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At least 235 records · Page 13

Enhancing the Useability of the IAEA's Physical Model: An Analysis of User Feedback

This study presents the results of Physical Model user interviews conducted with 12 people who have International Atomic Energy Agency (IAEA) safeguards experience. The goal of this report is to provide additional context for policy makers when prioritizing the needs of the IAEA regarding support for enhancements to the Physical Model. The interviews covered the general usability of the Physical Model, its effectiveness as a technical reference, and the scope and utility of the Physical Model's indicators and content. The key conclusions from these interviews are as follows: 1) The Physical Model is difficult to find and not well advertised. 2) The Physical Model can be difficult to use due to its format, which makes searching for information difficult, and lack of visual content. Therefore, the Physical Model should be supported in multiple formats (print, PDF, web) to maximize its usability for different stakeholders. 3) The scope of the Physical Model's content and indicators is likely sufficient, and translating indicators into other languages is unlikely to be worth the effort. 4) Despite its inefficiencies and other issues, the Physical Model in its current form is a vital (albeit under-utilized) resource for key stakeholders. 5) Despite its broad use case the Physical Model is not a catch-all tool and force-fitting the Physical Model into functions for which it has not been designed for would likely diminish its value. 6) It can be difficult to disentangle challenges related to the Physical Model and its usability from broader challenges at the Agency, such as general issues with communication and coordination. Based on these conclusions and considering the results of past studies on the Physical Model funded by NA-241, the analysis team developed a list of recommendations and associated actions for IAEA consideration. These recommendations are prioritized based on the assessed level of difficulty for the IAEA to implement a recommendation, emphasizing low hanging fruit then building to more ambitious changes to the Physical Model's format and content.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

Phasor-Measurement-Unit-Based Data Analytics Using Digital Twin and PhasorAnalytics Software

A major objective of this project was to apply GE’s commercial machine learning and data analytics toolsets to large-scale, real-world, anonymized Phasor Measurement Unit (PMU) datasets in order to extract signatures, correlated and/or causal factors, and precursor patterns associated with significant power system phenomena. The project had a particular emphasis on extraction of insights relevant to asset health monitoring, real-time load modeling and cybersecurity monitoring. Additionally, the team was directed to undertake a comprehensive data quality analysis for the provided datasets and encouraged to estimate the ‘machine-learning readiness’ of the datasets by documenting any major obstacles to the application of commercial machine learning algorithms. To accomplish the aforementioned objectives, the project team’s work centered around the identification of key event signatures and application of the identified event signatures for event detection and event classification. The industry-validated, semi-supervised machine learning strategy employed for event signature identification involved several major tasks, including data-preprocessing, generation of an overabundance of features, normal data identification, normality modeling, and event signature identification through a methodical, quantitative ranking of features in order of relevance to each studied event type. Throughout the project, data quality issues and mitigation techniques were investigated. In this report, insights are provided regarding the readiness of the provided synchrophasor datasets for application of machine learning and data analytics. The methodologies employed for this technical strategy are summarized in this report. With regards to data preprocessing and feature generation, the provided Training and Test Datasets were ingested into GE’s big data environment. Subsequently, the team applied bad data cleansing and data imputation scripts, event detection scripts, and application programming interfaces (APIs) to the datasets for convenient data access. The project team completed development and validation of dozens of physics-based, statistics-based and transformation-based feature functions used for the extraction of over 60 synchrophasor features. Using a new parallel feature generation technology developed on this project, over 60 features have been rapidly generated for the full two years’ worth of Training and Test Dataset data associated with both the Eastern and Western interconnects. Even accommodating for temporal down-sampling inherent to the feature extraction procedure, this parallel feature generation activity resulted in a massive feature set with a storage requirement approximately equal to that of the raw training dataset itself. With regards to normal data identification and normality modeling, a normality model was built using the feature data extracted from the Training Dataset and iteratively refined subsequent to incremental adjustments and expansions of the Training Dataset feature data. With respect to event characterization and signature identification, an event signature identification pipeline was developed and used in conjunction with the normality model to identify over 15 event signatures for key event categories within the Training Dataset. The identified event signatures were used to characterize hundreds of key events in terms of relative severity, duration, and location of the event. An investigation was undertaken to identify correlated and causal factors involved in transformer events. A separate investigation into temporal trends in ring-down analysis results was undertaken to determine possible associations between system dynamics and various other factors such as loading, season or year. To validate the identified event signatures, additional work was undertaken to develop signature-based anomaly detection and classification tools suitable for convenient application to the synchrophasor datasets. The anomaly detection and classification tools, suitable for online application, were then applied to the entirety of the Eastern Interconnect Training and Test Datasets. Performance of the event detection and classification tools was evaluated upon receipt of the Test Dataset event logs (i.e., the labels for events contained in the Test Dataset), and promising results were obtained despite several challenges (documented herein) associated with application of supervised or semi-supervised machine learning methods to large-scale, anonymized datasets. Finally, the detection and classification tools were used to detect, classify, and characterize thousands of new events not included in the original event logs provided by the DOE within both the Training and Test Datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

