Search NASA⌕ Search

SEARCH · Search NASA

Results for “sample update”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Current Status on Radiation Modeling for the Hayabusa Re-entry

On June 13, 2010 the Japanese Hayabusa capsule performed its reentry into the Earths atmosphere over Australia after a seven year journey to the asteroid Itokawa. The reentry was studied by numerous imaging and spectroscopic instruments onboard NASA's DC-8 Airborne Laboratory and from three sites on the ground, in order to measure surface and plasma radiation generated by the Hayabusa Sample Return Capsule (SRC). Post flight, the flow solutions were recomputed to include the whole flow field around the capsule at 11 points along the reentry trajectory using updated trajectory information. Again, material response was taken into account to obtain most reliable surface temperature information. These data will be used to compute thermal radiation of the glowing heat shield and plasma radiation by the shock/post-shock layer system to support analysis of the experimental observation data. For this purpose, lines of sight data are being extracted from the flow field volume grids and plasma radiation will be computed using NEQAIR [4] which is a line-by-line spectroscopic code with one-dimensional transport of radiation intensity. The procedures being used were already successfully applied to the analysis of the observation of the Stardust reentry [5].

Winter, Michael W.↗
DOE OSTI2023

SALT2 versus SALT3: updated model surfaces and their impacts on type Ia supernova cosmology

ABSTRACT For the past decade, SALT2 has been the most common model used to fit Type Ia supernova (SN Ia) light curves for dark energy analyses. Recently, the SALT3 model was released, which upgraded a number of model features but has not yet been used for measurements of dark energy. Here, we evaluate the impact of switching from SALT2 to SALT3 for a SN cosmology analysis. We train SALT2 and SALT3 on an identical training sample of 1083 well-calibrated Type Ia supernovae, ensuring that any differences found come from the underlying model framework. We publicly release the results of this training (the SALT ‘surfaces’). We then run a cosmology analysis on the public Dark Energy Survey 3-Yr Supernova data sample (DES-SN3YR), and on realistic simulations of those data. We provide the first estimate of the SN + CMB systematic uncertainty arising from the choice of SALT model framework (i.e. SALT2 versus SALT3), Δw = + 0.001 ± 0.005 – a negligible effect at the current level of dark energy analyses. We also find that the updated surfaces are less sensitive to photometric calibration uncertainties than previous SALT2 surfaces, with the average spectral energy density dispersion reduced by a factor of two over optical wavelengths. This offers an opportunity to reduce the contribution of calibration errors to SN cosmology uncertainty budgets.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2019

Nasa Glenn Icing Research Tunnel: 2018 Change in Drop-Sizing Equations Due to Change in Cloud Droplet Probe Sample Area

Although there has been no physical change to the cloud drop diameters in the NASA Glenn Icing Research Tunnel (IRT), the IRT cloud calibration team now has an improved understanding of the facility’s drop-sizing instrumentation, which has resulted in a recent change to the drop-sizing equations. Only the calculated values given in the previous calibration report have changed. In 2017, IRT staff found reason to believe that since at least 2014, the sample area for its Cloud Droplet Probe (CDP) (Droplet Measurement Technologies, Inc.) has been closer to 0.289 mm2, rather than the user manual’s suggested value of 0.24 mm2. In September 2017, the probe’s sample area was measured both before and after the probe was realigned, and the end sample area was measured to be 0.248 mm2. Following the probe’s realignment, drop size measurements were made in the IRT using the CDP as well as optical array probes OAP–230X and OAP–230Y (Particle Measurement Systems, Inc.). These measurements suggested that 0.289 mm2 was the more accurate value for historical measurements. When the CDP sample area used for calculations was changed from 0.24 to 0.289 mm2, distributions previously reported to have a median volumetric diameter (MVD) between 30 and 100 μm were instead calculated to have MVD values 10 to 18 percent higher. The analyses that led to these conclusions are reported in this paper, as well as the new drop-sizing equations that have been developed for the corrected measurement values. This report contains updates to drop-sizing data for the IRT’s “normal” operating conditions (MVD < 50 μm) and discusses the effects on the IRT’s “large-drop” conditions (Mod1 nozzles, Pair < 10 psig), but it does not include updates to the drop-sizing equations for those large-drop conditions.

