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Current Nuclear Data Needs for Applications
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Selection of a Pair of Experiments to Optimally Reduce Uncertainty in Targeted Nuclear Data
We propose a novel process to select a pair of differential and integral experiments that best reduce uncertainties in targeted 239 Pu nuclear data while compressing the current nuclear data pipeline from 20 to 3 years. 239 Pu nuclear data are poorly understood for neutrons in the intermediate energy range due to sparsity and uncertainty in historical experiments. New experiments targeting this range will enable better understanding of these nuclear data, but choosing the ideal experiments to conduct is challenging. Beginning with a prior distribution represented by samples of nuclear data generated from theory, generalized least squares adjustments are made to incorporate data from historical experiments. To quantify potential uncertainty reduction obtainable from a pair of candidate experiments, we compute the D-optimality criterion of the posterior covariance of intermediate energy range nuclear data compared to the equivalent covariance after additional adjustment to the pair of candidate experiments. Repeating the process for each of many candidate pairs facilitates the final selection. Results support 63 Cu total cross section measurements for differential experiments and alumina and alumina/graphite configurations for integral experiments. This analysis enables choosing differential and integral experiments to be executed concurrently while shortening decision times relative to the current nuclear data pipeline.
Autonomous Monitoring of Nuclear Repositories: Current State of the Art and Future Directions
Geological repositories for nuclear waste, including spent nuclear fuel, present a significant challenge for traditional International Atomic Energy Agency (IAEA) safeguards tools due to their inaccessibility and demanding operational conditions. The IAEA has been working closely with Member State organizations currently involved in repository construction and planning, including Euratom, the Finnish and Swedish regulatory authorities, and relevant facility operators. However, the verification challenge remains unsolved, and there persists an out- standing need for tools and approaches that will help the IAEA verify that no nuclear material is diverted from a repository environment. The challenge is also not static. Activities must encompass verification of the design, prior to and during the construction/operation phase, and post backfill. Throughout these various phases, it is imperative that the IAEA maintains a continuity of knowledge (CoK) of all material including information on material inventory and flow. This paper highlights these challenges and outlines how they might be addressed by using remote or autonomous vehicles. Specifically, we discuss the current state of the art in robotic autonomy for known or partially known environment mapping and patrolling, as well as shared autonomy, where humans collaborate with closed-loop autonomation to complete tasks. We explore the feasibility of using rovers for these verification tasks, along with the challenges associated with system implementation. Hardware and software suggestions are provided based on the adoption of similar technologies in other comparable areas and ability to close technical gaps. Lastly, human-robotic interactions are considered based on the challenges of the environment of the repository and effective deployment and continued operation of the robot system.
Evaluating Nuclear Forensic Signatures for Advanced Reactor Deployment: A Research Priority Assessment
The development and deployment of a new generation of nuclear reactors necessitates a thorough evaluation of techniques used to characterize nuclear materials for nuclear forensic applications. Advanced fuels proposed for use in these reactors present both challenges and opportunities for the nuclear forensic field. Many efforts in pre-detonation nuclear forensics are currently focused on the analysis of uranium oxides, uranium ore concentrates, and fuel pellets since these materials have historically been found outside of regulatory control. The increasing use of TRISO particles, metal fuels, molten fuel salts, and novel ceramic fuels will require an expansion of the current nuclear forensic suite of signatures to accommodate the different physical dimensions, chemical compositions, and material properties of these advanced fuel forms. In this work, a semi-quantitative priority scoring system is introduced to identify the order in which the nuclear forensics community should pursue research and development on material signatures for advanced reactor designs. This scoring system was applied to propose the following priority ranking of six major advanced reactor categories: (1) molten salt reactor (MSR), (2) liquid metal-cooled reactor (LMR), (3) very-high-temperature reactor (VHTR), (4) fluoride-salt-cooled high-temperature reactor (FHR), (5) gas-cooled fast reactor (GFR), and (6) supercritical water-cooled reactor (SWCR).