GIS @ LANL

Why is GIS important to LANL, how is it being used, and what can the GIS Program do for you? The GIS Program is an institutional resource for all things related to GIS/spatial data/mapping. We have a robust Enterprise GIS platform with over 25 years worth of LANL operational spatial data. We are constantly making ties to additional tabular data sources to integrate information so that it can be leveraged through interactive mapping applications.

97 MATHEMATICS AND COMPUTING↗

Chicago Pile-1 paved the way for nuclear science and a lab in Los Alamos First self-sustaining nuclear chain reaction was nearly 80 years ago

On a bitter-cold winter day, 43 scientists gathered at an abandoned squash court at the University of Chicago where they would ultimately enable a secret lab in Los Alamos to change the world just years later. It was December 2, 1942. The group, led by Italian physicist and Nobel laureate Enrico Fermi, stacked graphite bricks, piling 57 layers that totaled more than 770,000 pounds. Later named Chicago Pile-1, their goal was to create the world’s first self-sustaining, controlled nuclear chain reaction. Inside the approximately 20-feet-tall pile were smaller blocks of uranium and control rods that, when removed, would cause the reaction to go critical – meaning create a nuclear chain reaction. It was roughly $1 million worth of materials, equivalent to nearly $16 million today, and a concept that a nuclear chain reaction would allow the weaponization of the atom. “Its success would be the crucial proof needed to know it would be possible to create an atomic bomb,” said LANL Historian Roger Meade (C-NR). “This was the precursor to the Lab we have today, nearly 80 years later.”

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Enhancing Steam-Side Heat Transfer via Microdroplet Ejection using Inorganic Coatings

During condensation of water on a superhydrophobic nanostructured surfaces, droplets coalesce and jump (droplet ejection) due to the release of excess surface energy. Meticulously designed nanostructured surfaces or coatings capable of droplet ejection can enhance heat transfer performance by easy removal of droplets during condensation. In the present work, the capabilities of the Nelumbo droplet ejection coatings technology currently used in commercial heat exchangers are explored and optimized for materials and conditions relevant to steam condensers. Specifically, this includes (1) adapting and optimizing the procedures and chemistries to deposit droplet ejecting coatings on materials used in the steam condenser, (2) testing of the heat transfer, durability, and fouling of the fabricated coatings under a variety of steam condenser relevant conditions, and (3) modeling of the impact of droplet dynamics and interfacial properties on heat transfer in steam condensers. We experimentally demonstrated that at low supersaturation conditions (S~1.02), developed superhydrophobic nanostructured surface gives a 40% higher peak heat transfer flux and a 17% higher peak overall heat transfer coefficient (U) with droplet ejection mechanism compared to the dropwise condensation mechanism on the same nanostructured surface. Though the experimentally observed droplet ejection mechanism was short-lived (~3 min) due to the limitation of the chiller to maintain a constant supersaturation condition in fabricated steam condenser. And large variations in water inlet temperature (+ to - 2 degrees C) caused flooding of nanostructure (Wenzel state) at higher supersaturation (S > or = 1.12). This is an important finding because typical supersaturation levels in field operation are over 1.8 and as such, either the flooding potential for these materials should be improved or operation at lower supersaturation may be required to maximize heat transfer efficiency. If supersaturation conditions can be maintained reliably in the steam condenser in addition to droplet ejection mechanism during condensation, this could provide a potential 2% reduction in water flow rate which equates to a savings of over 3900 gallons of water per minute for a 500 MW steam turbine and over $0.3MM savings annually given a 0.02 cent marginal water withdrawal cost. It is also worth noting that these savings are based on improvement of droplet ejection coatings over coatings capable of performing consistent dropwise mechanism in in-field surface condensers. Savings due to the droplet ejections coatings when compared to bare substrates could be much higher. Additionally, the present work provides the importance of steam condenser operating conditions and insights into the challenges in modeling the condensing droplet dynamics on surfaces.

