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5 result(s) for "DeHart, Mark D"
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A Review of Candidates for a Validation Data Set for High-Assay Low-Enrichment Uranium Fuels
Many advanced reactor concept designs rely on high-assay low-enriched uranium (HALEU) fuel, enriched up to approximately 19.75% 235U by weight. Efforts are underway by the US government to increase HALEU production in the United States to meet anticipated needs. However, very few data exist for validation of computational models that include HALEU, beyond a few fresh fuel benchmark specifications in the International Reactor Physics Experiment Evaluation Project. Nevertheless, there are other data with potential value available for developing into quality benchmarks for use in data- and software-validation efforts. This paper reviews the available evaluated HALEU fuel benchmarks and some of the potentially relevant benchmarks for fresh highly enriched uranium. It then introduces experimental data for HALEU fuel irradiated at Idaho National Laboratory, from relatively recent irradiation programs at the Advanced Test Reactor. Such data should be evaluated and, if valuable, collected into detailed benchmark specifications to meet the needs of HALEU-based reactor designers.
Multiphysics Simulation of the NASA SIRIUS-CAL Fuel Experiment in the Transient Test Reactor Using Griffin
After approximately 50 years, NASA is restarting efforts to develop nuclear thermal propulsion (NTP) for interplanetary missions. Building upon nuclear engine tests performed from the late 1950s to the early 1970s, the present research and testing focuses on advanced materials and fabrication methods. A number of transient tests have been performed to evaluate materials performance under high-temperature, high-flux conditions, with several more experiments in the pipeline for future testing. The measured data obtained from those tests are being used to validate the Griffin reactor multiphysics code for this particular type of application. Griffin was developed at Idaho National Laboratory (INL) using the MOOSE framework. This article describes the simulation results of the SIRIUS-CAL calibration experiment in the Transient Reactor Test Facility (TREAT). SIRIUS-CAL was the first transient test conducted on NASA fuels, and although the test was performed with a relatively low core peak power, the test specimen survived a temperature exceeding 900 K. Griffin simulations of the experiment successfully matched the reactor’s power transient after calibrating the initial control rod position to match the initial reactor period. The thermal-hydraulics model largely matches the time-dependent response of a thermocouple located within the experiment specimen to within the uncertainty estimate. However, the uncertainty range is significant and must be reduced in the future.
PBMR-400 BENCHMARK SOLUTION OF EXERCISE 1 AND 2 USING THE MOOSE BASED APPLICATIONS: MAMMOTH, PRONGHORN
High temperature gas cooled reactors (HTGR) are a candidate for timely Gen-IV reactor technology deployment because of high technology readiness and walk-away safety. Among HTGRs, pebble bed reactors (PBRs) have attractive features such as low excess reactivity and online refueling. Pebble bed reactors pose unique challenges to analysts and reactor designers such as continuous burnup distribution depending on pebble motion and recirculation, radiative heat transfer across a variety of gas-filled gaps, and long design basis transients such as pressurized and depressurized loss of forced circulation. Modeling and simulation is essential for both the PBR’s safety case and design process. In order to verify and validate the new generation codes the Nuclear Energy Agency (NEA) Data bank provide a set of benchmarks data together with solutions calculated by the participants using the state of the art codes of that time. An important milestone to test the new PBR simulation codes is the OECD NEA PBMR-400 benchmark which includes thermal hydraulic and neutron kinetic standalone exercises as well as coupled exercises and transients scenarios. In this work, the reactor multiphysics code MAMMOTH and the thermal hydraulics code Pronghorn, both developed by the Idaho National Laboratory (INL) within the multiphysics object-oriented simulation environment (MOOSE), have been used to solve Phase 1 exercises 1 and 2 of the PBMR-400 benchmark. The steady state results are in agreement with the other participants’ solutions demonstrating the adequacy of MAMMOTH and Pronghorn for simulating PBRs.
EVALUATION OF CRITICAL EXPERIMENTS IN THE UNIVERSITY OF WISCONSIN NUCLEAR REACTOR (UWNR) WITH UNCERTAINTY QUANTIFICATION
An improved computational model of the University of Wisconsin Nuclear Reactor (UWNR) was developed to support the benchmark evaluation of recent data acquired during an experimental campaign conducted at UWNR. Previous efforts led to a scripted UWNR model for automated generation of MCNP6 and Serpent inputs. This capability was extended to SCALE/KENO. All three tools were used to evaluate a variety of zero-power, fresh-critical configurations, and the results agreed well. The MCNP6 model was extended to support shuffling the core configuration, which allows the modeling of burnup for evaluation of depleted critical configurations. The MCNP6 model successfully predicts core reactivity over time, after accounting for the initial reactivity bias. The inclusion of SCALE/KENO input generation enables sensitivity and uncertainty analyses using the TSUNAMI and Sampler modules of SCALE. A preliminary uncertainty analysis was performed with TSUNAMI for nuclear data uncertainties while direct perturbation calculations were performed using MCNP6 for geometry and material uncertainties, which helped to identify model parameters with the largest effect on the eigenvalue. A transient UWNR transport Model in Mammoth/Rattlesnake is under development to simulate the transient experiments. The existing MCNP6 and Serpent models are used to provide the CAD file for meshing and homogenized cross-sections. In conclusion, the evaluation of UWNR benchmark data provides increased confidence in various states of the UWNR computational model and will provide a unique model for use by other analysts.