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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

Gupta, U. K.↗
DOE OSTI2019

Thermally Conductive Backsheets (TCB) for Reduced Operating Temperatures

The performance of photovoltaic (PV) modules is primarily influenced by the plane of array (POA) irradiance and their operating temperature. The lower the module operating temperature, the higher is its performance. Increasing a module’s operating temperature reduces its power output due to an increase in the semiconductor’s intrinsic carrier density, leading to a reduction in the open-circuit voltage and, subsequently, reducing the maximum power point voltage. Reducing the operating temperature lowers the levelized cost of energy (LCOE) via increased energy production (i.e., more kilowatt hour over the life of the asset) and increased service lifetime (years in the field). The module operating temperature is dictated by the weather parameters and the thermal properties of module construction materials. The primary weather parameters influencing the PV module temperature are: the ambient temperature (directly related), irradiance (directly related), and wind speed (inversely related). The primary thermal properties of module construction materials influencing the PV module temperature are: the optical transmissivity and thermal conductivity of superstrate, the thermal conductivity of substrate, the thermal conductivity of encapsulant and the efficiency of the encapsulated solar cells. The primary goal of this study is to reduce the operating temperature of PV modules using thermally conductive backsheet (TCB) substrates developed by the industry. The temperature of PV modules installed in a large multi-MW plant can also be influenced by their physical locations in the plants due to the influence of wind direction. A thermal mapping of PV plants has also been investigated and presented in this study. The most commonly used PV backsheet material has been polyvinyl fluoride (DuPont trade name “Tedlar”)-based backsheet, which typically has three layers: Tedlar–polyethylene terephthalate (PET)–Tedlar (TPT). The primary goal of this project is to reduce the module operating temperature below the benchmark TPT backsheet temperature using newly developed TCBs by the industry. The overall approach of this project involves six focus areas: i) select and procure one TPT and thirteen promising TCBs available in the industry; ii) construct a large number of 1-cell and 9-cell modules using benchmark TPT and selected TCBs [all other construction materials are fixed and they are: glass superstrate, EVA encapsulant, mono-Si cell and junction box]; iii) to identify best performing TCBs, monitor the long-term field operating temperatures of the constructed modules which are installed in three climatic conditions (hot-low wind [Mesa, AZ], hot-high wind [Maricopa County, AZ] and temperate [Cumberland County, NC]; iv) to identify the most durable TCB, perform extended accelerated reliability testing of modules constructed with best three TCBs and benchmark TPT; v) to predict module temperature, develop physical and empirical thermal models with and without thermal properties of all construction materials in the modules, respectively; and vi) to determine the influence of wind speed and direction on the module operating temperature in a plant, and perform thermal mapping of PV modules in two large PV plants [Maricopa County, AZ and Cumberland County, NC]. The key achievements of this project are listed below: Backsheet selection: 14 backsheets were procured after an extensive literature and industry search. Finally, based on the thermal and other selection criteria, 1 TPT and 4 thermally conductive backsheets were selected for this project. Fabrication of mini modules: 50 one-cell modules were fabricated in year 1 for thermal performance evaluation. The module design was changed to nine-cell module at start of year 2 to mimic commercial design. 20 nine-cell modules were fabricated in year 2 for thermal performance evaluation. 28 four-cell modules were fabricated in year 3 for accelerated stress-testing. Thermal conductivity of backsheets: Year 1 TCBs showed at least 8% higher thermal conductivities than TPT. Year 2 and 3 TCBs showed at least 20% higher thermal conductivities than TPT. Installation of mini PV modules at three sites: 6 one-cell modules and 8 nine-cell modules were installed at AZ-1 site [Mesa, AZ]. 12 one-cell modules and 6 nine-cell modules were installed at each of two powerplants (AZ-2 [Maricopa County, AZ] and NC sites). Nominal operating cell temperatures (NOCT) of mini PV modules: NOCT of TCBs were observed to be lower than TPT with differences as high as 2°C. Comparison of thermal performance: The median operating temperature of one-cell modules was found to be reduced by 2°C by using TCB_A modules compared to TPT modules on several days in a month for few months in a year. The median temperature improvement of 4oC was achieved at several instances on a few days, but not all days, in a year using multiple TCBs compared to TPT. The final project milestone of achieving median temperature improvement of 5oC was achieved at several instances on a few days, but not all days, in a year using TCB_A compared to TPT. Empirical thermal model (without the need of construction material properties): Empirical thermal model for one-cell module was developed based on the input data of irradiance, wind speed and ambient temperatures. The primary input data differentiator for temperature differences between TPT and TCBs appears to be the irradiance level (solar gain). Accelerated durability testing: 20 four-cell modules using 4 backsheets (1 TPT and 3 TCBs) were exposed to Damp Heat 1000 hours (8 modules), UV/Thermal cycling (50 cycles)/Humidity freeze (10 cycles) test sequence (8 modules) and UV Weathering for qualification (8 modules). All the modules with four selected backsheets passed the stress tests per the retest guidelines of IEC 61215 standard for the backsheet change. Simplified comparative LCOE analysis: Using backsheet-specific power degradation levels in the accelerated tests (for TCB_A and TPT only), efficiency, service lifetime and assuming same cost for all backsheets, the LCOE of modules using TCB_A is determined to be lower than TPT. Due to lower operating temperature of TCB_A-based modules compared to TPT-based modules, the operating efficiency and service life of TCB_A-based modules are calculated to be higher than TPT-based modules. Temperature mapping of PV power plants: A distinct temperature difference (as high as 4°C) has been observed between the modules located in various parts of a single PV plant.

