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Accurate turbulence modeling remains a critical problem in the prediction capability of computational fluid dynamics. One particular area lacking accurate simulations is separated turbulent flows. In this paper, the recently developed one - equation Rahman-Agarwal-Siikonen (RAS) turbulence model is used to simulate the flow of several canonical turbulent flow cases. The commercially available software ANSYS Fluent and the open source software OpenFOAM are used for the flow field calculations. It is shown that the RAS model improves the accuracy of flow simulations compared to the commonly used one - equation Spalart-Allmaras (SA) and two-equation SST k-ω turbulence models.

The focus of this paper is on the numerical simulation of compressible flow in a diffusing S-duct inlet; this flow is characterized by secondary flow as well as regions of boundary layer separation. The S-Duct geometry produces streamline curvature and an adverse pressure gradient resulting in these flow characteristics. The geometry used in this investigation is based on a NASA Glenn Research Center experimental diffusing S-Duct which was studied in the early 1990's. The CFD flow solver ANSYS - Fluent is employed in the investigation of compressible flow through the S-duct. A second-order accurate, steady, density-based solver is employed in a finite-volume framework. The three-dimensional Reynolds-Averaged Navier-Stokes (RANS) equations are solved on a structured mesh with a number of turbulence models, namely the Spalart - Allmaras (SA), k-ε, k-ω SST, and Transition SST models, and the results are compared with the experimental data.

In U.S., the ground vehicles consume about 77% of all (domestic and imported) petroleum; 34% is consumed by automobiles, 25% by light trucks and 18% by large heavy-duty trucks and trailers. It has been estimated that 1% increase in fuel economy can save 245 million gallons of fuel/year. Furthermore, the fuel consumption by ground vehicles accounts for over 70% of CO₂ and other greenhouse gas (GHG) emissions in U.S. Most of the usable energy from the engine (after accounting for engine losses) at highway speed of 55 mph goes into overcoming the aerodynamic drag (53%) and rolling resistance (32%); only 9% is required for auxiliary equipment and 6% is used by the drivetrain. 15% reduction in aerodynamic drag at highway speed of 55 mph can result in about 5-7% in fuel saving.

A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent-circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials.

The ratio of the energy liberated during a flight to the revenue work done (ETRW) of an airplane can be employed as a key indicator to assess its environmental impact. It remains constant during the life cycle of the aircraft and is fixed by its designers. The goal of an environmentally optimum airplane is to minimize the ETRW. For an existing airplane, there are two major parameters that can greatly affect the ETRW, which are the ratio of actual payload to maximum possible payload “c” and the flight range R. The goal of this paper is to study the effect of c and R on ETRW and minimize it by using a genetic algorithm (GA). The study is performed on a Boeing 737-800 and a Boeing 747-400 aircraft. The optimization study is valuable in determining the payload and range of an existing aircraft for minimal environmental impact; it turns out that the maximum possible values of payload and range do not necessarily lead to a flight with minimal environmental impact.