20 FOSSIL-FUELED POWER PLANTS↗

Analysis of Approximations in Modeling of BWR Bundle Void Distributions

In boiling water reactors, complex heterogeneous bundle designs, control blades adjacent to the corner of bundles, and the presence of boiling can lead to complex internal void distributions. A few approximations exist to model these void distributions. They could be modeled using a 1D axial solver in which each axial node is assumed to be at an average void, or each pin cell could be modeled with its own void concentration. In the latter case, the void could be discretized in pin-centered or coolant-centered channels. The goal of this project was to quantify the effect of using the different approximations for modeling internal void distributions on neutronics calculations. Using 3D void distributions calculated with CTF, Monte Carlo Neutral Particle (MCNP) transport code models were created for GE-9 and GE-14 lattices. For each model, the internal void distribution from CTF at a given axial node was selected, and a lattice calculation was carried out with MCNP. Comparisons between models using a lattice-averaged void, or using a void distribution in coolant-centered channels, showed large differences in reactivity which in some cases were well above 1,000 pcm, and it also showed differences in normalized fission rates greater than 20%. It was also found that using a lattice average void can lead to a significant difference in the estimation of the worth of a control blade. The differences found when comparing results from models using pin-centered and coolant-centered channels were up to 200 pcm in reactivity and up to 1.4% in the normalized fission rates. In addition to these two sets of comparisons, MCNP models were set up so that each subchannel had a saturated liquid component around the fuel pins and a saturated vapor component in the center to approximate annular flow. In comparison to the models using coolant-centered subchannels, up to 1–3% differences in normalized fission rates could be found.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗

SCALE Analysis of a Fluoride Salt-Cooled High-Temperature Reactor in Support of Severe Accident Analysis

As part of a US Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with SCALE and MELCOR, SCALE was used for the modeling and simulation of a fluoride salt-cooled high-temperature reactor (FHR). Based on the preconceptual design for a small modular 236 MWth FHR developed by the University of California, Berkeley (PB-FHR-Mk1), a SCALE model of the PB-FHR-Mk1 reactor core was developed. The reactor was modeled at equilibrium state with different fuel compositions in different regions of the reactor. An iterative approach was used to interpolate and mix the burnup-dependent fuel compositions obtained through the depletion calculation of a core slice model. After demonstrating the applicability of SCALE’s multigroup (MG) approach for the simulation of the PB-FHR-Mk1, the resulting equilibrium core was studied in terms of the power profile, the flux profile, temperature reactivity coefficients, and the xenon reactivity. Furthermore, the tritium production rate in the salt coolant was determined, and the dependence of the one-group cross sections on the burnup and location in the reactor core was studied. The results obtained with SCALE were post-processed to provide the MELCOR team with the core inventory and decay heat of the equilibrium core, a zone-wise power profile, temperature feedback coefficients, the tritium production rate, and the xenon worth.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Stabilized Hyperfoam Modeling of the General Plastics EF4003 (3 PCF) Flexible Foam

Constitutive model parameterizations for the General Plastics EF4003 low density 3 pound per cubic foot are needed for design and qualification purposes in normal and abnormal mechanical simulations. The material is expected to be deformed in two ways: first during preloading, and second under impact conditions of the system (transient dynamic). All analyses are to be performed at room temperature. The goal is to provide the analysis community a robust constitutive model parameterization to represent the compression behavior of the EF4003 foam from small deformations up to massive compressive deformations when the foam is densifying. It is worth noting the EF4003 exhibits anisotropy in its stress-strain behavior between the rise and transverse directions (See figure 2.8c-d) as well as plateau behavior that is very likely to cause material stability issues, due to the buckling transition, (and has historically done so) when using Sandia’s current workhorse models for flexible foams, Hyperfoam and Flex Foam. A Stability-informed Hyperfoam parameterization procedure is developed and executed to calibrate a hyperfoam model for the EF4003 room temperature, transversely loaded data. A rise orientation parameterization was not attempted due to localization in the experiments.

