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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A new μ -high energy resolution fluorescence detection microprobe imaging spectrometer at the Stanford Synchrotron Radiation Lightsource beamline 6-2

In this report we describe a new synchrotron X-ray Fluorescence (XRF) imaging instrument with an integrated High Energy Fluorescence Detection X-ray Absorption Spectroscopy (HERFD-XAS) spectrometer at the Stanford Synchrotron Radiation Lightsource at beamline 6-2. The X-ray beam size on the sample can be defined via a range of pinhole apertures or focusing optics. XRF imaging is performed using a continuous rapid scan system with sample stages covering a travel range of 250 × 200 mm 2 , allowing for multiple samples and/or large samples to be mounted. The HERFD spectrometer is a Johann-type with seven spherically bent 100 mm diameter crystals arranged on intersecting Rowland circles of 1 m diameter with a total solid angle of about 0.44% of 4π sr. A wide range of emission lines can be studied with the available Bragg angle range of ~64.5°–82.6°. With this instrument, elements in a sample can be rapidly mapped via XRF and then selected features targeted for HERFD-XAS analysis. Furthermore, utilizing the higher spectral resolution of HERFD for XRF imaging provides better separation of interfering emission lines, and it can be used to select a much narrower emission bandwidth, resulting in increased image contrast for imaging specific element species, i.e., sparse excitation energy XAS imaging. This combination of features and characteristics provides a highly adaptable and valuable tool in the study of a wide range of materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Comparative transcriptomics between Synechococcus PCC 7942 and Synechocystis PCC 6803 provide insights into mechanisms of adaptation to stress.

Background: Synechococcus sp. PCC 7942 and Synechocystis sp. PCC 6803 are model cyanobacteria from which the metabolism and adaptive responses of other cyanobacteria are inferred. Here we report the gene expression response of these two strains to a variety of nutrient and environmental stresses of varying duration, using transcriptomics. Our data comprise both stranded and 5' enriched libraries in order to elucidate many aspects of the transcriptome. Results: Both organisms were exposed to stress conditions due to nutrient deficiency (inorganic carbon) or change of environmental conditions (salinity, temperature, pH, light) sampled at 1 and 24 hours after the application of stress. The transcriptome profile of each strain revealed similarities and differences in gene expression for photosynthetic and respiratory electron transport chains and carbon fixation. Transcriptome profiles also helped us improve the structural annotation of the genome and identify possible missed genes (including anti-sense) and determine transcriptional units (operons). Finally, we predicted association of proteins of unknown function biochemical pathways by associating them to well-characterized ones based on their transcript levels correlation. Conclusions: Overall, this study results an informative annotation of those species and the comparative analysis of the response of the two organisms revealed similarities but also significant changes in the way they respond to external stress and the duration of the response

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A miniaturized feedstocks-to-fuels pipeline for screening the efficiency of deconstruction and microbial conversion of lignocellulosic biomass

Sustainably grown biomass is a promising alternative to produce fuels and chemicals and reduce the dependency on fossil energy sources. However, the efficient conversion of lignocellulosic biomass into biofuels and bioproducts often requires extensive testing of components and reaction conditions used in the pretreatment, saccharification, and bioconversion steps. This restriction can result in a significant and unwieldy number of combinations of biomass types, solvents, microbial strains, and operational parameters that need to be characterized, turning these efforts into a daunting and time-consuming task. Here we developed a high-throughput feedstocks-to-fuels screening platform to address these challenges. The result is a miniaturized semi-automated platform that leverages the capabilities of a solid handling robot, a liquid handling robot, analytical instruments, and a centralized data repository, adapted to operate as an ionic-liquid-based biomass conversion pipeline. The pipeline was tested by using sorghum as feedstock, the biocompatible ionic liquid cholinium phosphate as pretreatment solvent, a “one-pot” process configuration that does not require ionic liquid removal after pretreatment, and an engineered strain of the yeast Rhodosporidium toruloides that produces the jet-fuel precursor bisabolene as a conversion microbe. By the simultaneous processing of 48 samples, we show that this configuration and reaction conditions result in sugar yields (~70%) and bisabolene titers (~1500 mg/L) that are comparable to the efficiencies observed at larger scales but require only a fraction of the time. We expect that this Feedstocks-to-Fuels pipeline will become an effective tool to screen thousands of bioenergy crop and feedstock samples and assist process optimization efforts and the development of predictive deconstruction approaches.

