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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗
NASA NTRS2023

Experimental Investigation of Flow Orientation Effects on Cryogenic Flow Boiling

Cryogenic flow boiling physics is of paramount importance for future cryogenic space applications employing Cryogenic Fluid Management (CFM) technologies. This experimental study investigates the two-phase flow and heat transfer performance of LN 2 flow boiling across five distinct flow orientations: vertical upflow, vertical downflow, horizontal flow, 45° inclined upflow, and 45° inclined downflow. The study employed the steady- state heating method within a circular heated tube featuring an 8.5-mm inner diameter and a 680-mm heated length. High-speed video recordings were utilized to capture two-phase flow patterns and interfacial behaviors across various flow orientations. The experiments covered a wide range of operating conditions, including mass velocities ranging from 351.80 to 1572.77 kg/m 2 s and inlet pressures from 297.14 to 1032.97 kPa, primarily with near-saturated inlet subcooling. Distinct two-phase flow patterns and regime transitions were identified for each flow orientation. Symmetrical flow patterns were evident in vertical orientations, whereas non-vertical orientations exhibited asymmetric flow stratifications, primarily influenced by the buoyancy force in a terrestrial gravity environment. Bubble dynamic parameters were quantified, and bubble collision and dispersion phenomena were visualized. Analyzing heat transfer performance based on local flow boiling curves and variations in heat transfer coefficients (HTCs), it was observed that vertical upflow demonstrated the most enhanced heat transfer performance, while vertical downflow exhibited the lowest. As mass velocity exceeded 830 kg/ m 2 s, the differences in heat transfer among orientations became less distinct, emphasizing the role of flow inertia in mitigating the influence of flow orientation. A direct comparison of microgravity HTC data from a recent study by the authors against the 1-𝘨 e HTC data indicated enhanced heat transfer performance in microgravity for flow orientation configurations in terrestrial gravity. However, this enhancement progressively diminished as the heat flux increased. Distinct HTC trends were observed as mass velocity increased for different flow orientations and gravity levels.

Cryogens↗
DOE OSTI2021

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

Abstract Artificial intelligence (AI) and machine learning (ML) have been increasingly used in materials science to build predictive models and accelerate discovery. For selected properties, availability of large databases has also facilitated application of deep learning (DL) and transfer learning (TL). However, unavailability of large datasets for a majority of properties prohibits widespread application of DL/TL. We present a cross-property deep-transfer-learning framework that leverages models trained on large datasets to build models on small datasets of different properties. We test the proposed framework on 39 computational and two experimental datasets and find that the TL models with only elemental fractions as input outperform ML/DL models trained from scratch even when they are allowed to use physical attributes as input, for 27/39 (≈ 69%) computational and both the experimental datasets. We believe that the proposed framework can be widely useful to tackle the small data challenge in applying AI/ML in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine learning predictions of near-surface permafrost extent at Teller 27, Teller 47, and the Kougarok 64 Hillslope sites on the Seward Peninsula, Alaska: Supporting Data

Geophysical surveys were conducted at the NGEE Arctic Teller mile marker 27 site, Teller mile marker 47 site, and Kougarok mile marker 64 site during the summers of 2018, 2019, and 2021. Additional data was collected at Teller mile marker 47 during September 2021 and August 2022. These surveys were used to identify locations of near-surface permafrost during the period of maximum seasonal thaw depth for ground truth data used in machine learning predictions of near-surface permafrost extent at each site. This dataset contains CSV files of ground truth observations of near-permafrost presence or absence for each site, where PF = 1 indicates permafrost presence and PF = 0 indicates permafrost absence. The dataset also includes 2 sets of binary rasters (WGS84 UTM zone 3) of permafrost extent for each site using 1) all of the training data and 2) the transferred model. For both sets of rasters, 0 = non-permafrost and 1 = permafrost. Included are 6 *.tif files and 5 *.csv files that include a data dictionary (dd.csv) and file-level metadata (flmd.csv). This dataset is in support of the paper "Machine learning-derived high-resolution maps of near-surface permafrost for three watersheds on the Seward Peninsula, Alaska" that is in review (May 2023). The Next-Generation Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1958

Calculated and measured stresses in simple panels subject to intense random acoustic loading including the near noise field of a turbojet engine

Flat 2024-t3 aluminum panels measuring 11 inches by 13 inches were tested in the near noise fields of a 4-inch air jet and turbojet engine. The stresses which were developed in the panels are compared with those calculated by generalized harmonic analysis. The calculated and measured stresses were found to be in good agreement. In order to make the stress calculations, supplementary data relating to the transfer characteristics, damping, and static response of flat and curved panels under periodic loading are necessary and were determined experimentally. In addition, an appendix containing detailed data on the near pressure field of the turbojet engine is included.

