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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Actor-based Runtime Verification with MESA

This work presents a runtime verification approach implemented in the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in data parameterized temporal logic and state machines. The tool is implemented as an internal Scala DSL. We employ the actor programming model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper presents a case study in which MESA is used to effectively monitor a large number of flights from live US airspace data streams. We also perform an empirical study by conducting experiments using monitoring systems with different numbers of concurrent monitors and different layers of indexing on the data contained in events. The paper describes the experiments, evaluates the results, and discusses challenges faced during the study. The evaluation shows the value of combining concurrency with indexing to handle data rich events.

runtime verification↗
NASA NTRS2020

Apparent dust size discrepancy in aerosol reanalysis in north African dust after long-range transport

North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

MEERA-2 aerosols reanalysis↗
DOE OSTI2020

Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.

25 ENERGY STORAGE↗
NASA NTRS1975

Application of LANDSAT-2 to the Management of Delaware's Marine and Wetland Resources

The author has identified the following significant results. The duPont waste disposal plume was observed in 12 NASA/LANDSAT satellite images during dump up to 54 hours after dump. The circulation processes at the acid waste disposal site are highly event-dominated, with the majority of the water transport occurring strong northeasters. There is a mean flow to the south alongshore. During the warm months, the ocean stratifies with warm water over cold water. During stratified conditions, the near-bottom drogues showed very little movement. LANDSAT, aircraft, and boats were used successfully to study estuarine and coastal fronts or boundaries. By capturing and holding oil slicks, frontal systems significantly influence the movement and dispersion of oil slicks in Delaware Bay. Recent oil slick tracking experiments conducted to verify a predictive oil dispersion and movement model have shown that during certain parts of the tidal cycle the oil slicks tend to line up along boundaries.

Klemas, V.↗
NASA NTRS2014

Inspiring the Next Generation: The International Space Station Education Accomplishments

The International Space Station (ISS) has a unique ability to capture the imagination of both students and teachers worldwide. Since 2000, the presence of humans onboard ISS has provided a foundation for numerous educational activities aimed at capturing that interest and motivating study in the sciences, technology, engineering and mathematics (STEM). Over 43 million students around the world have participated in ISS-related educational activities. Projects such as YouTube Space Lab, Sally Ride Earth Knowledge-based Acquired by Middle Schools (EarthKAM), SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) Zero-Robotics, Tomatosphere, and MAI-75 events among others have allowed for global student, teacher and public access to space through student classroom investigations and real-time audio and video contacts with crewmembers. Educational activities are not limited to STEM but encompass all aspects of the human condition. This is well illustrated in the Uchu Renshi project, a chain poem initiated by an astronaut while in space and continued and completed by people on Earth. With ISS operations now extended to 2024, projects like these and their accompanying educational materials are available to more students around the world. From very early on in the program's history, students have been provided with a unique opportunity to get involved and participate in science and engineering projects. Many of these projects support inquiry-based learning that allows students to ask questions, develop hypothesis-derived experiments, obtain supporting evidence and identify solutions or explanations. This approach to learning is well-published as one of the most effective ways to inspire students to pursue careers in scientific and technology fields. Ever since the first space station element was launched, a wide range of student experiments and educational activities have been performed, both individually and collaboratively, by all the international partner agencies, National Aeronautics and Space Administration (NASA), Canadian Space Agency (CSA), European Space Agency, (ESA), Japan Aerospace Exploration Agency (JAXA) and Russian Federal Space Agency (Roscosmos), and a number of non-participating countries, some under commercial agreements. Many of these programs still continue, and others are being developed and added to the stations tasks on a regular basis. These diverse student experiments and programs fall into one of the following categories: student-developed experiments; students performing classroom versions of ISS experiments; students participating in ISS investigator experiments; education competitions; students participating in ISS Engineering Education; Education Demonstrations and Cultural Activities. This paper summarizes some of the main student experiments and educational activities that have been conducted on the space station.