Particle sizing↗
DOE OSTI2022

Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Related sensor data are published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054. This data package was originally published September 2022. It was updated May 2023 (modified files) and November 2024 (new and modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), ions, and benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol (8) readme; (9) methods codes; (10) international generic-sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We thank the United States Forest Service, Washington Department of Natural Resources, Washington Department of Fish and Wildlife, Washington State Parks, Confederated Tribes and Bands of the Yakama Nation, and Cowiche Canyon Conservancy for access to field locations where these samples were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Genelab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

bioinformatics↗
NASA NTRS2016

GeneLab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASAs premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

spaceflight↗
NASA NTRS1978

Economic consequences of improved temperature forecasts: An experiment with the Florida citrus growers (an update of control group results)

The economic experiment, the results obtained to date and the work which still remains to be done are summarized. Specifically, the experiment design is described in detail as are the developed data collection methodology and procedures, sampling plan, data reduction techniques, cost and loss models, establishment of frost severity measures, data obtained from citrus growers, National Weather Service and Federal Crop Insurance Corp. Resulting protection costs and crop losses for the control group sample, extrapolation of results of control group to the Florida citrus industry and the method for normalization of these results to a normal or average frost season so that results may be compared with anticipated similar results from test group measurements are discussed.

Braen, C.↗
DOE OSTI2020

Materials preparation, single-crystal growth, and the phase diagram of the cuprate high-temperature superconductor La 1.6-x Nd 0.4 Sr x CuO 4

One branch of the La-214 family of cuprate superconductors, La 1.6-x Nd 0.4 Sr x CuO 4 (NdLSCO), has been of significant and sustained interest, in large part because it displays the full complexity of the phase diagram for canonical hole-doped, high TC superconductivity, while also displaying relatively low superconducting critical temperatures. The low superconducting TC’s imply that experimentally accessible magnetic fields can suppress the superconductivity to zero temperature. In particular, this has enabled various transport and thermodynamic studies of the T = 0 ground state in Nd-LSCO, free of superconductivity, across the critical doping p* = 0.23 where the pseudogap phase ends. The strong dependence of its superconducting properties on its crystal symmetry has itself motivated careful studies of the Nd-LSCO structural phase diagram. This paper provides a systematic study and summary of the materials preparation and characterization of both single crystal and polycrystalline samples of Nd-LSCO. Single-phase polycrystalline samples with x spanning the range from 0.01 to 0.40 have been synthesized, and large single crystals of La 1.6-x Nd 0.4 Sr x CuO 4 for select x across the region (0.07, 0.12, 0.17, 0.19, 0.225, 0.24, and 0.26) were grown by the optical floating zone method. Furthermore, systematic neutron and X-ray diffraction studies on these samples were performed at both low and room temperatures, 10 K and 300 K, respectively. These studies allowed us to follow the various structural phase transitions and propose an updated structural phase diagram for NdLSCO. In particular, we found that the low-temperature tetragonal (LTT) phase ends at a critical doping p LTT = 0.255±0.005, clearly separated from p*.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

mosartwmpy sample input data; 1980 - 1985

Sample input data spanning the years 1980-1985 for running the `mosartwmpy` water routing and management model: https://github.com/IMMM-SFA/mosartwmpy. More information is available in the README.md. Changelog: v0.0.6: updates reservoir parameters to indicate which reservoirs should follow generic operating rules and which should follow ISTARF data-driven operating rules. v0.0.5: adds supporting files for running the Farmer Agent Based Model of adaptive water demand.

Rexer, Emily↗
DOE OSTI2026

mosartwmpy sample input data; 1980 - 1985

Sample input data spanning the years 1980-1985 for running the `mosartwmpy` water routing and management model: https://github.com/IMMM-SFA/mosartwmpy. More information is available in the README.md. Changelog: v0.0.8: Update with new CAP_MIN reservoir parameter, corresponds with mosartwmpy v1.0.0 v0.0.7: new reservoir files with corrected locations based on an exhaustive review by Dan Broman for the 9505 project; corresponding long term mean demand and flow files updated based on VIC4 simulations using Daymet forcing. v0.0.6: updates reservoir parameters to indicate which reservoirs should follow generic operating rules and which should follow ISTARF data-driven operating rules. v0.0.5: adds supporting files for running the Farmer Agent Based Model of adaptive water demand.

Bracken, Cameron [Pacific Northwest National Labor↗
NASA NTRS2010

The Progress of CDAS

The Chinese Data Acquisition System (CDAS) based on FPGA techniques has been developed in China for the purpose of replacing the traditional analog baseband converter. CDAS is a high speed data acquisition and processing system with 1024 Msps sample rate for 512M bandwidth input and up to 16 channels (both USB and LSB) output with VSI interface compatible. The instrument is a flexible environment which can be updated easily. In this paper, the construction, the performance, the experiment results, and the future plans of CDAS will be reported.

