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At least 307 records · Page 17

PDC Modifications for Analysis of Gas-Cooled Reactors with Direct Helium Brayton Cycle

Capabilities of the Plant Dynamics Code (PDC) have been extended to allow steady-state and transient simulation of graphite-cooled reactors with direct helium Brayton cycle. On the cycle side, the most significant code modification is the addition of helium properties, in the format required by the code’s equations. Since the code was already formulated to handle more complex real gas properties, adding helium as working fluid that behaves like ideal gas was fairly straightforward. A reactor module was added to PDC to simulate a reactor cooled by the working fluid of the Brayton cycle. Two options are supported: channel type, typical for graphite gas-cooled reactors, and pin type, typical for light-water and liquid metal-cooled reactors. The reactor module is an extension of the electrical heater model and simulates heat deposition in the fuel and transfer of this heat from the fuel to the coolant through the matrix and tube materials. The new reactor module becomes the third option in PDC for modeling heat addition to the cycle, besides previously modeled heat addition heat exchanger and electrical heater. In addition to those changes, other minor code modifications and improvements were introduced during the work of expanding PDC to modeling of gas-cooled reactors. These modifications are summarized in the last chapter of this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Review of Potential Wigner Effect Impacts on the Irradiated Graphite in Decommissioned Hanford Reactors

This review of is motivated by the need to consider future disposal of the nine surplus Hanford Site production reactors (B, C, D, DR, F, H, KE, KW, and N) that are decommissioned as part of the Hanford Site Composite Analysis. The B Reactor has been designated as a museum. The other eight reactors will be evaluated in a future performance assessment before a final disposal facility can be authorized to construction or to receive this waste form. After a performance assessment is available, then the Hanford Site Composite Analysis would be updated to account for this additional source term. Disposal is currently assumed to occur in calendar year 2070 by one-piece removal to a projected disposal facility in the 200 West Area of the Hanford Site Central Plateau. The N Reactor core may also be disposed analogously to the single-pass reactors. It will further assume that the B Reactor will remain a museum permanently. The U.S. Department of Energy studied at least five decommissioning alternatives for long-term, safe management of radionuclide-contaminated materials inside the eight single-pass reactors (DOE/EIS-0119-FEIS, Decommissioning of Eight Surplus Production Reactors at the Hanford Site, Richland, Washington).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NEAMS Model Contributions in 2023 to the National Reactor Innovation Center Virtual Test Bed for Use by Industry and Other Stakeholders

The U.S. Department of Energy (DOE) Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program develops models of advanced reactor phenomena to demonstrate code applicability to challenging physics problems, drive code development through user assessment, and perform code verification and validation. Meanwhile, the U.S. DOE’s National Reactor Innovation Center (NRIC) hosts an open-source website and associated GitHub repository called the Virtual Test Bed (VTB) on which computational models for advanced reactors are documented and shared with the reactor community. This work documents NEAMS efforts to support industry adoption of advanced modeling tools through contribution of 10 NEAMS models to the NRIC Virtual Test Bed including models for the High Temperature Test Facility (HTTF), TRISO fuel failure in a microreactor, and multiphysics models of a molten chloride fast reactor, among others. The open sharing of these models benefits the reactor community by providing “best practice” examples using NEAMS tools for advanced reactor physics problems. In particular, the HTTF model is being used for code validation and benchmarking activities. The microreactor and molten chloride fast reactor models are representative of analysis that may be useful for current candidates of DOME and LOTUS, NRIC’s physical testbeds. This report summarizes and provides links to these new models, among others.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Safeguards Facility Model for Lead-cooled and Gas-cooled Fast Reactors

Efforts have been underway for many years on the development of safeguards for fast neutron reactors. The efforts have been primarily for sodium-cooled fast reactors (SFRs) in cooperation with Japan, to properly implement these safeguards as the reactors are conceptualized and ultimately commercialized. The primary challenge to development of adequate safeguard approaches for fast reactors has been in understanding how to apply different aspects of safeguards when facilities widely vary from one type of fast reactor to another and is largely dependent on several key aspects of the specific reactor type. For this report, the following key areas were identified for further analysis to determine where Lead-cooled Fast Reactors (LFRs) and Gas-Cooled Fast Reactors (GCFR) fuel material flow and key measurement points would differ from previously studied SFR safeguards.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SCALE 6.3 Validation: Reactor Physics