14 SOLAR ENERGY↗
DOE OSTI2024

Remote Sensing Detection of Growing Season Freeze-Induced Defoliation of Montane Quaking Aspen (Populus tremuloides) in Southern Utah, USA

Growing season freeze events pose a threat to quaking aspen (Populus tremuloides Michx.), leading to canopy defoliation, reduced vigor, and increased mortality, especially for declining montane populations western North America. Detecting the spatial distribution and progression of this damage is challenging due to limited in situ observations in this region. This study represents the first attempt to comprehensively resolve the spatial extent of freeze-induced aspen canopy damage in southern Utah using multispectral remote sensing data. We developed an approach to detect the spatial and temporal dynamics of freeze-damaged aspen stands, focusing on a freeze event from 8–9 June 2020 in southern Utah. By integrating medium- (~250 to 500 m) and high-resolution (~10 m) satellite data, we employed the Normalized Difference Vegetation Index (NDVI) to compare post-freeze conditions with historical norms and pre-freeze conditions. Our analysis revealed NDVI reductions of 0.10 to 0.40 from pre-freeze values and a second flush recovery. We introduced a pixel-based method to evaluate freeze vulnerability, establishing a strong correlation (R values 0.78 to 0.82) between the onset of the first flush (NDVI > 0.50) and the accumulation of 100 growing degree days (GDD). These methods support the potential for retrospective assessments, proactive forest monitoring, and forecasting future risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗
NASA NTRS1988

Integration of a computerized two-finger gripper for robot workstation safety

A microprocessor-based controller has been developed that continuously monitors and adjusts the gripping force applied by a special two-finger gripper. This computerized force sensing gripper system enables the endeffector gripping action to be independently detected and corrected. The gripping force applied to a manipulated object is real-time monitored for problem situations, situations which can occur during both planned and errant robot arm manipulation. When unspecified force conditions occur at the gripper, the gripping force controller initiates specific reactions to cause dynamic corrections to the continuously variable gripping action. The force controller for this intelligent gripper has been interfaced to the controller of an industrial robot. The gripper and robot controllers communicate to accomplish the successful completion of normal gripper operations as well as unexpected hazardous situations. An example of an unexpected gripping condition would be the sudden deformation of the object being manipulated by the robot. The capabilities of the interfaced gripper-robot system to apply workstation safety measures (e.g., stop the robot) when these unexpected gripping effects occur have been assessed.