36 MATERIALS SCIENCE↗

SCALE Modeling of the Fast Spectrum Heat Pipe Reactor

As part of the severe accident analysis collaboration with Sandia National Laboratories (SNL) and the Nuclear Regulatory Commission (NRC), SCALE models were developed for a fast-spectrum heat pipe reactor. These models were based on the Idaho National Laboratory (INL) Design A concept, which is an alternative design to the Los Alamos National Laboratory (LANL) Special Purpose Reactor (SPR), also known as the Megapower reactor. The model contains 1,134 heat pipes, surrounded by hexagonal fuel elements, with a potassium working fluid; the fuel is UO 2 with 19.75 wt% 235 U enrichment. The model contains axial beryllium oxide (BeO) reflectors above and below the active fuel region along with a radial alumina reflector containing 12 B 4 C control drums. The center of the core is left unfueled to make room for two shutdown control rods, one annular and one solid. The active region of the core was discretized into twenty axial and five radial zones to analyze spatial variations in power and burnup. Infinite lattice unit cell sensitivity studies were used to perform verification between the SCALE and INL models. The eigenvalue results agreed well with the reported results to within roughly 50 percent mille (pcm). Full-core model verification was performed by analyzing system eigenvalues with differing configurations of control drum and shutdown rod positions. These full core results all had eigenvalue differences less than 310 pcm. Control drum and shutdown rod worths were also compared, with differences of 3.2% or less. Using the verified model, the isotopic inventory and decay heat, as well as temperature feedback coefficients, were calculated and provided to SNL as input to the MELCOR severe accident code to analyze potential releases from this class of reactor. The results of the MELCOR analysis are provided in a different report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Surplus Plutonium Disposition Sphincter Seal Development & Testing

The Surplus Plutonium Disposition Project (SPD, Project Y744) requested the Savannah River National Laboratory (SRNL) to perform a series of leak and durability tests on sphincter seals that were designed to process blend cans and shield cans into an SPD glovebox. Each sphincter seal assembly consisted of a stainless-steel outer sleeve weldment that was bolted onto the test enclosure and an aluminum inner sleeve that housed seven to nine Neoprene seals. All tests were executed to determine long term effects from processing approximately a year’s worth of blend and shield cans through the sphincter seals.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ARDP Natrium Neutronic Methodology: Argonne Neutronic Assessment of ABR-1000

The Natrium Sodium-cooled Fast Reactor (SFR) concept developed by TerraPower, LLC was selected as one of the advanced reactor designs for demonstration under the Advanced Reactor Demonstration Program Natrium Demo project. In collaboration with TerraPower, the Argonne National Laboratory (ANL) team provide independent reviews of the neutronic methodology being used for the Natrium design. As part of this activity, both the TerraPower and ANL teams agreed to perform independent neutronics analyses of the ABR-1000 reactor problem as a demonstration on the usage of the neutronics methodologies. Comparison of the results from TerraPower and ANL would expose any methodological differences in the modeling approaches. This report describes and presents the Argonne analysis work on the ABR-1000, and will be provided to TerraPower, along with data files, to complete the comparison study. The comparison will cover the methodology to evaluate the reactivity coefficients for a safety analysis, the shutdown margin, and the reconstructed pin power distribution. The methods and models used to calculate the kinetic parameters and the reactivity coefficients (density, Doppler, axial/radial expansion, etc.) are described in detail with recommendations of specific method options and modelling techniques. The control system reactivity worth and the excess reactivity due to temperature defect are calculated for the shutdown margin analysis. The method to evaluate the excess reactivity is discussed in detail. The pin power reconstruction methodology used in SE2ANL, SE2RCT, and DASSH are discussed in this report. The pin power distribution evaluated by different methods are compared and discussed in the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Benchmark Exercise for the Control Rod Swelling Evaluation

The VTR core has six reactivity control assemblies and three safety assemblies. The control assemblies or primary control rods are adjusted during the normal operation to balance the core reactivity and to control the reactor power. A typical control assembly radial layout is presented in Figure 1. The figure shows the swelled absorber (B 4 C) rod. Initially, helium gas fills the gap between the pin and the cladding before irradiation swelling takes place. For VTR, HT9 steel was selected as the cladding and duct material. The main neutron absorbing material used in the VTR is B 4 C. When residing in the core, the neutronics, thermophysical, and mechanical properties of the materials used in a control assembly will degrade due to accumulated neutron damage. Material degradation limits how long a control assembly can reside in the core. Many phenomena affect the control assembly lifetime, such as the loss of reactivity worth due to B 4 C depletion, the mechanical interaction of the absorber rod and the cladding due to B 4 C swelling, the helium gas buildup in the pin due to B-10 capture, etc. B 4 C swelling, which causes closure of the gap between the absorber rod and the cladding, is usually considered as the main limiting factor from past experience. An initial study was conducted at PNNL to evaluate the irradiation behavior of a VTR control assembly. The evaluation was performed using the CNRD2 code that was initially developed for the FFTF. The study also included an assessment of the VTR control assembly and focused on a 61-pin control assembly design, which is different from that used (37-pin design) in the core design study. The study conducted by PNNL was reviewed independently by ANL. A Python script referred to as the Control Assembly Evaluation Script (CAES) was developed for the independent review and additional assessment of 37-pin control assembly design. The script has focused on the assessment of the absorber rod swelling for its importance in determining the control assembly lifetime. CAES uses geometry, neutronics, materials data as input to predict the swelling of the absorber rod during its residence in the reactor core. The results from CAES showed some non-negligible differences against the PNNL results. Some of the differences can be attributed to the different interpretation of the control rod assembly dimensions. To resolve this issue, a benchmark exercise was proposed. The benchmark specification was developed by PNNL. The benchmark exercise was performed independently at PNNL and ANL using different codes/scripts (CRND2 and CAES). This memo documents the results calculated using the different codes. However, this report is limited to presenting the results obtained. Further investigation of the cause of the observed difference will be performed as part of future activities, pending continuation of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SMART: Simplified Melting And Rotation-joint Technology

