Research in the R-NEAMS Group
The central theme of the research at R-NEAMS is to develop state-of-the-art methodologies to address the multi-physics multi-scale computational challenges for advanced nuclear energy systems. Currently, the group is pursuing several different research projects across different application areas. The research is split into different sections and spearheaded by one of the group members.
Semiconductor Radiation Effects and Damage
Semiconductors devices are used in a wide range of electrical components and are susceptible to the effects of radiation. This can be a serious issue in high radiation environments such as space, especially due to the time and cost of replacing damaged components. Simulation and modeling of the radiation effects lets us understand exactly how and when the devices will fail and allows them to be designed to prevent failure. These simulations start by modeling an energetic particle colliding with the device and then moving through the semiconductor region. As the particle travels, it knocks into atoms along the way and thus deposits its energy. The energized atoms lose some of their electrons which creates an electrical current. Current is important because it will cause heating which could lead to device burnout and destruction. Simulations are currently being done using the unstructured mesh capabilities of MCNP with Abaqus to model energy deposition on a realistic device geometry. Once this stage is complete, the Abaqus models will be used in electrical simulators along with the energy deposition data from MCNP.
Experimental Validation of Coupled Neutronics and Thermal Hydraulics Codes Using the RPI Walthousen Reactor Critical Facility (RCF)
The goal of the project is to validate multi-physics codes from the SHARP package (PROTEUS for neutronics and Nek5000 for thermal hydraulics) by performing coupled physics experiments in a real life nuclear reactor, the RCF. Thanks to its low power and open pool configuration, the reactor is easily manipulated and several experiments have been designed and performed, on top of the existing capabilities: Moderator temperature coefficient of reactivity, circulating hot water at the center of the core influence on reactivity, reactor change of state by thermal equilibrium between loop water and moderator, and many more. The broad range of experimental results is compared to the simulation results, and the accuracy of the codes can be assessed.
Development of Efficient Coupling Methods for Multiphysics Analysis of Nuclear Reactor Systems
Nuclear engineering is an inherently “multi-physical” field of study. Many different phenomena—including neutron transport, heat transfer, fluid flow, chemistry, and more—are all interrelated in nuclear reactors. Until recently the trend has been to solve each problem separately. Multiphysics applications attempt to solve two or more interrelated problems with one coupled simulation. The goal being to surpass the accuracy and efficiency of older, less tightly coupled analysis methods.
As multiphysics applications are developed, it is important to understand how linking various applications will affect computational costs. There are a variety of ways of putting the pieces together, with trade-offs involved. In general, the more loosely coupled two applications are, the easier it is to interface them. However it is often the case that performance is improved by combining the applications more tightly. Thus it is important to the growth of multiphysics tools to develop new coupling approaches that are robust, efficient, and easy to implement.
Application of Proper Generalized Decomposition to Reactor Analysis
Most high-fidelity computer simulations rely on very fine meshes. The size of a 3D problem increases by a factor of 8 when the mesh is made twice as fine, and it can quickly get out of hand. Proper Generalized Decomposition (PGD) is one method for that allows computers to solve very large multidimensional problems. This project uses the PGD method to solve neutron transport problems and multiphysics nuclear reactor analysis problems.
PGD transforms a multidimensional PDE into a set of coupled single-dimensional PDEs. The solutions to the set of equations are added as basis functions to a Reduced Order Model (ROM). New basis functions are progressively added until the ROM attains sufficient precision. We are implementing a PGD solver for neutron transport and coupling it with thermal-fluid simulations to produce a fast, scalable multiphysics nuclear reactor analysis code.
On the Fly Sampling Thermal Scattering Nuclear Data based on S(α,β) Models for Monte Carlo Simulations
During the lifetime of a nuclear reactor, the core and its surrounding materials will experience a wide range of temperatures which significantly impact the probabilities of certain neutron interactions (fission, capture, scattering, etc.). These probabilities are referred to in the nuclear community as ‘cross sections’ and are used as inputs for computer simulations. In the case of advanced reactor designs such as the gas-cooled reactors, there is a large axial temperature variation in the fuel pins from the fuel centerline. In the case of coupled neutronic-thermal-hydraulic codes, the temperatures are not always known a priori. A large amount of cross section data is necessary to encompass the entire energy and temperature range a neutron may experience in a problem. In recent years, methods have been developed to reduce data storage by only storing zero-temperature resolved-resonance cross section data and then using functional expansions to attain the cross section at the desired temperature ‘on-the-fly’ during the random walk of the neutron in the Monte Carlo process. These methods are not applicable at low energies because of the complicated nature of chemical and binding effects. This work focuses on developing methods to temperature-correct the thermal scattering cross section ‘on-the-fly’ for incorporation into current online Monte Carlo methods.
