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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Neutron scattering cross section measurements for Fe 56

Elastic and inelastic differential cross sections for neutron scattering from 56 Fe have been measured for several incident energies from 1.30 to 7.96 MeV at the University of Kentucky Accelerator Laboratory. Scattered neutrons were detected using a C 6 D 6 liquid scintillation detector using pulse-shape discrimination and time-of-flight techniques. The deduced cross sections have been compared with previously reported data, predictions from evaluation databases ENDF, JENDL, and JEFF, and theoretical calculations performed using different optical model potentials using the TALYS and EMPIRE nuclear reaction codes. The coupled-channel calculations based on the vibrational and soft-rotor models are found to describe the experimental (n,n 0 ) and (n,n 1 ) cross sections well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Metabolites Annotations and Genes Integrated (MAGI) v1.0

With the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the "omics" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. The 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.

Bowen, Benjamin↗
DOE OSTI2018

xxing9703/PAVE

Untargeted metabolomics can detect more than 10 000 peaks in a single LC–MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/z and C/N atom counts. Application of this procedure to Saccharomyces cerevisiae and Escherichia coli revealed that more than 80% of peaks do not label, i.e., are environmental contaminants. More than 70% of the biological peaks are isotopic variants, adducts, fragments, or mass spectrometry artifacts yielding ∼2000 apparent metabolites across the two organisms. About 650 match to a known metabolite formula based on m/z and C/N atom counts, with 220 assigned structures based on MS/MS and/or retention time to match to authenticated standards. Thus, PAVE enables systematic annotation of LC–MS metabolomics data with only ∼4% of peaks annotated as apparent metabolites.

Xing, Xi↗
DOE OSTI2020

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in deep clay/shale/argillaceous rock. International collaboration activities such as heater tests and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests has as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum vs. discrete) to tackle issues related to flow and transport at various scales of the host-rock and EBS design concept. Consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the EBS design. This is particularly important for backfilled repository concepts where temperature plays a key role in the EBS behavior and long-term performance. This report describes multiple R&D efforts on disposal in argillaceous geologic media through development and application of coupled THMC process models, experimental studies on clay/metal/cement barrier and host-rock (argillite) material interactions, molecular dynamic (MD) simulations of water transport during (swelling) clay dehydration, first-principles studies of metaschoepite (UO 2 corrosion product) stability, and advances in thermodynamic plus surface complexation database development. Drift-scale URL experiments provides key data for testing hydrological-chemical (HC) model involving strong couplings of fluid mixing and barrier material chemical interactions. The THM modeling focuses on heater test experiments in argillite rock and gas migration in bentonite as part of international collaboration activities at underground research laboratories (URLs). In addition, field testing at an URL involves in situ analysis of fault slip behavior and fault permeability. Pore-scale modeling of gas bubble migration is also being investigated within the gas migration modeling effort. Interaction experiments on bentonite samples from heater test under ambient and elevated temperatures permit the evaluation of ion exchange, phase stability, and mineral transformation changes that could impact clay swelling. Advances in the development, testing, and implementation of a spent nuclear fuel (SNF) degradation model coupled with canister corrosion focus on the effects of hydrogen gas generation and its integration with Geologic Disposal Safety Assessment (GDSA). GDSA integration activities includes evaluation of groundwater chemistries in shale formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Effect of Surrogate Fission Products on Thermal Conductivity and Viscosity of NaCl-UCl 3

Thermophysical properties of salt systems relevant to molten salt reactors (MSRs) are experimentally measured in support of the US Department of Energy Office of Nuclear Energy (DOE-NE) MSR campaign within the Advanced Reactor Technology (ART) Program. These property measurements also support the development of the thermophysical arm of the Molten Salt Database (MSD) within DOE-NE’s Nu clear Energy Advanced Modeling and Simulation (NEAMS) Program. Several US Department of Energy (DOE) laboratories, including Oak Ridge National Laboratory (ORNL), have been capitalizing on modern methodologies and sample characterization techniques to conduct thermophysical property measurements to support these programs and to provide MSR developers and modelers with more recent and higher-quality data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Experimental, Computational, Theoretical and Analytical Investigation of Flow Boiling in Reduced Gravity