09 BIOMASS FUELS↗
NASA NTRS2007

Investigation of Liner Characteristics in the NASA Langley Curved Duct Test Rig

The Curved Duct Test Rig (CDTR), which is designed to investigate propagation of sound in a duct with flow, has been developed at NASA Langley Research Center. The duct incorporates an adaptive control system to generate a tone in the duct at a specific frequency with a target Sound Pressure Level and a target mode shape. The size of the duct, the ability to isolate higher order modes, and the ability to modify the duct configuration make this rig unique among experimental duct acoustics facilities. An experiment is described in which the facility performance is evaluated by measuring the sound attenuation by a sample duct liner. The liner sample comprises one wall of the liner test section. Sound in tones from 500 to 2400 Hz, with modes that are parallel to the liner surface of order 0 to 5, and that are normal to the liner surface of order 0 to 2, can be generated incident on the liner test section. Tests are performed in which sound is generated without axial flow in the duct and with flow at a Mach number of 0.275. The attenuation of the liner is determined by comparing the sound power in a hard wall section downstream of the liner test section to the sound power in a hard wall section upstream of the liner test section. These experimentally determined attenuations are compared to numerically determined attenuations calculated by means of a finite element analysis code. The code incorporates liner impedance values educed from measured data from the NASA Langley Grazing Incidence Tube, a test rig that is used for investigating liner performance with flow and with (0,0) mode incident grazing. The analytical and experimental results compare favorably, indicating the validity of the finite element method and demonstrating that finite element prediction tools can be used together with experiment to characterize the liner attenuation.

Gerhold, Carl H.↗
DOE OSTI2017

Spectral X-ray Radiography for Safeguards at Nuclear Fuel Fabrication Facilities: A Feasibility Study

The methods currently used by the International Atomic Energy Agency to account for nuclear materials at fuel fabrication facilities are time consuming and require in-field chemistry and operation by experts. Spectral X-ray radiography, along with advanced inverse algorithms, is an alternative inspection that could be completed noninvasively, without any in-field chemistry, with inspections of tens of seconds. The proposed inspection system and algorithms are presented here. The inverse algorithm uses total variation regularization and adaptive regularization parameter selection with the unbiased predictive risk estimator. Performance of the system is quantified with simulated X-ray inspection data and sensitivity of the output is tested against various inspection system instabilities. Material quantification from a fully-characterized inspection system is shown to be very accurate, with biases on nuclear material estimations of < 0.02%. It is shown that the results are sensitive to variations in the fuel powder sample density and detector pixel gain, which increase biases to 1%. Options to mitigate these inaccuracies are discussed.

Gilbert, Andrew J.↗
DOE OSTI2017

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Comparison of Oxidation Performance of Graphite Samples in TGA versus Vertical Furnace

Oxidation influences the working life of nuclear graphite and can impact function during or after air (or steam) ingress accidents. Temperature, gas flow, oxygen content, and dimensional constraints at the microstructural and macrostructural levels can substantially influence the oxidation rate. The nature of these constraints must be considered when attempting to extrapolate performance from experimental results to service applications, but must also be evaluated in order to compare data among disparate experimental systems. This work compares oxidation test performance from a vertical furnace system (functioning as described by ASTM D7542) with tests using a thermogravimetric analyzer (TGA) adapted to operate in an analogous manner.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Automated Nanoflow Two-Dimensional Reversed-Phase Liquid Chromatography System Enables In-Depth Proteome and Phosphoproteome Profiling of Nanoscale Samples

