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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Causal Factors and Adverse Conditions of Aviation Accidents and Incidents Related to Integrated Resilient Aircraft Control

The causal factors of accidents from the National Transportation Safety Board (NTSB) database and incidents from the Federal Aviation Administration (FAA) database associated with loss of control (LOC) were examined for four types of operations (i.e., Federal Aviation Regulation Part 121, Part 135 Scheduled, Part 135 Nonscheduled, and Part 91) for the years 1988 to 2004. In-flight LOC is a serious aviation problem. Well over half of the LOC accidents included at least one fatality (80 percent in Part 121), and roughly half of all aviation fatalities in the studied time period occurred in conjunction with LOC. An adverse events table was updated to provide focus to the technology validation strategy of the Integrated Resilient Aircraft Control (IRAC) Project. The table contains three types of adverse conditions: failure, damage, and upset. Thirteen different adverse condition subtypes were gleaned from the Aviation Safety Reporting System (ASRS), the FAA Accident and Incident database, and the NTSB database. The severity and frequency of the damage conditions, initial test conditions, and milestones references are also provided.

Reveley, Mary S.↗
NASA NTRS1995

Combustion Technology Outreach

Lewis' High Speed Research (HSR) Propulsion Project Office initiated a targeted outreach effort to market combustion-related technologies developed at Lewis for the next generation of supersonic civil transport vehicles. These combustion-related innovations range from emissions measurement and reduction technologies, to diagnostics, spray technologies, NOx and SOx reduction of burners, noise reduction, sensors, and fuel-injection technologies. The Ohio Aerospace Institute and the Great Lakes Industrial Technology Center joined forces to assist Lewis' HSR Office in this outreach activity. From a database of thousands of nonaerospace firms considered likely to be interested in Lewis' combustion and emission-related technologies, the outreach team selected 41 companies to contact. The selected companies represent oil-gas refineries, vehicle/parts suppliers, and manufacturers of residential furnaces, power turbines, nonautomobile engines, and diesel internal combustion engines.

Source record↗
DOE OSTI2021

MultiPhATE2: code for functional annotation and comparison of phage genomes

To address a need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of multiPhATE, a functional annotation code released previously, multiPhATE2 performs gene finding using multiple algorithms, compares the results of the algorithms, performs functional annotation of coding sequences, and incorporates additional search algorithms and databases to extend the search space of the original code. MultiPhATE2 performs gene matching among sets of closely related bacteriophage genomes, and uses multiprocessing to speed computations. MultiPhATE2 can be re-started at multiple points within the workflow to allow the user to examine intermediate results and adjust the subsequent computations accordingly. In addition, multiPhATE2 accommodates custom gene calls and sequence databases, again adding flexibility. MultiPhATE2 was implemented in Python 3.7 and runs as a command-line code under Linux or MAC operating systems. Full documentation is provided as a README file and a Wiki website.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Particulate sulfur-containing lipids: Production and cycling from the epipelagic to the abyssopelagic zone

