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DOE OSTI2024

Summary of LWRS Research in Addressing RPV Research Gaps in NRC EMDA Report

Reactor Pressure Vessels (RPVs) are critical components in nuclear reactors, housing the reactor core and coolant under extreme conditions of temperature, pressure, and radiation. These harsh environments contribute to the degradation of RPV materials over time, presenting challenges for extending reactor operations beyond their original design lifespans. The NRC Expanded Materials Degradation Assessment (EMDA) report volume 3 have been instrumental in guiding research to support extending the operational life of light water reactors (LWRs) up to 80 years. It provides a comprehensive framework to address technical challenges related to aging and degradation mechanisms in RPVs. The LWRS program has played a key role in advancing this research, supporting projects such as the UCSB ATR-2 Experiment, material testing from Zion and Palisades reactors, and the development of advanced mini-compact tension testing techniques. These efforts have been crucial in identifying and addressing gaps in our understanding of RPV aging, contributing to the successful subsequent license renewals of eight LWR units in the U.S. The EMDA report volume 3, built on the Phenomena Identification and Ranking Table (PIRT) analysis from earlier versions of the EPRI Materials Degradation Matrix (MDM) and Issue Management Tables (IMTs), provides a detailed assessment of RPV degradation mechanisms. However, as EPRI has updated the MDM and IMT, it is important to revisit research priorities and methodologies to reflect these changes. The revised MDM and IMT may introduce new factors affecting long-term RPV performance and safety, highlighting the need for continued research and updated guidance to ensure the reliable and safe operation of reactors beyond 80 years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Water Vapor Resistant SiC/SiC Composite for Hydrogen-Based Turbines (Final Scientific Technical Report)

New material innovations are needed for the extreme environments of next generation, hydrogen-fueled turbine engines. Ceramic matrix composites (CMCs) offer high-temperature capability but are susceptible to degradation in high-temperature water vapor. Pratt & Whitney’s (P&W) baseline silicon carbide (SiC)/SiC CMC was initially applied to design a component in a hydrogen-fueled engine, verifying the existence of a design space and extracting boundary conditions to inform testing parameters. Several material innovations, including two fibers, interface coatings (IFC), and self-healing matrices (SHM), were investigated to improve high-temperature performance in water vapor. A boron-doped pyrocarbon (B-PyC) IFC and a SHM matrix with layers of zirconium nitride (ZrN) or zirconium diboride (ZrB 2 ) were developed to fabricate minicomposites with either standard Hi-Nicalon™ Type S (HNS) fibers or new Tyranno® SA4 fibers (SA4). The B-PyC IFC is functional but lacks in providing improved durability. A matrix consisting of thick layers of SiC and thin layers of ZrB 2 shows promise as a SHM that can effectively seal matrix cracks in this extreme environment. Minicomposites with HNS fibers generally outperform those with SA4 fibers.

08 HYDROGEN↗

DOE OSTI2020

A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm

Neither the disease mechanism nor treatments for COVID-19 are currently known. Here, we present a novel molecular mechanism for COVID-19 that provides therapeutic intervention points that can be addressed with existing FDA-approved pharmaceuticals. The entry point for the virus is ACE2, which is a component of the counteracting hypotensive axis of RAS. Bradykinin is a potent part of the vasopressor system that induces hypotension and vasodilation and is degraded by ACE and enhanced by the angiotensin 1-9 produced by ACE2. Here, we perform a new analysis on gene expression data from cells in bronchoalveolar lavage fluid (BALF) from COVID-19 patients that were used to sequence the virus. Comparison with BALF from controls identifies a critical imbalance in RAS represented by decreased expression of ACE in combination with increases in ACE2, renin, angiotensin, key RAS receptors, kinogen and many kallikrein enzymes that activate it, and both bradykinin receptors. This very atypical pattern of the RAS is predicted to elevate bradykinin levels in multiple tissues and systems that will likely cause increases in vascular dilation, vascular permeability and hypotension. These bradykinin-driven outcomes explain many of the symptoms being observed in COVID-19.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Impact of control signal phase noise on qubit fidelity

As qubit decoherence times are increased and readout technologies are improved, nonidealities in the drive signals, such as phase noise, are going to represent a growing limitation to the fidelity achievable at the end of complex control pulse sequencies. Here we study the impact on fidelity of phase noise affecting reference oscillators with the help of numerical simulations, which allow us to directly take into account the interaction between the phase fluctuations in the control signals and the evolution of the qubit state. Our method is based on the generation of phase noise realizations consistent with a given power spectral density, that are then applied to the pulse carrier in simulations, with Qiskit-Dynamics, of the qubit temporal evolution. By comparing the final state obtained at the end of a noisy pulse sequence with that in the ideal case and averaging over multiple noise realizations, we estimate the resulting degradation in fidelity, and exploiting an approximate analytical representation of a carrier affected by phase fluctuations, we discuss the contributions of the different spectral components of phase noise.