This study was performed to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the ENDF/B-VII.1 AMPX 56-group library for light-water reactor analysis by comparing the simulated results with the measured data for critical experiments and operating light-water reactors. Uncertainties of the SCALE/Polaris–PARCS code procedure for light-water reactor physics analysis were evaluated in the validation for key nuclear parameters such as reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors. In addition, the SCALE/TRITON v6.3.1 procedure with the ENDF/B-VII.1 and VIII.0 252-group and continuous-energy cross sections was validated for non-lightwater reactors including the HTR-10 reactor, the High-Temperature Test Reactor, the Molten Salt Reactor Experiment, and the Experimental Breeder Reactor II.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improvement and Verification of Online Cross Section Generation Capability of Griffin for TRISO-fueled Reactors

Griffin, a MOOSE-based reactor multiphysics code jointly developed by Idaho National Laboratory and Argonne National Laboratory under the DOE Office of Nuclear Energy’s NEAMS program, has pursued the development of an online multigroup cross section generation capability for a few years to enable high-fidelity, problem-dependent neutronics analyses of advanced thermal reactors. Recent advancements in Griffin’s online multigroup cross section generation capability have significantly improved the accuracy, robustness, and efficiency of self-shielding calculations for both prismatic and pebble-bed TRISO-fueled reactor applications. Key developments include a unified fuel self-shielding method applicable to both TRISO and annular compact/spherical shell fuel zone geometries; an advanced Dancoff Category-based Equivalence Theory using a bell function for non-fuel resonance treatment, achieving more than an order-of-magnitude speedup compared to the Tone method; an on-the-fly multigroup equivalence approach to mitigate group condensation errors; and a streaming correction method for pebble-bed homogenization. A proof-of-concept demonstration of on-the-fly group condensation with consistent P0 transport correction was also achieved. The method reproduced direct fine-group solutions with excellent accuracy (eigenvalue errors within 10 pcm and pin-power differences within 0.5%), but due to performance limitations of the current fixed-source solver, improvements to solver efficiency will be addressed in future work. Verification tests were performed on graphite-moderated TRISO-fueled two-dimensional core benchmark problems representing gas-cooled microreactors, heat pipe-cooled microreactors, gas-cooled pebble-bed reactors, and fluoride salt-cooled high-temperature reactors. Across all cases, Griffin showed excellent agreement with Serpent2 continuous energy Monte Carlo solutions: eigenvalue errors within 200 pcm, pin-power root-mean-square errors within 2%, and control rod and drum worth errors less than 2%. It should be noted that, for the benchmark problem, cross section generation contributed less than 3% of the total simulation times. These results demonstrate that Griffin’s online cross section generation capability delivers accurate and efficient reactor physics solutions across a wide spectrum of TRISO-fueled advanced reactor designs. With further improvements to the fine-group fixed-source solver and planned extensions to depletion, transients, and coupled neutron–gamma transport, Griffin will be well-positioned to become a powerful and comprehensive tool for advanced reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Developing Source Term Database for Advanced Reactors

A source term database is crucial to informing nuclear emergency response measures, enabling emergency responders to assess the potential severity of nuclear and radiological consequences. In recent times, various advanced reactor designs have come into operation, are under construction, or are being designed and developed. This report documents an effort carried out to develop a source term database for advanced reactors. The report covers key design features of these reactors and discusses radioactivity buildup and source term inventories of dose-significant radionuclides in the reactor core. For neutronic and depletion analyses, we used the SCALE code system, a computational suite for reactor physics, depletion, criticality, and sensitivity/uncertainty quantification. We used SCALE/TRITON to perform depletion calculations to predict cycle length and discharge burnup and to generate the ORIGEN reactor library. Subsequently, we used SCALE/ORIGAMI to calculate radioactivity buildup and, thereby, the source term inventories at the targeted discharge burnup, using the ENDF/B-VII.1 nuclear data library. This report covers several advanced reactors, including the KLT-40S, RITM-200N, VOYGR, and eVinci. However, other reactors, such as the RITM-200S and ARC-100, have yet to be investigated and will be explored in future efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling a Packed Bed Reactor Utilizing the Sabatier Process

