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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 505 records · Page 28

Global Aerodynamic Modeling for Stall/Upset Recovery Training Using Efficient Piloted Flight Test Techniques

Flight test and modeling techniques were developed for efficiently identifying global aerodynamic models that can be used to accurately simulate stall, upset, and recovery on large transport airplanes. The techniques were developed and validated in a high-fidelity fixed-base flight simulator using a wind-tunnel aerodynamic database, realistic sensor characteristics, and a realistic flight deck representative of a large transport aircraft. Results demonstrated that aerodynamic models for stall, upset, and recovery can be identified rapidly and accurately using relatively simple piloted flight test maneuvers. Stall maneuver predictions and comparisons of identified aerodynamic models with data from the underlying simulation aerodynamic database were used to validate the techniques.

Morelli, Eugene A.↗

Trends in Use of Hypofractionated Whole Breast Radiation in Breast Cancer: An Analysis of the National Cancer Database

Use of hypofractionated radiation (HR) as a component of breast-conserving treatment (BCT) in breast cancer is relatively low in the United States despite studies demonstrating its efficacy and guidelines supporting its use from the American Society for Radiation Oncology (ASTRO) in 2011 and 2018. Little is known regarding national trends in uptake and factors associated with uptake of HR in the US since the 2011 ASTRO guidelines.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

COINS: A composites information database system

An automated data abstraction form (ADAF) was developed to collect information on advanced fabrication processes and their related costs. The information will be collected for all components being fabricated as part of the Advanced Composite Technology (ACT) program and included in a COmposites INformation System (COINS) data base. The aim of the COINS development effort is to provide future airframe preliminary design and fabrication teams with a tool through which production cost can become a deterministic variable in the design optimization process. The effort was initiated by NASA Langley to implement the recommendations of a working group comprised of representatives from the commercial airframe companies. The principal working group recommendation was to reinstitute collection of composite part fabrication data in a format similar to the DOD/NASA Structural Composites Fabrication Guide. The fabrication information collection form was automated with current user friendly computer technology. The new automated form and features that make the form easy to use by an aircraft structural design manufacturing team are described.

Siddiqi, Shahid↗

A photostationary state analysis of the NO2-NO system based on airborne observations from the subtropical/tropical North and South Atlantic

The Chemical Instrumentation Test and Evaluation 3 (CITE 3) NO-NO2 database has provided a unique opportunity to examine important aspects of tropospheric photochemistry as related to the rapid cycling between NO and NO2. Our results suggest that when quantitative testing of this photochemical system is based on airborne field data, extra precautions may need to be taken in the analysis. This was particularly true in the CITE 3 data analysis where different regional environments produced quite different results when evaluating the photochemical test ratio (NO2)(sub expt)/(NO2)(sub calc), designated here as R(sub E)/R(sub C). The quantity (NO2)(sub Calc) was evaluated using the following photostationary state expression: (NO2)(sub Calc) = k(sub 1)(O3) + k(sub 4)(HO2) + k(sub 5)(CH3O2) + k(sub 6)(RO2))(NO)(sub Expt)/J(sub 2). The four most prominent regional environmental data sets identified in this analysis were those labeled here as free-tropospheric northern hemisphere (FTNH), free-tropospheric tropical northern hemisphere (FTTNH), free-tropospheric southern hemisphere (FTSH), and tropical-marine boundary layer (plume) (TMBL(P)). The respective R(sub E)/R(sub C) mean and median values for these four data subsets were 1.74, 1.69; 3.00, 2.79; 1.01, 0.97; and 0.99, 0.94. Of the four data subsets listed, the two that were statistically the most robust were FTNH and FTSH; for these the respective R(sub E)/R(sub C) mean and standard deviation of the mean values were 1.74 +/- 0.07 and 1.01 +/- 0.04. The FTSH observations were in good agreement with theory, whereas those from the FTNH data set were in significant disagreement. An examination of the critical photochemical parameters O3, UV(zenith), NO, NO2, and non-methane hydrocarbons (NMHCs) for these two databases indicated that the most likely source of the R(sub E)/R(sub C) bias in the FTNH results was the presence of a systematic error in the observational data rather than a shortening in our understanding of fundamental photochemical processes. Although neither a chemical nor meteorological analyses of these data identified this error with complete certainty, they did point to the three most likely possibilities: (1) an NO2 interference from a yet unidentified NO(y) species: (2) the presence of unmeasured hydrocarbons, the integrated reactivity of which would be equivalent to approximately 2.7 parts per billion by volume (ppbv) of toluene; or (3) some combination of points (1) and (2). Details concerning hypotheses (1) and (2) as well as possible ways to minimize these problems in future airborne missions are discussed.

