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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 1,261 records · Page 70

Data-Centric AI and the Open Energy Data Initiative (OEDI)

This presentation emphasizes the critical importance of data-centric AI. The limitations of model-centric AI when dealing with poor or insufficient data are highlighted, and it is illustrated how training models on inaccurate or noisy data leads to suboptimal results. This talk advocates for a hybrid approach that combines a focus on data quality and model parameters to achieve optimal results. The Open Energy Data Initiative (OEDI) is introduced as a valuable resource for obtaining high-quality energy-related datasets, hosting nearly 2,000 publicly accessible datasets, including 99 solar-related datasets, totaling over 2.7 petabytes of data. OEDI's data lakes enable users to query and work with data without extensive transfers. In conclusion, the significance of data-centric AI and adherence to data curation best practices is emphasized, positioning OEDI as a prime source of high-quality data for AI and machine learning in the renewable energy sector.

AI↗

Determination of lateral-stability derivatives and transfer-function coefficients from frequency-response data for lateral motions

A method is presented for determining the lateral-stability derivatives, transfer-function coefficients, and the modes for lateral motion from frequency-response data for a rigid aircraft. The method is based on the application of the vector technique to the equations of lateral motion, so that the three equations of lateral motion can be separated into six equations. The method of least squares is then applied to the data for each of these equations to yield the coefficients of the equations of lateral motion from which the lateral-stability derivatives and lateral transfer-function coefficients are computed. Two numerical examples are given to demonstrate the use of the method.

Donegan, James J↗

Computer method for identification of boiler transfer functions

Iterative computer aided procedure was developed which provides for identification of boiler transfer functions using frequency response data. Method uses frequency response data to obtain satisfactory transfer function for both high and low vapor exit quality data.

Miles, J. H.↗

The distribution of reconnection geometry in flux transfer events using energetic ion, plasma and magnetic data

The distribution of energetic ion anisotropies in flux transfer events (FTEs) about the dayside magnetopause has been determined for ISEE 2 crossings of the boundary in 1977 and 1978. When the events are sorted according to the sign of the east-west component of the magnetic field in the magnetosphere, a clear correlation is observed on the northern morningside. When the field is eastward, particles flow antiparallel to the field, implying field line connection to the Northern Hemisphere; when the field is westward, the opposite is true. On the afternoonside, the particle anisotropies are correlated with latitude. Explanations for this pattern are discussed which involve FTE formation at low latitudes with subsequent motion at a velocity given by the vector superposition of the Alfven velocity from the release of magnetic tension and the magnetosheath bulk flow velocity. Evidence that the geomagnetic and not the geocentric solar magnetospheric equator is the source of FTEs is considered.

Daly, P. W.↗

Enhancements to the SSME transfer function modeling code

This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.

Irwin, R. Dennis↗

Condensation heat transfer and pressure drop of low-global warming potential refrigerants in smooth aluminum tubes

In this work we report condensation heat transfer coefficient and pressure drop data for R-454B, R-32, and R-454C. These refrigerants are low Global Warming Potential (GWP) replacements for R-410A. We obtained these data in a smooth 7.2 mm outer diameter (5.94 mm inner diameter) aluminum tube. In these experiments, the key variables were condensation temperature (35 °C ≤ T cond ≤ 50 °C) and refrigerant mass flux (151.1 ≤ G ≤ 347.3 kg m –2 s –1 ). In general, for similar nominal operating conditions, we measured the highest heat transfer coefficients for R-32 and the lowest for R-454C. Among the correlations we used to predict the heat transfer data for all three refrigerants, the one developed by Thome et al. (2003) predicted the data with the greatest accuracy. Deviations between experimental data and predictions of this correlation were 21.7% for R-454B (with SBG correction), 22.0% for R-32, and 18.8% for R-454C (with SBG correction). Experimental pressure gradient data were predicted by the Friedel correlation Friedel (1979) with deviations of 13.8% for R-454B, 9.8% for R-32, and 10.2% for R-454C. In this work, we also compare the predictions of the Cavallini et al. correlation Cavallini et al. (2006) for R-454B and R-32 in smooth copper versus smooth aluminum tubes. To improve this correlation’s predictive capability for aluminum tubes, we have proposed some modifications. After incorporating these modifications, the deviations between the correlation’s predictions and our data were 10% for R-454B (with SBG correction), 8.1% for R-32, and 5.2% for R-454C (with SBG correction). Furthermore, these data and findings will assist the HVAC and refrigeration industry to implement low-GWP refrigerants in condensers using smooth aluminum tubes.