Sneckenberger, John E.↗
NASA NTRS2000

The Visibility of Earth Transits

The recent photometric detection of planetary transits of the solar-like star HD 209458 at a distance of 47 parsecs suggest that transits can reveal the presence of Jupiter-size planetary companions in the solar neighborhood. Recent space-based transit searches have achieved photometric precision within an order of magnitude of that required to detect the much smaller transit signal of an earth-size planet across a solar-size star. Laboratory experiments in the presence of realistic noise sources have shown that CCDs can achieve photometric precision adequate to detect the 9.6 E-5 dimming of the Sun due to a transit of the Earth. Space-based solar irradiance monitoring has shown that the intrinsic variability of the Sun would not preclude such a detection. Transits of the Sun by the Earth would be detectable by observers that reside within a narrow band of sky positions near the ecliptic plane, if the observers possess current Earth epoch levels of technology and astronomical expertise. A catalog of solar-like stars that satisfy the geometric condition for Earth transit visibility are presented.

Castellano, Timothy P.↗
NASA NTRS1997

Interaction of light and gravitropism with nutation of hypocotyls of Arabidopsis thaliana seedlings

Etiolated seedlings of Arabidopsis thaliana nutated under conditions of physiological darkness while about ten percent of monitored individuals exhibited regular elliptical nutation, circumnutation. Pre-irradiation with red light prevented occurrence of circumnutation without having an effect on the average rate of the nutational movement. Phototropic response of seedlings to unilateral blue light appeared to be superimposed over nutation. Throughout gravitropism, some seedlings continued to exhibit nutation suggesting that these two processes are independently controlled. Based on these results, we suggest that nutation in Arabidopsis probably is not controlled by the mechanism predicted by the theory of gravitropic overshoots.

NASA Discipline Plant Biology↗
NASA NTRS2004

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica, composed of the seven Central American countries and the five southernmost states of Mexico, make up only a small fraction of the world's land surface. However, the region is home to seven to eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica's biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, D. E.↗
NASA NTRS2005

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - make up only a small fraction of the world s land surface. However, the region is home to seven to eight percent of the planet s biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica s biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, Daniel E.↗
NASA NTRS2016

AirSTAR Hardware and Software Design for Beyond Visual Range Flight Research

The National Aeronautics and Space Administration (NASA) Airborne Subscale Transport Aircraft Research (AirSTAR) Unmanned Aerial System (UAS) is a facility developed to study the flight dynamics of vehicles in emergency conditions, in support of aviation safety research. The system was upgraded to have its operational range significantly expanded, going beyond the line of sight of a ground-based pilot. A redesign of the airborne flight hardware was undertaken, as well as significant changes to the software base, in order to provide appropriate autonomous behavior in response to a number of potential failures and hazards. Ground hardware and system monitors were also upgraded to include redundant communication links, including ADS-B based position displays and an independent flight termination system. The design included both custom and commercially available avionics, combined to allow flexibility in flight experiment design while still benefiting from tested configurations in reversionary flight modes. A similar hierarchy was employed in the software architecture, to allow research codes to be tested, with a fallback to more thoroughly validated flight controls. As a remotely piloted facility, ground systems were also developed to ensure the flight modes and system state were communicated to ground operations personnel in real-time. Presented in this paper is a general overview of the concept of operations for beyond visual range flight, and a detailed review of the airborne hardware and software design. This discussion is held in the context of the safety and procedural requirements that drove many of the design decisions for the AirSTAR UAS Beyond Visual Range capability.

