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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Effects of Polar Stratospheric Clouds in the Nimbus 7 LIMS Version 6 Data Set

The historic Limb Infrared Monitor of the Stratosphere (LIMS) measurements of 1978-1979 from the Nimbus 7 satellite were re-processed with Version 6 (V6) algorithms and archived in 2002. The V6 data set employs updated radiance registration methods, improved spectroscopic line parameters, and a common vertical resolution for all retrieved parameters. Retrieved profiles are spaced about every 1.6 of latitude along orbits and include the additional parameter of geopotential height. Profiles of O3 are sensitive to perturbations from emissions of polar stratospheric clouds (PSCs). This work presents results of implementing a first-order screening for effects of PSCs using simple algorithms based on vertical gradients of the O3 mixing ratio. Their occurrences are compared with the co-located, retrieved temperatures and related to the temperature thresholds needed for saturation of H2O and/or HNO3 vapor onto PSC particles. Observed daily locations where the major PSC screening criteria are satisfied are validated against PSCs observed with the Stratospheric Aerosol Monitor (SAM) II experiment also on Nimbus 7. Remnants of emissions from PSCs are characterized for O3 and HNO3 following the screening. PSCs may also impart a warm bias in the co-located LIMS temperatures, but by no more than 1-2K at the altitudes of where effects of PSCs are a maximum in the ozone; thus, no PSC screening was applied to the V6 temperatures. Minimum temperatures vary between 187 and 194K and often occur 1 to 2 km above where PSC effects are first identified in the ozone (most often between about 21 and 28 hPa). Those temperature-pressure values are consistent with conditions for the existence of nitric acid trihydrate (NAT) mixtures and to a lesser extent of super-cooled ternary solution (STS) droplets. A local, temporary uptake of HNO3 vapor of order 1-3 ppbv is indicated during mid-January for the 550K surface. Seven-month time series of the distributions of LIMS O3 and HNO3 are shown based on their gridded Level 3 data following the PSC screening. Zonal coefficients of both species are essentially free of effects from PSCs on the 550K surface, based on their average values along PV contours and in terms of equivalent latitude. Remnants of PSCs are still present in O3 on the 450K surface during mid- January. It is judged that the LIMS Level 3 data are of good quality for analyzing the larger-scale, stratospheric chemistry and transport processes during the Arctic winter of 1978- 1979.

Remsberg, Ellis↗
DOE OSTI2024

Soil microbiome interventions for carbon sequestration and climate mitigation

Mitigating climate change in soil ecosystems involves complex plant and microbial processes regulating carbon pools and flows. Here, we advocate for the use of soil microbiome interventions to help increase soil carbon stocks and curb greenhouse gas emissions from managed soils. Direct interventions include the introduction of microbial strains, consortia, phage, and soil transplants, whereas indirect interventions include managing soil conditions or additives to modulate community composition or its activities. Approaches to increase soil carbon stocks using microbially catalyzed processes include increasing carbon inputs from plants, promoting soil organic matter (SOM) formation, and reducing SOM turnover and production of diverse greenhouse gases. Marginal or degraded soils may provide the greatest opportunities for enhancing global soil carbon stocks. Among the many knowledge gaps in this field, crucial gaps include the processes influencing the transformation of plant-derived soil carbon inputs into SOM and the identity of the microbes and microbial activities impacting this transformation. As a critical step forward, we encourage broadening the current widespread screening of potentially beneficial soil microorganisms to encompass functions relevant to stimulating soil carbon stocks. Moreover, in developing these interventions, we must consider the potential ecological ramifications and uncertainties, such as incurred by the widespread introduction of homogenous inoculants and consortia, and the need for site-specificity given the extreme variation among soil habitats. Incentivization and implementation at large spatial scales could effectively harness increases in soil carbon stocks, helping to mitigate the impacts of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1979

Investigation of Proposed Process Sequence for the Array Automated Assembly Task, Phase 2

The technological readiness of the proposed process sequence was reviewed. Process steps evaluated include: (1) plasma etching to establish a standard surface; (2) forming junctions by diffusion from an N-type polymeric spray-on source; (3) forming a p+ back contact by firing a screen printed aluminum paste; (4) forming screen printed front contacts after cleaning the back aluminum and removing the diffusion oxide; (5) cleaning the junction by a laser scribe operation; (6) forming an antireflection coating by baking a polymeric spray-on film; (7) ultrasonically tin padding the cells; and (8) assembling cell strings into solar circuits using ethylene vinyl acetate as an encapsulant and laminating medium.

