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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Supraoptimal carbon dioxide effects on growth of soybean [Glycine max (L.) Merr.]

In tightly closed environments used for human life support in space, carbon dioxide (CO2) partial pressures can reach 500 to 1000 Pa, which may be supraoptimal or toxic to plants used for life support. To study this, soybeans [Glycine max (L.) Merr. cvs. McCall and Pixie] were grown for 90 days at 50, 100, 200, and 500 Pa partial pressure CO2 (500, 1000, 2000, and 5000 ppm). Plants were grown using recirculating nutrient film technique with a 12-h photoperiod, a 26 degrees C/20 degrees C thermoperiod, and approximately 300 micromoles m-2 s-1 photosynthetic photon flux (PPF). Seed yield and total biomass were greatest at 100 Pa for cv. McCall, suggesting that higher CO2 levels were supraoptimal. Seed yield and total biomass for cv. Pixie showed little difference between CO2 treatments. Average stomatal conductance of upper canopy leaves at 50 Pa CO2 approximately 500 Pa > 200 Pa > 100 Pa. Total water use over 90 d for both cultivars (combined on one recirculating system) equalled 822 kg water for 100 Pa CO2, 845 kg for 50 Pa, 879 kg for 200 Pa, and 1194 kg for 500 Pa. Water use efficiences for both cultivars combined equalled 3.03 (g biomass kg-1 water) for 100 Pa CO2, 2.54 g kg-1 for 200 Pa, 2.42 g kg-1 for 50 Pa, and 1.91 g kg-1 for 500 Pa. The increased stomatal conductance and stand water use at the highest CO2 level (500 Pa) were unexpected and pose interesting considerations for managing plants in a tightly closed system where CO2 concentrations may reach high levels.

NASA Discipline Life Support Systems↗
NASA NTRS2022

Biofilm Study Under Simulated Microgravity

The goal of this study was to understand biofilm formation under microgravity (µg), in support of biofilm mitigation efforts in exploration water recovery systems. The technical approach was to conduct a mass transfer and bacterial culture study under both simulated µg and ambient gravity. The aim was to correlate nutrient consumption to gene expression to better understand biofilm formation. A representative species of bacteria that is commonly cultured from the International Space Station (ISS) Water Processor Assembly (WPA) was cultured in a WPA influent water ersatz formulation that is tailored for microbiology studies. A mass transfer rate study was carried out using the ersatz WPA influent water by introducing a water-soluble dye to represent dissolved nutrients and nutrient particles. Imaging of dye diffusion over time allowed for the comparison of mass transport rates under a series of rotation per minute (RPM) speeds for the High Aspect Ratio Vessels (HARVs) on a Rotating Wall Vessel (RWV). This was done to determine the speed that will most accurately simulate the low convective rates experienced under actual µg conditions. Three biological replicates of the Burkholderia contaminans (B. contaminans) microbe were cultured under simulated µg with a rotating (R) control in the horizontal plane at the determined optimal RPM of 15, along with a stationary (S) reference culture. At T=0, and then at T=1,2,3 (in exponential phase) and T=4 (in S phase), the bacterial culture and ersatz were harvested for transcriptomic and nutrient content analysis, respectively. The experimental results illustrated that phosphate is a limiting nutrient in the WPA ersatz formula. Nutrient analysis illustrated that the µg treatment culture took up essential nutrients more rapidly than the R and S control cultures, yet non-essential nutrients remained higher in the µg treatment than in the controls at later timepoints. The rapid uptake and subsequent starvation of phosphate in the culture under µg conditions is further illustrated in the transcriptomic response when compared to that of the R control condition. The subsequent starvation response may serve as one element to explain a moderate enhancement of biofilm formation in the µg treatment. One implication of this work is that biofilm mitigation in the ISS environment could be supported by ensuring a steady flow of water as a vehicle for phosphate within the WPA to avoid complete phosphate consumption, which occurs in times of no flow and leads to undesired biofilm formation.