Aluminum tube↗

Data storage and retrieval system

The Data Storage and Retrieval System (DSRS) consists of off-the-shelf system components integrated as a file server supporting very large files. These files are on the order of one gigabyte of data per file, although smaller files on the order of one megabyte can be accommodated as well. For instance, one gigabyte of data occupies approximately six 9 track tape reels (recorded at 6250 bpi). Due to this large volume of media, it was desirable to shrink the size of the proposed media to a single portable cassette. In addition to large size, a key requirement was that the data needs to be transferred to a (VME based) workstation at very high data rates. One gigabyte (GB) of data needed to be transferred from an archiveable media on a file server to a workstation in less than 5 minutes. Equivalent size, on-line data needed to be transferred in less than 3 minutes. These requirements imply effective transfer rates on the order of four to eight megabytes per second (4-8 MB/s). The DSRS also needed to be able to send and receive data from a variety of other sources accessible from an Ethernet local area network.

Nakamoto, Glen↗

Data storage and retrieval system

The Data Storage and Retrieval System (DSRS) consists of off-the-shelf system components integrated as a file server supporting very large files. These files are on the order of one gigabyte of data per file, although smaller files on the order of one megabyte can be accommodated as well. For instance, one gigabyte of data occupies approximately six 9-track tape reels (recorded at 6250 bpi). Due to this large volume of media, it was desirable to 'shrink' the size of the proposed media to a single portable cassette. In addition to large size, a key requirement was that the data needs to be transferred to a (VME based) workstation at very high data rates. One gigabyte (GB) of data needed to be transferred from an archiveable media on a file server to a workstation in less than 5 minutes. Equivalent size, on-line data needed to be transferred in less than 3 minutes. These requirements imply effective transfer rates on the order of four to eight megabytes per second (4-8 MB/s). The DSRS also needed to be able to send and receive data from a variety of other sources accessible from an Ethernet local area network.

Nakamoto, Glen↗

Space shuttle: Heat transfer rate measurements on Convair booster (B-15B-2) at nominal Mach number of 8

Plotted and tabulated data on heat transfer from a thin-skin thermocouple are presented. The data is representative of the reentry event of the booster alone configuration. The data were generated during wind tunnel tests of the B-15B-2 delta wing booster at Mach 8. Thermocouple measurements are reduced to heat transfer coefficient ratio and the data are presented as plotted variations versus longitudinal, lateral, and vertical local model positions.

Warmbrod, J. D.↗

In Tube Condensation Heat Transfer and Pressure Drop for R454B and R32—Potential Replacements for R410A

The heating, ventilation and air conditioning (HVAC) industry in the United States seeks near-term alternative refrigerants to replace R-410A in unitary equipment. Two potential replacement refrigerants are R-454B and R-32. It is of interest to investigate the capability and accuracy of existing heat exchanger design methods when applied to these replacement refrigerants. To that end, this work presents empirical condensation quasi-local heat transfer coefficient and pressure drop data for R-454B and R-32. These data were obtained in a $\frac{3}{8}$ in. (9.52 mm) outside diameter (OD) smooth copper tube with a wall thickness of 0.032 in. (0.81 mm). The experimental variables and their ranges included refrigerant absolute pressure ( 1960 ≤ P a b s ≤ 3196 kPa), condensation temperature ( 35 ≤ T c o n d ≤ 50 °C), mass flux ( 100 ≤ G ≤ 200 kg m -2 s -1 ), vapor quality ( 0 ≤ x ≤ 1 ), and heat flux ( 32.9 ≤ q ″ ≤ 62.97 kW m -2 ). It was found that the heat transfer correlation developed by Cavallini et al. Cavallini et al. (2006) predicted the experimental condensation heat transfer data, for both R-454B and R-32, with the greatest accuracy. Using the Cavallini et al. correlation, it was found that the mean absolute percentage error (MAPE) was 10.5% and 15.1% for R-454B and R-32, respectively. Additionally, the pressure drop correlation developed by Friedel Friedel (1979) predicted the experimentally determined pressure gradient with a MAPE of 7.7% and 5.5% for R-454B and R-32, respectively. These results will assist the practicing thermal engineer to choose the most appropriate design correlation for these near-term replacement refrigerants.

