Drag Optimization Of Light Trucks Using Computational Fluid Dynamics

Abstract

There are 80 million light trucks on the road today with suboptimal aerodynamic forms. Previous research has found that several miles per gallon can be saved by specifically tailoring truck bodies for reduced aerodynamic drag. Even greater savings can be obtained if the shape of the trucks is numerically optimized. This could reduce fuel consumption in the United States by billions of gallons per year. The purpose of this research is to develop and quantify optimal light truck canopy designs using computational fluid dynamics (CFD). Both two-dimensional and three-dimensional models are used to do this. Initially, this research focuses on quantifying and generalizing the effects of traditional automotive aerodynamic accessories, such as canopies and air dams. Once the effects of various form factors are quantified an optimization of the canopy is performed. This thesis demonstrates a method for drag reduction using CFD and traditional numerical optimization techniques. Lastly, the optimized forms are physically constructed and their effects on fuel economy are compared to the CFD prediction. The results indicate that the CFD formulation provides an accurate predictor for improving fuel economy and drag characteristics. The prototype air dam and optimally shaped canopy generated a 21.23% savings in terms of fuel economy.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2003
Accession Number
ADA418232

Entities

People

  • Nathan A. Williams

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Aerodynamic Characteristics
  • Aerodynamic Drag
  • Aerodynamic Forces
  • Aircrafts
  • Boundary Layer
  • Computational Fluid Dynamics
  • Drag
  • Fluid Dynamics
  • Fluid Mechanics
  • Fuel Consumption
  • Geometry
  • Ground Vehicles
  • Mechanics
  • Pressure Distribution
  • Three Dimensional
  • Two Dimensional
  • United States

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Fluid Dynamics.
  • Logistics and Supply Chain Management.