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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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NASA NTRS2016

GeneLab Phase 2: Integrated Search Data Federation of Space Biology Experimental Data

The GeneLab project is a science initiative to maximize the scientific return of omics data collected from spaceflight and from ground simulations of microgravity and radiation experiments, supported by a data system for a public bioinformatics repository and collaborative analysis tools for these data. The mission of GeneLab is to maximize the utilization of the valuable biological research resources aboard the ISS by collecting genomic, transcriptomic, proteomic and metabolomic (so-called omics) data to enable the exploration of the molecular network responses of terrestrial biology to space environments using a systems biology approach. All GeneLab data are made available to a worldwide network of researchers through its open-access data system. GeneLab is currently being developed by NASA to support Open Science biomedical research in order to enable the human exploration of space and improve life on earth. Open access to Phase 1 of the GeneLab Data Systems (GLDS) was implemented in April 2015. Download volumes have grown steadily, mirroring the growth in curated space biology research data sets (61 as of June 2016), now exceeding 10 TB/month, with over 10,000 file downloads since the start of Phase 1. For the period April 2015 to May 2016, most frequently downloaded were data from studies of Mus musculus (39) followed closely by Arabidopsis thaliana (30), with the remaining downloads roughly equally split across 12 other organisms (each 10 of total downloads). GLDS Phase 2 is focusing on interoperability, supporting data federation, including integrated search capabilities, of GLDS-housed data sets with external data sources, such as gene expression data from NIHNCBIs Gene Expression Omnibus (GEO), proteomic data from EBIs PRIDE system, and metagenomic data from Argonne National Laboratory's MG-RAST. GEO and MG-RAST employ specifications for investigation metadata that are different from those used by the GLDS and PRIDE (e.g., ISA-Tab). The GLDS Phase 2 system will implement a Google-like, full-text search engine using a Service-Oriented Architecture by utilizing publicly available RESTful web services Application Programming Interfaces (e.g., GEO Entrez Programming Utilities) and a Common Metadata Model (CMM) in order to accommodate the different metadata formats between the heterogeneous bioinformatics databases. GLDS Phase 2 completion with fully implemented capabilities will be made available to the general public in September 2017.

Space Biology↗
DOE OSTI2024

Power and isotope effects in the ITER baseline scenario with tungsten and tungsten-equivalent radiators in DIII-D

Abstract Experiments in DIII-D document the ITER Baseline Scenario (IBS) at q 95 ∼ 3 and P IN / P LH ∼ 1–2, in both deuterium and hydrogen utilizing Kr and Xe as Tungsten-equivalent radiators. The power threshold for H-mode operation ( P LH ) was determined experimentally without added impurities and found to be about a factor of two higher than the scaling law. In recent IBS experiments in deuterium, intrinsic levels of metals such as Tungsten (W) or molybdenum and inconel are present that reduce the pedestal pressure by 20%–25%. A complete radiative collapse of deuterium IBS plasmas occurs at W core concentrations C W = 10 −5 . Simulations show that for core temperatures expected for ITER, the plasmas would not have a radiative collapse at C W = 1 × 10 −5 , moreover Q = 8–10 would still be achieved for C W up to 3 × 10 −5 . In contrast to deuterium, the IBS in hydrogen is not affected by intrinsic high-Z impurities, indicating that hydrogen H-modes in ITER may not inform the D-T phase with respect to W accumulation and discharge survival. Compared to deuterium, the pedestal pressure in hydrogen is ∼25% lower, with much higher ELM frequency of 150 Hz, decreasing with input power. Krypton was injected in a matrix scan of input power and impurity flow in IBS hydrogen discharges. Krypton impurity density profiles in hydrogen are similar to deuterium plasmas, but at Kr flows that are 2–3 times higher for the same input power. Krypton is transported into the core and affects the whole radius; at the highest injection rates a radiative collapse occurs at core radiation fractions of 0.3–0.35, consistent with the expected maximum W radiation fraction for ITER core plasmas. Comparing the results with previous International Tokamak Physics Activity database studies of the IBS confirms that at higher radiation fraction due to high-Z impurities, a drop in H 98 of >10% is observed. On the other hand, the results using Kr as a W-equivalent radiator indicate that metal (W) devices at lower core temperatures than ITER may provide overly pessimistic performance extrapolations to ITER for deuterium-tritium operation. The new DIII-D results support a more attractive option for the ITER Research Plan with a short hydrogen phase for system commissioning, transitioning to deuterium operations as soon as possible to provide relevant conditions for deuterium-tritium operations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2009

