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Modeling a Lead-Cooled Fast Reactor with Thermal Energy Storage using Optimal Dispatch and SAM
Increased contributions from wind and solar energy have helped set the United States on an attainable pathway towards carbon-free energy production. Though renewable energy is pivotal for this goal, saturating the grid with these variable energy sources has its challenges. Resources for wind and solar vary from factors beyond human control, hence the power output from these energy generators doesn’t necessarily match power demand for a specific region at a given moment in time. Solar photovoltaic production has a drastic mismatch since the peaks for power demand and power production are often out of phase: production peaks with available irradiance while demand peaks during the morning and evening hours. This “duck curve” in energy demand, the difference between high and low demand, grows as the grid becomes more saturated with renewable energy providers.
Fabrication and Testing of Advanced Fuels for Lead and Sodium Cooled Fast Reactors
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Estimation of the sub-criticality of the sodium-cooled fast reactor Monju using the modified neutron source multiplication method
The Modified Neutron Source Method (MNSM) is applied to the Monju reactor. This static method to estimate sub-criticality has already given good results on commercial Pressurized Water Reactors. The MNSM consists both in the extraction of the fundamental mode seen by a detector to avoid the effect of higher modes near sources, and the correction of flux distortion effects due to control rod movement. Among Monju's particularities that have a big influence on MNSM factors are: the presence of two californium sources and the position of the detector which is located far from the core outside of the reactor vessel. The importance of spontaneous fission and ({alpha}, n) reactions which have increased during the shutdown period of 15 years will also be discussed. The relative position of detectors and sources deeply affect the correction factors in some regions. In order to evaluate the detector count rate, an analytical propagation has been conducted from the reactor vessel. For two subcritical states, an estimation of the reactivity has been made and compared to experimental data obtained in the restart experiments at Monju (2010). (authors)
Validation of nuclear design method by measured data obtained in the physics test at a small fast reactor
The present paper discusses applicability of the measured data of Joyo cores from a view point of integral validation for the 4S nuclear design methodology. Through the evaluation of isothermal reactivity coefficients and reactivity losses due to burnup, the results confirm that those MK-I and MK-II database are effective in order to increase the dataset for uncertainty estimation for the prediction. Discussions on the 4S design method validation are also done through the analyses of criticality, power distributions and reactivity loss due to burn-up. The C/E values for criticality and reaction rate distributions are confirmed to be consistent with those obtained from the physics benchmark experiments. Through an analysis of burnup coefficient of the MK-I core by the detailed Monte Carlo calculations, the C/E value is 1.1, which is close to 1.06 obtained by the deterministic transport analysis. (authors)
Pyroprocessing of oxidized sodium-bonded fast reactor fuel - An experimental study of treatment options for degraded EBR-II fuel
An experimental study was conducted to assess pyrochemical treatment options for degraded EBR-II fuel. As oxidized material, the degraded fuel would need to be converted back to metal to enable electrorefining within an existing electro-metallurgical treatment process. A lithium-based electrolytic reduction process was studied to assess the efficacy of converting oxide materials to metal with a particular focus on the impact of zirconium oxide and sodium oxide on this process. Bench-scale electrolytic reduction experiments were performed in LiCl-Li{sub 2}O at 650 C. degrees with combinations of manganese oxide (used as a surrogate for uranium oxide), zirconium oxide, and sodium oxide. In the absence of zirconium or sodium oxide, the electrolytic reduction of MnO showed nearly complete conversion to metal. The electrolytic reduction of a blend of MnO-ZrO{sub 2} in LiCl - 1 wt% Li{sub 2}O showed substantial reduction of manganese, but only 8.5% of the zirconium was found in the metal phase. The electrolytic reduction of the same blend of MnO-ZrO{sub 2} in LiCl - 1 wt% Li{sub 2}O - 6.2 wt% Na{sub 2}O showed substantial reduction of manganese, but zirconium reduction was even less at 2.4%. This study concluded that ZrO{sub 2} cannot be substantially reduced to metal in an electrolytic reduction system with LiCl - 1 wt% Li{sub 2}O at 650 C. degrees due to the perceived preferential formation of lithium zirconate. This study also identified a possible interference that sodium oxide may have on the same system by introducing a parasitic and cyclic reaction of dissolved sodium metal between oxidation at the anode and reduction at the cathode. When applied to oxidized sodium-bonded EBR-II fuel (e.g., U-10Zr), the prescribed electrolytic reduction system would not be expected to substantially reduce zirconium oxide, and the accumulation of sodium in the electrolyte could interfere with the reduction of uranium oxide, or at least render it less efficient.
