Inductive aerodynamics


A novel approach is presented to predict wind pressure on tall buildings for early-stage generative design exploration and optimisation. The method provides instantaneous surface pressure data, reducing performance feedback time whilst maintaining accuracy. This is achieved through the use of a machine learning algorithm trained on procedurally generated towers and steady-state CFD simulation to evaluate the training set of models. Local shape features are then calculated for every vertex in each model, and a regression function is generated as a mapping between this shape description and wind pressure. We present a background literature review, general approach, and results for a number of cases of increasing complexity.

Title: Inductive aerodynamics

Authors: Wilkinson SHanna S SHesselgren L, .

Publication: Proceedings of eCAADe 2013: computation and performance, Delft, the Netherlands | view article

Year: 2013