42 ENGINEERING↗

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗

JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows

In modern science, the growing complexity of large-scale scientific projects has led to an increasing reliance on cross-facility scientific workflows, where resources and expertise from multiple institutions and geographic locations are leveraged to accelerate scientific discovery. These workflows often require transmitting huge amounts of scientific data through wide-area networks. Although high-speed networks like ESnet and transfer services such as Globus have improved data mobility, several challenges remain. The sheer volume of data can overwhelm network bandwidth, widely used transport protocols such as TCP suffer from inefficiencies due to retransmissions triggered by packet loss, and existing fault-tolerance mechanisms like erasure coding introduce substantial overhead. In this paper, we propose Janus, a resilient and adaptable data transmission approach designed for cross-facility scientific workflows. Unlike traditional TCP-based methods, Janus leverages UDP, integrates erasure coding for fault tolerance, and combines it with error-bounded lossy compression to reduce overhead. This novel design allows users to balance data transmission time and accuracy, optimizing transfer performance based on specific scientific requirements. Additionally, Janus dynamically adjusts erasure coding parameters in response to real-time network conditions, ensuring efficient data transfers even in fluctuating environments. We develop optimization models for determining ideal configurations and implement adaptive data transfer protocols to enhance reliability. Through extensive simulations and real-network experiments, we demonstrate that Janus significantly improves transfer efficiency while maintaining data fidelity.

Esaulov, Vladislav [Georgia State University, Atla↗

Experimental Investigation of Average Heat-Transfer and Friction Coefficients for Air Flowing in Circular Tubes Having Square-Thread-Type Roughness

An investigation of forced-convection heat transfer and associated pressure drops was conducted with air flowing through electrically heated Inconel tubes having various degrees of square-thread-type roughness, an inside diameter of 1/2 inch, and a length of 24 inches. were obtained for tubes having conventional roughness ratios (height of thread/radius of tube) of 0 (smooth tube), 0.016, 0.025, and 0.037 over ranges of bulk Reynolds numbers up to 350,000, average inside-tube-wall temperatures up to 1950deg R, and heat-flux densities up to 115,000 Btu per hour per square foot. Data The experimental data showed that both heat transfer and friction increased with increase in surface roughness, becoming more pronounced with increase in Reynolds number; for a given roughness, both heat transfer and friction were also influenced by the tube wall-to-bulk temperature ratio. Good correlation of the heat-transfer data for all the tubes investigated was obtained by use of a modification of the conventional Nusselt correlation parameters wherein the mass velocity in the Reynolds number was replaced by the product of air density evaluated at the average film temperature and the so-called friction velocity; in addition, the physical properties of air were evaluated at the average film temperature. The isothermal friction data for the rough tubes, when plotted in the conventional manner, resulted in curves similar to those obtained by other investigators; that is, the curve for a given roughness breaks away from the Blasius line (representing turbulent flow in smooth tubes) at some value of Reynolds number, which decreases with increase in surface roughness, and then becomes a horizontal line (friction coefficient independent of Reynolds number). A comparison of the friction data for the rough tubes used herein indicated that the conventional roughness ratio is not an adequate measure of relative roughness for tubes having a square-thread-type element. The present data, as well as those of other investigators, were used to isolate the influence of ratios of thread height to width, thread spacing to width, and the conventional roughness ratio on the friction coefficient. A fair correlation of the friction data was obtained for each tube with heat addition when the friction coefficient and Reynolds number were defined on the basis of film properties; however, the data for each tube retained the curve characteristic of that particular roughness. The friction data for all the rough tubes could be represented by a single line for the complete turbulence region by incorporating a roughness parameter in the film correlation. No correlation was obtained for the region of incomplete turbulence.