There are major gaps in our understanding of the distribution and role of lipids in the open ocean especially with regard to sulfur-containing lipids (S-lipids). In this study, we employ a powerful analytical approach based on high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to elucidate depth-related S-lipid production and molecular transformations in suspended particulate matter from the Northeast Atlantic Ocean in this depth range. We show that within the open-ocean environment S-lipids contribute up to 4.2% of the particulate organic carbon, and that up to 95% of these compounds have elemental compositions that do not match those found in the Nature Lipidomics Gateway database (termed “novel”). Among the remaining 5% of lipids that match the database, we find that sulphoquinovosyldiacylglycerol (SQDG) are efficiently removed while sinking through the mesopelagic zone. The relative abundance of other assigned lipids (sulphoquinovosylmonoacylglycerol (SQMG), sulfite and sulfate lipids, Vitamin D2 and D3 derivatives, and sphingolipids) did not change substantially with depth. The novel S-lipids, represented by hundreds of distinct elemental compositions (160–300 molecules at any one depth), contribute increasingly to the lipid and particulate organic matter pools with increased depth. Depth-related transformations cause (i) incomplete degradation/transformation of unsaturated S-lipids which leads to the depth-related accumulation of the refractory saturated compounds with reduced molecular weight (average 455 Da) and (ii) formation of highly unsaturated S-lipids (average abyssopelagic molecular double bond equivalents, DBE=7.8) with lower molecular weight (average 567 Da) than surface S-lipids (average 592 Da). A depth-related increase in molecular oxygen content is observed for all novel S-lipids and indicates that oxidation has a significant role in their transformation while (bio)hydrogenation possibly impacts the formation of saturated compounds. The instrumentation approach applied here represents a step change in our comprehension of marine S-lipid diversity and the potential role of these compounds in the oceanic carbon cycle. We describe a very much higher number of compounds than previously reported, albeit at the level of elemental composition and fold-change quantitation with depth, rather than isomeric confirmation and absolute quantitation of individual lipids. We emphasize that saturated S-lipids have the potential to transfer carbon from the upper ocean to depth and hence are significant vectors for carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving five-year survival prediction via multitask learning across HPV-related cancers

Oncology is a highly siloed field of research in which sub-disciplinary specialization has limited the amount of information shared between researchers of distinct cancer types. This can be attributed to legitimate differences in the physiology and carcinogenesis of cancers affecting distinct anatomical sites. However, underlying processes that are shared across seemingly disparate cancers probably affect prognosis. The objective of the current study is to investigate whether multitask learning improves 5-year survival cancer patient survival prediction by leveraging information across anatomically distinct HPV related cancers. Furthermore, data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program database. The study cohort consisted of 29,768 primary cancer cases diagnosed in the United States between 2004 and 2015. Ten different cancer diagnoses were selected, all with a known association with HPV risk. In the analysis, the cancer diagnoses were categorized into three distinct topography groups of varying specificity. The most specific topography grouping consisted of 10 original cancer diagnoses differentiated by the first two digits of the ICD-O-3 topography code. The second topography grouping consisted of cancer diagnoses categorized into six distinct organ groups. Finally, the third topography grouping consisted of just two groups, head-neck cancers and ano-genital cancers. The tasks were to predict 5-year survival for patients within the different topography groups using 14 predictive features which were selected among descriptive variables available in the SEER database. The information from the predictive features was shared between tasks in three different ways, resulting in three distinct predictive models: 1) Information was not shared between patients assigned to different tasks (single task learning); 2) Information was shared between all patients, regardless of task (pooled model); 3) Only relevant information was shared between patients grouped to different tasks (multitask learning). Prediction performance was evaluated with Brier scores. All three models were evaluated against one another on each of the three distinct topography-defined tasks. The results showed that multitask classifiers achieved relative improvement for the majority of the scenarios studied compared to single task learning and pooled baseline methods. In this study, we have demonstrated that sharing information among anatomically distinct cancer types can lead to improved predictive survival models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Prediction of Adsorption Energies for Chemical Species on Metal Catalyst Surfaces Using Machine Learning

