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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Extended FFT-based micromechanical formulation to consider general non-periodic boundary conditions

Here, this paper presents a new approach for applying non-periodic boundary conditions in the context of FFT-based methods to solve micromechanical problems in heterogeneous solids. The domain of the original problem is extended to satisfy the periodicity requirements at the boundary of the extended domain. The velocity constraint on the boundary of the original domain is replaced by a corresponding constraint on the velocity gradient in the extended volume, and a two-level augmented Lagrangian method is used to enforce the constraint. The proposed method is implemented as an extension of the large-strain elasto-viscoplastic FFT-based (LS-EVPFFT) model of Zecevic et al. (2022). The proposed method is verified in the cases of fully imposed velocity boundary conditions and mixed velocity/traction-free boundary conditions. The accuracy and convergence of the method are studied next, followed by applications to bending and indentation of polycrystals that illustrate the extended capabilities of the proposed formulation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗
DOE OSTI2024

A high efficiency rooftop air conditioning system using multi-speed compressors

This study delineates a meticulous exploration of technologies to enhance the energy efficiency of rooftop air conditioning units, employing the DOE/ORNL heat pump design model for comprehensive engineering design and optimization. A baseline rooftop air conditioning unit, featuring a 13 ton (45.7 kW) cooling capacity and a 17.9 integrated energy efficiency ratio, served as the point of departure for substantive efficiency enhancements. Key modifications included the consolidation of two refrigerant circuits into one, integrating three parallel 2-stage (dual-speed) compressors, fan replacements with high-efficiency substitutes. Notably, a lower global warming potential refrigerant, R452B, was evaluated as a substitute for R-410A, demonstrating better performance in the lab prototype. Further, the achieved measured integrated energy efficiency ratio of 21.4 in the lab prototype surpassed the baseline integrated energy efficiency ratio. Comparative evaluations between R410A and R452B indicated heightened efficiency with the latter, showcasing a lab-demonstrated integrated energy efficiency ratio of 22.4 at the rated capacity of 13.8 ton (48.5 kW) and 23.9 integrated energy efficiency ratio at the rated capacity of 10 ton (35.2 kW). This research underscores the successful development of a rigorous, energy efficient rooftop air conditioning unit prototype with noteworthy environmental and economic implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Effect of seasonal anoxia on geochemical cycling in a stratified pond: Comparison to cooler pond conditions 40 years ago

Seasonal stratification in temperate lakes deeper than a few meters creates favorable conditions for pronounced vertical redox zones, often resulting in anaerobic hypolimnions and significant geochemical changes. Here, this study examined thermocline formation and trace element behavior in a seasonally stratified pond amid rising air temperatures. Over two years, data were collected from Pond B at the US Department of Energy Savannah River Site in Aiken, South Carolina. Pond B, a man-made monomictic reservoir, received cooling water from a nuclear reactor from 1961 to 1964. Strong thermal stratification forms a distinct thermocline in May and progresses downward until November. Compared to the 1980s, this study shows a delayed onset and extended duration of stratification. The prolonged summer stratification reduces deep water oxygen replenishment, extending hypoxic conditions. Trace and major elements sampled in the water column revealed strong correlations between As, Fe, and Mn profiles, with concentrations increasing by 1–2 orders of magnitude in the anaerobic hypolimnion. This period captured the seasonal transition from winter mixing to summer stratification to fall overturn. Under anoxic conditions, Fe(III) reduces to Fe(II) in the sediment, releasing dissolved iron into the water column. The extended anoxic periods likely promoted arsenic release from sediments. Prolonged anoxia may enhance arsenic mobilization and solubility in the lake. This study illustrates how climate-induced changes in seasonal stratification of contaminated waters can convert contaminant sinks into sources, offering insights into the cycling of arsenic and other dissolved ions in stratified lakes and their implications for water quality management.

Anoxic conditions↗
DOE OSTI2026

Machine Learning–Based Condition Monitoring of a Circulating Water System of a Canadian Nuclear Plant

With the need to maintain long-term reliable energy using nuclear power plants, there is an underlying demand to ensure that the maintenance of plant components and systems is also done in an efficient and cost-effective manner. One way to achieve this is by moving from time-based maintenance to condition-based maintenance. The research presented in this paper focuses on applying statistical and machine-learning-based methods to capture anomalies within data for fault detection to further develop into condition monitoring. This paper focuses on system data for a circulating water system (CWS) of a pressurized heavy-water reactor for detecting anomalies. The different methodologies used for detecting and capturing anomalies in the CWS data are matrix profile, density-based spatial clustering of applications with noise (DBSCAN), and support vector machines (SVMs). Matrix profile and DBSCAN are used to distinguish between normal data and anomalous data. This paper presents a hybrid method using DBSCAN and SVM when a portion of the data is used for DBSCAN to generate clusters. This portion of data is then used to train the SVM along with the clusters generated by DBSCAN as output. SVM is then tested on unseen data as a predictive tool, which can work in real time to categorize data points as either normal or anomalous. This paper presents results that show the high accuracies of DBSCAN and SVM in capturing anomalies within the data for a CWS for fault detection. Thus, the maintenance plan would be focused on component condition rather than a time-based schedule by switching to an automated system to identify and predict faults within a CWS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Wall conditioning effects of boron powder injection in KSTAR with a tungsten divertor