A numerical model is being developed using Python which characterizes the conversion and temperature profiles of a packed bed reactor (PBR) that utilizes the Sabatier process; the reaction produces methane and water from carbon dioxide and hydrogen. While the specific kinetics of the Sabatier reaction on the RuAl2O3 catalyst pellets are unknown, an empirical reaction rate equation1 is used for the overall reaction. As this reaction is highly exothermic, proper thermal control is of the utmost importance to ensure maximum conversion and to avoid reactor runaway. It is therefore necessary to determine what wall temperature profile will ensure safe and efficient operation of the reactor. This wall temperature will be maintained by active thermal controls on the outer surface of the reactor. Two cylindrical PBRs are currently being tested experimentally and will be used for validation of the Python model. They are similar in design except one of them is larger and incorporates a preheat loop by feeding the reactant gas through a pipe along the center of the catalyst bed. The further complexity of adding a preheat pipe to the model to mimic the larger reactor is yet to be implemented and validated; preliminary validation is done using the smaller PBR with no reactant preheating. When mapping experimental values of the wall temperature from the smaller PBR into the Python model, a good approximation of the total conversion and temperature profile has been achieved. A separate CFD model incorporates more complex three-dimensional effects by including the solid catalyst pellets within the domain. The goal is to improve the Python model to the point where the results of other reactor geometry can be reasonably predicted relatively quickly when compared to the much more computationally expensive CFD approach. Once a reactor size is narrowed down using the Python approach, CFD will be used to generate a more thorough prediction of the reactors performance.

Reactor↗

Coupled Reactor Multiphysics and Mass Scalability Assessment for Crewed Megawatt-Class NEP System Architectures

Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution (PMAD), electric propulsion subsystem (EPS), and a primary heat rejection system. Specific mass, or αe (kg / kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass estimates for individual components. To inform technology maturation planning, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium (HALEU) reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively cooled heat pipe reactor concepts. Each concept requires specific geometries and working fluids to reach the performance goals of PCS interface conditions (temperature, pressure, flow rate) and system mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support technology down-selection along with related technology development planning. The reactor and shield αe are a function of several PCS design choices, and reactor scaling with these parameters must be considered to enable an informed decision on reactor geometry and working fluid combination.

Nuclear Electric Propulsion↗

Coupled Reactor Multiphysics and Mass Scalability Assessment for Crewed Megawatt-Class NEP System Architectures

Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution, electric propulsion system, and heat rejection system. Specific mass, or α (kg/kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass predictions for each individual component. To inform technology maturation planning activities, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively-cooled heat pipe reactor concepts. Each concept requires specific geometries, fluids, and power conversion interface conditions (temperature, pressure, flow rate) to meet desired performance and mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support concept down-selection along with related technology development planning. The reactor and shield α are a function of several PCS and heat rejection system design choices, and reactor scaling with these parameters must be considered to enable an informed decision on an optimal reactor geometry and working fluid combination.

Nuclear Electric Propulsion↗

CFD Validation of a Methanation Reactor With Cooling Jacket Used in an ISRU Propellant Production System

A digital model of an OxEon Energy methanation reactor (with a cooling jacket) planned for use in a NASA designed In-Situ Resource Utilization (ISRU) propellant production system was developed by the UTEP Aerospace Center using STAR-CCM+ software, a Siemens Computational Fluid Dynamics (CFD) package. The reactor digital model created includes two primary components: (i) a cooling jacket that maintains the required reactor chamber surface temperature and (ii) a reactor core chamber where the exothermic methanation reactions occur. The StarCCM+ digital model has two objectives: (i) maintain the surface temperature of the reactor below a set value so that the extra heat accumulation does not melt or crack the chamber, and (ii) produce the desired amount of methane (CH4) according to test cases completed by OxEon Energy for NASA JSC. The computational digital model was validated with the test data enabling the cooling jacket scale to be predicted based on the reactor's operating temperature. The StarCCM+ simulation of the digital model shows a good agreement with the cooling jacket performance and the CH4 production. One test case for the cooling jacket maintained the reactor wall temperature around 310 °C was validated and the reactor produced 185 g/hr CH 4 .