Computational catalyst screening has the potential to significantly accelerate heterogeneous catalyst discovery. Typically, this involves developing microkinetic reactor models that are based on parameters obtained from density functional theory and transition-state theory. To reduce the large computational cost involved in computing various adsorption and transition-state energies of all possible surface states on a large number of catalyst models, linear scaling relations for surface intermediates and transition states have been developed that only depend on a few, typically one or two descriptors, such as the carbon atom adsorption energy. As a result, only the descriptor values have to be computed for various active site models to generate volcano curves in activity or selectivity. Unfortunately, for more complex chemistries the predictability of linear scaling relations is unknown. Also, the selection of descriptors is essentially a trial and error process. Here, using a database of adsorption energies of the surface species involved in the decarboxylation and decarbonylation of propionic acid over eight monometalic transition-metal catalyst surfaces (Ni, Pt, Pd, Ru, Rh, Re, Cu, Ag), we tested if nonlinear machine learning (ML) models can outperform the linear scaling relations in prediction accuracy when predicting the adsorption energy for various species on a metal surface based on data from the rest of the metal surfaces. We found linear scaling relations to hold well for predictions across metals with a mean-absolute error of 0.12 eV, and ML methods being unable to outperform linear scaling relations when the training dataset contains a complete set of energies for all of the species on various metal surfaces. Only when the training dataset is incomplete, namely, contains a random subset of species’ energies for each metal, a currently unlikely scenario for catalyst screening, do kernel-based ML models significantly outperform linear scaling relations. We also found that simple coordinate-free species descriptors, such as bond counts, achieve as good results as sophisticated coordinate-based descriptors. Finally, we propose an approach for automatic discovery of appropriate metal descriptors using principal component analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Effect of solid-state characteristics on the critical parameters of the vapor–liquid phase transition

Database for the critical point parameters of almost all metals (including transition metals) and semiconductors is used to derive a number of empirical expressions to relate these parameters to the heat of evaporation, the normal density, and the isothermal bulk modulus of these substances in a solid state under normal conditions. The database is obtained using the thermodynamic model proposed earlier.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Diffusion model of the non-stoichiometric uranium dioxide

Uranium dioxide (UO{sub 2}), which is used in light water reactors, exhibits a large range of non-stoichiometry over a wide temperature scale up to 2000 K. Understanding diffusion behavior of uranium oxides under such conditions is essential to ensure safe reactor operation. The current understanding of diffusion properties is largely limited by the stoichiometric deviations inherent to the fuel. The present DICTRA-based model considers diffusion across non-stoichiometric ranges described by experimentally available data. A vacancy and interstitial model of diffusion is applied to the U–O system as a function of its defect structure derived from CALPHAD-type thermodynamic descriptions. Oxygen and uranium self and tracer diffusion coefficients are assessed for the construction of a mobility database. Chemical diffusion coefficients of oxygen are derived with respect to the Darken relation and migration energies of defects are evaluated as a function of stoichiometric deviation. - Graphical abstract: Complete description of Oxygen–Uranium diffusion as a function of composition at various temperatures according to the developed Dictra model. - Highlights: • Assessment of a uranium–oxygen diffusion model with Dictra. • Complete description of U–O diffusion over wide temperature and composition range. • Oxygen model includes terms for interstitial and vacancy migration. • Interaction terms between defects help describe non-stoichiometric domain of UO{sub 2±x}. • Uranium model is separated into mobility terms for the cationic species.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2016

Reaction rate constant for radiative association of CF{sup +}

Reaction rate constants and cross sections are computed for the radiative association of carbon cations (C{sup +}) and fluorine atoms (F) in their ground states. We consider reactions through the electronic transition 1{sup 1}Π → X{sup 1}Σ{sup +} and rovibrational transitions on the X{sup 1}Σ{sup +} and a{sup 3}Π potentials. Semiclassical and classical methods are used for the direct contribution and Breit–Wigner theory for the resonance contribution. Quantum mechanical perturbation theory is used for comparison. A modified formulation of the classical method applicable to permanent dipoles of unequally charged reactants is implemented. The total rate constant is fitted to the Arrhenius–Kooij formula in five temperature intervals with a relative difference of <3%. The fit parameters will be added to the online database KIDA. For a temperature of 10–250 K, the rate constant is about 10{sup −21} cm{sup 3} s{sup −1}, rising toward 10{sup −16} cm{sup 3} s{sup −1} for a temperature of 30 000 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A side-by-side comparison of the solidification dynamics of quasicrystalline and approximant phases in the Al–Co–Ni system