Barsotti, Agata [Pisa U.]↗

DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗

DOE OSTI2025

Laser Confocal Microscopy Uncertainty Quantification Study

At Los Alamos National Laboratory (LANL), the Storage Safety and Engineering (SSE) team completes annual surveillance on a subset of in-use interim nuclear material storage containers in fulfilment of requirements outlined in DOE Manual M 441.1-1. The containers are selected through several methods, such as subject matter expert judgement, random selection, and trending items. Following these selections, the SSE team has the capacity to complete surveillance on 15-20 containers each fiscal year, composed of a combination of SAVY-4000 and Hagan storage containers. Through previous work, the stainless-steel components of the containers have been identified as life limiting components, with an emphasis on the thin-walled bodies. The team is focused on understanding the extent of general and pitting corrosion, due to observations of extensive corrosion from stored contents and bag-out-bag degradation. Quantifying corrosion effects on the thin-walled stainless steel container bodies, and understanding potential impacts to the respective design release rates and design qualification release rates is paramount to the team. To date, destructive examination (DE) has proven to be the most insightful method for developing an understanding on the extent of corrosion on used containers. To standardize this process, the SSE team developed a destructive examination guide for analyzing stainless steel components of the containers. Corroded containers of interest are identified during surveillance activities and set aside for sectioning and characterization. Following sectioning, a major step in the DE workflow is the utilization of laser confocal microscopy for scanning corroded samples of interest and extracting data on pits, such as count, depth, and equivalent diameter. Adhering to the techniques outlined in the DE guide, analysis has been completed on two Hagans and one SAVY-4000 container, with the maximum pit depth recorded as 139.1 ± 22.82 μm on a 17.5 year old Hagan. The findings from the completed destructive examinations will be utilized to support lifetime extension efforts of the SAVY-4000 as the team can better estimate corrosion rates and effects over time based on stored contents and age. Due to the implications of observing extreme pit depths that approach the nominal container body thickness of .0299 inches (0.759 mm) or minimum container thickness of 0.236” (0.6 mm), high confidence in the LCM measurements is desired. Through testing outlined in, it was concluded that the total error ascribed to the 20x objective when conducting large image mapping on the Keyence VK-X3050 laser confocal microscope (LCM) relative to a 50x objective (reference) is 16.4% (± 8.73%). For shallow features on the order of pristine SAVY surface defects (i.e. 5 μm), this uncertainty is appropriate. However, this conservative estimate of total error poses a fundamental concern for pit depths that approach the thickness of the measured samples. That is, with the measurement uncertainty currently employed on all measurements, the LCM would be unable to resolve if a pit with a depth of 515 μm is through wall. Standard step height samples were procured and used in the present study to assess the resolution and repeatability of height measurements. Understanding the resolution and repeatability of height measurements was the first focus of the team as it relates directly to pit depth, which is of primary concern. Calibration gratings were procured to evaluate the resolution and repeatability of measurements in the X and Y axes of the LCM stage. The results of the depth uncertainty study were conducted first and presented in the subsequent sections. The planar uncertainty study is appended to the depth study with conclusions from both summarized at the end of the report.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simultaneous Degradation‐Depolymerization of Bioderived Comb Copolymers

Poly(lactic acid) (PLA) is the most widely explored biodegradable alternative for polystyrene; however, its low toughness and glass transition temperature may limit its wider adoption as a sustainable replacement. To improve its material and thermal properties, PLA can be chemically or physically combined with other polymers, like poly(methyl methacrylate) (PMMA), though the incorporation of vinyl‐based polymer components complicates chemical recycling and reduces the sustainability of the material. Here, in this study, we synthesized polymethacrylate‐PLA comb copolymers designed to be thermally deconstructed. Our design strategically extends current polymer deconstruction methodologies to more complex macromolecular systems. Thermally labile units within the polymethacrylate backbone permitted depolymerization that was concurrent with PLA side chain degradation during heating. This dual degradation‐depolymerization process enhances the overall sustainability of lactide/vinyl‐based copolymers and demonstrates the synergistic potential of integrating multiple deconstruction pathways into a single system. This report elaborates on the design of advanced, degradable copolymers, contributing to the further development of sustainable polymer materials.

