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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Improving perovskite solar module stability by understanding and mitigating scribe-induced chemo-thermomechanical degradation

Recognizing the correlation between the design of perovskite solar module (PSM) and their degradation mechanisms under environmental stressors helps to enable their long- term reliability. This work reports on the impact of the hole-transport layer (HTL) on thermal cyclability and degradation mechanisms of p-i-n PSMs by comparing 3 HTLs: NiO x , MeO-2PACz (a self-assembled monolayer), and a bilayer HTL of MeO-2PACz on NiO x . We observe surprising thermal cyclability from a performance standpoint despite generating clear degradation products. We find that without a fully dense HTL, seemingly insignificant moisture/oxygen ingress through the edge of the PSMs can lead to rapid destabilization of the metal halide perovskite (MHP) layer due to reactions between MHP degradation byproducts and the indium-tin oxide layer. We also show that illumination-induced cation phase segregation is dependent on the presence of an inactive area (regions of the substrate uncovered by the top electrode). As such, we find that a dense interface between the MHP and ITO is necessary for chemically robust PSMs and highlight criteria for testing field-relevant configurations in lab-scale architectures.

14 SOLAR ENERGY↗
DOE OSTI2024

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗
DOE OSTI2026

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗
DOE OSTI2025

Global QCD analysis of spin PDFs in the proton with high-𝑥 and lattice constraints

We perform a comprehensive global QCD analysis of spin-dependent parton distribution functions (PDFs), combining all available data on inclusive and semi-inclusive deep-inelastic scattering (DIS), as well as inclusive weak boson and jet production in polarized 𝑝⁢𝑝 collisions, simultaneously extracting spin-averaged PDFs and fragmentation functions. Including recent Jefferson Lab DIS data at high 𝑥, together with subleading power corrections to the leading-twist framework, allows us to verify the stability of the PDFs for 𝑊 2 ≥ 4 GeV 2 and quantify the uncertainties on the spin structure functions more reliably. We explore the use of new lattice QCD data on gluonic pseudo-Ioffe time distributions, which, together with jet production and high-𝑥 DIS data, improve the constraints on the polarized gluon PDF. The expanded kinematic reach afforded by the data into the high-𝑥 region allows us to refine the bounds on higher-twist contributions to the spin structure functions, and test the validity of the Bjorken sum rule.

Perturbative QCD↗
DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗
DOE OSTI2024

Distributed Wind Monitoring Best Practices

Accessible performance and operational data have been identified as a key enabler for distributed wind energy industry advancement. While utility-scale wind turbines benefit from reliable and continuous supervisory control and data acquisition (SCADA)-based monitoring platforms, monitoring of the U.S. fleet of distributed wind (DW) turbines has been more inconsistent, unreliable, and sometime difficult to access. Without fleet monitoring data, the industry will never understand and thus work to improve turbine under-performance and reliability issues. For the DW industry to scale up, attract investors, and boost credibility, fleetwide monitoring must be robust and reliable, select data must be made accessible to stakeholders, and the data must be in a format useful to users. To help move the industry toward a more standardized, accessible stream of monitoring data, this distributed wind monitoring best practices report attempts to cover topics including key monitoring channels, hardware, communication strategies, and accessibility. Strategic engagement with DW original equipment manufacturers (OEMs), service providers, lab and university researchers, testing organization, certification bodies, end users and solar photovoltaic (PV) monitoring experts has enabled a better understanding of the current state-of-the-art of monitoring and aided in articulating this set of best practices that will guide OEMs toward harmonized monitoring strategies, aimed at a future goal of achieving accessible performance and operational data for the entire fleet of U.S. distributed wind turbines.