Boron powder dropped into KSTAR plasmas decreased the radiated power, core electron density, and Z eff , indicating that the ablated and redeposited boron powder helped to condition the plasma-facing surfaces. Visible line emission of oxygen and tungsten were also reduced by 50% (80%) with boron injection into H-mode (L-mode) discharges that used the new KSTAR tungsten monoblock lower divertor. Dynamic particle balance analysis found a negligible difference in the inferred wall pumping rate during the steady portion of the discharges. It is inferred that the observed conditioning effects were principally caused by a reduction in intrinsic impurities as opposed to a reduction in wall recycling. These results are in qualitative agreement with low-Z injected powder experiments across many fusion devices, confirming the utility of low-Z powder injection as a real-time wall conditioning tool.

boron powder injection↗
DOE OSTI2026

Geologic Seawater Air Conditioning (GeoSWAC) System: Resource Assessment and Techno-Economic Evaluation in Puerto Rico

Puerto Rico's hot, humid climate drives a high and persistent demand for cooling, straining an aging and fuel-dependent energy grid while increasing peak electricity loads. Much of this challenge stems from inefficient air-conditioning systems operating in buildings without passive cooling design, making cooling both costly and vulnerable to disruption - especially during hurricanes. To address these issues, researchers evaluated a new alternative called Geologic Seawater Air Conditioning (GeoSWAC), which uses inland wells connected to naturally cold, deep seawater. By avoiding long offshore pipelines and energy-intensive refrigeration cycles, GeoSWAC can cut electricity use by 75-90%, reduce environmental impacts, and operate more reliably during power outages. A case study at the University of Puerto Rico's Rio Piedras campus found that GeoSWAC could deliver significantly lower levelized costs of cooling, reduced operational expenses, and improved water conservation compared to the campus's existing chilled-water plant. The system offers key advantages - including access to a constant cold heat sink, low pumping requirements, and enhanced resilience - for coastal regions such as Puerto Rico, the broader Caribbean, and Florida. However, its effectiveness depends heavily on site-specific geological conditions, such as subsurface connectivity and aquifer characteristics, which require detailed investigation. Future research should refine hydrogeological models, conduct performance and economic analyses, and address regulatory and permitting frameworks to support broader adoption of this promising technology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Sulfonate Group Improves the Solubility and Electrocatalytic Performance of Ru‐Based bda‐ and pda‐Type Water Oxidation Catalysts under Neutral Conditions

Four ruthenium water oxidation catalysts that bear carboxylate and sulfonate groups in the active site have been synthesized and analyzed for their catalytic activity. Here, the sulfonate‐containing catalysts show higher electrochemical activity in pH 7 phosphate buffer with 4 times larger catalytic current, improved durability with sacrificial oxidant, and increased solubility compared to similar species containing two carboxylate groups. Density functional theory calculations suggest that the sulfonate group provides a more favorable geometry for water nucleophilic attack, which is both the energetically most favorable mechanism calculated and the experimentally predicted mechanism under electrochemical conditions. Further experimental studies have been performed to show that under certain conditions catalysts can perform well electrochemically under pH conditions as low as 1.6 and that various structural components can greatly change solubility and catalytic operation.

14 SOLAR ENERGY↗
DOE OSTI2025

Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions

Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.

17 WIND ENERGY↗
DOE OSTI2026

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗
DOE OSTI2025

Application of a temporal multiscale method for efficient simulation of degradation in PEM Water Electrolysis under dynamic operating conditions

Hydrogen is emerging as a vital energy carrier, driven by the need to reduce carbon emissions. Proton Electrolyte Membrane Water Electrolysis (PEMWE) enables hydrogen production under fluctuating renewable power conditions but requires improved understanding and stability of the anode catalyst layer under dynamic operating conditions, especially with low noble metal loadings. Long-term degradation experiments are both time-consuming and costly; therefore, a systematic, model-aided approach is essential. In the present work, a temporal multiscale method is applied to reduce the computational effort of simulating long-term degradation processes in PEMWE, with an exemplary focus on catalyst dissolution. A mechanistic model incorporating the oxygen evolution reaction, catalyst dissolution, and hydrogen permeation from the cathode to the anode was hypothesized and implemented. In this way, the local periodicity of transport and reaction processes in dynamic PEMWE operation, which influence the gradual degradation of the catalyst layer, is captured. The temporal multiscale method significantly reduces the computational effort of simulation, decreasing processing time from hours to mere minutes. This efficiency gain is attributed to the limited evolution of Slow-Scale variables during each period of time P of the Fast-Scale variables. Consequently, simulation is required only until local periodicity is achieved within each Slow-Scale time step. Hence, the fully resolved dynamic problem is decoupled into these two scales, employing a heterogeneous multiscale technique. The developed approach effectively accelerates parameter estimation and predictive simulations, supporting systematic modeling of PEMWE degradation under dynamic conditions.