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗
DOE OSTI2020

A Curated Experimental Compilation Analyzed by Theory Is More than a Review

Macromolecules is an exceptional resource in the field of polymer science and now publishes more than 1000 original articles a year that set the standard for scientific rigor and creative insights. Over the years, these individual contributions have combined to build the foundation of polymer science, broadly and inclusively defined. In addition to the individual articles, many of which are being celebrated in this series of editorials, Macromolecules has published invaluable reviews and perspectives. These scholarly contributions integrate the insights and results from numerous sources into a unified whole and often recommend future directions for the field. Novices and experts alike benefit from these works that capture topics from emerging discoveries to long-pondered topics and everything in between. To explore the importance of Macromolecules’ reviews and perspectives, we considered their influence on the field and found the 1994 review by Fetters et al. entitled “Connection between Polymer Molecular Weight, Density, Chain Dimensions, and Melt Viscoelastic Properties”1 to be a singularity. This review expertly curates and compiles a trove of data to build robust correlations between molecular characteristics and macroscopic viscoelastic properties of polymer melts, in the context of the tube model of entanglements.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Quantitative interpretation of molecular dynamics simulations for X-ray photoelectron spectroscopy of aqueous solutions

Over the past decade, energy-dependent ambient pressure X-ray photoelectron spectroscopy (XPS) has emerged as a powerful analytical probe of the ion spatial distributions at the vapor (vacuum)-aqueous electrolyte interface. These experiments are often paired with complementary molecular dynamics (MD) simulations in an attempt to provide a complete description of the liquid interface. There is, however, no systematic protocol that permits a straightforward comparison of the two sets of results. XPS is an integrated technique that averages signals from multiple layers in a solution even at the lowest photoelectron kinetic energies routinely employed, whereas MD simulations provide a microscopic layer-by-layer description of the solution composition near the interface. Here, we use the National Institute of Standards and Technology database for the Simulation of Electron Spectra for Surface Analysis (SESSA) to quantitatively interpret atom-density profiles from MD simulations for XPS signal intensities using sodium and potassium iodide solutions as examples. We show that electron inelastic mean free paths calculated from a semi-empirical formula depend strongly on solution composition, varying by up to 30% between pure water and concentrated NaI. The XPS signal thus arises from different information depths in different solutions for a fixed photoelectron kinetic energy. XPS signal intensities are calculated using SESSA as a function of photoelectron kinetic energy (probe depth) and compared with a widely employed ad hoc method. SESSA simulations illustrate the importance of accounting for elastic-scattering events at low photoelectron kinetic energies (<300 eV) where the ad hoc method systematically underestimates the preferential enhancement of anions over cations. Finally, some technical aspects of applying SESSA to liquid interfaces are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Obstructive Sleep Apnea Among Army Aircrew

INTRODUCTION: Obstructive sleep apnea (OSA) is a condition characterized by disrupted sleep and excessive daytime fatigue. Associated cognitive and psychomotor decrements pose a threat to aviators’ performance and flight safety. Additionally, the longer term health effects associated with the disease can jeopardize an aviator’s career and negatively impact operational outputs. This study reviews OSA prevalence, related comorbid conditions in Army aviators, and analyzes the aeromedical dispositions of affected individuals. METHODS: The U.S. Army Aeromedical Electronic Resource Office (AERO) database was interrogated for all cases of OSA from June 2005 through June 2015 using ICD-9 code 327.23. Prevalence rates for OSA and other comorbid conditions were then calculated using the total number of aviators in the AERO database. RESULTS: A total of 663 unique instances of OSA were found among the aviator population ( N = 24,568), giving a point prevalence of 2.69%. Four cases affected women. Mean age of initial presentation was 42.62 yr and mean Body Mass Index was 28.69. The top five most prevalent comorbid conditions were hypertension, lumbago, degeneration of a lumbar or lumbosacral intervertebral disc, PTSD, and testicular hypofunction. DISCUSSION: Prevalence of OSA among aviators is lower than the general population but is not uncommon. A positive diagnosis requires a waiver or can result in suspension if not managed effectively, potentially leading to a reduction in aviator numbers. Aggressive health promotion and robust medical surveillance and aeromedical disposition management by the aeromedical community is essential to reduce OSA numbers, maintain aviator health, and maximize flight safety. Goldie C, Stork B, Bernhardt K, Gaydos SJ, Kelley AM. Obstructive sleep apnea among army aircrew . Aerosp Med Hum Perform. 2022; 93(5):415–420.

