Dr. Yidong Xia is a senior staff scientist specializing in computational modeling and simulation for the U.S. Department of Energy (DOE) Idaho National Laboratory's (INL) Energy and Environment Science and Technology (EES&T) Directorate. He obtained his Ph.D. degree in Aerospace Engineering with a Minor in General Mathematics at North Carolina State University. At INL, Dr. Xia's research and leadership experiences have been in the areas of environmental subsurface science, bioenergy technologies, high-performance scientific computing, nuclear energy, and geothermal energy. His technical expertise spans several fields, including computational fluid dynamics and heat transfer, computational particle mechanics, computational chemistry, nuclear material and thermal hydraulics, nano/micro-computed tomography (nano/micro-CT), and image-based machine learning (ML) and artificial intelligence (AI) for material characterization. Dr. Xia serves as a principal investigator (PI) or co-PI on multiple research projects and coordinates the efforts of multiple national laboratories and universities. He has served as PI on the INL-partner project “Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials" (MUSE), an Energy Frontier Research Center (EFRC) supported by DOE Office of Science Basic Energy Sciences Program. He has also been leading the Material Handling Task in the DOE Bioenergy Technologies Office (BETO) Feedstock-Conversion Interface Consortium (FCIC) project.
Dr. Yidong Xia is a senior staff scientist specializing in computational modeling and simulation for the U.S. Department of Energy (DOE) Idaho National Laboratory's (INL) Energy and Environment Science and Technology (EES&T) Directorate. He obtained his Ph.D. degree in Aerospace Engineering with a Minor in General Mathematics at North Carolina State University. At INL, Dr. Xia's research and leadership experiences have been in the areas of environmental subsurface science, bioenergy technologies, high-performance scientific computing, nuclear energy, and geothermal energy. His technical expertise spans several fields, including computational fluid dynamics and heat transfer, computational particle mechanics, computational chemistry, nuclear material and thermal hydraulics, nano/micro-computed tomography (nano/micro-CT), and image-based machine learning (ML) and artificial intelligence (AI) for material characterization. Dr. Xia serves as a principal investigator (PI) or co-PI on multiple research projects and coordinates the efforts of multiple national laboratories and universities. He has served as PI on the INL-partner project “Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials" (MUSE), an Energy Frontier Research Center (EFRC) supported by DOE Office of Science Basic Energy Sciences Program. He has also been leading the Material Handling Task in the DOE Bioenergy Technologies Office (BETO) Feedstock-Conversion Interface Consortium (FCIC) project.