Two-dimensional reversed-phase liquid chromatography (2D RPLC) separations have enabled near-comprehensive proteome profiling of biological systems. However, large samples containing milligram amounts of protein are usually required due to the significant sample losses incurred during offline fractionation. The large sample requirements preclude the application of 2D RPLC to biological systems having sample availability in the nanogram to low-microgram range. To achieve in-depth proteomic studies of trace samples, we have developed an automated nanoflow 2D RPLC platform in which the first dimension high-pH fractionation was performed at 300 nL/min on a 75-µm i.d. capillary column.Each fraction was then fully transferred to a second-dimension nanoLC separation using an autosampler equipped with a custom-machined syringe. In addition to optimizing fractionation conditions, we found that the use of a plastic 96-well plate as collection device and the adding of n-Dodecyl ß-D-Maltoside (0.01%) in the collection buffer can significantly improve sample recovery. We have demonstrated the nanoflow 2D RPLC platform can achieve confident identifications of ~37,000–69,000 unique peptides, corresponding to ~5300–6900 protein groups using only 100 to 1000 ng of HeLa tryptic digest. Furthermore, by integrating phosphopeptide enrichment, the platform can identify as many as ~20,000 phosphopeptides from 100 µg of MCF7 protein digest. Because this platform is assembled from commercially available components, our approach can be readily adapted in other proteomics laboratories.

Mass spectrometry, multidimensional separations, n↗
DOE OSTI2015

PLANETS AROUND LOW-MASS STARS (PALMS). IV. THE OUTER ARCHITECTURE OF M DWARF PLANETARY SYSTEMS

We present results from a high-contrast adaptive optics imaging search for giant planets and brown dwarfs (≳1 M {sub Jup}) around 122 newly identified nearby (≲40 pc) young M dwarfs. Half of our targets are younger than 135 Myr and 90% are younger than the Hyades (620 Myr). After removing 44 close stellar binaries (implying a stellar companion fraction of >35.4% ± 4.3% within 100 AU), 27 of which are new or spatially resolved for the first time, our remaining sample of 78 single M dwarfs makes this the largest imaging search for planets around young low-mass stars (0.1-0.6 M {sub ☉}) to date. Our H- and K-band coronagraphic observations with Keck/NIRC2 and Subaru/HiCIAO achieve typical contrasts of 12-14 mag and 9-13 mag at 1'', respectively, which correspond to limiting planet masses of 0.5-10 M {sub Jup} at 5-33 AU for 85% of our sample. We discovered four young brown dwarf companions: 1RXS J235133.3+312720 B (32 ± 6 M {sub Jup}; L0{sub −1}{sup +2}; 120 ± 20 AU), GJ 3629 B (64{sub −23}{sup +30} M {sub Jup}; M7.5 ± 0.5; 6.5 ± 0.5 AU), 1RXS J034231.8+121622 B (35 ± 8 M {sub Jup}; L0 ± 1; 19.8 ± 0.9 AU), and 2MASS J15594729+4403595 B (43 ± 9 M {sub Jup}; M8.0 ± 0.5; 190 ± 20 AU). Over 150 candidate planets were identified; we obtained follow-up imaging for 56% of these but all are consistent with background stars. Our null detection of planets enables strong statistical constraints on the occurrence rate of long-period giant planets around single M dwarfs. We infer an upper limit (at the 95% confidence level) of 10.3% and 16.0% for 1-13 M {sub Jup} planets between 10-100 AU for hot-start and cold-start (Fortney) evolutionary models, respectively. Fewer than 6.0% (9.9%) of M dwarfs harbor massive gas giants in the 5-13 M {sub Jup} range like those orbiting HR 8799 and β Pictoris between 10-100 AU for a hot-start (cold-start) formation scenario. The frequency of brown dwarf (13-75 M {sub Jup}) companions to single M dwarfs between 10-100 AU is 2.8{sub −1.5}{sup +2.4}%. Altogether we find that giant planets, especially massive ones, are rare in the outskirts of M dwarf planetary systems. Although the first directly imaged planets were found around massive stars, there is currently no statistical evidence for a trend of giant planet frequency with stellar host mass at large separations as predicted by the disk instability model of giant planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

GPU-Accelerated Analytic Simulation of Sparse Ionization Signal Formation in Pixelated Projection Detector

This paper presents a GPU-accelerated simulation package, TRED, for next-generation neutrino detectors with pixelated charge readout, leveraging community-driven software ecosystems to ensure adaptability and extensibility. We introduce two generic contributions: (i) an effective-charge representation based on Gaussian quadrature rules, in which the linear- interpolation factors for the field response inside each voxel are absorbed into the effective charge, and (ii) a sparse, block- binned tensor representation that enables efficient FFT-based computation of induced signals on readout electrodes for sparsely activated detector volumes. The former captures structure inside a voxel without dense sampling, while the latter achieves low memory usage and scalable runtime, as demonstrated in bench- mark studies. The underlying data representation is applicable to large-scale detectors and to other computational problems involving sparse activity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