Aubrie O’Rourke↗
NASA NTRS2012

Next Generation Life Support Project Status

Next Generation Life Support (NGLS) is one of several technology development projects sponsored by NASA s Game Changing Development Program. The NGLS Project is developing life support technologies (including water recovery and space suit life support technologies) needed for humans to live and work productively in space. NGLS has three project tasks: Variable Oxygen Regulator (VOR), Rapid Cycle Amine (RCA) swing bed, and Alternative Water Processor (AWP). The RCA swing bed and VOR tasks are directed at key technology needs for the Portable Life Support System (PLSS) for an Advanced Extravehicular Mobility Unit, with focus on test article development and integrated testing in an Advanced PLSS in cooperation with the Advanced Extra Vehicular Activity (EVA) Project. An RCA swing-bed provides integrated carbon dioxide removal and humidity control that can be regenerated in real time during an EVA. The VOR technology will significantly increase the number of pressure settings available to the space suit. Current space suit pressure regulators are limited to only two settings whereas the adjustability of the advanced regulator will be nearly continuous. The AWP effort, based on natural biological processes and membrane-based secondary treatment, will result in the development of a system capable of recycling wastewater from sources expected in future exploration missions, including hygiene and laundry water. This paper will provide a status of technology development activities and future plans.

Barta, Daniel J.↗
DOE OSTI2021

Habit–Dependent Vapor Growth Modulates Arctic Supercooled Water Occurrence

We present an analysis of long-term data collected at Utqiagvik, Alaska, to explore the impacts of cloud processes on the probability of finding supercooled water given cloud temperature, P(L|T), in the topmost unseeded liquid-bearing layers. P(L|T) has local minima at temperatures around –6°C and –15°C. Simulations using habit-evolving ice microphysics models suggest that these minima are the result of efficient vapor growth by non-isometric habits found at these temperatures. Here, we conclude that habit-dependent vapor growth of ice crystals modulates the macrophysical occurrence of supercooled water in polar clouds, the effect of which should be included in model parametrizations to avoid biases and/or error compensation. Our methodology is adaptable for spherical ice treatments implemented in models (example parametrizations provided), amenable for use with satellite measurements to give global impartial observational targets for model evaluations, and may allow empirical characterization of bulk responses to seeding and possibly secondary ice effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Field Validation of Electrocoagulation Treatment for Oily Wastewater at a Steel Mill

Oily wastewater is a significant byproduct across various industries, including steel production, posing environmental and health risks. Steelmaking is particularly water-intensive, with an estimated 75,000 gallons required to produce 1 ton of steel, although recycling reduces this to 13,000–23,000 gallons per ton.1 Water serves multiple purposes in steelmaking, including equipment cooling, scale removal, steam generation, lubrication, and pollution control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cooperative roles of water and metal-support interfaces in the selective hydrogenation of cinnamaldehyde over cobalt boride catalysts

Chemoselectivity in the hydrogenation of carbonyl over alkene bonds is valuable for producing industrial chemicals. In this study, we investigate the role of water in the selective hydrogenation of cinnamaldehyde on cobalt and cobalt boride catalysts by combining rate measurements, in situ characterization, and computational calculations. Ex situ and in situ spectroscopic analyses indicate that the boron species do not significantly modify the intrinsic electronic properties of cobalt. However, during thermal treatments, they exsolve from the bulk phase and become enriched on the surface, forming acidic species that enhance the activity and selectivity of carbonyl bond hydrogenation by three and two times, respectively. A small amount of water is able to promote hydrogenation. When titania, ceria, and zirconia are used as supports, metal-support interactions result in smaller particles that show a drop in selectivity toward the desirable unsaturated alcohol. Overall, the combination of the presence of boron species and strong metal-support interactions protects the catalysts from water attack, resulting in enhanced stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2021