Davis, D. D.↗

Small Spacecraft Systems Virtual Institute's Federated Databases and State of the Art of Small Spacecraft Technology Report

NASA's Small Spacecraft Systems Virtual Institute (S3VI) is collaborating with the Air Force Research Laboratory and Space Dynamics Laboratory on the development of a small spacecraft parts database called SmallSat Parts On Orbit Now (SPOON). The SPOON database contains small spacecraft parts and technologies categorized by major satellite subsystems developed by industry, academia and government. The State of the Art of Small Spacecraft Technology report reflects small spacecraft parts submitted to the SPOON database and technologies compiled from other sources that were assessed as the current state of the art in each of the major subsystems. The report, first commissioned by NASA's Small Spacecraft Technology Program in mid-2013, is developed in response to the continuing growth in interest in using small spacecraft for many types of missions in Earth orbit and beyond. Due to the high market penetration of CubeSats, particular emphasis is placed on the state of the art of CubeSat-related technology. The 2018 report is planned for release in late summer. A review of SPOON database functionality, federation of additional NASA-internal and external databases along with a common search capability, as well as an overview of the State of the Art of Small Spacecraft Technology report will be presented. The S3VI is jointly sponsored by NASA's Space Technology Mission Directorate and Science Mission Directorate.

Small spacecraft↗

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS: Teams Risk

BACKGROUNDThe Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogsof the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.METHODSWe followed best practices for data harmonization. Characteristics of each research setting were assessed for harmonization potential, and we deemed NEK-SIRIUS 17 as inappropriate due to study aims, length, and data quality. Common variables of interest were identified. Study characteristics and key variables with which datafiles could be merged were defined as “meta-data.” HFBP-EM data from all settings were processed under a common format. We then created a harmonized team-level database designed to facilitate analyses that address HRP research gaps related to HRP’s Team risk. In this database, team cohesion, processes, performance, psychological safety, and group living were operationalized as the team mean of the crew responses for each data collection (e.g., on mission day 7). Data collected on the International Space Station (ISS) included a subset of scale items administered to participants. Data collected from ISS team members within +/- 7 days of the first data collection and every following 30 +/-4 days were aggregated to the team level. We generated figures that display the mean and variability of team constructs across research settings. We also generated plots of changes in team constructs with mission day and with percentage of the mission completed. Where possible, we compared data from spaceflight analogs with data from astronauts aboard the ISS. RESULTS AND DISCUSSIONThe team-level harmonized database was structured such that each row represents data for a team on a specific mission day. Team constructs (e.g., team cohesion) were included as columns (i.e., wide format) with repeated measures across mission days given in rows (i.e., long format). The database included data from 18 crews: five, 4-person American crews in HERA C4, four 4-person American crews in HERA C5, one 6-person multinational crew in NEK-SIRIUS 19, and eight, 2–11-person multinational crews aboard the ISS. Results provide insights into mission and campaign differences in team functioning and performance. For example, between campaign differences were observed for team processes—the interdependent team actions that orchestrate taskwork in pursuit of the team’s goals [1]. Greater between-team variability on team processes was detected during HERA C4 than during C5, and a downward trend was observed over the duration of C4, but not C5 or SIRIUS 19. This may be due to the campaign-level differences such as the sleep deprivation implemented during C4. Responses on the subset of team process items administered on the ISS indicate between-crew variability more like those observed in C4 than C5 and NEK, with some, but not all ISS crews demonstrating a downward trend over time. Additional findings will be presented. REFERENCESMarks, M. A., et al (2001) Academy of Management Review, 26(3), 356-376.

