Rapid Aerodynamic Development of Two-Volume Vehicle Shapes

Koromilas, C. A.; Harris, C. L.; Sumantran, V.; Pachon, L.; Zeng, Shi

doi:10.4271/2000-01-0488

Cited by 5 publications

(6 citation statements)

References 5 publications

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“…Finally, the lift coefficient (C L ) has been characterised by vehicle's dimensions and flow angle as: giving the final lift coefficient equation as: Figure 12 depicts the correlation between the CFD predicted values of the aerodynamic coefficients, and those obtained from Eqs. (11), (13) and (15). It can be clearly seen that the CFD predicted values agree reasonably well with those obtained from the semi-empirical equations.…”

Section: Development Of Semi-empirical Prediction Models For the Aerosupporting

confidence: 76%

“…Hence, Eqs. (11), (13) and (15), developed for characterising the aerodynamic coefficients in terms of the vehicle's dimensions and the relative flow angle, are capable of predicting the aerodynamic coefficients for a tractor-trailer unit of various sizes for different flow conditions, with reasonable accuracy. This methodology allows for the effective use of CFD in the early design phases of tractor-trailer units.…”

Section: Development Of Semi-empirical Prediction Models For the Aeromentioning

confidence: 99%

“…In order to further validate the aerodynamic coefficients computed using Eqs. (11), (13) and (15), the flow around the baseline tractor-trailer unit has been numerically simulated for ψ = 10 • , 40 • and 70 • . The numerically predicted aerodynamic coefficients have been recorded and then compared against the values computed from the equations developed for the same yaw angles.…”

Section: Development Of Semi-empirical Prediction Models For the Aeromentioning

confidence: 99%

“…Koromilas et al [13] applied neural network prediction techniques to quantify the aerodynamic drag force, specifically for two-box vehicle configuration. This system has been found to be fully capable of computing the drag coefficient of a vehicle.…”

Section: Introductionmentioning

confidence: 99%

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Development of a Novel Characterisation Methodology for the Aerodynamic Coefficients of a Tractor–Trailer Unit Based on Relative Flow Angles and Vehicle Dimensions

et al. 2018

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Tractor-trailer units are integral part of the heavy commercial vehicle industry, used globally for goods transportation. Manufacturers have been trying to design aerodynamically efficient tractor-trailer units to reduce ever increasing fuel costs. In order to investigate the aerodynamic response of tractor-trailer units, the aerodynamic forces and moments have to be determined accurately, especially under crosswind conditions. In the present study, a computational fluid dynamics-based solver has been employed to simulate the flow field around a tractor-trailer with a view to quantify the effects of side wind and size variations on aerodynamic force moment system acting on tractor-trailer combination. It has been shown that the aerodynamic forces are significantly influenced by both the geometrical and flow characteristics. The drag, lift and side forces acting on a tractor-trailer unit are highest at relative flow angles of 15 • , 30 • and 90 • , respectively. Aerodynamic forces and coefficients have been enumerated for these geometrical and flow conditions, and have been used to develop novel semi-empirical correlations for the aerodynamic coefficients for the tractor-trailer unit. These correlations have been shown to predict the aerodynamic coefficients for various vehicle dimensions under a range of flow conditions with reasonable accuracy. Keywords Heavy commercial vehicle (HCV) • Computational fluid dynamics (CFD) • Computer-aided design (CAD) • Computer-aided engineering (CAE) • Aerodynamic coefficients List of symbols C D Drag coefficient vehicle (-) C L Lift coefficient of the vehicle (-) C S Side coefficient of the vehicle (-) C P Coefficient of pressure (-) l Length of the vehicle (m) h Height of the vehicle (m) w Width of the vehicle (m)

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Section: Development Of Semi-empirical Prediction Models For the Aerosupporting

confidence: 76%

Section: Development Of Semi-empirical Prediction Models For the Aeromentioning

confidence: 99%

Section: Development Of Semi-empirical Prediction Models For the Aeromentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Development of a Novel Characterisation Methodology for the Aerodynamic Coefficients of a Tractor–Trailer Unit Based on Relative Flow Angles and Vehicle Dimensions

et al. 2018

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“…CFD codes are used in many design phases to reduce the time and cost of product development. A lot of effort has been devoted on the development of CFD tools for automotive engineering [1,2,3,4,5]. In previous paper, CFD software was evaluated and always recognized as a helpful tool to many industrial fields.…”

Section: Introductionmentioning

confidence: 99%

The CFD Application for Efficient Designing in the Automotive Engineering

Watanabe

Miyamoto

Kuba

et al. 2003

SAE Technical Paper Series

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Recently, many CFD analyses which assist mechanical designing have been carried out in every aspects of automotive engineering. While many CFD tools have been developed for easies of use and advances in CFD analyses tools continue, instances of effective design using these tools are not well discussed in the literature. This paper discusses a CFD analysis system, SC/Tetra, is equipped with an automatic hybrid mesh generator, a high-speed flow solver and a state of the art postprocessor. In SC/Tetra, the flow solver is built on a node-based finite-volume discretization method to achieve both high-speed computation and small memory consumption. The advancing-front method is applied to the automatic mesh generator. These features of efficient computation are desired to achieve shorter design times. Discussions are made after performing sample computations of a torque converter for an automobile, which presents difficulties for efficient CFD analysis. The difficulties are based on the numerical modeling, the mesh generation and retaining the accuracy of the computational result. SC/Tetra is optimized for effective computation and copes with these difficulties with adequate strategies. CFD tools will be able to give more parametric data to accelerate product design processes and to improve products.

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