Zhu, Renjie↗
DOE OSTI2021

Using GANs with adaptive training data to search for new molecules

The process of drug discovery involves a search over the space of all possible chemical compounds. Generative Adversarial Networks (GANs) provide a valuable tool towards exploring chemical space and optimizing known compounds for a desired functionality. Standard approaches to training GANs, however, can result in mode collapse, in which the generator primarily produces samples closely related to a small subset of the training data. In contrast, the search for novel compounds necessitates exploration beyond the original data. In this work, we present an approach to training GANs that promotes incremental exploration and limits the impacts of mode collapse using concepts from Genetic Algorithms. In our approach, valid samples from the generator are used to replace samples from the training data. We consider both random and guided selection along with recombination during replacement. By tracking the number of novel compounds produced during training, we show that updates to the training data drastically outperform the traditional approach, increasing potential applications for GANs in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Urine sampling and collection system optimization and testing

A Urine Sampling and Collection System (USCS) engineering model was developed to provide for the automatic collection, volume sensing and sampling of urine from each micturition. The purpose of the engineering model was to demonstrate verification of the system concept. The objective of the optimization and testing program was to update the engineering model, to provide additional performance features and to conduct system testing to determine operational problems. Optimization tasks were defined as modifications to minimize system fluid residual and addition of thermoelectric cooling.

Fogal, G. L.↗
NASA NTRS1984

TEQUEL: The query language of SADDLE

A relational database management system is presented that is tailored for engineering applications. A wide variety of engineering data types are supported and the data definition language (DDL) and data manipulation language (DML) are extended to handle matrices. The system can be used either in the standalone mode or through a FORTRAN or PASCAL application program. The query language is of the relational calculus type and allows the user to store, retrieve, update and delete tuples from relations. The relational operations including union, intersect and differ facilitate creation of temporary relations that can be used for manipulating information in a powerful manner. Sample applications are shown to illustrate the creation of data through a FORTRAN program and data manipulation using the TEQUEL DML.

Rajan, S. D.↗
NASA NTRS1996

International Research Project on the Effects of Chemical Ageing of Polymers on Performance Properties: Chemical and Thermal Analysis

Work during the past six months has included significant research in several areas aimed at further clarification of the aging and chemical failure mechanism of thermoplastics (PVDF or Tefzel) pipes. Among the areas investigated were the crystallinity changes associated with both the Coflon and Tefzel after various simulated environmental exposures using X-ray diffraction analysis. We have found that significant changes in polymer crystallinity levels occur as a function of the exposures. These crystallinity changes may have important consequences on the fracture, fatigue, tensile, and chemical resistance of the materials. We have also noted small changes in the molecular weight distribution. Again these changes may result in variations in the mechanical and chemical properties in the material. We conducted numerous analytical studies with methods including X-ray Diffraction, Gel Permeation Chromatography, Fourier Transform Infrared Spectroscopy, Ultra- Violet Scanning Analysis, GC/Mass Spectrometry, Differential Scanning Calorimetry and Thermomechanical Analysis. In the ultra-violet analysis we noted the presence of an absorption band indicative of triene formation. We investigated a number of aged samples of both Tefzel and Coflon that were forwarded from MERL. We also cast films at SWT and subjected these films to a refluxing methanol 1% ethylene diamine solution. An updated literature search was conducted using Dialog and DROLLS to identify any new papers that may have been published in the open literature since the start of this project. The updated literature search and abstracts are contained in the Appendix section of this report.

Bulluck, J. W.↗
NASA NTRS2012

A Bayesian Framework for Reliability Analysis of Spacecraft Deployments

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.

Evans, John W.↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Lunar Sample Analysis

The titles in this section include: 1) Global Mixing as a Mechanism for Compositional Anomalies of Agglutinitic Glasses; 2) Electron Microscopy of Apollo 12 Glass Spherules; 3) 40Ar-39Ar Geochronology on Apollo 12 Regolith; 4) LSCC Apollo and Luna Soil Analyses: Update of Soil Evolution Model; 5) Planetary Regolith Microstructure: An Unexpected Opposition Effect Result; 6) Infrared Spectroscopy on a Microscopic Scale: Investigating the Technique of Microspectroscopy and Its Application to a Lunar Breccia; 7) The Most Reduced Rock from the Moon - Apollo 14 Basalt 14053: Extreme Reduction Entirely from a Re-Heating Event.

Source record↗
DOE OSTI2021

Short Term Plasticity for Artificial Neural Networks

Achieving efficient learning for AI systems was identified as a major challenge in the DOE's recently released, AI for Science , report. The human brain is capable of efficient and low-powered learning. It is likely that implementing brain-like principles will lead to more efficient AI systems. In this LDRD, I aim to contribute to this goal by creating a foundation for implementing and studying a brain phenomenon termed short term plasticity (STP) in spiking artificial neural networks within Sandia. First, data collected by the Allen Institute for Brain Science (AIBS) was analyzed to see if STP could be classified into types using the data collected. Although the data was inadequate at the time, AIBS has updated their database and created models that could be utilized in the future. Second, I began creating a software package to assess the ability of a Boltzmann machine utilizing STP to sample from national security data.

59 BASIC BIOLOGICAL SCIENCES↗