08 HYDROGEN↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2026

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗
DOE OSTI2025

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗
DOE OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2027

Hydrotreating pine-derived catalytic fast pyrolysis oil to jet fuel: Process durability and impact of operating conditions

Hydrotreating woody biomass-derived catalytic fast pyrolysis (CFP) oil to jet fuel has the potential to enhance energy security due to the large abundance of forest and woody resources. CFP oil produced from pine over ZSM-5 was hydrotreated over sulfided NiMo/Al 2 O 3 for 410 h to study the impact of hydrotreating conditions (pressure, temperature, and weight hourly space velocity (WHSV)). The degree of deoxygenation remained high across the tested hydrotreating conditions, and the products contained < 0.01 wt% oxygen. Increasing hydrotreating pressure from 84 to 125 bar enhanced hydrogenation of aromatic rings and the formation of cycloalkanes and increasing the temperature from 385 to 400 degrees C enhanced cracking and the formation of jet-range molecules. Decreasing the weight hourly space velocity from 0.2 to 0.1 g/(g cat h) further enhanced cracking and led to higher gasoline- and lower jet fuel-range fractions. The highest jet fuel fraction (49 wt%) was obtained at 400 degrees C, 125 bar, 0.2 g/(g cat h) WHSV. CFP oils produced from pine over phosphorous-modified ZSM-5 were hydrotreated at this condition for 588 h to investigate the process durability. The hydrogenation performance of the catalyst gradually stabilized in approximately 300 h after which the product composition remained constant. Of the final hydrotreated CFP oil, 53 wt% fell in the jet fuel range with most of the tested fuel properties meeting ASTM D4054 and/or ASTM D7566 specifications. The freeze points were < -50 degrees C vs. guideline of < -40 degrees C and the viscosities at -20 degrees C were 3.8-4.1 mm 2 /s vs guideline of 8 mm 2 /s. Increasing the fraction of cycloalkanes could increase the cetane number and heating value, which did not meet the guidelines.

09 BIOMASS FUELS↗
DOE OSTI2024

CFD unified approach under Eulerian–Lagrangian framework for methanol and gasoline direct injection sprays in evaporative and flash boiling conditions

Innovative synthetic fuels for advanced propulsion systems, such as methanol and ammonia, and synthetic blended fuels (E00, E10, and E30), known for their high volatility, are often injected directly into combustion chambers. It follows that Eulerian–Lagrangian spray models need to accurately capture the spray collapse as a consequence of flash boiling onset and be capable of proficiently handling the preferential evaporation of multi-component fuels in evaporative scenarios. So, we performed the assessment of an Eulerian–Lagrangian CFD code for simulating methanol and E00 gasoline blend sprays in both early and late injection conditions involving flash boiling conditions and preferential evaporation. The adoption of an effervescent breakup model and of a non-equilibrium phase transition model for the discrete phase allows the adoption of a setup that is almost completely free from specific constant tuning, especially for what concerns the breakup model. We validated the simulations using experimental PLV maps of methanol and E00 sprays issued from the ECN Spray M injector. The results highlight a significantly different morphology of the methanol spray compared to the E00 one under late injection conditions. Under stratified combustion, low-volatile fuels are likely to be ignited first, and the flame propagates toward the high-volatile fuels. In conclusion, the spray collapse was also correctly reproduced, inducing the presence of a low-pressure zone and modifying the spray morphology.

E00↗
DOE OSTI2026

Evaluating transient fission gas release in high burnup light water reactor fuel during loss of coolant accident conditions via new capabilities

In this work, the role of transient fission gas release (tFGR) in the cladding burst behavior of high burnup fuel during a loss-of-coolant accident (LOCA) in commercial light water reactors was further investigated via the use of a new apparatus. During the LOCA-related temperature ramps of high burnup fuel, the release of fission gases exceeds the steady-state release observed under normal operating conditions. An enhancement was made to the Oak Ridge National Laboratory Severe Accident Test Station (SATS) to probe the various factors influencing tFGR. Experiments were performed on commercially irradiated, zirconium-clad uranium dioxide fuel, and this paper details the design of the experimental setup, the initial test results, and the subsequent post-test analyses. Notably, the first test on high burnup fuel demonstrated a LOCA-relevant tFGR of 5.3% from an unpressurized fuel segment. The ultimate tFGR was 10.7% for beyond LOCA conditions. A follow-up test on similar fuel revealed a tFGR of 12.6% under comparable conditions. Microstructural analysis and an analysis of the released gas provide some insight regarding the source of tFGR in the fuel. Finally, a grain boundary bubble model may aid in the interpretation of the results and offer a guide for future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