Fast Reactor Materials R&D Update
Focus on materials and design methods to support advanced reactors deployment Design, construction, licensing and operations
Sodium Fast Reactor Probabilistic Risk Assessment Activities
Powerpoint slides for meeting with KAERI, organized by YungJoon Choi
Powder Injection Molding Processes for Manufacture of Fast Reactor Nuclear Fuels
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COUPLED GRIFFIN AND PRONGHORN SIMULATION OF THE MOLTEN SALT FAST REACTOR (MSFR) FOR THE VIRTUAL TEST BED
The Virtual Test Bed (VTB) repository hosts a wide range of challenge problems to showcase modeling and simulation capabilities to support advanced reactor demonstration. An overview of a coupled multiphysics model for Molten Salt Reactors (MSR) is presented here. The analysis leverages MOOSE-based tools (notably Griffin and Pronghorn) for neutronic and thermal hydraulic simulation. Neutron precursor drifting capability is showcased, along with some initial turbulence models. Both steady-state and transient coupled multiphysics results for an MSR concept are discussed.
Assessment of Fission Product Release Behavior in Sodium-Cooled Fast Reactors for Consequence Assessment
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Removal and Deactivation of Bond Sodium from Fast Reactor Blanket Materials
The disposition of sodium-bonded spent nuclear fuel and blanket materials in a repository is complicated by the presence of sodium metal that is used as a thermal bond between the uranium metal fuel and blanket slugs and their cladding. The concern is that the metallic sodium could react with water, producing explosive hydrogen gas, or could exhibit a pyrophoric character. Thus, experimental studies were performed to investigate and demonstrate the removal and deactivation of bond sodium from blanket material in a dry environment. Specifically, bond sodium was removed from unirradiated Fermi-1 blanket elements and an assembly via a melt-drain-evaporate process using elevated temperature and reduced pressure. The effectiveness of sodium metal removal from the blanket materials and their associated cladding was =99.9998%, based on post-test quantitative analyses. The separated sodium metal was collected and subsequently deactivated by reacting it in a molten state with a controlled addition of ammonium chloride particles atop a molten salt medium. In this process sodium chloride is formed and assimilates into the salt pool. The subsequent deactivation of the bond sodium produced a solid ingot of sodium chloride, potassium chloride, lithium chloride, and cesium chloride that was devoid of sodium metal based on post-test analyses of the salt product. Both the sodium removal and deactivation operations were conducted within a dry inert atmosphere enclosure. The results of this study substantiate a path forward for the disposition of sodium-bonded blanket materials, including 34 metric tons heavy metal in irradiated Fermi-1 blanket material currently stored at Idaho National Laboratory.
Removal and Deactivation of Bond Sodium from Fast Reactor Blanket Materials
The attached power point slides summarize work described in an accompanying paper for the conference. See PRS/CON-24-04285 and INL/CON-24-76787.
Irradiation Damages of Structural Materials under Different Irradiation Environments
For the advancement and development of nuclear systems used in heavy irradiation environments such as fusion DEMO reactors, fission reactors, fast reactors, and accelerator driven target systems, it is necessary to fully understand the changes of mechanical properties and the other properties of the materials induced by irradiation and to clarify the synergistic effect of displacement damage and helium generation. In this study the mechanical property changes and microstructural development induce by displacement damage and helium production have been mainly examined in austenitic stainless steels, 316FR and type304, and ferritic/martensitic steel, HCM12A, irradiated at around 550oC in JRR-3M reactor and/or JOYO fast reactor. At 550°C, 316FR steel was superior to 304 steel in terms of the amount of ductility and strength with respect to irradiation resistance. It is noteworthy that at 550 °C as well as room temperature, the higher fracture strength of the 316FR steels is a remarkable result. It is found that helium atoms strongly influenced on creep lifetime of the irradiated austenitic stainless steel, 316FR. It was found that the ratio of creep rupture time is slightly lower than the lower limit of previous study’s Miyaji and co-workers in the region from 0.01 appm to 1 appm. It is also found that the lower limit of reduction ratio of creep rupture time (irradiation specimen to unirradiation one) does not decrease linearly with the helium production above 10 appm up to about 33 appm. dpa enhanced the reduction of creep lifetime. Recent R&D of high-energy accelerator driven target systems used under heavy irradiation environment is also introduced and discussed for high radiation resistance materials such as Ti alloys with very high number density of nano size precipitate, which have been studying under RaDIATE collaboration, from points of view of irradiation damage and materials development.
