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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Reduction and analysis of ATS-6 data

A data reduction program was developed and debugged which presents the Aerospace particle data and the UCLA magnetometer data in a variety of formats suitable for analysis as well as further data processing. Fifty days of data were processed through this program and analysis of these data were begun. In addition, modifications were made to an old ATS-1 program in order to enable this program to process ATS-1 data obtained simultaneously with ATS-6 data acquisitions during 1974. Some analysis of ATS-1 data and comparison with ATS-6 data also went forward. Preparations were begun to transfer ATS-6 data to the National Space Science Data Center. These efforts are described in detail.

Paulikas, G. A.↗
NASA NTRS1988

The GONG Data Reduction and Analysis System

Each of the six GONG observing stations will produce three, 16-bit, 256X256 images of the Sun every 60 sec of sunlight. These data will be transferred from the observing sites to the GONG Data Management and Analysis Center (DMAC), in Tucson, on high-density tapes at a combined rate of over 1 gibabyte per day. The contemporaneous processing of these data will produce several standard data products and will require a sustained throughput in excess of 7 megaflops. Peak rates may exceed 50 megaflops. Archives will accumulate at the rate of approximately 1 terabyte per year, reaching nearly 3 terabytes in 3 yr of observing. Researchers will access the data products with a machine-independent GONG Reduction and Analysis Software Package (GRASP). Based on the Image Reduction and Analysis Facility, this package will include database facilities and helioseismic analysis tools. Users may access the data as visitors in Tucson, or may access DMAC remotely through networks, or may process subsets of the data at their local institutions using GRASP or other systems of their choice. Elements of the system will reach the prototype stage by the end of 1988. Full operation is expected in 1992 when data acquisition begins.

Pintar, James A.↗
NASA NTRS1984

The relation of flux transfer events to magnetic reconnection

Preliminary results of a search for heat-transfer signatures in electron data on 31 flux-transfer events (FTEs) are reported. Strong acceleration or deceleration, large parallel pressure anisotropies, and temperatures and densities between those of the magnetosphere and the magnetosheath are commonly observed within the surface of the flux-transfer interval defined by the heat-flow peaks, with some evidence of field-aligned ionospheric electrons. A theoretical model is developed to explain some of the observations and illustrated with diagrams. Dynamical tests on a large well-resolved FTE show that the data are consistent with a one-sided passage of the probe into and out of a rotational shear layer.

Scudder, J. D.↗
DOE OSTI2024

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗
DOE OSTI2020

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Transitioning CMS to Rucio Data Managment

Following a thorough review in 2018, the CMS experiment at the CERN LHC decided to adopt Rucio as its new data management system. Rucio is emerging as a community software project and will replace an aging CMSonly system before the start-up of LHC Run 3 in 2021. Rucio was chosen after an evaluation determined that Rucio could meet the technical and scale needs of CMS. The data management system for CMS needs to manage the current data sample of approximately 200 PB of data with 1 PB of transfers per day. The data management system must also have a development path suitable for LHC Run 4 (2026) data rates, which are expected to be 50 times larger.This contribution details the ongoing CMS adoption process as we replace our legacy system with Rucio, focusing on the challenges of integrating Rucio into an established set of experimental tools and procedures. This will include the migration of metadata, the construction of interfaces to the rest of the CMS computing tools, scale tests, operations, monitoring, and the plan to gradually turn over primary responsibility for the management of data to Rucio. A description of CMS user data management with Rucio will also be provided.

Vaandering, Eric↗
NASA NTRS1992

Heat transfer with very high free-stream turbulence. I - Experimental data. II - Analysis of results

Boundary layer heat transfer with very high freestream turbulence is investigated. The problem is studied experimentally by placing a constant-temperature heat transfer surface at various locations in the margin of a turbulent free jet and measuring both the surface heat transfer rate and the turbulence in the freestream. Freestream turbulent fluctuations 20 to 60 percent relative to the mean velocity augment heat transfer 1.8 to 4 times that which would be predicted locally using accepted correlations for turbulent boundary layers at the same Reynolds number. The correlations of Simonich and Bradshaw (1989), Pedisius et al. (1983), and Blair (1983) each fail to describe the present data. For flows over flat surfaces in air with very high freestream turbulence, greater than 0.2, u-prime determines h. A new heat transfer parameter, St-prime, characterizes turbulent boundary layer heat transfer with freestream turbulence on the domain 0-0.65 to within +/- 15 percent for high Reynolds number flows with uniform thermal boundary conditions.

Maciejewski, P. K.↗
DOE OSTI2024

Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems

Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.

asset health management↗
DOE OSTI2021

Predicting fault slip via transfer learning

Abstract Data-driven machine-learning for predicting instantaneous and future fault-slip in laboratory experiments has recently progressed markedly, primarily due to large training data sets. In Earth however, earthquake interevent times range from 10’s-100’s of years and geophysical data typically exist for only a portion of an earthquake cycle. Sparse data presents a serious challenge to training machine learning models for predicting fault slip in Earth. Here we describe a transfer learning approach using numerical simulations to train a convolutional encoder-decoder that predicts fault-slip behavior in laboratory experiments. The model learns a mapping between acoustic emission and fault friction histories from numerical simulations, and generalizes to produce accurate predictions of laboratory fault friction. Notably, the predictions improve by further training the model latent space using only a portion of data from a single laboratory earthquake-cycle. The transfer learning results elucidate the potential of using models trained on numerical simulations and fine-tuned with small geophysical data sets for potential applications to faults in Earth.