Alleyne, Camille W.↗
NASA NTRS2021

Tracking Smoke from a Prescribed Fire and its Impacts on Local Air Quality using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD)

Aerosol optical depth (AOD) retrieved from the GOES-16 Advanced Baseline Imager (ABI) was used to track a smoke plume from a prescribed fire in northeastern Virginia on 8 March 2020. Weather and atmospheric conditions created a favorable environment to transport the plume through the Washington, D.C., and Baltimore, Maryland, metro areas in the afternoon and concentrate smoke near the surface, degrading air quality for several hours. ABI AOD with 5-min temporal resolution and 2-km spatial resolution definitively identified the timing and geographic extent of the plume during daylight hours. Comparison to AERONET AOD indicates that ABI AOD captured the relative change in AOD due to passage of the smoke, with a mean absolute error of 0.047. Ground-based measurements of fine particulate matter (PM2.5) confirm deteriorations in air quality coincident with the progression of the smoke. Ceilometer aerosol backscatter profiles verify plume transport timing and indicate that smoke aerosols were well mixed in a shallow boundary layer. This event illustrates the advantages of using multiple datasets to analyze the impacts of aerosols on ambient air quality. Given the quickly evolving nature of the event over several hours, ABI AOD provided information for the public and decision-makers that was not available from any other source, including polar-orbiting satellite sensors. This study suggests that PM2.5 concentrations estimated from ABI AOD can be used to fill in the gaps in nationwide regulatory PM2.5 monitor networks and may be a valuable addition to EPA’s PM2.5 NowCast of current air quality conditions.

satellite observations↗
NASA NTRS2020

Actor-based Runtime Verification with MESA

This work presents a runtime verification approach implemented in the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in data parameterized temporal logic and state machines. The tool is implemented as an internal Scala DSL. We employ the actor programming model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper presents a case study in which MESA is used to effectively monitor a large number of flights from live US airspace data streams. We also perform an empirical study by conducting experiments using monitoring systems with different num- bers of concurrent monitors and different layers of indexing on the data contained in events. The paper describes the experiments, evaluates the results, and discusses challenges faced during the study. The evaluation shows the value of combining concurrency with indexing to handle data rich events.

Mehlitz, Peter↗
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

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the Solvation and Acidity of Carboxylic Acids Using an Ab Initio Deep Neural Network Potential

Formic and acetic acid constitute the simplest of carboxylic acids, yet they exhibit fascinating chemistry in the condensed phase such as proton transfer and dimerization. The go-to method of choice for modeling these rare events have been accurate but expensive ab-initio molecular dynamics simulations. Here, we present a deep neural network potential trained using accurate ab-initio data that can be used in tandem with enhanced-sampling methods to perform an efficient exploration of the free-energy surface of aqueous solutions of weak carboxylic acids. In particular, we show that our model captures proton dissociation and provides a good estimate of the pK a , as well as the dimerization of formic and acetic acid. This provides a suitable starting point for applications in different research areas where computational efficiency coupled with the accuracy of ab-initio methods is required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Similarities in Meteorological Composites Among Different Atmospheric River Detection Tools During Landfall Over Western Coastal North America

Many atmospheric river detection tools (ARDTs) have been developed over the past few decades to identify atmospheric rivers (ARs). Different ARDTs have been observed to capture a variety of frequencies, shapes, and sizes of ARs. Due to this, questions have arisen about the underlying phenomena associated with the detected ARs: do all ARDTs detect the same meteorological phenomena? In this paper, we assess eight ARDTs and investigate the underlying synoptic scale phenomena during landfalling ARs along the west coast of North America. We find that during landfalling AR events, prevalent low-pressure and high-pressure systems converge and enhance moisture influx toward the landfalling site. We identify that all eight ARDTs identify AR conditions associated with baroclinic waves, with the region of intense integrated vapor transport (IVT) located downstream of the upper level (500 hPa) trough. The magnitude of IVT is enhanced by the strength of the pressure gradients in the confluence region. Although the ARDTs assessed agree on the general phenomena, there are however subtle differences in each ARDT per the clustering analysis we performed. We conclude that the eight ARDTs identify similar underpinning synoptic scale meteorological phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Development and Validation of the Near-Miss Safety Score (NMSS) Framework for Heavy-Duty Vehicle Safety Assessment