Quasicrystals and their approximants have triggered widespread interest due to the challenge of solving their complex crystal structures as well as their possibly exceptional properties. The structural motifs of approximants are similar to those of the corresponding quasicrystals, but to what extent are their crystallization pathways the same? Unfortunately, there have been very few in situ experimental investigations to answer this question. Here, by leveraging the high penetrating power of hard X-rays, synchrotron-based X-ray tomography was conducted in order to capture the nucleation and growth of a decagonal quasicrystal and its related approximant. The combination of data-driven computational analysis with new thermodynamic databases allowed the characterization, with high precision, of the constitutional and kinetic driving forces for crystallization. The experimental results prove that the growth of both crystals from a liquid is dominated by first-order kinetics. Nevertheless, and somewhat surprisingly, significant differences were observed in their rates of nucleation and growth. The reasons for such divergent behaviours are discussed in light of contemporary theories of intermetallic crystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantitative differentiation of benign and misfolded glaucoma-causing myocilin variants on the basis of protein thermal stability

Accurate predictions of the pathogenicity of mutations associated with genetic diseases are key to the success of precision medicine. Inherited missense mutations in the myocilin (MYOC) gene, within its olfactomedin (OLF) domain, constitute the strongest genetic link to primary open-angle glaucoma via a toxic gain of function, and thus MYOC is an attractive precision-medicine target. However, not all mutations in MYOC cause glaucoma, and common variants are expected to be neutral polymorphisms. The Genome Aggregation Database (gnomAD) lists ~100 missense variants documented within OLF, all of which are relatively rare (allele frequency <0.001%) and nearly all are of unknown pathogenicity. To distinguish disease-causing OLF variants from benign OLF variants, we first characterized the most prevalent population-based variants using a suite of cellular and biophysical assays, and identified two variants with features of aggregation-prone familial disease variants. Next, we considered all available biochemical and clinical data to demonstrate that pathogenic and benign variants can be differentiated statistically based on a single metric: the thermal stability of OLF. Our results motivate genotyping MYOC in patients for clinical monitoring of this widespread, painless and irreversible ocular disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Long Term Environment and Economic Impacts of Coal Liquefaction in China

The project currently is composed of six specific tasks – three research tasks, two outreach and training tasks, and one project management and communications task. Task 1 addresses project management and communication. Research activities focused on Task 2 (Describe and Quantify the Economic Impacts and Implications of the Development and Deployment of Coal-to-Liquid Facilities in China), Task 3 (Development of Alternative Coal Gasification Database), and Task 4 (Geologic Carbon Management Options). There also were significant activities related to Task 5 (US-China Communication, Collaboration, and Training on Clean Coal Technologies) as well as planning activity performed in support of Task 6 (Training Programs).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Paths Forward for Nuclear Energy: Using a Nationwide Post-Stratified Hierarchical Model to Facilitate Matching of New Nuclear Technologies to Receptive Host Communities

This project was a collaboration between the University of Oklahoma (OU) and the University of Michigan (UMich). The overall objective of the project was to address a critical problem facing the siting of nuclear facilities, where there is no mechanism for incorporating public attitudes at a state and local level into decision-making. Utilizing recent advances in data modeling over local spatial scales, the research team created a state and county level map of public attitudes towards nuclear energy. Current estimates for public acceptance of nuclear technologies primarily exists on a national level, and sub-national estimates of public opinion about reactor siting, research facilities, transport routes, or storage and disposal facilities are very scarce. Model results from this project provide a systematic basis for technology developers to evaluate public acceptance across alternative siting options as a critical component for weighing potential benefit-cost tradeoffs for alternative paths to deploy new nuclear facilities. The project utilized data from the largest database of nuclear attitudes in the US, coupled with Census and elections-related data as well as data on social vulnerability and proximity to current nuclear facilities. In addition to modeling public support, the team also developed an interactive map to showcase results, using an online tool called Public and Local Attitudes about Nuclear Energy Technologies (PLANET). The tool allows technology developers and stakeholders to interact with the model results and better understand variation in support for nuclear facility siting on a state and county level. The interactive nature of the tool also allows users to analyze results in a targeted way, by comparing levels of support across different states and/or counties as desired.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1993

