Quantification of Shear Stress Field Using Tuft Visualization and Deep Learning

A method for determining shear wall stress comprising:

• providing a model of an aerodynamic surface;
• determining the spatial coordinates of the model for use as a first set of input variables;
• disposing the model within a testing system;
• determining the spatial coordinates of the testing system for use as a second set of input variables;
• connecting a plurality of tufts to the model in a manner such that the tufts can flow freely in a direction of an applied flow;
• applying a generally horizontal dynamic flow force to the model thereby creating movement of the plurality of tufts;
• using a camera visualization system to generate input data from the movement of the tufts for use as a third set of input variables;
• applying the first, second, and third sets of input variables to a physics informed neural network to generate a set of output flow variables;
• utilizing the output flow variables to determine velocity profile of the model;
• and
• utilizing the velocity profile as well as a set of pressure outputs of the model to estimate the shear walls stress of the model.