Mardesich, N.↗
NASA NTRS1989

Intersubband Auger recombination and population inversion in quantum-well subbands

The intersubband-Auger-recombination time of electrons under population-inversion conditions in a single quantum well is calculated by taking into account momentum- and energy-conservation rules, and by employing Fermi-Dirac statistics. The screened matrix element of the electron-electron interaction and the overlap integral are calculated for an infinitely deep quantum well. The results are in a good agreement with published experimental data. As a major nonradiative process, the Auger recombination is related to threshold current of infrared lasers based on intersubband transitions in quantum-well structures. The realization of these devices and other limitations to achieving population inversion are discussed. In view of the results, development of these lasers for emission wavelengths corresponding to energies below the LO-phonon energy seems feasible.

Borenstain, S.↗
NASA NTRS2011

Possible Responsibility of Silicone Materials for Degradation of the CO2 Removal System in the International Space Station

From data concerning the degradation of the CO2 removal system in the International Space Station (ISS) two important features were apparent: (1) The atmosphere within the International Space Station (ISS) contained many organic compounds including alcohols, halocarbons, aldehydes, esters, and ketones, inter alia. Various cyclosiloxanes Dn, hexamethylcyclotrisiloxane (D3) and its higher homologs (D4) and (D5) are also present presumably due to offgassing. (2) Screens within the zeolite-containing canisters, used for the removal of CO2, exhibited partial clogging due to zeolitic fragments (dust) along with "sticky" residues, that in toto significantly reduced the efficiency of the CO2 removal process. Samples of the ISS fresh zeolite, used zeolite, filter clogging zeolite particles and residual polymeric materials were examined using, inter alia, NMR, EM and HRSEM. These data were compared to equivalent samples obtained prior and subsequent to Dn polymerization experiments performed in our laboratories using the clean ISS zeolite samples as catalyst. Polysiloxane materials produced were essentially equivalent in the two cases and the EM images demonstrate a remarkable similarity between the ISS filter zeolite samples and the post-polymerization zeolite material from our experiments. In this regard even the changes in the Al/Si ratio from the virgin zeolite material to the filter samples and the post-polymerization laboratory samples samples is noteworthy. This research was supported by a contract from the Boeing Company

Baeza, Mario↗
NASA NTRS2011

Method for Impeding Degradation of Porous Silicon Structures

This invention relates to surface modification of porosified silicon (pSi) structures with poly(alkylene) glycols for the purpose of controlled degradation of the silicon matrix and tailored release of encapsulated substances for biomedical applications. The pSi structures are currently used in diverse biomedical applications including bio-molecular screening, optical bio-sensoring, and drug delivery by means of injectable/orally administered carriers and implantable devices. The size of the pores and the surface chemistry of the pSi structure can be controlled during the microfabrication process and thereafter. A fine regulation of the degradation kinetics of mesoporous silicon structures is of fundamental importance. Polyethylene glycols (PEGs) represent the major category of surface modifying agents used in classical drug delivery systems and in pharmaceutical dosage forms. PEGylation enables avoidance of RES uptake, thus prolonging circulation time of intravenously injectable nanovectors. PEG molecules demonstrate little toxicity and immunogenicity, and are cleared from the body through the urine (molecular weight, MW less than 30 kDa) or in the feces (MW greater than 30kDa). The invention focuses on the possibility of finely tuning the degradation kinetics of the pSi nanovectors and other structures through surface conjugation of PEGs with various backbone lengths/MWs. To prove the concept, pSi nanovectors were covalently conjugated to seven PEGs with MW from 245 to 5,000 Da and their degradation kinetics in physiologically relevant media (phosphate buffer saline, PBS pH7.4, and fetal bovine serum) was assessed by the elemental analysis of the Si using inductive coupled plasma atomic emission spectroscopy (ICP-AES). The conjugation of the PEG with lowest MW to the nanovectors surface did not induce any change in the degradation kinetics in serum, but inhibited degradation and consequently the release of orthosilicic acid into buffer. When PEGs with the longer chains were evaluated, Si mass loss from the nanovectors was slowed down, and the PEGylated structures were almost fully degraded within 18 24 hours in serum and within 48 hours in PBS. The most dramatic effect was observed for high MW PEGs 3,400 and 5,000 Da, which prominently inhibited the degradation of the systems, with complete degradation achieved only after four days. For these PEGs, during the early stages of the degradation, there was a lag period of little or no Si mass loss from the nanovector. The obtained profiles were in agreement with the erosion of the nanovector surface as observed by scanning electron microscopy.

