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Utilizing spectral analysis to quantify resolution of low frequency behavior in testing commercial vehicles
Technical Paper
2018-01-0747
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Despite the recent broadening of acceptable test methods for certifying aerodynamic performance, there has been little attention on how to determine the time averaging window used for providing mean forces. This is of particular relevance to the assessment of commercial vehicles as they are significantly affected by low-frequency patterns that are hard to predict and vary with different geometry configurations. Published guidelines in the industry suggest that good engineering judgement be used and a qualitative assessment of force histories is adequate. These suggested methods leave the accuracy of the time averaging to the experience and judgement of the user and is highly dependent on the specific characteristics of the benchmark case. Furthermore these methods are not able to quantify the error present due to motions slower than length of the sampled data. In order to robustly determine appropriate averaging window a new method is proposed which utilizes spectral analysis of the drag. By investigating changes in the power spectral density for different averaging windows it is possible to determine adequate averaging time as well as to assess the error introduced by selecting a particular averaging window. The method detailed presently is applied to both wind tunnel measurements and computation fluid dynamics simulations.
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Landfried, D., Alex, D., and Mosedale, A., "Utilizing spectral analysis to quantify resolution of low frequency behavior in testing commercial vehicles," SAE Technical Paper 2018-01-0747, 2018, https://doi.org/10.4271/2018-01-0747.Also In
References
- Code of Federal
- Guidelines for aerodynamic assessment of medium and heavy commercial ground vehicles using computational fluid dynamics SAE Paper, 2017-04-18
- Wind Tunnel Test Procedure for Trucks and Buses SAE Paper, 2012-07-16
- Islam , A. , Gaylard , A. , and Thornber , B. A detailed statistical study of unsteady wake dynamics from automotive bluff bodies Journal of Wind Engineering and Industrial Aerodynamics 172 December 2017
- Gaylard , A.P. et al. Simulation of rear surface contamination for a simple bluff body Journal of Wind Engineering and Industrial Aerodynamics. 165 June 2017
- Garbaruk , A. , Leicher , S. , Mockett , C. , Spalart , P. et al. Evaluation of Time Sample and Span Size Effects in DES of Nominally 2D Airfoils beyond Stall Progress in Hybrid RANS-LES Modelling Notes on Numerical Fluid Mechanics and Multidisciplinary Design 111 Berlin, Heidelberg Springer 2010
- Bendat , J.S. and Piersol , A.G. Random data, analysis and measurement procedures Chichester John Wiley & Sons, Inc 1986
- Welch , P. The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms IEEE Transactions on audio and electroacoustics 15 2 70 73 1967
- Bracewell , R.N. and Bracewell , R.N. The Fourier transform and its applications. Vol. 31999 New York McGraw-Hill 1986
- Marple , S.L. and Lawrence Marple , S. Digital spectral analysis: with applications Vol. 5 Englewood Cliffs, NJ Prentice-Hall 1987 130 144
- Stoica , P. and Moses , R.L. Spectral analysis of signals 452 Upper Saddle River, NJ Pearson Prentice Hall 2005
- Beckwith , T.G. , Marangoni , R.D. , and Lienhard , J.H.V. Mechanical measurements Pearson 2009
- Harris , F.J. On the use of windows for harmonic analysis with the discrete Fourier transform Proceedings of the IEEE 66 1 51 83 1978