Oil based parabolic trough solar power plants are the most commercially mature CSP technology. However, the upper limit of about 400°C of the current organic heat transfer fluid(HTF)significantly limits the future potential of the technology. Advances in parabolic trough receiver and collector technology have enabled higher operating temperatures of potentially 500°C or above. The search for an improved higher temperature HTF has identified inorganic molten salts, specifically the mix referred to as Solar Salt, a 60:40 mix of sodium nitrate and potassium nitrate salt. However, Solar Salt starts to freeze at about 240°C. This poses a significant challenge for large parabolic trough plants that could have many kilometers of header piping and hundreds of kilometers of receiver piping all filled with molten salt. Plants using molten salt need to be designed to minimize the risk of freezing and to be able to recover from freeze events. Studies and field experiments have shown that this appears to be feasible and the approach appears to have strong economic advantages over conventional trough plants. However, some technical challenges remain related to the use of molten salt in trough solar fields, the cost of the freeze recovery system is significant, and many still question whether the risk of using molten salt is worth the economic upside. In our view, the potential economic upside justifies the continued look at molten salt HTF in parabolic trough plants. The objective of this project was to address the key technical issue remaining, look for opportunities to reduce the cost of the freeze recovery system, and improve the general information and tools available for assessing the design, performance and economics of trough plants using molten salt HTF.

14 SOLAR ENERGY↗

Drought Impacts on Hydroelectric Power Generation in the Western United States

The Western United States experiences large fluctuations in rain and snowfall from year to year, affecting river flows and reservoir levels throughout the region. This interannual variability in water resources leaves a strong signature on total annual energy generated by the region’s fleet of hydroelectric dams. In a wet year, like 2011, hydroelectric power can meet 30 percent of annual western electricity demand. That contribution can drop below 20 percent during severe drought years. Characterizing the contribution of hydroelectric power to the western generation portfolio during drought is crucial to understanding the resilience of the hydropower sector to climate-related risk, both now and in the future. This report analyzes the impacts of historical western droughts on hydroelectric power production by combining two decades’ worth of annual generation—recorded at more than 600 hydroelectric power plants—with historical climate data developed for distinct hydropower subregions of the West. The most extreme impacts of drought on hydroelectric power are found at individual dams where reservoir levels are so low that released water and thus generation becomes severely restricted. These isolated cases often receive widespread media attention, leading to a common misconception that hydroelectric power is an unreliable technology whose role will diminish over time as the western climate produces longer and more severe droughts. Yet, when aggregated to the scale of the West, the observational records of hydropower generation reveal a different story. Even during the most severe droughts experienced since the turn of the century, the western hydropower fleet sustained more than 80% of its typical annual generation. Observational data indicate that drought in 2021 led to the worst year for hydropower generation in the West since 2001, with total generation approximately 16 percent below the 21st century two-decade average. The year 2021 was particularly severe in California (second worst hydro year of last two decades, ~48 percent below average) and Oregon (worst hydro year of last two decades), while generation in Washington and Idaho was affected to a lesser degree (~12 percent below average for combined region). The year 2001 remains the year of lowest western hydropower generation of the twenty-first century so far, owing to extreme drought in the Pacific Northwest, where about two-thirds of western hydropower capacity is located. The primary reason for this relative stability is the diversity of weather across the West; drought rarely impairs hydroelectric power across all river basins at the same time.

13 HYDRO ENERGY↗

IER-523: Feasibility of Experiments Focused on Measuring the Effects of UO 2 BeO Material on Critical Configurations using 7uPCX [Slides]

Sandia National Labs has access to unused ACRR fuel, which is unique in its enrichment 35% and material composition BeO. ACRR fuel is available in quantities well above what is needed for experiments. Two experiment concepts have been investigated: UO 2 BeO fuel elements and pellets with 7uPCX fuel. The worth of UO 2 BeO is large enough to be well above the anticipated experiment uncertainties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