Instrumentation for the In-Core Real-Time Mechanical Testing of Structural Materials (INCREASE) Project
Idaho National Laboratory (INL), in collaboration with the Electric Power Research Institute (EPRI), the Nuclear Regulatory Commission (NRC), the French Atomic and Alternative Energies Commission (CEA), the Joint Research Center (JRC), the Nuclear Research and Consultancy Group (NRG), and the Research Center Rez (CVR), started a Joint Experimental Program (JEEP) project that operates within the Nuclear Energy Agency’s Framework for Irradiation Experiments (FIDES II) program in order to develop capabilities for the in-core real-time mechanical testing of structural materials. This effort will focus on designing a shared capsule capable of housing a variety of in-core mechanical testing instrumentation allowing enhanced experiments for the material science community. The outcome of the project would be high-priority, stress relaxation data for stainless-steel-based materials provided by EPRI and CEA. Stress relaxation is a major phenomenon that contributes to material degradation in nuclear reactor components. Currently, nuclear material stress relaxation is assessed both before and after irradiation, using complex and costly post-irradiation examination (PIE) activities. In-situ data would support the development of precision modeling and simulation of this degradation phenomena and would provide validation and benchmarking for existing models using the PIE data. As part of the U.S. Department of Energy Advanced Sensor and Instrumentation (ASI) program, INL has fabricated and tested out-of-core mechanical test instrumentation. This instrumentation was designed for easy adaptation to the irradiation capsule proposed under this JEEP, and can be deployed to measure real-time stress relaxation under pressurized-water reactor (PWR) conditions. This initial effort will partially serve to replace the testing capabilities lost because of shutting down the Halden Boiling Water Reactor (HBWR). The project would provide these capabilities to the international community via a shared capsule design that is easily adaptable to additional material test reactors. The design features will incorporate expansion to PWR and non-light-water reactor (LWR) environments that will be developed in future work. The capsule and instrumentation will be demonstrated in the Massachusetts Institute of Technology Reactor (MITR) for phase I and the Petten High Flux Reactor (HFR) for phase II irradiations to deliver real-time stress relaxation data on high priority stainless steel structural materials.
Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States
Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.
Modernizing the Nuclear Industry and New Ways of Working
Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.
Discovery of nuclear isomers
Currently, 1917 nuclear isomers with half-lives longer than 100 ns have been discovered in 1310 different nuclides and 103 different elements. Here, while the physical properties of isomers have been compiled before, this is the first compilation of the isomer discoveries. For each isomer the reference, year, laboratory and country are documented.
Development of a bench-scale dissolution concept for the direct extraction of nuclear fuel
Current used nuclear fuel reprocessing efforts utilize a hydrometallurgical approach in which the UNF is dissolved in hot nitric acid followed by solvent extraction into an organic solvent to harvest target nuclides. Previous studies have shown that the dissolution and loading process could be combined into a single organic dissolution/extraction step, producing loaded organic in a single step process. This single step process also includes the advantage of selectively targeting key nuclides in the dissolution while leaving undesirable constituents as part of the undissolved solids. This process is referred to hereafter as direct extraction. Ongoing research from multiple national labs has proven the effectiveness of this technique at research scale. Therefore, potential methods to implement direct extraction at both bench and industrial scale have been developed. The key features of potential dissolver system designs were identified via the team at Pacific Northwest National Laboratory and several designs based on industrial counterparts were assessed for feasibility. This report summarizes the advantages and disadvantages of multiple methods, concluding with a path forward to create multiple unique dissolver designs. The first design will be a single stage recirculating eductor mixer. The second design recommendation is a stator rotor static mixing flow loop design. Each dissolver could be utilized separately, simultaneously, or in series to answer questions surrounding reaction kinetics including residence time, provide a proof of concept for targeted extractions of specific nuclides, and inform needs for industrial scale implementation
Molten Salt Reactors and Electrochemical Reprocessing: Synthesis and Chemical Durability of Potential Waste Forms for Metal and Salt Waste Streams
The molten salt reactor (MSR) is one of the leading advanced nuclear reactor candidates to replace current nuclear reactor technologies in the U.S. Besides having more economical and reliable designs, MSRs have are amenable to a closed fuel cycle, in which electrochemical reprocessing can be performed to recycle the used nuclear fuel. This review intends to provide information about potential waste forms for metal and salt waste streams from these salt-based nuclear processes. Metal waste streams arise from reactor components and structural materials. Salt waste streams are generated during reactor operations as fission products build up in salt-fueled systems. Waste forms that have the highest waste loading and/or have shown the most commercial promise are discussed with an emphasis on the current state of efforts to understand the synthesis and chemical durability of metal and ceramic waste forms.
