Stochastic media is important in many fields of nuclear engineering including reactor design, radiation transport applications, and reactor safety. This project will assess the impact of the random fragmentation of fuel assemblies on reactivity and kinetic parameters which can be applied to the evaluation of criticality safety to prevent future accidents.

Accurate simulations of nuclear systems rely on accurate cross-section data.  Due to the complications of thermal scattering, a large amount of thermal data needs to be stored for large temperature ranges due to the needed accuracy.  This work aims to reduce the memory burden for large temperature ranges while preserving the needed accuracy.

Powerful, modern, and user-friendly nuclear engineering workflows are achieved with metamodel-driven modeling. The full potential of codes like MCNP can be harnessed for advanced multi-physics reactor simulations.

Insoluble fission product & corrosion product generation, behavior, and transport have a significant effect on reactor neutronics and thermal-hydraulics which require new modeling capabilities for Molten Salt Reactors (MSRs). Main objective of this research is developing and coupling mesoscale and system level models for species transport to replicate and simulate possible multiphysics effects caused by species transport. This research must tackle several key challenges:

• Species/chemical concentration changes through fission and mass transfer in ionic fuel-salt changes the thermochemical state of fuel-salt which drive surface corrosion/deposition of insoluble species.
• Deposition of insoluble species causes multiphysics effects in reactor including the generation of circulating bubbles/voids which cause power blips in the reactor, effect source term generation in the off-gas system, and can cause localized decay heat regions.
• Understanding and determining the impact of these multiphysics effects on the reactor are critical for future design considerations and mitigation strategies to ensure safe reactor designs during normal reactor operation and accident condition scenarios.

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. 

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.

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.

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.

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.

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.

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.

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.