ISRU↗

Establishing Regulatory Jurisdictional Boundaries at Collocated Advanced-Reactor Facilities

This white paper discusses establishing and applying nuclear facility jurisdictional boundaries at advanced-nuclear-reactor facilities. It was written for industry review and evaluation with possible consideration by the U.S. Nuclear Regulatory Commission (NRC) for subsequent regulatory action. The paper proposes a regulatory basis for establishing jurisdictional boundaries at operational advanced (i.e., non-light water) reactor installations at sites proximate to and sharing systems with non-NRC regulated facilities (e.g., users of process heat, fossil-plant retrofits, microgrid electrical power, desalination, etc.). Advanced-reactor technologies can be applied to support many industrial applications to replace the burning of fossil fuels as well as produce steam for electricity. The principal application of the current light-water reactor fleet is electricity generation. These varied industrial applications may involve an advanced-reactor design in combination with different site-specific energy-conversion systems. Some of these process-heat applications will require process-heat delivery systems to lie partially outside the advanced-reactor operator’s facility. Energy conversion systems are conventional, non-nuclear equipment and buildings. Given these varied applications, there should be a clear understanding between the advanced-reactor applicant and the NRC regarding a nominal demarcation between those systems that reside within the nuclear facility under the regulatory jurisdiction of the NRC (i.e., within the scope of a 10 Code of Federal Regulations (CFR) 50 operating license or Part 52 design certification and a combined license) and those that fall outside the scope of the NRC (e.g., an industrial facility). Additionally, it is important to have a clear understanding regarding the plant scope that should be addressed in an advanced-reactor facility Part 52, design certification application and the part of the plant scope that could be addressed as part of a site specific combined license application.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Preliminary Analysis of Advanced Reactor Spent Nuclear Fuel Storage, Transportation, and Disposal

Due to increased interest in advanced reactor deployment and their associated potential new fuel cycles, the U.S. Department of Energy (DOE) Spent Fuel and Waste Science and Technology (SFWST) program has begun to evaluate the possible implications of long term management and final disposition of the spent nuclear fuel (SNF) generated. Safely managing and dispositioning this SNF, along with any other associated radioactive waste, is the primary focus of this initial preliminary assessment. This paper summarizes efforts to evaluate the characteristics and packaging options for three types of advanced reactor SNF forms: (1) tristructural isotropic (TRISO), (2) metallic, and (3) irradiated fuel salt presented in the report titled “Storage, Transportation, and Disposal of Advanced Reactor Spent Nuclear Fuel and High-Level Waste”. TRISO and metallic SNF and their associated waste streams were emphasized because of the near-term anticipated demonstrations of X-energy’s Xe-100 and TerraPower and GE Hitachi’s Natrium advanced reactors. Preliminary information on spent fuel salts discharged from molten-salt reactors (MSRs) was also examined to provide a baseline for future efforts. All calculations and assumptions were based on publicly available information. This paper identifies several different reactors that produce either TRISO or metallic SNF as well as a few of the reactor and fuel characteristics used for the assessments. Based on these characteristics, calculations were performed to determine the applicability of packaging SNF into existing canister designs. The evaluations included geometric (e.g., dimension, volume) and mass/weight considerations, known operational approaches and loading procedures, physical and chemical considerations/conditions for storage environments, and as-loaded radiation, thermal, and criticality analyses to identify constraints on storage, transportation, and disposal. Gaps in publicly available data pertaining to reactor operation and/or fuel composition provide increased uncertainty in some evaluations. Additionally, uncertainty in packaging and SNF management operations provide additional uncertainty. However, preliminary conclusions can still be assessed through this work and are presented in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparing Legacy Waste Management to Advanced Reactor Waste Management