S T Bell↗

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗

IRAS low resolution spectra of 26 symbiotic stars

Data related to the spectral scans for 26 symbiotic stars are described which were extracted from the IRAS low resolution database. Data from the 8-15- and 15-23-micron bands are merged in a program that scales the longer wavelength and produces a weighted average of the spectral scans for each source. The survey shows that active dust producers can probably be isolated and some theories related to the presence of dust emission features are discussed in terms of source variability for measurements made with low resolution spectra.

Stencel, Robert E.↗

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗

Machine-learning enabled thermodynamic model for the design of new rare-earth compounds

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been sparse due to limited availability of reliable datasets. In this work, we developed an ‘in-house’ rare-earth database with more than 600 + compounds, each entry was populated with formation enthalpy and related atomic features using high-throughput density-functional theory (DFT). The SISSO (sure independence screening and sparsifying operator) based machine-learning method with meaningful atomic features was used for training and testing the formation enthalpies of rare earth compounds. The complex lattice function coupled with the machine-learning model was used to explore the effect of transition metal alloying on the energy stability of Ce based cubic Laves phases (MgCu 2 type). The SISSO predictions show good agreement with high-fidelity DFT calculations and X-ray powder diffraction measurements. Our study provides quantitative guidance for compositional considerations within a machine-learning model and discovering new metastable materials. The electronic-structure of Ce-Fe-Cu based compound was also analyzed to get an in-depth understanding of the electronic origin of phase stability. The interpretable analytical models in combination with density-functional theory and experiments provide a fast and reliable design guide for discovering technologically useful materials.

36 MATERIALS SCIENCE↗

Proposed minimal standards for description of methanogenic archaea

Methanogenic archaea are a diverse, polyphyletic group of strictly anaerobic prokaryotes capable of producing methane as their primary metabolic product. It has been over three decades since minimal standards for their taxonomic description have been proposed. In light of advancements in technology and amendments in systematic microbiology, revision of the older criteria for taxonomic description is essential. Most of the previously recommended minimum standards regarding phenotypic characterization of pure cultures are maintained. Electron microscopy and chemotaxonomic methods like whole-cell protein and lipid analysis are desirable but not required. Because of advancements in DNA sequencing technologies, obtaining a complete or draft whole genome sequence for type strains and its deposition in a public database are now mandatory. Genomic data should be used for rigorous comparison to close relatives using overall genome related indices such as average nucleotide identity and digital DNA–DNA hybridization. Phylogenetic analysis of the 16S rRNA gene is also required and can be supplemented by phylogenies of the mcrA gene and phylogenomic analysis using multiple conserved, single-copy marker genes. Additionally, it is now established that culture purity is not essential for studying prokaryotes, and description of Candidatus methanogenic taxa using single-cell or metagenomics along with other appropriate criteria is a viable alternative. The revisions to the minimal criteria proposed here by the members of the Subcommittee on the Taxonomy of Methanogenic Archaea of the International Committee on Systematics of Prokaryotes should allow for rigorous yet practical taxonomic description of these important and diverse microbes.

Microbiology↗

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

Athena - Digital Twin and Infrastructure Model [SWR 20-106]

The software provides database access and analysis code for project ATHENA data. In particular, it provides (1) access to the AWS RDS database and (2) supporting code for analysis. Additionally, the software contains all the code related to modeling the Dallas-Fort Worth International Airport (DFW) curbside (CTA modeling) using SUMO simulator. It demonstrates how to install, run and derive useful data from SUMO simulations. We will describe the basic files needed to run a simulation and how those files are generated. The software also has code for generating simulations representing different traffic management policies for DFW and simulating those policies on personal computer or on NREL's Eagle supercomputer. The examples provided are a representation of the DFW airport for curbside dropoff and and pickup.