Heavy-duty commercial vehicles present unique safety challenges due to their size, articulation dynamics, and operational complexity. As Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) become more common in Class 8 tractor-trailers, traditional crash-based metrics are no longer sufficient to evaluate safety performance. This study introduces the Near-Miss Safety Score (NMSS)—a quantitative, physics-informed framework developed as a leading indicator of safety for advanced commercial vehicle technologies. NMSS quantifies how close a vehicle or operator comes to a collision or safety-critical event by integrating vehicle kinematics (relative distance, velocity, and acceleration) with driver or system response latency and time-to-collision. A modifier function adjusts the base score for vehicle-specific and environmental factors such as trailer articulation, load distribution, braking condition, and roadway environment. The framework enables systematic evaluation of ADAS/ADS performance under a range of operational and degraded conditions. By capturing near-miss dynamics rather than relying on crash data, NMSS provides a proactive approach to risk assessment, accelerates technology validation, and enhances interpretability for regulators and fleet operators. The proposed NMSS was validated using data collected from a motorcoach platform, demonstrating the framework’s applicability to heavy-duty safety evaluation and performance benchmarking. Results and key insights are presented in this paper.

Siekmann, Adam [ORNL] (ORCID:0000000284653935)↗
DOE OSTI2026

Multispectral UAV imagery of experimental freshwater wetlands under 5 ppt saltwater intrusion, Louisiana, 2023 and 2024

Multispectral imagery was collected using an unmanned aerial vehicle (UAV) to evaluate how freshwater vegetation responds to short-term simulated saltwater intrusion events. The purpose of this data collection was to understand how plant health changes in response to acute salinity exposure, which is increasingly relevant in coastal wetland ecosystems facing sea level rise and storm surge events, such as in coastal Louisiana. Three experimental saltwater intrusions were conducted at a salinity of approximately 5 parts per thousand (ppt) for durations of 6-days, 10-days, and 17-days. UAV flights occurred both before and after each treatment. The resulting imagery was processed using Pix4DMapper software to georeference the images and generate orthomosaics. The multispectral sensor used in this study captures reflectance in five bands: blue, green, red, red-edge, and near-infrared. The uploaded data consist of georeferenced .tif orthomosaics for each spectral band, which are compatible with GIS software for vegetation analysis. This imagery can be utilized in investigations into vegetation stress, remote sensing of freshwater wetland ecosystems, and modeling of plant response to environmental changes.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS↗
DOE OSTI2023

The Energy Transition: Advanced Nuclear Needed but Address Climate Vulnerabilities Now

The term “Energy Transition” is an attempt to capture an elaborate set of activities related to the modernization and decarbonization of energy grids. Performed concurrently and often in an ad hoc manner across local, state, regional and national boundaries, it is bringing chaos to what should arguably be one of the most conservatively managed of all critical infrastructure sectors. What’s more, with climate change producing an increasing tempo of extreme events, confidence in the intended resilient and redundant structure of the electric grids is likely to ebb. Even without these climate induced stressors, the nation’s electric grid was built for an earlier century. In addition to a drive towards greater efficiency via digitization and a continuing price decline in distributed energy resources (DERs), one could argue that climate change concerns are the primary driver of the energy transition. Non-CO2 emitting generation sources like wind and solar have become an important part of the overall generation fleet, albeit ones that cannot be counted upon to provide dispatchable power. Current projections indicate deployment of even larger percentages of DERs in coming years. Until far better storage capabilities arrive, the variability of wind and solar, inconsistent performance of traditional thermal generation plants, and energy delivery failures associated with natural gas pipelines will reinforce mounting reliability concerns. This pertains to both electric transmission and distribution. The recent shuttering of nuclear power plants in Germany, Japan, the US and elsewhere are also putting more downward pressure on dispatchable generation. Russia’s attack on Ukraine has roiled energy markets worldwide and forced some countries to return to coal as a primary fuel. In view circumstances such as these, it is essential that significant changes be made to policies and planning criteria, and to the standards and code on which they are based. Given the accelerating pace of extreme weather events, this needs to occur as soon as possible.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Short-term Electricity Price Forecasting with Constrained Regressors

The volatility of electricity price presents a challenge to market participants as their decision-making process are highly depend on the accuracy of price forecasts. However, there is growing empirical evidence of increasing price volatility and price spikes in electricity markets as a result of variable renewable energy generation, extreme weather events, and other factors. The distribution shift caused by spikes in electricity price data differentiates the forecasting tasks from other renewable energy sources. Moreover, the observations may be compromised by cyberattacks and thus not available in the testing phase. To this end, we propose a Similarity-Enhanced Electricity Decomposition Forecasting model (SEED-Forecaster) to address the missing response problem and spikes capturing in short-term electricity price forecasting. The effectiveness of the proposed framework is tested on real-world electricity price data from California Independent System Operator (CAISO). Numerical results of case studies show that the proposed SEED-Forecsater can enhance forecasting performance, particularly in capturing electricity spikes, even under conditions without regressors during testing stage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Thermal Energy Transport in Oxide Nuclear Fuel