Biophysics↗
DOE OSTI2023

PV Inverter Experimental Dataset Version 2 with 100 Percent Power

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and controllable DC supply to emulate AC and DC side characteristics. The experiments were performed at NREL's Energy Systems Integration Facility. The PV inverter is tested under 100%, 75%, 50%, 25% load conditions. In the first dataset, for each operating condition, controllable AC source voltage is varied from 0.88 to 1.09 per unit (p.u) with a step value of 0.025 p.u while keeping the frequency at 60 Hz. In the second dataset, under similar load conditions (100%, 75%, 50%, 25% ), the frequency of the controllable AC source voltage was varied from 59.4 Hz to 60.45 Hz with a step value of 0.2 Hz. Voltage and frequency range is chosen based on inverter protection. Voltages and currents on DC and AC side are included in the dataset.

14 SOLAR ENERGY↗
NASA NTRS1989

Infrared focal plane performance in the South Atlantic anomaly

Proton-induced pulse height distributions (PHD's) in Si:XX detectors were studied analytically and experimentally. In addition, a preliminary design for a flight experiment to characterize the response of Si:XX detectors to the trapped proton environment and verify PHD models was developed. PHD's were computed for two orbit altitudes for a variety of shielding configurations. Most of the proton-induced pulses have amplitudes less that about 3.5 x 10(exp 5) e-h pairs. Shielding has a small effect on the shape of the PHD's. The primary effect of shielding is to reduce the total number of pulses produced. Proton-induced PHD's in a Si:Sb focal plane array bombarded by a unidirectional 67-MeV beam were measured. The maximum pulse height recorded was 6 x 10(exp 5) pairs. The distribution had two peaks: the larger peak corresponded to 3.8 x 10(exp 5) pairs and the smaller peak to 1.2 x 10(exp 5) pairs. The maximum pulse height and the larger peak are within a factor of two of predicted values. The low-energy peak was not expected, but is believed to be an artifact of inefficient charge collection in the detector. The planned flight experiment will be conducted on a Space Shuttle flight. Lockheed's helium extended life dewar (HELD) will be used to provide the required cryogenic environment for the detector. Two bulk Si:Sb arrays and two Si:As impurity band conduction arrays will be tested. The tests will be conducted while the Space Shuttle passes through the South Atlantic Anomaly. PHD's will be recorded and responsivity changes tracked. This experiment will provide a new database on proton-induced PHD's, compare two infrared detector technologies in a space environment, and provide the data necessary to validate PHD modeling.

Junga, Frank A.↗
DOE OSTI2023

Split phase inverter data

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 8.35 kW off-the-shelf grid following split phase PV inverter in the experiments. We used controllable AC supply and controllable DC supply to emulate AC and DC side characteristics. The experiments were performed at NREL's Energy Systems Integration Facility. Inverter is tested under 100%, 75%, 50%, 25% load conditions. In the first dataset, for each operating condition, controllable AC source voltage is varied from 0.9 to 1.1 per unit (p.u) with a step value of 0.025 p.u while keeping the frequency at 60 Hz. In the second dataset, under similar load conditions (100%, 75%, 50%, 25% ), the frequency of the controllable AC source voltage was varied from 59 Hz to 61 Hz with a step value of 0.2 Hz. Voltage and frequency range is chosen based on inverter protection. Voltages and currents on DC and AC side are included in the dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Laboratory Studies of Processing of Carbonaceous Aerosols by Atmospheric Oxidants/Hygroscopicity and CCN Activity of Secondary & Processed Primary Organic Aerosols

