Publication: Interpolation of Pressure Coefficients for Low-Rise Buildings of Different Plan Dimensions and Roof Slopes using Artificial Neural Networks

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Title	Interpolation of Pressure Coefficients for Low-Rise Buildings of Different Plan Dimensions and Roof Slopes using Artificial Neural Networks
Authors/Editors*	X. Gavalda, J. Ferrer-Gener, Gregory A. Kopp, Francesc Giralt
Where published*	Journal of wind engineering and industrial aerodynamics
How published*	Journal
Year*	2010
Volume	Submitted
Number
Pages
Publisher
Keywords	Database-Assisted Design; Artificial Neural Networks; Wind-induced pressures; Low-rise buildings; Aerodynamic loads.
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Abstract	Database-assisted design (DAD) is emerging as an important tool to design buildings for wind effects. However, there is a need for robust interpolation methods for pressure coefficients to extend the range of conditions beyond those in the aerodynamic database from wind tunnel experiments. An interpolation methodology, using artificial neural networks (ANN), was developed to include variable plan dimensions and roof slopes in the set of parameters considered in earlier interpolation studies. In addition to expanding the capabilities for interpolation, the new models improved predictions in the lee of the ridges for gable-roofed, low-rise buildings.