To efficiently capture the energy of the nuclear bond, advanced nuclear reactor concepts seek solid fuels that must withstand unprecedented temperature and radiation extremes. In these advanced fuels, thermal energy transport under irradiation is directly related to reactor performance as well as reactor safety. The science of thermal transport in nuclear fuel is a grand challenge as a result of both computational and experimental complexities. Here we provide a comprehensive review of thermal transport research on two actinide oxides: one currently in use in commercial nuclear reactors, uranium dioxide (UO 2 ), and one advanced fuel candidate material, thorium dioxide (ThO 2 ). In both materials, heat is carried by lattice waves or phonons. Crystalline defects caused by fission events effectively scatter phonons and lead to a degradation in fuel performance over time. Bolstered by new computational and experimental tools, researchers are now developing the foundational work necessary to accurately model and ultimately control thermal transport in advanced nuclear fuels. We begin by reviewing research aimed at understanding thermal transport in perfect single crystals. The absence of defects enables studies that focus on the fundamental aspects of phonon transport. Next, we review research that targets defect generation and evolution. Here the focus is on ion irradiation studies used as surrogates for damage caused by fission products. We end this review with a discussion of modeling and experimental efforts directed at predicting and validating mesoscale thermal transport in the presence of irradiation defects. While efforts in these research areas have been robust, challenging work remains in developing holistic tools to capture and predict thermal energy transport across widely varying environmental conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Muon-induced fission of actinide nuclei

A negative muon captured by an actinide cascades down through the muonic atomic levels; deeply bound transitions can proceed via inverse internal conversion, depositing the muonic transition energy directly into the nucleus and, when the deposited energy exceeds the fission barrier, inducing prompt fission. Because the muon mean lifetime exceeds the saddle-to-scission timescale by orders of magnitude, the muon can survive the entire fission event as a 1⁢𝑠 spectator and ultimately attach to one or both of the emerging fragments. Its postscission attachment probability to the light fragment, 𝑃 𝐿 , can be used as a direct electromagnetic probe of fission dynamics on a timescale of 10 −21 s. In previous work, we introduced a three-dimensional lattice solution of the time-dependent Dirac equation coupled to the electromagnetic field generated by a fissioning nucleus and reported 𝑃 𝐿 for several actinides at a single dissipation strength. In this work, we extend that framework to a systematic survey of 232 Th , 238 U , and 240 Pu and implement a more realistic fission model which incorporates dynamic pairing correlations. We find that 𝑃 𝐿 falls steeply with the fragment charge asymmetry, a robust structural fingerprint of the fissioning system, while its dependence on nuclear dissipation is secondary and sensitive to the phenomenological friction prescription. These results establish 𝑃 𝐿 as a clean electromagnetic probe of fragment charge asymmetry and motivate a self-consistent, coordinate- and time-dependent treatment of nuclear dissipation as the natural next step.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS

In the face of atypical weather events, power infrastructure failures, and limited resources for resilience investment, energy decision-makers need data-driven metrics to allocate resilience investments and maximize the reduction of power outage impacts. For state-level planning, for instance, ranking the resilience of each county is key to ensuring effective distribution of resources. In such cases, resilience for each spatial unit is multifaceted and is captured by a set of indicators (i.e., metrics) that can be combined into an overall score that reduces the complexity of power outage dynamics to a single decision metric. However, weighting of these indicators is often addressed by simplifying assumptions (i.e., equal weights) or semi-subjective methods that rely on user-defined weights that can introduce biases (e.g., weighted average score). Within the disaster risk reduction and resilience engineering community, a recurring challenge in multicriteria decision-making is the objective weighting of indicators for composite indices. To address this issue, we have leveraged a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with an entropy-based weighting approach to calculated the integrated scores. This method objectively determines the importance of each metric, better discerns between spatial units (i.e., counties), and offers a more reliable ranking of counties according to their relative resilience attributes. By improving methods for integrating resilience indicators, our approach helps planners and decision-makers prioritize resources more effectively for more efficient resilience investments.

Bhusal, Narayan [Oak Ridge National Laboratory (OR↗