Sams, E. W.↗

Place polarized neutron reflectivity data in bins of constant wavevector transfer

Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel. The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data. The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections. A future intention is to create a version of this code that will be one module of many in the data analysis workflow.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗

High Density Digital Data Storage System

The High Density Digital Data Storage System was designed to provide a cost effective means for storing real-time data from the field-deployable digital acoustic measurement system. However, the high density data storage system is a standalone system that could provide a storage solution for many other real time data acquisition applications. The storage system has inputs for up to 20 channels of 16-bit digital data. The high density tape recorders presently being used in the storage system are capable of storing over 5 gigabytes of data at overall transfer rates of 500 kilobytes per second. However, through the use of data compression techniques the system storage capacity and transfer rate can be doubled. Two tape recorders have been incorporated into the storage system to produce a backup tape of data in real-time. An analog output is provided for each data channel as a means of monitoring the data as it is being recorded.

Wright, Kenneth D., II↗

Transfer function characteristics of super resolving systems

Signal quality in an optical storage device greatly depends on the optical system transfer function used to write and read data patterns. The problem is similar to analysis of scanning optical microscopes. Hopkins and Braat have analyzed write-once-read-many (WORM) optical data storage devices. Herein, transfer function analysis of magnetooptic (MO) data storage devices is discussed with respect to improving transfer-function characteristics. Several authors have described improving the transfer function as super resolution. However, none have thoroughly analyzed the MO optical system and effects of the medium. Both the optical system transfer function and effects of the medium of this development are discussed.

Milster, Tom D.↗

Data-Driven Reduced-Order Modeling of Convective Heat Transfer in Porous Media

This work presents a data-driven Reduced-Order Model (ROM) for parametric convective heat transfer problems in porous media. The intrusive Proper Orthogonal Decomposition aided Reduced-Basis (POD-RB) technique is employed to reduce the porous medium formulation of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations coupled with heat transfer. Instead of resolving the exact flow configuration with high fidelity, the porous medium formulation solves a homogenized flow in which the fluid-structure interactions are captured via volumetric flow resistances with nonlinear, semi-empirical friction correlations. A supremizer approach is implemented for the stabilization of the reduced fluid dynamics equations. The reduced nonlinear flow resistances are treated using the Discrete Empirical Interpolation Method (DEIM), while the turbulent eddy viscosity and diffusivity are approximated by adopting a Radial Basis Function (RBF) interpolation-based approach. The proposed method is tested using a 2D numerical model of the Molten Salt Fast Reactor (MSFR), which involves the simulation of both clean and porous medium regions in the same domain. For the steady-state example, five model parameters are considered to be uncertain: the magnitude of the pumping force, the external coolant temperature, the heat transfer coefficient, the thermal expansion coefficient, and the Prandtl number. For transient scenarios, on the other hand, the coastdown-time of the pump is the only uncertain parameter. The results indicate that the POD-RB-ROMs are suitable for the reduction of similar problems. The relative L2 errors are below 3.34% for every field of interest for all cases analyzed, while the speedup factors vary between 54 (transient) and 40,000 (steady-state).

German, Péter (ORCID:0000000307285283)↗

Optimizing Error-Bounded Lossy Compression for Scientific Data by Dynamic Spline Interpolation

Today's scientific simulations are producing vast volumes of data that cannot be stored and transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and network bandwidth. The situation is getting worse over time because of the ever-increasing gap between relatively slow data transfer speed and fast-growing computation power in modern supercomputers. Error-bounded lossy compression is becoming one of the most critical techniques for resolving the big scientific data issue, in that it can significantly reduce the scientific data volume while guaranteeing that the reconstructed data is valid for users because of its compression-error-bounding feature. In this paper, we present a novel error-bounded lossy compressor based on a state-of-the-art prediction-based compression framework. Our solution exhibits substantially better compression quality than all of the existing error-bounded lossy compressors, with comparable compression speed. Specifically, our contribution is threefold. (1) We provide an in-depth analysis of why the best-existing prediction-based lossy compressor can only minimally improve the compression quality. (2) We propose a dynamic spline interpolation approach with a series of optimization strategies that can significantly improve the data prediction accuracy, substantially improving the compression quality in turn. (3) We perform a thorough evaluation using six real-world scientific simulation datasets across different science domains to evaluate our solution vs. all other related works. Experiments show that the compression ratio of our solution is higher than that of the second-best lossy compressor by 20%similar to 460% with the same error bound in most of the cases.

Zhao, Kai↗