Laughter, Sean↗
NASA NTRS2018

Northern Hemisphere Surface Freeze-Thaw Product from Aquarius L-Band Radiometers

In the Northern Hemisphere, seasonal changes in surface freeze–thaw (FT) cycles are an important component of surface energy, hydrological and eco-biogeochemical processes that must be accurately monitored. This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the Equal-Area Scalable Earth Grid version 2.0, above the parallel 50 N, with a spatial resolution of 36 km36 km. The FT-AP classification algorithm is based on a seasonal threshold approach using the normalized polarization ratio, references for frozen and thawed conditions and optimized thresholds. To evaluate the uncertainties of the product, we compared it with another satellite FT product also derived from passive microwave observations but at higher frequency: the resampled 37 GHz FT Earth Science Data Record (FTESDR). The assessment was carried out during the overlapping period between 2011 and 2014. Results show that 77.1% of their common grid cells have an agreement better than 80 %. Their differences vary with land cover type (tundra, forest and open land) and freezing and thawing periods. The best agreement is obtained during the thawing transition and over forest areas, with differences between product mean freeze or thaw onsets of under 0.4 weeks. Over tundra, FT-AP tends to detect freeze onset 2–5 weeks earlier than FT-ESDR, likely due to FT sensitivity to the different frequencies used. Analysis with mean surface air temperature time series from six in situ meteorological stations shows that the main discrepancies between FT-AP and FT-ESDR are related to false frozen retrievals in summer for some regions with FT-AP. The Aquarius product is distributed by the U.S. National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/aq3_ft/versions/5 with the DOI https://doi.org/10.5067/OV4R18NL3BQR.

Prince, Michael↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Microstructural Evolution of Tantalum During Deformation and Subsequent Annealing

Microstructure-aware models are necessary to predict the behavior of material based on process knowledge or to extrapolate mechanical properties of materials to environmental conditions which are not easily reproduced in the laboratory, e.g., nuclear reactor environments. Elemental Ta provides a relatively simple BCC system in which to develop a microstructural understanding of deformation processes which can then be applied to more complicated BCC alloys. In situ neutron diffraction during compressive deformation and subsequent heat treatment have been used to monitor the evolution of microstructural features in Ta throughout simulated processing steps. Crystallographic texture and dislocation density are determined as a function of first plastic strain, then temperature. Lattice strains are determined and attributed to stresses at macroscopic, grain and dislocation length scales. The increase of the dislocation density through deformation and subsequent recovery during heat treatment is monitored through the changing diffraction line profile. Also, randomization of the texture is used as a signature of recrystallization. The recovery of dislocations through annihilation is not observed to depend on the initial dislocation density in the range studied here. In contrast, recrystallization is observed to depend strongly on the initially dislocation density.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Correlating armature and needle dynamics with voltage waveforms of solenoid-actuated GDI injector

The injector voltage hump that appears near the needle closing has been used for the real-time monitoring and feedback control of fuel injection duration in modern engines. This voltage hump has been thought to result from the abrupt change in electromagnetic induction by the stoppage of needle motion but detailed electromagnetic processes and associated armature and needle dynamics during the needle closing have not been thoroughly investigated in a wide range of injection conditions, which knowledge is crucial for the delicate control of fuel injection based on the voltage hump. Here, the current study analyzes the transient armature and needle dynamics of a solenoid-actuated gasoline direct injection injector using an X-ray phase-contrast imaging technique. Then, the results are correlated with voltage waveforms during the needle closing transient under various injection pressures, injection pulse durations, and dwell times of split injections. The time derivatives of voltage waveforms showed lower and upper peaks in order in the regime of the voltage hump. Inconsistent with conventional understandings, the lower peak timing of the voltage derivative did not match with the timing of needle closing (end of injection) but rather matched with the abrupt descent timing of the armature and needle. The inflection timing and upper peak timing of the voltage derivative matched with the timings of actual needle closing and armature closing respectively. The amplitude of the voltage hump was near linearly dependent on the needle closing speed. The needle closing speed decreased upon the decrease of injection pulse duration and injection pressure which made it difficult to detect the voltage humps in ballistic injection regimes and low injection pressures. In split injection conditions, the voltage hump of the first injection was not detectable if the dwell time was shorter than the needle closing delay, the time from the current cut-off to the actual needle closing.