The atmosphere is composed of a complex mixture of gases and suspended microscopic aerosol particles. The ability of these particles to take up water (hygroscopicity) and to act as nuclei for cloud droplet formation significantly impacts aerosol light scattering and absorption, and cloud formation, thereby influencing air quality, visibility, and climate in important ways. A substantial, yet poorly characterized component of the atmospheric aerosol is organic matter. Its major sources are direct emissions from combustion processes, which are referred to as primary organic aerosol (POA), or in situ processes in which volatile organic compounds (VOCs) are oxidized in the atmosphere to low volatility reaction products that subsequent condense to form particles that are referred to as secondary organic aerosol (SOA). POA and VOCs are emitted to the atmosphere from both anthropogenic and natural (biogenic) sources. The overall goal of this experimental research project was to conduct laboratory studies under simulated atmospheric conditions to investigate the effects of the chemical composition of organic aerosol particles on their hygroscopicity and cloud condensation nucleation (CCN) activity, in order to develop quantitative relationships that could be used to more accurately incorporate aerosol-cloud interactions into regional and global atmospheric models. More specifically, the project aimed to determine the products, mechanisms, and rates of chemical reactions involved in the processing of organic aerosol particles by atmospheric oxidants and to investigate the relationships between the chemical composition of organic particles (as represented by molecule sizes and the specific functional groups that are present) and the hygroscopicity and CCN activity of oxidized POA and SOA formed from the oxidation of the major classes of anthropogenic and biogenic VOCs that are emitted to the atmosphere, as well as model hydrocarbons. The general approach for this project was to carry out reactions of representative anthropogenic and biogenic VOCs and organic particles with ozone (O 3 ), and hydroxyl (OH), nitrate (NO 3 ), and chlorine (Cl) radicals, which are the major atmospheric oxidants, under simulated atmospheric conditions in large-volume environmental chambers. A combination of on-line and off-line analytical techniques were used to monitor the chemical and physical properties of the particles including their hygroscopicity and CCN activity. The results of the studies were used to (1) improve scientific understanding of the relationships between the chemical composition of organic particles and their hygroscopicity and CCN activity, (2) develop an improved molecular level theoretical framework for describing these relationships, and (3) establish a large database that is being used to develop parameterizations relating organic aerosol chemical properties and SOA sources to particle hygroscopicity and CCN activity for use in regional and global atmospheric air quality and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗
NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗
NASA NTRSDate not supplied

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗
DOE OSTI2023

Battery inverter experimental data

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We used controllable AC supply and controllable DC supply to emulate AC and DC side characteristics. The experiments were performed at NREL's Energy Systems Integration Facility. Inverter is tested under 100%, 75%, 50%, 25% load conditions. In the first dataset, for each operating condition, controllable AC source voltage is varied from 0.9 to 1.1 per unit (p.u) with a step value of 0.025 p.u while keeping the frequency at 60 Hz. In the second dataset, under similar load conditions (100%, 75%, 50%, 25% ), the frequency of the controllable AC source voltage was varied from 59 Hz to 61 Hz with a step value of 0.2 Hz. Voltage and frequency range is chosen based on inverter protection. Voltages and currents on DC and AC side are included in the dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗
DOE OSTI2016

Thermal Diffusivity Measurement of Irradiated SiC-SiC Composite Material

Silicon Carbide fiber and matrix composite (SiC-SiC) is being considered as a fuel cladding candidate because of its high melting point, low susceptibility to corrosion, good thermal and mechanical shock resistance, and low degradation of mechanical properties under irradiation. The thermal properties of SiC-SiC composite depend heavily on the fabrication process, thus cannot be simply referenced from available database. Similarly, the influence of irradiation on SiC-SiC composite thermal properties needs to be measured to provide general trends of property degradation. For ion irradiated samples, the damaged layer is only a few to a few tens of micrometers. It is impossible to directly measure the bulk property change of a SiC-SiC composite because of the thin, damaged layer. This paper focuses on a methodology that is based on microscale measurement of fiber and matrix properties to determine the overall bulk property change due to ion irradiation. Laser-based photothermal reflectance technique is one of the ideal methods to measure local thermal conductivity and diffusivity with high spatial resolution. The main principle of this technique is to heat the solid sample using an intensity-modulated laser, and scan the sample with a constant intensity continuous-wave (CW) laser to detect the phase lag of the thermal wave propagation. On bulk, isotropic material, if the heating laser intensity is modulated as a sine wave, thermal diffusivity of the sample can be derived from the phase lag, scan distance and modulation frequency in a straight forward manner. By using more specific analytical models, thermal conductivity and diffusivity in complicated cases, such as layered structure materials, composite materials, and/or anisotropic materials, are measurable as well. In this work, a new measurement approach of SiC-SiC composite thermal diffusivity is presented. Due to the micrometer spatial resolution of the photothermal reflectance technique, the measurements are performed locally on fibers along both radial and axial directions, and on the matrix. The influence of Silicon ion irradiation (75 MeV, 10 dpa) is then examined by comparing the experimental results of samples before and after irradiation. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2013

