This course covers the introduction to surrogate and reduced order modeling to speed up engineering workflows, including, but not limited to, multiphysics applications in engineering where reduced-order modeling can mitigate many expensive computations. Such examples include: reservoir simulation, production optimization, complex multiphase flow simulation, neutron diffusion, coupled neutronics/thermal-hydraulics, nuclear heat transfer, and other pertinent areas. It is intended primarily for graduate students interested in any computational science/ engineering application. The course material is complemented by a balanced set of theoretical, algorithmic, and MATLAB/Python computer programming homeworkâs and assignments. Invited lectures from researchers and professionals in model reduction will be given as time permits.
Please contact Dr. Gildin (egildin@tamu.edu) or Dr. Ragusa (jean.ragusa@tamu.edu) for more information on the class.