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Member, American Nuclear Society (ANS)

Chair, Program Committee, Reactor Physics Division, ANS

Member, Executive Committee, Mathematics and Computation Division, ANS 

Associate Editor, Annals of Nuclear Energy

Member, Advisory Editorial Board, Nuclear Technology

EGMN 303 - Thermal System Design

EGMN-321: Numerical Methods

EGMN 352 - Nuclear Reactor Theory

Dr. Wu joined the Department of Mechanical and Nuclear Engineering at Virginia Commonwealth University (VCU) in August 2017 and directs the Computation Applied Reactor Physics Laboratory (CARPL). Prior to VCU, Dr. Wu worked at National Institute of Standards and Technology (NIST) in charge of a replacement research reactor design project. Dr. Wu received his B.S. degree in Engineering Physics from Tsinghua University at Beijing China and Ph.D. degree in Nuclear Engineering from Texas A&M University at College Station Texas. Dr. Wu's research interests encompass reactor physics, multiphysics based reactor design and analysis, computational methods on neutron transport and uncertainty and sensitivity analysis in nuclear applications, machine learning and data analytics.

Reactor Physics

Reactor core design and analysis

Computational method for neutron transport

Uncertainty and sensitivity analysis

Advanced data analytics

Dr. Wu's Google Scholar

Dr. Wu's Research Group (CARPL)

Dr. Wu's Publications

In search of lost data

Young Former Student Award 2019

Improving the computational efficiency and usability of dynamic PRA with reinforcement learning

Development of a Benchmark Model for the Near Real-Time Radionuclide Composition Measurement System using Microcalorimetry for Advanced Reactors

Research, Education and Training Center of Excellence on Nuclear Fuel Cycle and Waste Management Towards Advanced Reactor Technology​

Creation of a Pebble Database for Material Control and Accountancy in Pebble Bed Reactors

Regenerating Missing Experimental Parameters with Data-Assimilation Methods for MSRE Transient Benchmark Development and Evaluation

Identifying and Prioritizing Sources of Uncertainty in External Hazard Probabilistic Risk Assessment

neutrons-by-the-trillions-using-computational-physics-to-understand-nuclear-reactors

Associate Professor, Department of Mechanical and Nuclear Engineering

Zeyun Wu, Ph.D., associate professor in the mechanical and nuclear engineering department at VCU Engineering, is reshaping the future of nuclear power. 

Nuclear reactors are among the most complex engineered systems on earth, with different physical processes interacting simultaneously across various scales. Even the world's most powerful computers cannot simulate every detail of an operating reactor at once.

With a background in computational reactor physics, Wu’s research develops modeling and simulation techniques crucial to understanding next-generation nuclear reactors. By creating these advanced tools, his research eliminates the need for costly physical experimentation while ensuring the safety, efficiency and environmental sustainability of future nuclear power plants. 

Wu's research focuses on understanding reactor behavior through two aspects: multi-physics and multi-scale modeling. The multi-physics approach integrates various physical phenomena, such as nuclear physics reactions, fluid dynamics, heat transfer and structural mechanics, into a unified simulation framework. The multi-scale modeling technique addresses the vast range of physical scales involved, from subatomic neutron interactions to meter-sized reactor components. 

Wu’s research can simulate the complex phenomena within reactors at different scales. These models, developed using advanced numerical methods, help predict reactor behavior under various conditions. 

One of the models Wu uses tracks neutron behavior, a fundamental aspect to understand nuclear reactions. His simulations track trillions of neutrons as they move through various reactor materials, cause fission events and generate power. 

"What drives power is actually the neutron," explained Wu. "Once an atom splits, along with the nuclear energy release, lots of neutrons come out. We're talking about 1012 to 1013 neutrons per second. Our code tracks each neutron to understand where it comes from and where it goes."

By understanding neutron distribution across space, time and energy domains, Wu's team can predict power distribution throughout the reactor core. This helps identify potential hotspots –  areas of heightened thermal activity that could pose safety challenges. Beyond neutron behavior, Wu's research also explores how cooling fluids interact with neutrons and carry away thermal energy, a field known as thermal hydraulics, because how the reactor components are cooled significantly affects the neutron behavior as well. This also explains why the multi-physics modeling becomes essential for nuclear reactor simulations. 

Wu founded the Computational Applied Reactor Physics Laboratory (CARPL) to continue his research in nuclear reactor modeling and simulation. Undergraduate and master’s students learn to use established nuclear simulation codes to analyze reactor problems – skills highly valued in the industry and national labs. Ph.D. students build on theoretical foundations to deepen their understanding, enhance existing models, and develop new ones.