Vilentchouk, Biana Godin↗
NASA NTRS2016

Analysis of Satellite and Airborne Imagery for Detection of Water Hyacinth and Other Invasive Floating Macrophytes and Tracking of Aquatic Weed Control Efficacy

Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Agriculture↗
NASA NTRS2017

Using Satellite Remote Sensing to Map Changes in Aquatic Invasive Plant Cover in the Sacramento-San Joaquin River Delta of California

Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed a 80% overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Map Changes↗
DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Harvesting Energy from Wastewater by Converting Sewage

This project aims were to develop and demonstrate a scalable, integrated process to convert sewage sludge into renewable natural gas (RNG), enabling wastewater treatment plants (WWTPs) to become net energy producers. The system proposal integrates autothermal hydrothermal liquefaction (AT-HTL), supercritical salt precipitation (SCSP), and hydrothermal gasification (HTG), collectively forming the Supercritical Sludge-to-Gas (SC-S2G) platform. Initially, batch hydrothermal liquefaction reactions were used to screen sewage sludge using AT-HTL (later termed RI-HTL) conversion to biocrude, aqueous and char phases compared to hydrothermal liquefaction (HTL). Significant improvement in biocrude yield using peroxide addition at O:C ratio of 0.05 and under conditions of 300°C for 10 minutes gave 57% biocrude yield and 85% fluid carbon yield (biocrude plus aqueous), while minimizing the loss of carbon to char solids (~7%). Hence, RI-HTL was shown to be effective for conversion of real sewage sludge. The corrosion of the alloy reactor tubes or vessels is an important factor when developing a process that includes an oxidant and a chemically complex feed like sewage sludge. We investigated the corrosion rates on metal alloys at 350°C for 240 hours. Corrosion rates of 0.21 and 0.26 mpy for 304L and 316L stainless steel were measured respectively. The corrosion information obtained in this investigation was utilized by PNNL for design, materials sourcing and construction of the pilot scale continuous flow system.

09 BIOMASS FUELS↗
DOE OSTI2026

The Influence of Shielding Gas on the Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Wire-arc additive manufacturing (WAAM) enables building large near-net-shaped parts using fast deposition rates and is attractive due to the potential cost and schedule savings. Haynes® 282® is a Ni-based superalloy with wide application in advanced power generation systems for its superior high temperature mechanical properties. High-quality WAAM H282 parts are achieved through careful process optimization, hence, we have focused on systematically characterizing the processing-structure-properties relationships over a wide range of wire-feed and travel speeds using a standard Ar30He shielding gas. Here the influence of adding 0.25-3% of H2 and CO2 to Ar-30He standard on our findings is examined. Multi-bead tracks were used to screen 20+ gas combinations to examine impact on wettability, porosity, oxidation, and grain structures. Improved multi-tracks are observed for gases with up to 1% H2 and 0.25% CO2. WAAM H282 builds within this range are examined to reveal differences in microstructure as evaluated with CT, SEM-EDS, and EBSD.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ultrafast Dynamics of Excitonic Complexes in Electrolyte-Gated Monolayer MoS 2

Understanding and controlling ultrafast excitons and trion dynamics in monolayer transition metal dichalcogenides (TMDs) is critical for optoelectronic and photonic applications. These dynamics depend strongly on carrier density, but most studies use fluence-dependence to modulate electron-hole populations rather than direct electrostatic gating that is more relevant to optoelectronic devices. We utilize electrolyte gating to tune the ground-state carrier density of monolayer MoS 2 and probe excitonic dynamics using transient absorption spectroscopy, thereby modifying absorption through bandgap renormalization, screening, phase-space filling, and exciton-trion crossover. Spectral deconvolution reveals distinct but coupled exciton and trion dynamics. Excitons form independently of voltage but relax faster with increasing carrier density, consistent with Auger-like processes, while trions decay more rapidly through multiple channels. At higher voltages, trion relaxation shifts from a sub-picosecond cooling to slower trapping-assisted processes. Furthermore, our results provide missing insights into the interplay between excitons and trions in monolayer MoS 2 , relevant for TMD-based optoelectronics.

chalcogenides↗
DOE OSTI2020

In vitro prototyping and rapid optimization of biosynthetic enzymes for cell design