58 GEOSCIENCES↗
DOE OSTI2024

Experimental Study on Flow Condensation of Low Global Warming Potential Refrigerants in a Micro-fin Aluminum Tube

This study investigates the dynamic shifts in refrigerant technologies driven by environmental regulations, particularly emphasizing low global warming potential (GWP). Moreover, there is a rising trend in the adoption of aluminum tubes with internal axial micro-fin structures in heat exchangers to reduce costs. The research focuses on the condensation process within an expanded axial micro-fin aluminum tube with a 5.96 mm fin-tip diameter. Various refrigerants are analyzed, including both single compounds (R-32, R-1234yf, R-1234ze(E)) and zeotropic mixtures (R-454B, R-454C, R-455A). Experimental procedures cover a range of condensation temperatures (35~45 °C), reduced pressures (0.21~0.55), and mass fluxes (150~350 kg/(m² s)), providing crucial data on heat transfer coefficients (HTC) and frictional pressure gradient (FPG). This data is particularly significant for high-glide refrigerants and is instrumental in the design of advanced air conditioning and refrigeration systems aimed at mitigating global warming.

Hu, Yifeng↗
NASA NTRS1960

Heat-Transfer Coefficients for a Full-Scale Pebble-Bed Heater

Large quantities of high-temperature air are needed for work with hypersonic flight problems. At temperatures above 2500 degrees Reamur, where conventional heat exchangers have exceeded their material limits, regenerative pebble-bed exchangers may be used with high-temperature refractories. The design of such a heat exchanger requires the use of reliable heat-transfer coefficients for a packed bed. Considerable data are available on the subject, but they spread over two orders of magnitude at any one Reynolds number value. The facility from which the present data were obtained is used at the Lewis Research Center (NASA) for testing air-breathing engine components. The purpose of this work was to obtain heat-transfer data during the initial operation of the bed as a guide to the design of similar equipment. The facility was designed with a conservative estimate of the heat-transfer coefficient, and is shown schematically. Temperatures throughout the packing were measured continuously so that point values of the coefficient might be obtained.

Lancashire, R. B.↗
NASA NTRS1978

Aerothermodynamic Assessment of Corrugated Panel Thermal Protection Systems

The feasibility of using corrugated panels as a thermal protection system for an advanced space transportation vehicle was investigated. The study consisted of two major tasks: development of improved correlations for wind tunnel heat transfer and pressure data to yield design techniques, and application of the design techniques to determine if corrugated panels have application future aerospace vehicles. A single-stage-to-orbit vehicle was used to assess advantages and aerothermodynamic penalties associated with use of such panels. In the correlation task, experimental turbulent heat transfer and pressure data obtained on corrugation roughened surfaces during wind tunnel testing were analyzed and compared with flat plate data. The correlations and data comparisons included the effects of a large range of geometric, inviscid flow, internal boundary layer, and bulk boundary layer parameters in supersonic and hypersonic flow.

Brandon, H. J.↗
NASA NTRS1994

Measurements of the Influence of Integral Length Scale on Stagnation Region Heat Transfer

The purpose was twofold: first, to determine if a length scale existed that would cause the greatest augmentation in stagnation region heat transfer for a given turbulence intensity and second, to develop a prediction tool for stagnation heat transfer in the presence of free stream turbulence. Toward this end, a model with a circular leading edge was fabricated with heat transfer gages in the stagnation region. The model was qualified in a low turbulence wind tunnel by comparing measurements with Frossling's solution for stagnation region heat transfer in a laminar free stream. Five turbulence generating grids were fabricated; four were square mesh, biplane grids made from square bars. Each had identical mesh to bar width ratio but different bar widths. The fifth grid was an array of fine parallel wires that were perpendicular to the axis of the cylindrical leading edge. Turbulence intensity and integral length scale were measured as a function of distance from the grids. Stagnation region heat transfer was measured at various distances downstream of each grid. Data were taken at cylinder Reynolds numbers ranging from 42,000 to 193,000. Turbulence intensities were in the range 1.1 to 15.9 percent while the ratio of integral length scale to cylinder diameter ranged from 0.05 to 0.30. Stagnation region heat transfer augmentation increased with decreasing length scale. An optimum scale was not found. A correlation was developed that fit heat transfer data for the square bar grids to within +4 percent. The data from the array of wires were not predicted by the correlation; augmentation was higher for this case indicating that the degree of isotropy in the turbulent flow field has a large effect on stagnation heat transfer. The data of other researchers are also compared with the correlation.

Vanfossen, G. James↗
NASA NTRS1999

Revisit to the RXTE and ASCA Data for GRO J1655-40: Effects of Radiative Transfer in Corona and Color Hardening in the Disk

The results of spectral modeling of the data for a series of RXTE observations and four ASCA observations of GRO J1655-40 are presented. The thermal Comptonization model is used instead of the power-law model for the hard component of the two-component continuum spectra. The previously reported dramatic variations of the apparent inner disk radius of GRO J1655-40 during its outburst may be due to the inverse Compton scattering in the hot corona. A procedure is developed for making the radiative transfer correction to the fitting parameters from RXTE data and a more stable inner disk radius is obtained. A practical process of determining the color correction (hardening) factor from observational data is proposed and applied to the four ASCA observations of GRO J1655-40. We found that the color correction factor may vary significantly between different observations and the finally corrected physical inner disk radius remains reasonably stable over a large range of luminosity and spectral states.

Zhang, S. Nan↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
NASA NTRS1973

Mach number and Reynolds number effect on orbiter/tank interference heating.

Analysis of the variations in orbiter/tank interference heating rates in the Space Shuttle configuration at M numbers up to 19 and Re numbers down to 250,000. Experimental data on heat transfer rate distribution in the tank and on orbiter-induced interference heat transfer factors in the tank are included in diagrams. The data suggest that the primary effect of interference can be a fully developed turbulent boundary layer.

Creel, T. R., Jr.↗