PLA↗

DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗

DOE OSTI2025

Fully Bayesian Analysis With Model Inadequacy Correction For Nuclear Graphite Property Models With Hierarchical Variance Structure

Nuclear-grade graphites are extensively utilized in the core designs of various advanced nuclear reactors. Within the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, such as nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity, forecasting component performance over the reactor's lifespan, and developing design standards necessitate robust tools for predicting fracture initiation and propagation in graphite structural components within nuclear reactors. This code enables the Bayesian calibration of properties for nuclear-grade graphites. Using a hierarchical Bayesian approach, multiple experimental data sources are combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due inadequacies in the model and the inherent spread in the experimental data are quantified.

Dhulipala, Som Lakshmi NarasimhaLakshmi Narasimha ↗

DOE OSTI2020

Development of Mockups and Instrumentation for Spent Fuel Drying Tests

The purpose of this report is to provide updates on the experimental components, methodology, and instrumentation under development for use in advanced studies of realistic drying operations conducted on surrogate spent nuclear fuel. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. Water remaining in canisters upon completion of drying procedures can lead to cladding corrosion, embrittlement, and breaching, as well as fuel degradation. Additional information is needed on the drying process efficacy to help evaluate the potential impacts of water retention on extended longterm dry storage. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates additional, well-designed investigations. Smaller-scale tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report describes the implementation of moisture monitoring equipment on a pressurized, submersible system employing a single waterproof, electrically heated spent fuel rod simulator as a demonstration of analytical capabilities during a drying process. A mass spectrometer with specially designed inlets was used to monitor moisture and other gases at 150 kPa to 800 kPa for a test simulating a forced helium dehydration procedure and below 1 torr for tests mimicking a vacuum drying process. The dew point data from the mass spectrometer was found to be in good agreement with a solid-state moisture probe. A distinct advantage of the mass spectrometer system was the capability to directly sample from the hightemperature (>200 °C) head space expected in a prototypic scale experiment where a solid-state moisture probe would suffer considerable loss of accuracy or fail altogether. The operational and analytical experiences gained from this test series are poised to support an expansion to assembly-scale tests at prototypic length. These assemblies are designed to feature prototypic assembly hardware, advanced diagnostics for in situ internal rod pressure monitoring, and failed fuel rod simulators with engineered cladding defects to challenge the drying system with waterlogged fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Demonstration of CFD to support the coupled analysis of a reactor pressure vessel subjected to pressurized thermal shock

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended duration or under accident condition. As one of the most significant components of a reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Aging degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The prediction of the temperature field is achieved by using computational fluid dynamics (CFD) simulation. In this report, a demonstration CFD standalone simulation is performed to support coupled analysis for Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS). The study use a simplified computational domain to represents a real RPV. The purpose of the study is to demonstrate the transient temperature response of RPV to ECC injection. The CFD model is built in a robust and efficient way for further coupled calculation. The next steps of this work, including the coupled thermal and tensor mechanics capabilities using Cardinal are expected to be complete by the end of FY21 for the demo problem. After this, into FY22, the capability will be demonstrated for a realistic RPV.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Multi physics simulation on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) by using Cardinal

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Development of Graphite Thermal and Mechanical Modeling Capabilities in Grizzly

Nuclear-grade graphites are used extensively in the core designs of multiple types of advanced nuclear reactors. In the reactor environment, graphite is exposed over long durations to extreme conditions, including high temperatures, radiation and potentially molten salt and oxygen. Exposure to these conditions can cause several degradation mechanisms in graphite, including nonuniform volumetric strains induced by irradiation and thermal expansion, which lead to stresses that can compromise the performance of graphite components. Evaluating component integrity, predicting component performance over the reactor lifetime, and developing design standards all require robust tools for predicting fracture initiation and propagation in graphite structural components in nuclear reactors. This report documents progress in an ongoing effort to develop modeling and simulation tools in the Grizzly code for predicting the performance of graphite exposed to reactor conditions. Recent developments include a set of thermal and mechanical models that now include the IG-110, NBG-18, and H-451 graphite grades. Improvements have also been made to a nonlinear damaged plasticity model applicable to predicting damage under tension and compression to quasibrittle materials, including graphite. In addition, enhancements have been made to the extended finite element method implementation targeted at simulating graphite fracture. These include new capabilities for crack nucleation in the interior of a solid body, improved treatment of crack nucleation on free surfaces, and more robust modeling approaches for crack growth approaching free surfaces or other cracks.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Lifetime extension drop-test of real-world corroded 5 Quart Hagan nuclear material storage container