42 ENGINEERING↗
DOE OSTI2022

Additively manufactured strain sensors for in-pile applications

Accurate, real-time monitoring of strain in fuel, cladding, and structural components of nuclear reactors is critical to better understand radiation induced phenomena during reactor tests and operations. The data provided is crucial to verify physics-based, multiscale modeling and simulation efforts, which aim to shorten the timeline for the development of new nuclear materials. Resistive strain gauges have limited performance during in-pile experiments due to the harsh operating conditions and limited physical space between fuel and cladding components. In this work, aerosol jet printing using silver nanoparticle inks was used to fabricate interdigitated electrode capacitive strain gauges on aluminum alloy 6061 tensile specimens. Here to simulate the temperatures of a traditional light water reactor, the capacitive strain gauges were tested with a mechanical test frame up to 300 °C and compared to commercially available bondable resistive strain gauges. The printed capacitive strain gauges exhibited a gauge factor of 1.0 and showed higher reproducibility and predictability of strain sensing performance than the resistive strain gauge. The results demonstrate the potential of aerosol jet printing to fabricate strain sensors with predictable performance and reduced invasiveness for high-temperature applications with confined spacing.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Radionuclide uptake by colloidal and particulate humic acids obtained from 14 soils collected worldwide

Uptake of six particle-reactive and/or redox-sensitive radionuclides ( 210 Pb, 234 Th, 7 Be, 59 Fe, 237 Np and 233 Pa) by 14 humic acids (HAs) was investigated in artificial groundwater under mildly acidic conditions (pH~5.5). In HA-groundwater slurry, Pb, Be, Fe and Pa bound strongly to particulate HA (>0.45 μm), supporting their application as tracers of soil erosion. Th bound strongly to the colloidal HA (3 kDa- 0.45 μm) and as such, would not be a good candidate as a tracer for monitoring soil erosion. HAs likely reduced the oxidized neptunyl form (Np(V)O 4 +) to Np(IV) based on its enhanced particle-reactivity and Np uptake by particulate HAs, partially retarding the movement of anthropogenic 237 Np in field polluted environments. Particulate/colloidal carbonyl/O-aryl (likely through hydroquinone/quinone) functionalities in the HA correlated to Np and Pa uptake, but only particulate O-aryl functionalities was responsible for Fe uptake. The carboxylate- and carbonyl/O-aryl-containing organic functionalities in the HA correlated strongly with Th uptake. In contrast, no significant correlations between organic parameters and Pb or Be uptake implied their predominance of uniform surface adsorption onto particles. Our work provides novel insight into the binding of six radionuclides with different organic functionalities of three size fractions, as well as its possible impact on their application in the soiltracing research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Central Hanford Ecological Integrity Assessments: Final Report

The Hanford Site is comprised of an expanse of shrub-steppe habitats that provides exceptional ecological value to plants and animals located on the site and in the surrounding greater Columbia Basin. The U.S. Department of Energy, Hanford Field Office (HFO)-managed portion of the Hanford Site, referred to herein as Central Hanford, has been the focus of various ecological monitoring efforts, such as vegetation monitoring. The scope and goals of vegetation surveys have varied greatly since the Hanford Site was established, but studies have documented a rapidly changing landscape, making it clear that routine vegetation monitoring is integral to understanding ecological changes and preserving the ecological value of the Hanford Site. A new vegetation monitoring effort was initiated in calendar year (CY) 2023 and continued through CY 2025 using methods based on ecological integrity assessments (EIA) (NHR-2024-04, Field Manual for Applying Rapid Ecological Integrity Assessments in Upland Plant Communities of Washington State ) developed by the Washington Natural Heritage Program (WNHP), a division of the Department of Natural Resources (DNR), and NatureServe.® The methods were modified and supplemented to meet monitoring goals at the Hanford Site. The EIA monitoring effort consisted of field surveys to evaluate vegetation and soil conditions for upland habitats throughout Central Hanford. Vegetation cover estimates were used to score a variety of metrics for vegetation condition. This report summarizes monitoring methods, monitoring results, and provides management recommendations.

54 ENVIRONMENTAL SCIENCES↗