17 WIND ENERGY↗
DOE OSTI2026

Pilot Development Progress to Demonstrate Electric Thermal Energy Storage (ETES) Using Low-Cost Particles

The rapid growth of variable renewable power generation increases the need to economically store electrical energy over durations up to several days in long-duration energy storage (LDES) applications. LDES can bridge the intermittency of increasing variable renewable energy (VRE) and facilitate emission-free dispatchable electricity to improve the resilience of the grid and provide reliable and potentially cost-effective energy. Several energy storage approaches including mechanical, chemical and electrochemical methods are currently deployed or under development. However, LDES requirements pose unique challenges for scalability, energy capacity, and cost. Electro-thermal energy storage (ETES) can store a large capacity of energy with site flexibility and has attracted significant interest for LDES purposes. This paper shows the progress of developing a demonstration test facility for particle ETES technology including pilot-scale component design and fabrication.

25 ENERGY STORAGE↗
DOE OSTI2025

Conceptual Designs for Irradiation Creep Testing of SiC in HFIR

Understanding irradiation creep of nuclear fuel cladding is important to properly size the initial fuel-cladding gap and understand when pellet-cladding contact is expected to occur due to a combination of fuel swelling and cladding creep-down. Irradiation creep also plays a role in relaxing stresses that develop in-pile. Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are the leading long-term accident-tolerant fuel cladding concept for light-water reactors (LWRs). Although some limited data are available regarding irradiation creep of the individual constituents (fibers, matrix), data regarding irradiation creep of SiC/SiC composites are currently insufficient. Additional data regarding irradiation creep compliance and the rupture lifetime (combination of creep and slow crack growth) are needed to understand material limitations. This work describes the design and development of two irradiation vehicles that are being pursued for testing SiC/SiC concepts in the High Flux Isotope Reactor (HFIR). The first is a passive experiment, referred to as the PRECISE experiment, that leverages the constant coolant pressure of HFIR to compress a metallic bellows and provide a well-characterized load to drive creep in a SiC/SiC dog bone specimen. The total creep strain would be quantified post-irradiation by measuring dimensional changes of the specimen length as well as local dimensional changes within the gauge region. Non-stressed specimens would also be irradiated under the same conditions to provide an indication of dimensional changes due to radiation-induced swelling in the absence of creep. A second, more complex experiment, referred to as the INSITE experiment, is being designed in parallel that would use pneumatics to pressurize a metal bellows and linear variable differential transformers (LVDTs) to measure the specimen displacement in situ during irradiation. Such an experiment would provide significantly more data regarding the evolution of the creep compliance as a function of dose and applied stress within a single experiment but would require significantly more development time and cost to execute. The primary concern with the INSITE experiment is the accuracy, reliability, and expected lifetime of the LVDTs during irradiation at elevated temperatures. Efforts are being made to adjust the experiment design and operating procedure to limit LVDT temperatures and mitigate or otherwise compensate for uncertainties due to factors such as temperature fluctuations, creep in the surrounding structural materials, and drift of the LVDTs. This work describes the experiment designs, thermal and structural analysis that were performed to ensure that the desired temperature and stress conditions can be achieved, some initial sensitivity analyses to predict the evolution of the radiation-induced specimen displacements, and potential sources of uncertainty in the measurements. Out-of-pile testing is being performed in parallel to confirm that the test trains achieve the expected stress states in the specimens and do not result in prohibitive stress concentrators (e.g., in the grip regions) that might risk pre-mature failure. The PRECISE experiments are proceeding toward fabrication and assembly with HFIR insertion planned during fiscal year 2026. The INSITE experiment is progressing toward out-of-pile demonstrations, which will provide more conclusive evidence regarding the feasibility of executing these tests in HFIR or whether alternative displacement monitoring techniques may need to be considered.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Optimal Droop Setting for Congestion Reduction in a 100% Grid-Forming Inverter-based Power System

he high penetration of inverter-based resources (IBRs) introduces new challenges to power systems due to the complex inverter control. However, IBRs can be configured to maximize their benefits to improve system resilience and reliability. This paper proposes a steady-state optimization model that aims to mitigate transmission congestion in a 100% grid- forming (GFM) IBR-based power system. This goal is achieved by determining the optimal droop settings for the GFM IBRs under different congestion conditions due to renewable energy and load variations. The numerical solution is rigorously verified by a high-fidelity model of the IEEE 39-bus test system with detailed GFM IBR control in the time-domain electromagnetic transient (EMT) simulation tool PSCAD. The numerical solution and simulation results show a significant congestion reduction while meeting all other operating requirements. It is also observed that the numerical solving time is substantially less compared to the EMT simulation time.