Strong tough hydrogels via the synergy of freeze-casting and salting out

Natural load-bearing materials like tendons possess high water content of ~70% but14 are still strong and tough even when used for over 1 million cycles per year, which is owed to the hierarchical assembly of anisotropic structures across multi-length-scales . In imitation of natural systems, various hydrogels have been created via methods like electro-spinning, extrusion, compositing, freeze casting, self-assembly, and mechanical stretching for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, large toughness or high fatigue resistance. In this work, we present a strategy to produce strong, tough and fatigue resistant hydrogels with multi-length-scale hierarchical architecture using a freezing-assisted salting-out treatment. The produced exemplary poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometer-scale honeycomb-like pore walls, which in turn comprise interconnected nanofibrils meshes, entirely physically assembled from polymer chains. These hydrogels are made of 70-95% water but can exhibit ultra-high ultimate stress (23.5 ± 2.7 MPa) and strain (2900 ± 450%), giant 32226 toughness (210 ± 13 MJ/m , 175 ± 8 kJ/m) and remarkable fatigue threshold (10.5 ± 1.3 kJ/m), which are 10 times tougher than natural tendon. The presented strategy could expand the applicability of weak polymeric material, like hydrogels, in practical applications that requires long-term services with high-loads and abrupt-impacts and extend the development of structural hydrogels.

36 MATERIALS SCIENCE↗
NASA NTRS2022

GNSS-RO Deep Refraction Signals from Moist Marine Atmospheric Boundary Layer (MABL)

The marine atmospheric boundary layer (MABL) has a profound impact on sensible heat and moisture exchanges between the surface and the free troposphere. The goal of this study is to develop an alternative technique for retrieving MABL-specific humidity (q) using GNSS-RO data in deep-refracted signals. The GNSS-RO signal amplitude (i.e., signal-to-noise ratio or SNR) at the deep straight-line height (H(SL)) was been found to be strongly impacted by water vapor within the MABL. This study presents a statistical analysis to empirically relate the normalized SNR (S(RO)) at deep HSL to the MABL q at 950 hPa (~400 m). When compared to the ERA5 reanalysis data, a good linear q–S(RO) relationship is found with the deep H(SL) S(RO) data, but careful treatments of receiver noise, SNR normalization, and receiver orbital altitude are required. We attribute the good q–S(RO) correlation to the strong refraction from a uniform, horizontally stratiform and dynamically quiet MABL water vapor layer. Ducting and diffraction/interference by this layer help to enhance the S(RO) amplitude at deep H(SL). Potential MABL water vapor retrieval can be further developed to take advantage of a higher number of S(RO) measurements in the MABL compared to the Level-2 products. A better sampled diurnal variation of the MABL q is demonstrated with the S(RO) data over the Southeast Pacific (SEP) and the Northeast Pacific (NEP) regions, which appear to be consistent with the low cloud amount variations reported in previous studies.

diurnal variation↗
DOE OSTI2023

Totally chlorine-free peracetic acid pulping for nanocellulose isolation from hemp and poplar

Nanocellulose is a promising and sustainable feedstock for developing advanced and functional materials. However, the characteristics of nanocellulose, such as crystallinity, surface energy, and aspect ratio, can vary depending on biomass source and pretreatment methods, leading to variable performance of the nanocellu-lose-based materials. In this study, cellulose nanocrystals (CNCs) were isolated from hemp and poplar using totally chlorine free (TCF) peracetic acid and sodium chlorite delignification and bleaching pretreatments to probe the influences of biomass source and treatment methods on the isolation and characteristics of CNCs. Our results showed that hemp and poplar were almost completely delignified by peracetic acid treatment, whereas sodium chlorite treatment left 5%–6% lignin in the pulp. The yields of CNCs from raw hemp and poplar biomass ranged from 9.8% to 21.9% and 10.9% to 28.3%, respectively, depending on the treatment methods. The dimensions of CNCs from TCF-treated biomass generally maintained a larger width and aspect ratio than those from sodium chlorite-treated biomass. The poplar-derived CNCs exhibited slightly higher crystallinity of 53%–58% than hemp-derived CNCs of 49%–54%. The zeta potential of the CNCs, ranging from -20.1 mV to -31.1 mV, ensured a well-dispersed aqueous solution. The surface energy (dispersive energy of 40–80 mJ/m2 and specific energy of 2–10 mJ/m2), water interaction, and thermal stability of the CNCs were comparable, regardless of the biomass source and pretreatment methods. Our finding suggests that the TCF technique with peracetic acid treatment is a promising delignification and bleaching approach to obtain cellulose-rich pulps from herbaceous and hardwood biomass for nanocellulose isolation.