Workload management and geographic disorientation in aviation incidents: A review of the ASRS data base

NASA's Aviation Safety Reporting System (ASRS) incident reports are reviewed in two related areas: pilots' failures to appropriately manage tasks, and breakdowns in geographic orientation. Examination of 51 relevant reports on task management breakdowns revealed that altitude busts and inappropriate runway usee were the most frequently reported consequences. Task management breakdowns appeared to occur at all levels of expertise, and prominent causal factors were related to breakdowns in crew communications, over-involvement with the flight management system and, for small (general aviation) aircraft, preoccupation with weather. Analysis of the 83 cases of geographic disorientation suggested that these too occurred at all levels of pilot experience. With regard to causal factors, a majority was related to poor cockpit resource management, in which inattention led to a loss of geographic awareness. Other leading causes were related to poor weather and poor decision making. The potential of the ASRS database for contributing to research and design issues is addressed.

Williams, Henry P.↗
NASA NTRS2004

Managing Content in a Matter of Minutes

NASA software created to help scientists expeditiously search and organize their research documents is now aiding compliance personnel, law enforcement investigators, and the general public in their efforts to search, store, manage, and retrieve documents more efficiently. Developed at Ames Research Center, NETMARK software was designed to manipulate vast amounts of unstructured and semi-structured NASA documents. NETMARK is both a relational and object-oriented technology built on an Oracle enterprise-wide database. To ensure easy user access, Ames constructed NETMARK as a Web-enabled platform utilizing the latest in Internet technology. One of the significant benefits of the program was its ability to store and manage mission-critical data.

Source record↗
NASA NTRS2012

Shuttle Case Study Collection Website Development

As a continuation from summer 2012, the Shuttle Case Study Collection has been developed using lessons learned documented by NASA engineers, analysts, and contractors. Decades of information related to processing and launching the Space Shuttle is gathered into a single database to provide educators with an alternative means to teach real-world engineering processes. The goal is to provide additional engineering materials that enhance critical thinking, decision making, and problem solving skills. During this second phase of the project, the Shuttle Case Study Collection website was developed. Extensive HTML coding to link downloadable documents, videos, and images was required, as was training to learn NASA's Content Management System (CMS) for website design. As the final stage of the collection development, the website is designed to allow for distribution of information to the public as well as for case study report submissions from other educators online.

Ransom, Khadijah S.↗
NASA NTRS2016

Inviscid and Viscous CFD Analysis of Booster Separation for the Space Launch System Vehicle

This paper presents details of Computational Fluid Dynamic (CFD) simulations of the Space Launch System during solid-rocket booster separation using the Cart3D inviscid and Overflow viscous CFD codes. The discussion addresses the use of multiple data sources of computational aerodynamics, experimental aerodynamics, and trajectory simulations for this critical phase of flight. Comparisons are shown between Cart3D simulations and a wind tunnel test performed at NASA Langley Research Center's Unitary Plan Wind Tunnel, and further comparisons are shown between Cart3D and viscous Overflow solutions for the flight vehicle. The Space Launch System (SLS) is a new exploration-class launch vehicle currently in development that includes two Solid Rocket Boosters (SRBs) modified from Space Shuttle hardware. These SRBs must separate from the SLS core during a phase of flight where aerodynamic loads are nontrivial. The main challenges for creating a separation aerodynamic database are the large number of independent variables (including orientation of the core, relative position and orientation of the boosters, and rocket thrust levels) and the complex flow caused by exhaust plumes of the booster separation motors (BSMs), which are small rockets designed to push the boosters away from the core by firing partially in the direction opposite to the motion of the vehicle.

Viscous↗