Two-phase thermal management systems are far superior to their single-phase counterparts because of their ability to capitalize on the coolant’s both sensible and latent heats, thereby yielding orders of magnitude higher heat transfer coefficients and smaller system footprints. A vital knowledge necessary for their implementation in future space systems is performance in microgravity. Long-duration microgravity experiments are necessary to obtain reliable databases, which would then be used to build reliable predictive tools. To achieve this goal, investigators at the Purdue University Boiling and Two-Phase Flow Laboratory (PU-BTPFL) and the NASA Glenn Research Center (NASA-GRC) have been collaborating towards the development of the Flow Boiling and Condensation Experiment (FBCE) and eventual execution onboard the International Space Station (ISS). FBCE has now matured to a point where it is ready for transport to the ISS, where first tests will be conducted using the Flow Boiling Module (FBM). In preparation for the ISS tests, a series of pre-launch Mission Sequence Tests (MSTs) was performed at GRC in Earth gravity with FBM mounted in a vertical upflow orientation using n-perfluorohexane as working fluid. The pre-launch tests included variations of flow rate, surface heat flux, inlet conditions, and both single-sided and double-sided wall heating. This presentation will summarize experimental results from these tests as well as both analytic and theoretical tools for prediction of two-phase heat transfer coefficient and critical heat flux (CHF). Also discussed will be an assessment of predictive accuracy of these tools against the experimental data.

Mission Sequence tests↗
DOE OSTI2025

Development of a TRISO assessment case for BISON based on transient experiments in the NSRR

The tristructural isotropic (TRISO) fuel assessment and validation database currently available in BISON is based mainly on steady-state irradiation and high-temperature furnace testing. Transient assessment cases are needed to support ongoing U.S. industry efforts to design and deploy commercial reactors that utilize TRISO fuels. Most available historical transient tests involving TRISO fuels were characterized by power densities, temperatures, and energy depositions that were highly conservative with respect to typical high-temperature gas-cooled reactor (HTGR) accident conditions. Nonetheless, assessment of BISON's predictive capabilities, adaptation of material properties toward high-temperature and high-particle-power regimes, and development of a systematic approach to validating BISON for TRISO transient applications now motivate the modeling of historical transient tests. This work describes the development of 1-D thermal models of transient experiments conducted at the Nuclear Safety Research Reactor (NSRR) in Japan, with BISON predictions of energy deposition, UO2 melting onset, and molten volume fractions being compared against experimental measurements. Melting is accounted for by defining an effective specific heat capacity for UO2—one that leverages the material's heat of melting. BISON's predictions of energy deposition and molten volume fraction are in good agreement with the experimental data from the low-energy-deposition tests; however, BISON tends to overpredict melting at higher energy depositions. Though overly conservative compared to the operating conditions expected for near-term TRISO-fueled reactor applications, these simulations effectively exercise BISON TRISO models over a wider range of conditions than those encompassed by the existing assessment database. Potential contributors to the observed discrepancies are noted and additional future developments proposed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

High-throughput exploration of the WMoVTaNbAl refractory multi-principal-element alloys under multiple-property constraints

Development of next-generation gas turbines requires the design and fabrication of novel high-temperature structural materials capable of operating beyond 1300°C. Here, we propose a high-throughput alloy design framework under multiple-property constraints to discover new refractory multi-principal element alloys (MPEAs) for high-temperature applications. The framework treats the development of MPEAs as a composition-agnostic constraint satisfaction problem, i.e., no prescriptions are made concerning the design space before performing investigatory calculations. We target alloys in the WMoVTaNbAl chemistry space that are predicted to meet constraints on the following properties simultaneously: single-phase stability, density, solidus temperature, yield strength at 1300°C, and ductile-to-brittle-transition temperature. These properties are relevant to both applications in gas turbines and manufacturability. A set of 214 MoNbV-rich alloys meet these relevant constraints. These feasible alloys are investigated with density functional theory (DFT) to provide a fundamental electronic basis for their superior properties. Three compositionally representative alloys from the feasible design space (Mo 45 Nb 35 Ta 5 V 15 , Mo 25 Nb 50 V 20 W 5 , and Mo 30 Nb 35 Ta 5 V 25 W 5 ) are selected with a k-medoids-based design scheme for detailed DFT analysis and experimental characterization. The DFT analysis predicted a single-phase BCC at high temperatures with a high yield strength for all three MPEAs, in agreement with CALPHAD (CALculation of PHAse Diagrams) and experiments, respectively. These three alloys are benchmarked against a public database of 1546 MPEAs. Concerning the aforementioned constraints, the Mo 30 Nb 35 Ta 5 V 25 W 5 alloy outperforms these 1546 MPEAs. The present work demonstrates the ability of the proposed design methodology to identify candidate alloys for a given application under multiple property constraints in a combinatorically vast design space.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improved departure from nucleate boiling prediction in rod bundles using a physics-informed machine learning-aided framework