“My area of research has been continually evolving for the past 60 years or so,” said Wu. “Most of the codes we use have been developed by national labs, like Oak Ridge National Lab, but these codes aren’t perfect. National labs hire Ph.D. level students with this niche to identify deficits in the code, correct errors and even add new functions and improve them.”

Looking forward, Wu hopes his research will have a real-world impact on the upcoming shift in nuclear power in America. Over the next 20 to 30 years, the nation's approximately 90 light-water-cooled nuclear reactors reach the end of their operational lifetimes. Light water refers to ordinary water (H₂O), used in most existing reactors to both cool the system and slow down neutrons to sustain the nuclear reaction. To replace them, experts are looking toward advanced, non-light-water-cooled reactors, such as the Molten Uranium Breeder Reactor (MUBR) shown in the figure. Computational methods and tools like Wu’s research lab developed will be essential to their development and implementation. 

 Non-light-water cooled reactors offer significant advantages over the older designs. Some can operate at higher temperatures while others produce substantially less nuclear waste, addressing one of the industry's persistent challenges.

"Unlike traditional water reactors, where we have decades of operational experience and established analysis tools, these new designs present unique challenges," explained Wu. "Companies like Dominion employ large teams of analysts who use well-tested computational tools to maintain their existing reactors, but those same tools aren't calibrated for these next-generation reactors. Our research is developing the computational methods and simulations these advanced reactors will need. When these new reactors come online, the methodologies we're creating now can be quickly converted into production-level nuclear codes, providing immediate practical value to industry.”



Neutrons by the trillions: Using computational physics to understand nuclear reactors

researcher-to-build-fuel-database-to-improve-nuclear-reactor-sustainability

Braden Goddard, Ph.D., assistant professor in the Department of Mechanical and Nuclear Engineering, has received a grant from the U.S. Department of Energy’s Nuclear Energy University Program (NEUP) to create a database for use in nuclear material control of pebble bed reactors (PBR).

Advances in material science and technology have revitalized the nuclear energy industry, allowing for the design and construction of advanced nuclear reactors. New high-temperature materials developed by researchers allow ideas from as early as 1970, like pebble bed reactors, to be re-explored and make nuclear power more efficient and sustainable.

Pebble bed reactors are one of many ideas from as early as 1970 that researchers are once again exploring to make nuclear power more efficient and sustainable now that science has developed new high-temperature materials.

“Imagine a gumball machine,” said Goddard, “A pebble bed reactor functions similarly. The pebbles are the gumballs, which are fed into a reservoir. As they make their way through the reactor, heat generated from the radiation is removed by a gas which then spins an electrical turbine to generate electricity. The pebbles then exit from the bottom of the reservoir and those that can be reused are returned to the top of the reservoir.”

Each pebble contains thousands of microscopic uranium particles encased in silicon-carbide cladding. As the pebble passes through the PBR, the path it follows affects how much fissioning occurs within the uranium. This means pebbles deplete at different rates based on how they travel through the reactor.

Goddard’s database seeks to characterize the state of a pebble after it leaves the PBR by determining precisely how much plutonium and uranium remains in the pebble. This informs PBR operators if the pebble can be reused or if it needs to be sent off as waste. Better characterizing these pebbles improves the sustainability and security of PBRs while reducing the amount of waste generated.

Measuring gamma radiation from the radioactive isotope cesium-137 created from the fission of uranium is the traditional method of determining how much nuclear fuel is still viable. However, this system does not work for PBRs because the correlation between the uranium fuel and the gamma radiation it emits is not consistent between pebbles. To remedy this, Goddard will measure both gamma and neutron radiation emitted by all radioactive isotopes in the pebble, which varies depending on the route the pebble takes through the reactor. Partners like Brookhaven National Laboratory and similar institutions within the United States will assist in the research by applying machine learning techniques to the gamma and neutron radiation signature.

“Nuclear reactor operators have instruments that tell them what’s going on inside the reactor, but it’s not the same as knowing how much uranium mass you have in fuel going into or coming out of the reactor,” said Goddard. 

Goddard and his colleague, Zeyun Wu, Ph.D., will use computer modeling to run countless simulations and map every possible course a pebble can take through a PBR. The resulting catalog of data will allow PBR operators to characterize the state of any pebble leaving the PBR and assess if it can be reused or if it is ready to be stored at a nuclear waste facility. The catalog also serves as a material inventory, allowing nuclear facilities to better track waste material.


Researcher to build fuel database to improve nuclear reactor sustainability

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