A novel methodology for 3D deformable dosimetry

Purpose: Interfraction and intrafraction variation in anatomic structures is a significant challenge in contemporary radiotherapy. The objective of this work is to develop a novel tool for deformable structure dosimetry, using a tissue-equivalent deformable gel dosimeter that can reproducibly simulate targets subject to deformation. This will enable direct measurement of integrated doses delivered in different deformation states, and the verification of dose deforming algorithms. Methods: A modified version of the nPAG polymer gel has been used as a deformable 3D dosimeter and phantom to investigate doses delivered to deforming tissue-equivalent geometry. The deformable gel (DEFGEL) dosimeter/phantom is comprised of polymer gel in a latex membrane, moulded (in this case) into a cylindrical geometry, and deformed with an acrylic compressor. Fifteen aluminium fiducial markers (FM) were implanted into DEFGEL phantoms and the reproducibility of deformation was determined via multiple computed tomography (CT) scans in deformed and nondeformed states before and after multiple (up to 150) deformations. Dose was delivered to the DEFGEL phantom in three arrangements: (i) without deformation, (ii) with deformation, and (iii) cumulative exposures with and without deformation, i.e., dose integration. Irradiations included both square field and a stereotactic multiple dynamic arc treatment adapted from a patient plan. Doses delivered to the DEFGEL phantom were read out using cone beam optical CT. Results: Reproducibility was verified by observation of interscan shifts of FM locations (as determined via CT), measured from an absolute reference point and in terms of inter-FM distance. The majority (76%) of points exhibited zero shift, with others shifting by one pixel size consistent with setup error as confirmed with a control sample. Comparison of dose profiles and 2D isodose distributions from the three arrangements illustrated complex spatial redistribution of dose in all three dimensions occurring as a result of the change in shape of the target between irradiations, even for a relatively simple deformation. Discrepancies of up to 30% of the maximum dose were evident from dose difference maps for three orthogonal planes taken through the isocenter of a stereotactic field. Conclusions: This paper describes the first use of a tissue-equivalent, 3D dose-integrating deformable phantom that yields integrated or redistributed dosimetric information. The proposed methodology readily yields three-dimensional (3D) dosimetric data from radiation delivery to the DEFGEL phantom in deformed and undeformed states. The impacts of deformation on dose distributions were readily seen in the isodose contours and line profiles from the three arrangements. It is demonstrated that the system is potentially capable of reproducibly emulating the physical deformation of an organ, and therefore can be used to evaluate absorbed doses to deformable targets and organs at risk in three dimensions and to validate deformation algorithms applied to dose distributions.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Potential Risks Associated with Short-Term Hydrogen Storage in Methane Reservoirs

Hydrogen (H2) has been identified as a flexible energy carrier with zero emissions. It is possible to utilize H2 by storing Hyblend, or H2 blended with CH4, in existing natural gas infrastructure. However, the compatibility of adapting the current CH4 storage strategies to include H2 injection has not been fully demonstrated. It is essential that we understand the impact of H2 gas on the naturally occurring microbial community of subsurface storage reservoirs before deploying large-scale H2-CH4 storage. We designed a series of experiments that allowed us to identify potential challenges of HyBlend Storage in existing methane reservoirs (Figure 1). First, we characterized two field fluid samples from a methane reservoir located in Western United States. Next, we used these samples to complete a series of short-term reactor experiments at reservoir conditions for a natural gas (100% CH4) and HyBlend (80% CH4/20% H2) storage environment.

geomicrobiology↗
NASA NTRS1972

Effect of a 30-day isolation stress on calcium, phosphorus and other excretory products in an unrestrained chimpanzee.