Nguyen, Quan H.↗
DOE OSTI2024

Misclassification of causes of death among a small all-autopsied group of former nuclear workers: Death certificates vs. autopsy reports

The U.S. Transuranium and Uranium Registries performs autopsies on each of its deceased Registrants as a part of its mission to follow up occupationally-exposed individuals. This provides a unique opportunity to explore death certificate misclassification errors, and the factors that influence them, among this small population of former nuclear workers. Underlying causes of death from death certificates and autopsy reports were coded using the 10 th revision of the International Classification of Diseases (ICD-10). These codes were then used to quantify misclassification rates among 268 individuals for whom both full autopsy reports and death certificates with legible underlying causes of death were available. When underlying causes of death were compared between death certificates and autopsy reports, death certificates correctly identified the underlying cause of death’s ICD-10 disease chapter in 74.6% of cases. The remaining 25.4% of misclassified cases resulted in over-classification rates that ranged from 1.2% for external causes of mortality to 12.2% for circulatory disease, and under-classification rates that ranged from 7.7% for external causes of mortality to 47.4% for respiratory disease. Neoplasms had generally lower misclassification rates with 4.3% over-classification and 13.3% under-classification. A logistic regression revealed that the odds of a match were 2.8 times higher when clinical history was mentioned on the autopsy report than when it was not. Similarly, the odds of a match were 3.4 times higher when death certificates were completed using autopsy findings than when autopsy findings were not used. This analysis excluded cases where it could not be determined if autopsy findings were used to complete death certificates. The findings of this study are useful to investigate the impact of death certificate misclassification errors on radiation risk estimates and, therefore, improve the reliability of epidemiological studies.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

A two-stage optical fusion framework for wildfire severity mapping across the conterminous United States

Accurate wildfire severity mapping (WSM) is essential for post-fire recovery planning, erosion risk assessment, ecosystem monitoring, and disaster risk reduction. Although Landsat and Sentinel optical imagery have been widely used for burn severity assessment, the added value of fusing multiple optical sensors has not been sufficiently quantified across diverse fire events, particularly since the launch of Landsat-9. This study evaluates whether multisensor optical fusion improves wildfire severity mapping relative to single-sensor baselines using Sentinel-2, Landsat-8, and Landsat-9 imagery across 40 wildfire events in the conterminous United States. We tested a two-stage fusion framework that combines feature-level fusion with pixel-level dimensionality reduction. First, feature-level fused datasets were created through early fusion by combining standardized post-fire bands from each sensor into a single predictor stack. Both raw reflectance bands and pairwise spectral transforms were retained to capture within- and cross-sensor spectral interactions. Second, Linear Discriminant Analysis was applied to both single-sensor and fused datasets to produce comparable low-dimensional feature spaces. Six machine-learning classifiers were then used to benchmark model performance with repeated spatially buffered train–test splits. Results show that Landsat-9 was the strongest single-sensor baseline. Among the fusion strategies, Sentinel-2 + Landsat-9 produced the most consistent improvement and reduced performance variability. Landscape-condition analysis further showed that this fusion was most beneficial in shrubland-dominated and high-terrain fires, where it achieved the highest overall mean accuracy and the fewest failures. In contrast, its benefits were less reliable in evergreen forests, mixed vegetation, and low- to moderate-elevation terrain. In operational settings, the Sentinel-2 + Landsat-9 configuration offers a practical solution for post-fire recovery planning, erosion-risk assessment, watershed management, and ecological monitoring when field observations are available and timely satellite-based information is needed.