Severino, Joseph↗

Full ribosomal operon sequencing of anaerobic gut fungi (phylum Neocallimastigomycota ): insights on its markers and phylogenetic resolution

The phylogenetic affiliations of anaerobic gut fungi (Neocallimastigomycota) are typically evaluated using single-gene markers. However, this approach often fails to resolve relationships between closely related lineages. To address this issue and identify alternative markers, we created a curated database comprising the complete ribosomal operon sequences of 156 isolates, representing 20 of the 22 recognized genera and two new genus-level clades. Using long-read sequencing, we obtained ~9 kbp operon sequences and developed a robust analysis pipeline. Incorporating both coding genes and non-coding regions (excluding IGS1) improved phylogenetic resolution. This phylogenetic approach successfully resolved the Cyllamyces and Caecomyces clades (hard-to-distinguish genetically), as well as seven analysed Piromyces species. We also scanned the operon for markers that are suitable for short-read sequencing platforms, with the aim of enhancing biodiversity and phylogenetic studies. Notably, the ETS1 genetic region also enabled the distinction between these lineages, indicating its phylogenetic value within the ribosomal operon. The resulting database is a valuable resource for expanding and strengthening phylogenetic frameworks.

High-throughput sequencing↗

Interconnecting heterogeneous database management systems

It is pointed out that there is still a great need for the development of improved communication between remote, heterogeneous database management systems (DBMS). Problems regarding the effective communication between distributed DBMSs are primarily related to significant differences between local data managers, local data models and representations, and local transaction managers. A system of interconnected DBMSs which exhibit such differences is called a network of distributed, heterogeneous DBMSs. In order to achieve effective interconnection of remote, heterogeneous DBMSs, the users must have uniform, integrated access to the different DBMs. The present investigation is mainly concerned with an analysis of the existing approaches to interconnecting heterogeneous DBMSs, taking into account four experimental DBMS projects.

Gligor, V. D.↗

The human role in space (THURIS) applications study. Final briefing

The THURIS (The Human Role in Space) application is an iterative process involving successive assessments of man/machine mixes in terms of performance, cost and technology to arrive at an optimum man/machine mode for the mission application. The process begins with user inputs which define the mission in terms of an event sequence and performance time requirements. The desired initial operational capability date is also an input requirement. THURIS terms and definitions (e.g., generic activities) are applied to the input data converting it into a form which can be analyzed using the THURIS cost model outputs. The cost model produces tabular and graphical outputs for determining the relative cost-effectiveness of a given man/machine mode and generic activity. A technology database is provided to enable assessment of support equipment availability for selected man/machine modes. If technology gaps exist for an application, the database contains information supportive of further investigation into the relevant technologies. The present study concentrated on testing and enhancing the THURIS cost model and subordinate data files and developing a technology database which interfaces directly with the user via technology readiness displays. This effort has resulted in a more powerful, easy-to-use applications system for optimization of man/machine roles. Volume 1 is an executive summary.

Maybee, George W.↗

Final shuttle-derived atmospheric database: Development and results from thirty-two flights

The final Shuttle-derived atmospheric data base is presented. The relational data base is comprised of data from 32 Space Transportation System (STS) descent flights, to include available meteorology data taken in support of each flight. For the most part, the available data are restricted to the middle atmosphere. In situ accelerations, sensed by the tri-redundant Inertial Measurement Unit (IMU) to an accuracy better than 1 mg, are combined with post-flight Best Estimate Trajectory (BET) information and predicted, flight-substantiated Orbiter aerodynamics to provide determinations up to altitudes of 95 km. In some instances, alternate accelerometry data with micro-g resolution were utilized to extend the data base well into the thermosphere. Though somewhat limited, the ensemble of flights permit a reasonable sampling of monthly, seasonal, and latitudinal variations which can be utilized for atmospheric science investigations and model evaluations and upgrades as appropriate. More significantly, the unparallel vertical resolution in the Shuttle-derived results indicate density shears normally associated with internal gravity waves or local atmospheric instabilities. Consequently, these atmospheres can also be used as stress-atmospheres for Guidance, Navigation and Control (GN and C) system development and analysis as part of any advanced space vehicle design activities.

Findlay, John T.↗

Building a generalized distributed system model

A number of topics related to building a generalized distributed system model are discussed. The effects of distributed database modeling on evaluation of transaction rollbacks, the measurement of effects of distributed database models on transaction availability measures, and a performance analysis of static locking in replicated distributed database systems are covered.

Mukkamala, Ravi↗