Semi-integral LOCA test of cold-spray chromium coated zircaloy-4 accident tolerant fuel cladding
Enhancing the accident tolerance of PWRs came under serious consideration following the 2011 Fukushima Daiichi nuclear power plant events. While the current nuclear fuels are based on mature technology and have an excellent operational record, further enhancing their strength through accident tolerant fuel (ATF) research and development continues to be of interest. Particularly, the chromium coated clad ATF technology represents an evolutionary change to improve the high temperature performance of existing Zircaloy claddings. Additionally, despite several years of investigation of coated cladding, the integral loss of coolant accident (LOCA) performance of chromium coated cladding has had little attention. In this work, cold-spray chromium coated zircaloy-4 claddings are evaluated using EDF's semi-integral LOCA test facility. Results show that the chromium coating induces a reduced ballooning and burst and an increased burst temperature in the investigated conditions. However, these tests exhibit limited benefits concerning the post-quench behavior of the coated specimens which occurs in the last stage of a prototypical LOCA scenario.
Nuclear Forensics
Nuclear forensics is a key part of the nuclear security strategy for the United States and the international community. The NACS Division is central to the leadership role that LLNL has had in nuclear forensics over the past 25 years. Our current nuclear forensic program includes conducting R&D on provenance and attribution signatures, collaborating with international partners, training the next generation of nuclear forensic experts, developing test materials for verification and validation exercises, and providing expert advice to national and international policy makers. Key to our success in these areas has been the strong and continuing involvement in nuclear forensic casework obtained through law enforcement and intelligence channels as well as our outstanding analytical capabilities. NACS must continue to conduct forward-thinking R&D in nuclear forensics that supports operational programs and addresses intelligence gaps. To maintain leadership in nuclear forensics, we must attract, develop, and retain the best talent. The NNSA has a central leadership role in developing educational initiatives for nuclear forensics. In concert with the Glenn T. Seaborg Institute, the NACS Division will continue to participate in all nuclear forensic educational initiatives (undergraduate, graduate, postdoctoral) and incorporate LLNL’s D&I vision into its student and postdoc recruitment efforts. We will continue to build formal relationships with key academic partners and institutions with active and emerging nuclear forensic research interests. We will also strengthen relationships with NNSA DNN and SSAA funded university consortia (e.g. NSSC, ACE, CNEC, CVT, ETI, MTV), helping them conduct research of interest and relevance to nuclear forensics, while at the same time evaluating and recruiting promising talent from these programs.
SAFARI - Secure Automation For Advanced Reactor Innovation (Final Technical Report)
The Secure Automation For Advanced Reactor Innovation (SAFARI) project was a pioneering initiative aimed at fundamentally changing how nuclear power plants are operated and maintained. Recognizing that current nuclear plants often rely on extensive manual procedures and large staffs, leading to higher costs compared to other energy sources like natural gas, SAFARI sought to introduce smart, automated technologies to make nuclear energy more efficient, cost-effective, and safer. This report details the research and development efforts of the SAFARI project, bringing us closer to a future where advanced nuclear reactors can operate more autonomously, adapt flexibly to energy demands, and predict their maintenance needs before issues arise. One of the key achievements of the SAFARI project is its contribution to our understanding of how Artificial Intelligence (AI) and sophisticated computer models, known as Digital Twins, can be effectively integrated with the complex physics of nuclear reactors.
Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6
Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.
Updating Nuclear Energy Cost Estimates for Net Zero World Initiative
Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.
GaAs Neutron Response Functions and Radiation Damage Metrics
The radiation effects community needs clear, well-documented, neutron energy-dependent responses that can be used in assessing radiation-induced material damage to GaAs semiconductors and for correlating observed radiation-induced changes in the GaAs electronic properties with computed damage metrics. In support of the objective, this document provides: a) a clearly defined set of relevant neutron response functions for use in dosimetry applications; b) clear mathematical expressions for the defined response functions; and c) updated quantitative values for the energy- dependent response functions that reflect the best current nuclear data and modelling. This document recaps the legacy response functions. It then surveys the latest nuclear data and updates the recommended response function to support current GaAs damage studies. A detailed tabulation for six of the energy-dependent response functions is provided in an Appendix.
Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D
With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.