Lassiter, Leslie W↗
NASA NTRS2006

Evaluation of Open Cell Foam Heat Transfer Enhancement for Liquid Rocket Engine

As NASA pursues the exploration mission, advanced propulsion for the next generation of spacecraft will be needed. These new propulsion systems will require higher performance and increased durability, despite current limitations on materials. A break-through technology is needed in the thrust chamber. In this paper the idea of using a porous metallic foam is examined for its potential cooling enhancement capabilities. The goal is to increase the chamber wall cooling without creating an additional pressure drop penalty. A feasibility study based on experiments at laboratory-scale conditions was performed and analysis at rocket conditions is underway. In the experiment, heat transfer and pressure drop data were collected using air as the coolant in a copper or nickel foam filled annular channel. The foam-channel performance was evaluated based on comparison with conventional microchannel cooling passages under equal pressure drop conditions. The heat transfer enhancement of the foam channel over the microchannel ranges from 130% to 172%. The enhancement is relatively independent of the pressure drop and increases with decreasing pore size. A direct numerical simulation model of the foam heat exchange has been built. The model is based on the actual metal foam microstructure of thin ligaments (0.2- 0.3 mm in diameter) that form a network of interconnected open-cells. The cell dimension is around 2 mm. The numerical model was built using the FLUENT CFD code. Comparison of the pressure drop results predicted by the current model with those experimental data of Leong and Jin [8] shows favorable comparisons. Pressure drop predictions have been made using hydrogen as a coolant at typical rocket conditions. Conjugate heat transfer analysis using the foam filled channel is planned for the future.

Chung, J. N.↗
NASA NTRS1978

In-flight Compressible Turbulent Boundary Layer Measurements on a Hollow Cylinder at a Mach Number of 3.0

Skin temperatures, shearing forces, surface static pressures, and boundary layer pitot pressures and total temperatures were measured on a hollow cylinder 3.04 meters long and 0.437 meter in diameter mounted beneath the fuselage of the YF-12A airplane. The data were obtained at a nominal free stream Mach number of 3.0 and at wall-to-recovery temperature ratios of 0.66 to 0.91. The free stream Reynolds number had a minimal value of 4.2 million per meter. Heat transfer coefficients and skin friction coefficients were derived from skin temperature time histories and shear force measurements, respectively. Boundary layer velocity profiles were derived from pitot pressure measurements, and a Reynolds analogy factor of 1.11 was obtained from the measured heat transfer and skin friction data. The skin friction coefficients predicted by the theory of van Driest were in excellent agreement with the measurements. Theoretical heat transfer coefficients, in the form of Stanton numbers calculated by using a modified Reynolds analogy between skin friction and heat transfer, were compared with measured values. The measured velocity profiles were compared to Coles' incompressible law-of-the-wall profile.

Quinn, R. D.↗
DOE OSTI2021

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2001

[Limb Scattering Data Analysis]

The primary purpose of this grant was to support analysis of the limb scattering data taken during the 1997 flight of the SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments. Work was done to assess the performance of the retrieval algorithms for cloudy and clear sky cases in preparation for a poster presentation. The nadir-viewing data were also compared to coincident GOME (Global Ozone Monitoring Experiment) data and to radiative transfer calculations. An algorithm similar to the TOMS (Total Ozone Mapping Spectrometer) ozone retrieval algorithm was developed to infer the ozone column amount from the SOLSE nadir data. Comparison with coincident TOMS ozone column data confirmed that column ozone could be derived successfully from SOLSE nadir radiances, and also revealed significant changes in the SOLSE wavelength resolution and absolute radiometric calibration that were subsequently confirmed by comparing the post-flight instrument characterization to the pre-flight characterization, indicating a potentially useful method for monitoring instrument behavior in-flight.

Loughman, Robert↗
NASA NTRS1986

Measurement of airfoil heat transfer coefficients on a turbine stage

The Primary basis for heat transfer analysis of turbine airfoils is experimental data obtained in linear cascades. These data were very valuable in identifying the major heat transfer and fluid flow features of a turbine airfoil. The first program objective is to obtain a detailed set of heat transfer coefficients along the midspan of a stator and a rotor in a rotating turbine stage. The data are to be compared to some standard analysis of blade boundary layer heat transfer which is in use today. A second program objective is to obtain a detailed set of heat transfer coefficients along the midspan of a stator located in the wake of an upstream turbine stage.

