena. This is being accomplished through joint experiments and computations, leading to the 'smart' design of drag reducing devices. This paper will describe our objective and approach, provide an overview of our efforts and accomplishments, and discuss our future direction.

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Steady-state Reynolds-Averaged Navier-Stokes (RANS) simulations are presented for the three-dimensional flow over a simplified tractor-trailer geometry at zero degrees yaw angle. The simulations are conducted using the SACCARA multi-block, structured CFD code. Two turbulence closure models are employed: the one-equation Spalart-Allmaras model and the two-equation k-w model of Menter. The discretization error is estimated by employing two grid levels: a fine mesh of approximately 20 million grid points and a coarse mesh of approximately 2.5 million grid points. Simulation results are compared to the experimental data obtained at the NASA-Ames 7x10 ft wind tunnel. Quantities compared include: surface pressures on the tractor/trailer, vehicle drag, and time-averaged velocities in the base region behind the trailer. The results indicate that both turbulence models are able to accurately capture the surface pressure on the vehicle, with the exception of the base region. The Menter k-w model does a reasonable job of matching the experimental data for base pressure and velocities in the near wake, and thus gives an accurate prediction of the drag. The Spalart-Allmaras model significantly underpredicted the base pressure, thereby overpredicting the vehicle drag.