The design and optimization of biosynthetic pathways for industrially relevant, non-model organisms is challenging due to transformation idiosyncrasies, reduced numbers of validated genetic parts and a lack of high-throughput workflows. Here we describe a platform for in vitro prototyping and rapid optimization of biosynthetic enzymes (iPROBE) to accelerate this process. In iPROBE, cell lysates are enriched with biosynthetic enzymes by cell-free protein synthesis and then metabolic pathways are assembled in a mix-and-match fashion to assess pathway performance. We demonstrate iPROBE by screening 54 different cell-free pathways for 3-hydroxybutyrate production and optimizing a six-step butanol pathway across 205 permutations using data-driven design. Observing a strong correlation (r = 0.79) between cell-free and cellular performance, we then scaled up our highest-performing pathway, which improved in vivo 3-HB production in Clostridium by 20-fold to 14.63 ± 0.48 g l -1 . Finally, we expect iPROBE to accelerate design–build–test cycles for industrial biotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Groundwater level elevation and temperature data, Oct 2018-Dec 2021, Slate River Floodplain, Crested Butte, CO

This data package includes a time series of water level and temperature measurements from October 2018 to December 2021 in groundwater and surface water from the Slate River floodplain outside Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data were recorded by pressure transducers were installed in four types of piezometers: 1) a network of gravel bed ("GB") drive-point piezometers with a 6-inch screen interval installed all at ~330 cm below ground surface. 2) a network of piezometers screened across the water table, used to measure evapotranspiration ("ET") using the White method. Each of these piezometers is screened along almost its entire length.3) a suite nested piezometers used the measure the vertical hydraulic gradient ("VHG") across the fines-cobble interface. Each of these piezometers uses a 6-inch screen length.4) a group of piezometers scattered across the boundaries of the floodplain, used to monitor boundary conditions ("BC") flowing into and out of the floodplain. With the exception of "SR-BD-WT", each of these piezometers is screened along its entire length. Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 11 "*data.csv" files, one for each piezometer type for each calendar year. Because piezometers have been added over time, not every sensor has data dating back to Oct 2018. Each "*data.csv" file has a corresponding "*_InstallationMethods.csv" file that describes the location, elevation, screen depth, sediment type and sensor metadata for each piezometer and pressure transducer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Lunar regolith fines - A source of hydrogen

The theoretical evaluation of the lunar regolith fines as a primary source of hydrogen reveals that a minimum order of magnitude increase in hydrogen content is possible in beneficiated fines because both particle size and particle shape play a significant role in the relationship of volume percent of surface coating to grain size. The lunar regolith fines meet the basic requirement for beneficiation because a major portion (minimum two-thirds) of the hydrogen occurs in the less than 20-micron-size fraction, a relatively small part of the fines. Beneficiation should be accomplished by a combination of vibratory screening followed by cyclone and/or possibly electrostatic separation. Early exploitation of the lunar regolith fines for hydrogen probably will be limited to hydrogen obtained as a by-product or co-product from the mining and processing for other elements or materials because a minimum of about 13,600 tons to about 19,600 tons of 100 ppm hydrogen-bearing lunar regolith fines will have to be processed with about 3,100 tons to about 4,500 tons, respectively, of concentrate heated to supply 1 ton of hydrogen, yielding a recovery of about 74 percent to about 51 percent respectively, of the hydrogen.

Carter, J. L.↗
NASA NTRS1991

Radiation sensitive area detection device and method

A radiation sensitive area detection device for use in conjunction with an X ray, ultraviolet or other radiation source is provided which comprises a phosphor containing film which releases a stored diffraction pattern image in response to incoming light or other electromagnetic wave. A light source such as a helium-neon laser, an optical fiber capable of directing light from the laser source onto the phosphor film and also capable of channelling the fluoresced light from the phosphor film to an integrating sphere which directs the light to a signal processing means including a light receiving means such as a photomultiplier tube. The signal processing means allows translation of the fluoresced light in order to detect the original pattern caused by the diffraction of the radiation by the original sample. The optical fiber is retained directly in front of the phosphor screen by a thin metal holder which moves up and down across the phosphor screen and which features a replaceable pinhole which allows easy adjustment of the resolution of the light projected onto the phosphor film. The device produces near real time images with high spatial resolution and without the distortion that accompanies prior art devices employing photomultiplier tubes. A method is also provided for carrying out radiation area detection using the device of the invention.

Carter, Daniel C.↗