Dring, Robert P.↗
DOE OSTI2021

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in information theory, such that it could be found as a fundamental step in many modern compression algorithms such as DEFLATE. On the other hand, today's HPC applications are more and more relying on the accelerators such as GPU on supercomputers, while Huffman encoding suffers from low throughput on GPUs, resulting in a significant bottleneck in the entire data processing. In this paper, we propose and implement an efficient Huffman encoding approach based on modern GPU architectures, which addresses two key challenges: (1) how to parallelize the entire Huffman encoding algorithm, including codebook construction, and (2) how to fully utilize the high memory-bandwidth feature of modern GPU architectures. The detailed contribution is fourfold. (1) We develop an efficient parallel codebook construction on GPUs that scales effectively with the number of input symbols. (2) We propose a novel reduction based encoding scheme that can efficiently merge the codewords on GPUs. (3) We optimize the overall GPU performance by leveraging the state-of-the-art CUDA APIs such as Cooperative Groups. (4) We evaluate our Huffman encoder thoroughly using six real-world application datasets on two advanced GPUs and compare with our implemented multi-threaded Huffman encoder. Experiments show that our solution can improve the encoding throughput by up to 5.0x and 6.8x on NVIDIA RTX 5000 and V100, respectively, over the state-of-the-art GPU Huffman encoder, and by up to 3.3x over the multi-thread encoder on two 28-core Xeon Platinum 8280 CPUs.

Tian, Jiannan↗
NASA NTRS1974

Experimental study of sharp and blunt nose streamwise corners at Mach 20

Extensive heat transfer and pressure distribution data and oil flow studies on sharp and blunt-nose streamwise corners at Mach 20 in helium are presented. The far corner boundary layers on the wedge surfaces forming the corners are laminar for most test conditions. Analysis of the data indicates that the corner flow field geometry can be described in terms of the inviscid shock pattern on the two dimensional surfaces forming the corner. Parameters used to correlate blunt shock growth can be used to correlate features of the flow field observed in oil flow photographs in addition to the measured pressure and heat transfer distributions on the models. The flow field structure is described from available experimental data. Regions of the flow in which the structure still is not known are discussed.

Watson, R. D.↗
NASA NTRS1974

ERTS operations and data processing

The overall communications and data flow between the ERTS spacecraft and the ground stations and processing centers are generally described. Data from the multispectral scanner and the return beam vidicon are telemetered to a primary ground station where they are demodulated, processed, and recorded. The tapes are then transferred to the NASA Data Processing Facility (NDPF) at Goddard. Housekeeping data are relayed from the prime ground stations to the Operations Control Center at Goddard. Tracking data are processed at the ground stations, and the calculated parameters are transmitted by teletype to the orbit determination group at Goddard. The ERTS orbit has been designed so that the same swaths of the ground coverage pattern viewed during one 18-day coverage cycle are repeated by the swaths viewed on all subsequent cycles. The Operations Control Center is the focal point for all communications with the spacecraft. NDPF is a job-oriented facility which processes and stores all sensor data, and which disseminates large quantities of these data to users in the form of films, computer-compatible tapes, and data collection system data.

Gonzales, L.↗
NASA NTRS1982

Perspectives in remote sensing in Brazil. An approach of the remote sensing applications to Earth resources surveys

Since the systematic use of earth surface data collection by orbital sensor systems started in 1972 with the launching of the North American LANDSAT satellite, a great effort has been made to assimilate, develop and transfer remote sensing technology (data acquisition and analysis) in its many applications in Brazil. The availability of sensor systems and existing data is considered approached, as well as those which will soon be available to the Brazilian researchers. The new systems of the LANDSAT-4, of the Columbia space shuttle and of the French satellites of the SPOT series are discussed. Some characteristics of the sensor system for the first Brazilian remote sensing satellite, to be launched by the end of the decade, are presented. Some LANDSAT-4 and SPOT simulation products are shown, emphasizing how the data obtained by these new satellites can be applied.

Parada, N. D. J.↗
NASA NTRS1991

Properties of scatterers in the troposphere and lower stratosphere of Uranus based on Voyager imaging data

Scalar and vector radiative transfer and microphysical models are presently constructed from photometrically and geometrically corrected Voyager images of Uranus defining spatially-resolved intensities over a range of phase angles for two latitude bands. The methane ice cloud occupying 1.2-1.3 bar is of 0.7 optical depth at 22.5 deg S, rising to 2.4 at 65 deg S; the volume absorption coefficient of the cloud particles is 50 percent greater at the low latitude than at the high, assuming constant mean cloud particle size. The scattering model also includes photochemically-produced stratospheric hydrocarbon ices in the upper troposphere and stratosphere, as well as an optically thick hydrogen sulfide cloud.

Rages, Kathy↗
NASA NTRS1991

An evaluation of techniques for the extraction of mineral absorption features from high spectral resolution remote sensing data

Airborne Visible/Infrared Imaging Spectrometer data covering the wavelength range between 2000 and 2400 nm are examined for their ability to display the diagnostic mineral absorption features of certain alteration minerals, employing various data processing techniques. The techniques may be separated into two broad categories: scene based techniques that use parameters derived from the data themselves, and correction techniques utilizing external information such as solar/atmospheric models. Results indicate that the data corrected utilizing the LOWTRAN 7 atmospheric transfer code constrained with local weather station data are the most effective at showing the diagnostic absorption features of the regions of known mineralogy and introduce the least number of artifacts into the data.

Rast, Michael↗