Landsat↗
DOE OSTI2024

Flexible operation of nuclear hybrid energy systems for load following and water desalination

Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The results demonstrate that nuclear power is capable of flexibly responding to changing grid demand while simultaneously producing clean water, particularly during periods of low electricity demand. The MSR-RO system was found to be the most efficient in electricity generation and water production, and all hybrid systems reduced CO2 emissions by 356,000 to 682,000 tons annually. Economic analysis reveals that nuclear desalination technologies are cost-competitive with conventional systems, especially when paired with RO. Finally, these findings confirm the technical feasibility and environmental benefits of nuclear hybrid systems for sustainable electricity and water production.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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↗
DOE OSTI2025

Development of Calcined Clay/Calcium Sulfate Blends for Robust Performance of LC3 Concrete

This report documents the development of robust blends of calcined clays (CCs) with calcium sulfate (gypsum) for application in limestone calcined clay cement (LC3) systems. The U.S. cement industry faces supply chain constraints and high energy intensity, motivating the need for alternative supplementary cementitious materials. Calcined clays are abundant and highly reactive when properly processed, but their variable physical and chemical characteristics can negatively impact hydration balance, rheology, and admixture demand in LC3 concretes. To address this, five calcined clays, two Portland cements, ground limestone, gypsum, and a polycarboxylate dispersant were procured. Isothermal calorimetry and mini-cone flow tests were used to determine sulfate and dispersant demand. Results show that the addition of approximately 6.7% gypsum, relative to the calcined clay weight, consistently balanced sulfate consumption across the LC3 systems studied. Dispersant demand, however, varied significantly with clay source, demonstrating the need for tailored admixture strategies. These findings confirm that supplying CC–gypsum blends directly to concrete producers is a viable approach to overcoming current manufacturing constraints, enabling reliable fresh and hardened performance of LC3 concretes, and supporting broader adoption of calcined clays in the U.S. market.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Performance Validation of Endcap Timing Layer Detector Modules for CMS Phase-2 Upgrade

The High-Luminosity Large Hadron Collider (HL-LHC) will operate up to 200 simultaneous collisions per bunch crossing, which is a significant jump from the current value of about 30 collisions per bunch crossing, producing significant pileup that challenges accurate event reconstruction. To address this, the Compact Muon Solenoid (CMS) experiment is implementing the Endcap Timing Layer (ETL), a precision timing detector designed to provide timing measurements with a resolution of approximately 50 ps per hit and 35 ps per reconstructed track. This project focuses on the characterization and validation of ETL detector modules using laboratory laser test data. ETL performance is evaluated by analyzing key quantities such as Bunch Crossing Identification (BCID), Time-of-Arrival (TOA), Time-over-Threshold (TOT), Noise Stability etc. The resulting analysis provides insight into the timing performance and operational stability of ETL modules, contributing to the quality assurance process req uired before their installation in the CMS experiment and ensure that the modules can meet the long-term reliability requirements of approximately 10 years of operation without replacement.

Chipara, Munashe [Fermilab]↗
DOE OSTI2026

Gaussian processes for inferring parton distributions

The extraction of parton distribution functions (PDFs) from experimental or lattice QCD data is an ill-posed inverse problem, where regularization strongly impacts both systematic uncertainties and the reliability of the results. We study a framework based on Gaussian Process Regression (GPR) to reconstruct PDFs from lattice QCD matrix elements. Within a Bayesian framework, Gaussian processes serve as flexible priors that encode uncertainties, correlations, and constraints without imposing rigid functional forms. We investigate a wide range of kernel choices, mean functions, and hyperparameter treatments. We quantify information gained from the data using the Kullback-Leibler divergence. Synthetic data tests demonstrate the consistency and robustness of the method. Our study establishes GPR as a systematic and non-parametric approach to PDF reconstruction, offering controlled uncertainty estimates and reduced model bias in lattice QCD analyses.

hadronic spectroscopy↗