The Fast Modular Reactor (FMR) - Development Plan of a New 50 MWe Gas-cooled Fast Reactor
General Atomics Electromagnetic Systems (GA-EMS) will be developing a new 50-megawatt electric (MWe) fast modular reactor (FMR), under the Department of Energy’s (DOE’s) Advanced Reactor Demonstration Program (ARDP), Advanced Reactor Concepts 2020 (ARC-20) development pathway, that provides safe, carbon free electricity, capable of incremental capacity additions. A modular design allows it to be factory-built and assembled on-site to keep the cost of capital low, while the dry-cooling facilitates siting to complement renewables in nearly any location. GA-EMS is committed to commercialization of the proposed reactor, with a demonstration by 2030, and deployment by the mid-2030s. The ultimate goal of the design is to develop flexible and dispatchable carbon-free power source for the 2035 US electricity market. The GAEMS- led team will verify that simplified characteristics (e.g., inert helium gas coolant, pellet-loaded fuel rod, installation-free of heat sink requirements, small and passive heat removal systems) of the FMR will result in a safe, maintainable, cost-effective, distributed, nuclear energygenerating station. Three key specific project objectives for the next three years include: Development of the conceptual design of the 50- MWe FMR plant, Achievement of Technology Readiness Level (TRL) 4 for key system and component technologies through in-pile tests, out-of-pile tests, and numerical experiments; and Development of robust techno-economic analysis (TEA) and pre-application licensing approach necessary for timely demonstration and eventual commercialization.
Validation of Criticality Analysis Capability of SuperMC with ICSBEP
SuperMC is a general purpose, intelligent and multifunctional, continuous energy Monte Carlo program for the design and safety evaluation of nuclear systems. It is designed to perform the comprehensive neutronics calculation, taking the radiation transport as the core and including the depletion, radiation source term/dose/biohazard, material activation and transmutation, etc. The latest version of SuperMC can perform the simulation of neutron, photon and coupled neutron and photon transport, and also equipped with the functions of automatic modeling and visualization. SuperMC has been verified by more than 2000 benchmark models and experiments including the handbook of International Criticality Safety Benchmark Evaluation Project (ICSBEP), the Shielding Integral Benchmark Archive Database (SINBAD), etc. The fusion reactor (ITER benchmark model, FDS Fusion Reactors), fast reactors (BN600, CLEAR-I), PWR reactors (HM, BEAVRS) and cases from the International Reactor Physics handbook Evaluation Program (IRPhEP) were employed for validating the comprehensive capability for reactor applications. In this paper, the validation of SuperMC based on the handbook of ICSBEP will be presented. ICSBEP, released by OECD/NEA, contains criticality safety benchmark specifications derived from experiments that were performed at various nuclear critical facilities around the world, which was widely used to verify neutronic codes and associated nuclear data libraries for criticality safety analysis. (authors)
Group Structure Optimization Using the PyGroup Code
Group constants are used as coefficients in the energy domain discretized Linear Boltzmann Equation (LBE), in which the Continuous-Energy (CE) fluxes are also integrated over energy bins and transformed into group fluxes. This procedure, based on the Multi-Group (MG) theory, is widely applied in radiation transport and diffusion simulations Careful preparation of MG cross section data, or group constants, is thus a prerequisite for success in acquiring high-fidelity LBE solutions. Generation of MG cross section data itself is a complicated multi-step task, since group constants are indispensably coupled with the solution of the LBE, i.e. the flux spectrum in the problem to be solved. Theoretically, a MG cross section library is only valid for the problem that it is built upon. Nevertheless, in practice MG cross section libraries are prepared for similar type of problems, such as thermal reactors, fast reactors, etc., to facilitate the neutronic simulations. Generally, CE point-wise cross section data set, generated by both theoretical models and experimental data, is first converted to Fine-Group (FG) libraries using a pre-defined or precalculated flux spectra, then, Broad-Group (BG) libraries are collapsed from the fine-group libraries using problem-dependent flux spectra. Proper treatments of energy and spatial self-shielding and resonance cross section are required in the CE-to-MG converting process Previously, we have developed a computer code, YGROUP, for fine-to-broad group cross section collapsing. To maintain high accuracy of the resulting BG libraries, YGROUP provides users several options on collapsing strategies and weighting schemes for group binning and evaluation of BG cross section data in users' specific problems.. An approach based on Particle Swarm Optimization was applied to automatically determine the optimal group structure. We also developed a hybrid weighting scheme to further improve BG library performance for Special Nuclear Materials (SNM) detection applications. In this work, a new computer code, PyGroup, has been developed to implement the PSO approach with an improved simulation-driven fitness function design that includes both response and forward/adjoint flux errors. Together with YGROUP, and deterministic transport code TITAN/PENMSHXP, the PyGroup code package is tested on a Dual Range Coincident Counter (DRCC) model. In this paper, we demonstrated the capability of the PyGroup code for group structure optimization using the DRCC detector model. In the future, an iteration scheme can be implemented to determine the number of broad groups based on a user-defined tolerance. we will also apply PyGroup to more complicated reactor models, and investigate physics-based fitness function designs to further reduce computational cost. (authors)