An unrestrained chimpanzee was studied in an isolation chamber and in his home cage environment. The study consisted of 49 urine collection days (14 days pre-, 5 days post- and 30 days of isolation), and then of 10 days in the home cage. Dietary intake, urine and fecal data were obtained. The effect of isolation on various excretory parameters was studied. Urine samples were analyzed for volume, osmolarity, creatinine, creatine, urea-N, 17-hydroxy corticosteroids, VMA, calcium and inorganic phosphorus. One way analyses of variance performed on the urinary excretion parameters showed all except creatinine excretion to vary significantly during periods of the study. The changes observed in calcium and phosphorus were highly significant. The data suggests that the calcium to phosphorus excretion ratio might serve as a physiological stress indicator of Selye's adaptation syndrome (period of resistance).

Sabbot, I. M.↗
NASA NTRS2025

A Preliminary Study on the Feasibility of Large Language Models for Detecting Micro-Behaviors Among Team Members in Space Missions

Large-language models (LLMs) have been recently used for spoken language understanding (SLU) to infer meaning and semantics from speech in tasks such as speaker intent and sentiment classification. Due to being trained on large amounts of data, and their ability to understand context and relationships between words, LLMs are competent, enabling them to generalize across tasks without requiring many task-specific training samples. This research examines the feasibility of few-shot learning in LLMs for detecting subtle, brief, and possibly unconscious interactions between team members, called ``micro-behaviors," and provides insights into the appropriate design of LLMs for this task. Our data came from 5 teams participating in a 45-day mission at the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA). More specifically we used data collected from team interaction battery (TIB) tasks teams performed five times in-mission which comprise an average 1.5 hours of conversation data per day. Micro-behaviors were coded according to an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). We explore the ability of LLMs to detect the presence and intensity of micro-behaviors. We examine employing and fine-tuning readily available LLMs (i.e., RoBERTa, DistilBERT), as well as prompting state-of-the-art sequence classification models (i.e., Llama-2, Llama-3). In a total of 13,058 conversational turns (17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls), we compute the macro F1-score of the 3-way micro-behavior classification task (i.e., classifying among uplifting, discouraging, and neutral; 33% chance). Results indicate that the RoBERTa model achieves a F1-score of 36.2% (uplift: 43.3% precision (P), 15.1% recall (R); discourage: 20% P, 0.5% R). These results significantly improve when we augment the data via paraphrasing in the RoBERTa model, reaching a 41.2% macro F1-score (uplift: 37.7% P, 86.3% R; discourage: 3.5% P, 1.8% R). Finally, the Llama-2 model with 3-shot prompting yields 38% macro F1-score (uplift: 28.7% P, 20% R; discourage: 7.2% P, 18% R), which is slightly better compared to the RoBERTa model without data augmentation, highlighting the effectiveness of sequence classification models in detecting minority classes with a small sample size. Findings indicate that LLMs hold potential to detect subtle behaviors in conversations, which could be valuable in assessing team behavior in space exploration missions. Future studies will evaluate the performance of different LLM prompting strategies or fine-tuning methods.

Ankush Raut↗
NASA NTRS2011

Auto-Gopher: A Wire-Line Rotary-Hammer Ultrasonic Drill

Developing technologies that would enable NASA to sample rock, soil, and ice by coring, drilling or abrading at a significant depth is of great importance for a large number of in-situ exploration missions as well as for earth applications. Proven techniques to sample Mars subsurface will be critical for future NASA astrobiology missions that will search for records of past and present life on the planet, as well as, the search for water and other resources. A deep corer, called Auto-Gopher, is currently being developed as a joint effort of the JPL's NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher is a wire-line rotary-hammer drill that combines rock breaking by hammering using an ultrasonic actuator and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) that has been developed as an adaptable tool for many of drilling and coring applications. The USDC uses an intermediate free-flying mass to transform the high frequency vibrations of the horn tip into a sonic hammering of a drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher. The lessons learned from testing the ice gopher were implemented into the design of the Auto-Gopher by inducing a rotary motion onto the fluted coring bit. A wire-line version of such a system would allow penetration of significant depth without a large increase in mass. A laboratory version of the corer was developed in the NDEAA lab to determine the design and drive parameters of the integrated system. The design configuration lab version of the design and fabrication and preliminary testing results are presented in this paper

life dectection↗
DOE OSTI2013

STEPS: A Grid Search Methodology for Optimized Peptide Identification Filtering of MS/MS Database Search Results

For bottom-up proteomics there are a wide variety of database searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection - referred to as STEPS - utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.

Environmental Molecular Sciences Laboratory↗