A 5Qt Hagan container with a 20-year history of nuclear material storage was challenged with three successive drop tests at a height of 3.7 meters. The total mass of the test package was 12.1 kg. The 1st and 2nd drop tests (center of gravity over the container bottom corner but 180 degrees apart on the container bottom face) passed the pre- and post- impact helium leak criterion at less than 1.00E-6 atm-cc/sec (ambient cubic centimeters per second). The 3rd and final test (center of gravity over top corner) failed with a post-impact gross leak of 1.1E-1 atmcc/sec. The RRFMC (Respirable Release Fraction Measurement Chamber) is a drop tower test system that is critical for the sustainability of the SAVY-4000™ series and Hagan-type (NFT Inc. Golden CO) nuclear material storage containers. These are the primary in-use nuclear material storage container types at the Los Alamos National Laboratory TA-55 facility. Results are presented to expand the technical knowledge basis for container lifetime, regarding actual exposure to corrosive gas species on the container inner surfaces. The primary source of general corrosion throughout the container is gaseous hydrogen chloride (HCl). This gas is generated by the degradation of the polyvinylchloride (PVC) bag-out bag. Additionally, in most cases, the nuclear material itself also releases HCl gas (due to residual chemical components associated with the material formation). The RRFMC drop tower gives the end-user the ability record and analyze high-speed video and photography and if needed aerosol mass release measurements. In this report the principal issue is the physical deformation of the 5Qt Hagan container. There were no mass release experiments of test aerosol mass in the present study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Evaluation of Hydrogen Gas Generation and Permeation in the 9979 Type AF Shipping Package

The 9979 Type AF Shipping Packaging is a cost-effective radioactive material package designed by Savannah River National Laboratory (SRNL) that consists of two primary components: a foamed outer drum for structural protection and an inner containment drum. The packaging was designed to transport Highly Enriched Uranium (HEU), Low Enriched Uranium (LEU), and other isotopes not exceeding a Type A quantity. These contents have the potential to generate flammable hydrogen gas during transport due to the degradation of hydrogenous materials (e.g. water vapor, plastics, etc) by high-energy alpha radiation. Since 10 CFR 71.43(h) prohibits the incorporation of packaging features explicitly designed for continuous venting, alternative justification was required to demonstrate that the requirements of 10 CFR 71.43(d) for negligible reactions between packaging components and contents were satisfied. An analysis was performed to demonstrate that the potential for hydrogen gas generation over a one-year period was limited by the effects of permeation through the packaging materials. The rate of hydrogen collection was evaluated for both the inner containment drum and the outer structural drum under 10 CFR 71.71 Normal Conditions of Transport (NCT). The analysis concludes that the Lower Flammability Limit (LFL) for hydrogen gas will not be reached in a one-year shipping period assuming a minimum void volume is maintained within the drum.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Ultrafast pre-solvated dodecane hole capture and subsequent damage of used nuclear fuel extraction ligands DEHBA, DEH i BA, HONTA, CMPO, HEH[EHP] and TBP

Here, two classes of used nuclear fuel (UNF) extraction ligands, amide (DEHBA, DEH i BA, HONTA) and organophosphorus (CMPO, HEH[EHP], TBP), were selected to study radiation induced damage at picosecond to nanosecond timescale using electron pulse radiolysis in n-dodecane (DD) and supported by quantum chemical calculations. Spectra after radiolysis of 200 mM extraction ligands were recorded in DD/0.3 M DCM. Absorption peaks at 365, 365, 400 and 387 nm in case of DEHBA, DEH i BA, HONTA and CMPO respectively are assigned to triplet excited states. Additional absorption peaks at 420, 460 and 600 nm of DEHBA, DEH i BA and HONTA respectively were identified as due to ligand radical cations. A concentration dependent absorption peak at 600 nm in the case of CMPO was observed and assigned due to a combination of CMPO˙ + , (CMPO) 2 ˙ + and possibly a radical degradation product of CMPO. Weak absorption peaks at 650 and 550 nm in case of HEH[EHP] and TBP were observed and tentatively assigned to their radical cations. A two-component DD˙ + decay in the presence of ligands was observed due to different ligand oxidation mechanisms: ultrafast capture of pre-solvated DD holes and diffusive capture of solvated DD holes. At high extraction ligand concentrations (>100 mM), the majority of DD holes were captured via the ultrafast pre-solvated pathway in <10 ps with C 37 values of 389, 401, 270, 374, 458 and 340 mM for DEHBA, DEHiBA, HONTA, CMPO, HEH[EHP] and TBP respectively. Following ultrafast capture, the remainder of DD holes became solvated and were captured with k = (2.32 ± 0.13), (1.78 ± 0.12), (1.38 ± 0.2), (0.98 ± 0.081), (1.09 ± 0.08) and (1.77 ± 0.046) × 10 10 for DEHBA, DEH i BA, HONTA, CMPO, HEH[EHP] and TBP respectively. Subsequent hole transfer from the extraction ligands˙ + to the low IP solute tri-p-tolylamine (TTA) showed only 4–16% hole transfer, most likely indicating ligand˙ + degradation in 0.9–4.6 ns.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