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Electro-Magnetic Pulse Research
An Electromagnetic Pulse (EMP) can severely disrupt the use of electronic devices in its path causing a significant amount of infrastructural damage. EMP can also cause breakdown of the surrounding atmosphere during lightning discharges. This makes modeling EMP phenomenon an important research area in many military and atmospheric physics applications. Our research work includes developing an electron swarm model to be integrated into Los Alamos National Laboratories multiphysics EMP code, CHAP-LA. The electron swarm model monitors the time evolution of low-energy, conduction electrons created by the ionizing radiation that characterizes EMP. CHAP-LA currently employs an equilibrium ohmic conduction electron model that leads to inaccurate EMP calculations at high altitudes. Implementing the swarm model in CHAP-LA allows us to overcome the limitations imposed by the ohmic model and gives us a state-of-the-art capability for high altitude EMP modeling. This capability allows us to simulate novel EMP scenarios, including EMP propagating upwards towards a satellite.
High Fidelity Modeling and Simulation of Coupled Pebble Flow and Coolant Flow in Pebble-bed Nuclear Reactors
In the safety analysis of high temperature pebble-bed nuclear reactors (PBR), one of the next generation nuclear reactor designs, great computational challenges are presented due to its unique design features. In PBR, tennis ball-sized spherical fuel pebbles are loaded and circulating through the reactor core region under the pressure of high speed helium or fluoride salt coolant flow around each pebble. Interactions of pebble-to-pebble, pebble-to-coolant and pebble-to-reflector wall result in a complicated coupled pebble flow and coolant flow process in PBR. This process is further complicated by the reactor power and temperature distributions, which have strong effect on pebble friction coefficient and coolant flow viscosities. To predict local power and temperature distribution accurately, especially under severe accident scenarios, high fidelity simulation of fully coupled pebble flow and coolant flow in PBR is needed. The development of new methodology used in this high fidelity simulation can significantly improve the current reactor safety prediction capability and provide the safest design margin for PBR.
Our research team has developed a high-fidelity code PEBble Fluid Dynamics (PEBFD), which tightly coupled two advanced computational methods, the discrete element method (DEM) and the computational fluid dynamics (CFD) method, to model the pebble flow and high-speed coolant flow simultaneously. A realistic simulation of pebble dynamics, including initial fuel loading process, dynamic fuel flowing (upward or downward) process, and fuel discharge and reloading process, in cylindrical and annular core designs in high temperature pebble-bed reactor designs has been implemented. A series of verification and validation have been done by comparing the results with other literature and experimental results. Critical safety design parameters, such as pebble distribution, void fraction (porosity) distribution, coolant flow speed distribution, etc. used for full core neutronic/thermal hydraulic analysis, can be provided using the developed code.
Radiation Transport Modeling and Simulation in Stochastic Media
Stochastic media contains many different materials and particles that are mixed together. Several different types of reactors use nuclear fuel that can be considered a stochastic media. This research focuses on developing fast and efficient models to analyze radiation transport behavior in the media. These models can help computer simulations improve the understanding of several important properties of the fuel and make better reactor core designs.
3-D particle systems, characterized by the stochastic distribution of spherical inclusions in a background material, are typical radiation transport media encountered in many scientific and engineering fields. In the area of nuclear engineering, some advanced nuclear reactor designs, such as the Very High Temperature Gas-Cooled Reactors (VHTR), the Fort Saint Vrain (FSV) reactor or innovative light water reactor designs (LWRs) loaded with fully ceramic microencapsulated (FCM), utilize unique fuel elements called TRISO fuel particles that are fabricated to different fuel types (fissile or fertile) and different sizes (to achieve high packing fractions). These fuel particles are randomly packed in the reactor core at volume packing fractions ranging from 5% to 60%. To provide reliable predictions neutronic safety analysis in nuclear reactors, one needs to model the stochastic distributions of particles in the system, which presents a significant computational challenge to the study of radiation transport in 3-D particle systems. The work focuses on developing new algorithm targeting stochastic properties for Monte Carlo transport code and the applications on fuel design assessment. This research becomes important in the analysis of the stochastic distribution of fuel particles in Very High Temperature Gas-cooled Reactors (VHTR’s) and current light water reactors loaded with TRISO fuels. Nuclear reactors loaded with TRISO fuels have increased safety and are key in the design of some next generation reactors.