Hybrid Applied Mathematics Seminar

Talk Title: Solving Heat Transfer and Fluid Flow Problems with Reduced Order Models and Neural Networks

Speaker: Dr. Zilong Song Department of Math & Stat, USU

Abstract: The friction stir welding process can be modelled using a system of heat transfer and Navier-Stokes equations with a shear dependent viscosity. Finding numerical solutions of this system of nonlinear partial differential equations over a set of parameter space, however, is extremely time-consuming. Therefore, it is desirable to find a computationally efficient method that can be used to obtain an approximation of the solution with acceptable accuracy. In this talk, we present a reduced basis method for solving the parametrized coupled system of heat and Navier-Stokes equations using a proper orthogonal decomposition (POD). In addition, we apply a machine learning algorithm based on an artificial neural network (ANN) to learn (approximately) the relationship between relevant parameters and the POD coefficients. Our computational experiments demonstrate that substantial speed-up can be achieved while maintaining reasonable accuracy.

When

Monday, September 13, 2021 | 10:30 am - 11:30 am

Where

Animal Science
   Room: 119

Event Type

Conference/Seminar

Department

Mathematics and Statistics

Target Audience

Students,Faculty

Website

https://usu-edu.zoom.us/j/86060924997? pwd=ZGhmTnNLdW1FVzdveE5WejhKbGVsZz09

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Event Contact

Name: Jia Zhao
Phone: 4357971953
Email: jia.zhao@usu.edu

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