DOI QR코드

DOI QR Code

Tunable compression of wind tunnel data

  • Possolo, Antonio (Statistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, U.S. Department of Commerce) ;
  • Kasperski, Michael (Department of Civil and Environmental Engineering Sciences, Ruhr-Universitat Bochum) ;
  • Simiu, Emil (Materials and Construction Research Division, Building & Fire Research Laboratory, National Institute of Standards and Technology, U.S. Department of Commerce)
  • 투고 : 2009.04.14
  • 심사 : 2009.07.09
  • 발행 : 2009.11.25

초록

Synchronous wind-induced pressures, measured in wind-tunnel tests on model buildings instrumented with hundreds of pressure taps, are an invaluable resource for designing safe buildings efficiently. They enable a much more detailed, accurate representation of the forces and moments that drive engineering design than conventional tables and graphs do. However, the very large volumes of data that such tests typically generate pose a challenge to their widespread use in practice. This paper explains how a wavelet representation for the time series of pressure measurements acquired at each tap can be used to compress the data drastically while preserving those features that are most influential for design, and also how it enables incremental data transmission, adaptable to the accuracy needs of each particular application. The loss incurred in such compression is tunable and known. Compression rates as high as 90% induce distortions that are statistically indistinguishable from the intrinsic variability of wind-tunnel testing, which we gauge based on an unusually large collection of replicated tests done under the same wind-tunnel conditions.

키워드

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피인용 문헌

  1. Discussion on “Reconstruction of the envelope of non-Gaussian structural responses with principal static wind loads” authored by N. Blaise, T. Canor and V. Denoël, published in Journal of Wind Engineering and Industrial Aerodynamics 149 (2016) pp 59–76 vol.163, 2017, https://doi.org/10.1016/j.jweia.2017.01.009