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is a regulatory limit for the licensing of pressurized water reactors (PWRs) worldwide. Despite the abundance of predictive tools available to the reactor thermal-hydraulics community, the path for an accurate CHF model remains elusive. This work approaches the prediction of DNB through a physics-informed machine learning-aided framework (PIMLAF) with the objective of achieving superior predictive capabilities for a rod bundle. In view of the limitations in existing macro-scale physics-driven tools, an improved mechanistic model is first proposed, leveraging key concepts in the liquid sublayer dryout and bubble crowding mechanisms. Furthermore, the proposed mechanistic model is able to predict DNB in different heater geometries for a broad range of flow conditions without the need for recalibration. This model is then incorporated as the physics-informed component of the hybrid framework PIMLAF, which takes advantage of established understanding in the field (i.e., domain knowledge [DK]) and uses machine learning (ML) to capture undiscovered information from the mismatch between the actual and DK-predicted output. Two bundle-related case studies using the PWR subchannel and bundle tests (PSBT) database are carried out to illustrate the PIMLAF’s improved performance over traditional approaches for both interpolation and extrapolation purposes. In light of the PIMLAF’s promising potential to reduce prediction error, reactor vendors are encouraged to leverage their in-house experimental efforts and apply the hybrid framework to potentially achieve margin reductions in the minimum DNB ratio (MDNBR) for the designs of interest.

42 ENGINEERING↗
DOE OSTI2022

Analysis of historic fires to determine most frequent challenging events

The fire probabilistic risk assessment framework for nuclear power plants relies on experimental data to determine expected fire behavior or to validate models to predict fire conditions in the plant. To support reducing the uncertainty in this experimental data, a research effort was conducted to identify the most frequent and challenging fire scenarios using historic fire data from nuclear power plants in the United States. To support this effort, an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute was produced resulting in data on 2111 fire events, 540 events were labelled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. In conclusion, of these fire types, electrical and electronic equipment, transient combustibles, and liquid fires were the most frequent of the challenging fires. The fire scenario specifics were characterized for each of the eleven selected types and then related to existing fire experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation

Various databases of density functional theory (DFT) calculations for materials and adsorption properties are currently available. Using the Materials Project and GASpy databases of material stability and binding energies (H* and CO*), respectively, we evaluate multiple aspects of catalysts to discover active, stable, CO-tolerant, and cost-effective hydrogen evolution and oxidation catalysts. Finally, we suggest a few candidate materials for future experimental validations. We highlight that the stability analysis is easily obtainable but provides invaluable information to assess thermodynamic and electrochemical stability, bridging the gap between simulations and experiments. Furthermore, it reduces the number of expensive DFT calculations required to predict catalytic activities of surfaces by filtering out unstable materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data

The accurate interpretation of experiments with matter at extreme densities and pressures is a notoriously difficult challenge. In a recent work [Dornheim et al., Nat. Commun. 13, 7911 (2022)], we have introduced a formally exact methodology that allows extracting the temperature of arbitrary complex materials without any model assumptions or simulations. Here, we provide a more detailed introduction to this approach and analyze the impact of experimental noise on the extracted temperatures. In particular, we extensively apply our method both to synthetic scattering data and to previous experimental measurements over a broad range of temperatures and wave numbers. We expect that our approach will be of high interest to a gamut of applications, including inertial confinement fusion, laboratory astrophysics, and the compilation of highly accurate equation-of-state databases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Progress on the FabrIc for Frontier Experiments project at Fermilab

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. Hence, the progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Content-based retrieval of remote sensed images using a feature-based approach

A feature-based representation model for content-based retrieval from a remote sensed image database is described in this work. The representation is formed by clustering spatially local pixels, and the cluster features are used to process several types of queries which are expected to occur frequently in the context of remote sensed image retrieval. Preliminary experimental results show that the feature-based representation provides a very promising tool for content-based access.