09 BIOMASS FUELS↗
DOE OSTI2024

Bioelectrochemical reactor to manage anthropogenic sulfate pollution for freshwater ecosystems: Mathematical modeling and experimental validation

Anthropogenic sulfate loading into otherwise low-sulfate freshwater systems can cause significant ecological consequences as a biogeochemical stressor. To address this challenge, in situ bioremediation technologies have been developed to leverage naturally occurring microorganisms that transform sulfate into sulfide rather than implementing resource-intensive physio-chemical processes. However, bioremediation technologies often require the supply of electron donors to facilitate biological sulfate reduction. Bioelectrochemical systems (BES) can be an alternative approach for supplying molecular hydrogen as an electron donor for sulfate-reducing bacteria through water electrolysis. Although the fundamental mechanisms behind BESs have been studied, limited research has evaluated the design and operational parameters of treatment systems when developing BESs on a scale relevant to environmental systems. Further, this study aimed to develop an application-based mathematical model to evaluate the performance of BESs across a range of reactor configurations and operational modes. The model was based on sulfate transformation by hydrogenotrophic sulfate-reducing bacteria coupled with the recovery of solid iron sulfide species formed by the oxidative dissolution of dissolved ferrous iron from a stainless steel anode. Sulfate removal closely corresponded to the rate of electrolytic hydrogen production and hydraulic residence time but was less sensitive to specific microbial rate constants. The mathematical model results were compared to experimental data from a pilot-scale BES tested with nonacidic mine drainage as a case study. The close agreement between the mathematical model and the pilot-scale BES experiment highlights the efficacy of using a mathematical model as a tool to develop a conceptual design of a scaled-up treatment system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

VA EDH Data Curation Documentation (FY24-Q1)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VA EDH Data Curation Documentation (FY24-Q2)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

VA EDH Data Curation Documentation (FY24-Q3)

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VA EDH Data Curation Documentation FY24-Q4

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. Health outcomes, including suicide, are typically influenced by both genetics and environmental factors, such as air quality, transportation access, food availability, homelessness, and more. Mental health outcomes are associated with various stressors across socioeconomic, economic, and physical environments. Analyzing the connections between these stressors, covariates, and health outcomes relies on standardized data, which can be integrated into models like the VA’s Recovery Engagement and Coordination for Health, Veterans Enhanced Treatment (REACH VET). The World Health Organization (WHO) defines Environmental Determinants of Health (EDH) as factors like clean air, stable climate, water and sanitation, chemical safety, radiation protection, safe workplaces, sustainable agriculture, healthy urban environments, and nature preservation, all of which are crucial for good health.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1977

Strength enhancement process for prealloyed powder superalloys

A technique involving superplastic processing and high pressure autoclaving was applied to a nickel base prealloyed powder alloy. Tensile strengths as high as 2865 MN/sq m at 480 C were obtained with as-superplastically deformed material. Appropriate treatments yielding materials with high temperature tensile and stress rupture strengths were also devised.

Waters, W. J.↗
NASA NTRS1988

Thermal effects on the mechanical properties of SiC fiber reinforced reaction bonded silicon nitride matrix (SiC/RBSN) composites

The elevated temperature four-point flexural strength and the room temperature tensile and flexural strength properties after thermal shock were measured for ceramic composites consisting of 30 vol pct uniaxially aligned 142 micron diameter SiC fibers in a reaction bonded Si3N4 matrix. The elevated temperature strengths were measured after 15 min of exposure in air at temperatures to 1400 C. Thermal shock treatment was accomplished by heating the composite in air for 15 min at temperatures to 1200 C and then quenching in water at 25 C. The results indicate no significant loss in strength properties either at temperature or after thermal shock when compared with the strength data for composites in the as-fabricated condition.

Bhatt, R. T.↗