AGR-2 Data Qualification Report for ATR Cycles 151B-2, 152A, 152B, 153A, 153B and 154A

This report documents the data qualification status of AGR-2 fuel irradiation experimental data from Advanced Test Reactor (ATR) Cycles 152A, 152B, 153A, 153B, and 154A, as recorded in the Nuclear Data Management and Analysis System (NDMAS). The AGR-2 data streams addressed include thermocouple (TC) temperatures, sweep gas data (flow rate, pressure, and moisture content), and fission product monitoring system (FPMS) data for each of the six capsules in the experiment. A total of 13,400,520 every minute instantaneous TC and sweep gas data records were received and processed by NDMAS for this period. Of these data, 8,911,791 records (66.5% of the total) were determined to be Qualified based on NDMAS accuracy testing and data validity assessment. For temperature, there were 4,266,081 records (74% of the total TC data) that were Failed due to TC instrument failures. For sweep gas flows, there were 222,648 gas flow records (2.91% of the flow data) that were Failed. The inlet gas flow failures due to gas flow cross-talk and leakage problems that occurred after Cycle 150A were corrected by using the same gas mixture in all six capsules and the Leadout. For FPMS data, NDMAS received and processed preliminary release rate and release-to-birth rate ratio (R/B) data for three reactor cycles (Cycles 149B, 150B, and 151A) . This data consists of 45,983 release rate records and 45,235 R/B records for the 12 radionuclides reported. The qualification status of these FPMS data has been set to In Process until receipt of Quality Assurance-approved data generator reports. All of the above data have been processed and tested using a SAS®-based enterprise application software system, stored in a secure Structured Query Language database, made available on the NDMAS Web portal (http://ndmas.inl.gov), and approved by the INL STIM for release to both internal and appropriate external Very High Temperature Reactor Program participants.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Interrelationship between sex, age, blood volume and VO 2 max

Background Circulating blood volume (BV) and maximal oxygen uptake (VO 2 max) are physiological characteristics important for optimal human performance in aerospace and military operational environments. Addressing the interrelationships between BV, VO 2 max, sex, and age together is relevant to identifying those individuals with greatest risk of poor outcomes from hemorrhage, as well as assessing the levels of performance competence of individuals deployed in operational environments. In the present investigation, we report and compare for the first time BV and VO 2 max in a cohort of males and females together to test the hypothesis that BV and VO 2 max is lower in older people independent of sex. Methods To accomplish this, a ‘data mining’ effort of an historic database generated from NASA and U.S. Air Force experiments was conducted. BV, red cell volume, plasma volume, hematocrit, and VO 2 max were measured in 94 healthy individuals (28 females, 66 males) across an age range of 23 to 65 years to assess the interrelationship between sex, age, BV, and VO 2 max. Subjects were classified in age groups by < 40 years and ≥ 40 years; these groups identified females as pre‐ vs. post‐menopausal. Results Consistent with our hypothesis, comparisons revealed that males had higher (p < 0.01) BV, red cell volume, hematocrit, and VO 2 max than females when standardized for body size. Against expectations, BV was not different in older compared with younger males and females. VO 2 max was not different in older compared with younger females, while VO 2 max was lower in older males (p < 0.01). Conclusion We conclude that physiological mechanisms other than BV associated with aging appear to be responsible for a decline in VO 2 max of our older male subjects. Furthermore, factors other than menopause may also influence the control of BV in the female population. Our results provide evidence that aging may not compromise males or females in scenarios where BV can affect performance in aerospace and military environments. Support or Funding Information This research was supported in part by appointment of Ms. Koons to the Postgraduate Research Fellowship Program at the US Army Institute of Surgical Research administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and USAMRMC. Study funding was provided by a grant from the US Army Combat Casualty Care Research Program (D‐009‐2014‐USAISR). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Convertino, Victor↗

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