Vellaikal, Asha↗
NASA NTRS2000

Neural Network Based Representation of UH-60A Pilot and Hub Accelerations

Neural network relationships between the full-scale, experimental hub accelerations and the corresponding pilot floor vertical vibration are studied. The present physics-based, quantitative effort represents an initial systematic study on the UH-60A Black Hawk hub accelerations. The NASA/Army UH-60A Airloads Program flight test database was used. A 'maneuver-effect-factor (MEF)', derived using the roll-angle and the pitch-rate, was used. Three neural network based representation-cases were considered. The pilot floor vertical vibration was considered in the first case and the hub accelerations were separately considered in the second case. The third case considered both the hub accelerations and the pilot floor vertical vibration. Neither the advance ratio nor the gross weight alone could be used to predict the pilot floor vertical vibration. However, the advance ratio and the gross weight together could be used to predict the pilot floor vertical vibration over the entire flight envelope. The hub accelerations data were modeled and found to be of very acceptable quality. The hub accelerations alone could not be used to predict the pilot floor vertical vibration. Thus, the hub accelerations alone do not drive the pilot floor vertical vibration. However, the hub accelerations, along with either the advance ratio or the gross weight or both, could be used to satisfactorily predict the pilot floor vertical vibration. The hub accelerations are clearly a factor in determining the pilot floor vertical vibration.

Kottapalli, Sesi↗
NASA NTRS2015

Unsteady Pressures on a Generic Capsule Shape

While developing the aerodynamic database for the Orion spacecraft, the low-speed flight regime (transonic and below) proved to be the most difficult to predict and measure accurately. The flow over the capsule heat shield in descent flight was particularly troublesome for both computational and experimental efforts due to its unsteady nature and uncertainty about the boundary layer state. The data described here were acquired as part of a study to improve the understanding of the overall flow around a generic capsule. The unsteady pressure measurements acquired on a generic capsule shape are presented along with a discussion about the effects of various flight conditions and heat-shield surface roughness on the resulting pressure fluctuations.

Wake Flow↗
DOE OSTI2017

In silico environmental chemical science: properties and processes from statistical and computational modelling

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Open Rotor Tone Shielding Methods for System Noise Assessments Using Multiple Databases

Advanced aircraft designs such as the hybrid wing body, in conjunction with open rotor engines, may allow for significant improvements in the environmental impact of aviation. System noise assessments allow for the prediction of the aircraft noise of such designs while they are still in the conceptual phase. Due to significant requirements of computational methods, these predictions still rely on experimental data to account for the interaction of the open rotor tones with the hybrid wing body airframe. Recently, multiple aircraft system noise assessments have been conducted for hybrid wing body designs with open rotor engines. These assessments utilized measured benchmark data from a Propulsion Airframe Aeroacoustic interaction effects test. The measured data demonstrated airframe shielding of open rotor tonal and broadband noise with legacy F7/A7 open rotor blades. Two methods are proposed for improving the use of these data on general open rotor designs in a system noise assessment. The first, direct difference, is a simple octave band subtraction which does not account for tone distribution within the rotor acoustic signal. The second, tone matching, is a higher-fidelity process incorporating additional physical aspects of the problem, where isolated rotor tones are matched by their directivity to determine tone-by-tone shielding. A case study is conducted with the two methods to assess how well each reproduces the measured data and identify the merits of each. Both methods perform similarly for system level results and successfully approach the experimental data for the case study. The tone matching method provides additional tools for assessing the quality of the match to the data set. Additionally, a potential path to improve the tone matching method is provided.

Bahr, Christopher J.↗