William L. Gurecky

William is a Research and Development staff member in the Nuclear Energy and Fuel Cycle Division at Oak Ridge National Laboratory. He currently works with the Radiation Transport & HPC Methods Group developing performant software solutions to address industry identified challenge problems. His research interests include applying Bayesian statistics and machine learning to reactor physics problems.  As the principle investigator of a laboratory directed research and development project, William developed a flexible parallel optimization package, ML-PSA, that joins modern machine learning methods with multi-fidelity physics tools to solve multi-constrained and combinatorial optimization problems encountered in reactor core design. 

William co-developed the crud simulation code, MAMBA, that is a coupled component of the Virtual Environment for Reactor Applications (VERA). MAMBA allows prediction of crud-induced power shifts, constituting a key capability in the Consortium for the Advanced Simulation of LWRs’ (CASL) technical portfolio.  Additionally, he develops reduced order models and applies statistical inference techniques to a variety of model calibration tasks in MAMBA and CTF.

William holds a B.Sc. in Mechanical Engineering (2013), an M.S.E. in Mechanical Engineering (2015) and a Ph.D. in Nuclear & Radiation Engineering (2018) from the University of Texas at Austin. In his doctoral work, William developed a statistical downscaling method to capture the influence of fine-scale flow details down stream from spacer grids on the growth rate of crud in PWRs.