The Nuclear Energy Agency (NEA) and Natural Resources Canada (NRCan) are organizing an international workshop on the implementation of radioactive waste management and decommissioning strategies in small modular reactors (SMRs) and advance reactor technologies. The event will take place in Ottawa, Canada on 7-10 November 2022. The workshop will convene participants from various fields of expertise in the areas of radioactive waste management, decommissioning, nuclear science and development, transportation, as well as young professionals, communication experts and researchers. The goal of the workshop is to devise a guideline document that will serve implementers in understanding key issues in decommissioning and waste management of new reactors from the design perspective, aiding in the licensing process and in future decommissioning and waste management activities. DOE has invested considerably in the innovation of advanced reactors. Interaction in this workshop allows INL and DOE to articulate the importance of looking at the back-end of the fuel cycle for advanced reactors. The back-end of the fuel cycle is important to the success of advanced reactors, and DOE may need to manage this material in the future after it is discharged from reactors. I have been asked to present at the track titled "Operational and Design Optimization Consideration Related to Decommissioning and Radioactive Waste Management for SMRs/Advanced Reactors".

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multi-cycle reload analysis of a long cycle gas-cooled fast modular reactor

There is currently significant interest in deploying HALEU-fueled fast reactors, including the General Atomics (GA) Fast Modular Reactor (FMR). Such reactors can achieve very long fuel cycles, but with multi-batch loading will take decades to reach equilibrium. This motivates design and analysis of both the initial core and multi-cycle reload, which is typically performed using fast-running, deterministic fast reactor codes such as the Argonne Reactor Computation (ARC) codes. In this paper, multicycle reload of the GA FMR is analyzed using the ARC codes. The GA FMR utilizes 19.75 % enriched fuel in a 16 year cycle with a three-batch strategy, with twice-burned fuel placed on the core periphery. The GA FMR has a softened neutron spectrum due to reflecting elements in the core, so the neutronic solution is first benchmarked against the OpenMC Monte Carlo code. Discrepancy on k eff is 400–600 pcm, likely due to the softened neutron spectrum, heterogeneous fuel assembly design and central reflector. However, the rms discrepancy on the assembly power distribution is only 0.6 %, despite the presence of the central reflector. A reload strategy is devised for the first three cycles of such a reactor, ultimately spanning the first 45–48 years of its operation. The fresh core uses 19.75 %, 19.25 % and 16.75 % enriched fuel in place of fresh, once-burned and twice-burned and is then subsequently refueled with only 19.75 % enriched fuel. The cycle length is varied over 3 cycles of operation to balance fuel utilization and reactor availability, specifically with use of an extended 18-year Cycle 1, followed by a shortened 11-year Cycle 2. Cycle 3 is close to the target 16-year length. Finally, placing twice burned assemblies next to the GA FMR central reflector can reduce power peaking by 3 %, at the expense of slightly reducing the cycle length.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms

The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Technoeconomic Design Optimization for Fast Reactors. Part II: Impact of Technoeconomic Constraints on Optimal Design

There is a current drive toward optimizing reactors, particularly small/micro reactors to minimize cost and maximize performance. Previous work has investigated the development of technoeconomic workflows for the design optimization of pool-type fast reactors that aim to deploy into district energy grids. Initial scoping studies verified that the workflow was capable of capturing design trends throughout a variety of design configurations and problem formulations while remaining sufficiently flexible. In this paper, this methodology is applied to understand how cost functions and technoeconomic constraints can drive optimal reactor design. Specifically, the UPu10Zr-fueled fast reactor model from Part I is adapted to include changes in the fissile content limits, control rod worth limits, control rod drive cost, and assumed fuel form. In the case of constraint relaxation at fixed power (fissile content and control rod worth limits), cost sensitivities of 5% to 10% were uncovered. Multi-objective optimization at varying reactor power levels with individualized control rod drives for each assembly (as opposed to one operational and one safety drive) increased cost by $\$10$ to $\$25$ million and substantially altered the optimal core geometry, favoring geometries with substantially fewer control rod placements relative to baseline optimization. Finally, a multi-objective optimization was performed at varying power levels with the fuel form overhauled to metallic, high-assay low-enriched uranium–based U10Zr with more refined fuel cost models. In the case of uranium fueling, the costs increased by at least $50 million relative to the baseline case. Furthermore, economic fuel zoning and lower reactivity swing cores were recovered. Each case serves to demonstrate the value of applying technoeconomic workflows to initial reactor design scoping studies to better understand the trade-off for a proposed concept between different design options.

Argonne Reactor Computation (ARC) codes↗