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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 1,585 records · Page 88

Measurements of Heat Transfer, Flow, and Pressures in a Simulated Turbine Blade Internal Cooling Passage

An experimental study was made to obtain quantitative information on heat transfer, flow, and pressure distribution in a branched duct test section that had several significant features of an internal cooling passage of a turbine blade. The objective of this study was to generate a set of experimental data that could be used for validation of computer codes that would be used to model internal cooling. Surface heat transfer coefficients and entrance flow conditions were measured at nominal entrance Reynolds numbers of 45,000, 335,000, and 726,000. Heat transfer data were obtained by using a steady-state technique in which an Inconel heater sheet is attached to the surface and coated with liquid crystals. Visual and quantitative flow-field data from particle image velocimetry measurements for a plane at midchannel height for a Reynolds number of 45,000 were also obtained. The flow was seeded with polystyrene particles and illuminated by a laser light sheet. Pressure distribution measurements were made both on the surface with discrete holes and in the flow field with a total pressure probe. The flow-field measurements yielded flow-field velocities at selected locations. A relatively new method, pressure sensitive paint, was also used to measure surface pressure distribution. The pressure paint data obtained at Reynolds numbers of 335,000 and 726,000 compared well with the more standard method of measuring pressures by using discrete holes.

Russell, Louis M.↗

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗

High Resolution Far-Infrared Studies of Compact Regions in Star-Forming Molecular Clouds

This grant supported the acquisition, analysis and publication of high spatial resolution observations of the far-infrared emission from compact regions of star-forming molecular clouds using the Kuiper Airborne Observatory. We studied regions which are forming stars of low and intermediate mass. In analyzing the data, we utilized radiative transfer codes, incorporating disk models and envelopes, including departures from spherical symmetry. These data, along with data at other wavelengths, were used to probe the distribution of dust temperature and density around young stars and to test theoretical predictions about star formation.

Mundy, Lee G.↗

System and method for forward error correction

A system and method are provided for transferring a packet across a data link. The packet may include a stream of data symbols which is delimited by one or more framing symbols. Corruptions of the framing symbol which result in valid data symbols may be mapped to invalid symbols. If it is desired to transfer one of the valid data symbols that has been mapped to an invalid symbol, the data symbol may be replaced with an unused symbol. At the receiving end, these unused symbols are replaced with the corresponding valid data symbols. The data stream of the packet may be encoded with forward error correction information to detect and correct errors in the data stream.

Cole, Robert M.↗

Orbital flight test Shuttle External Tank flowfield and aerothermal analysis

This paper discusses the evaluation of aerothermal flight measurements made on the orbital flight test Space Shuttle External Tanks (ET). These ETs were instrumented to measure various quantities during flight including heat transfer, pressure and structural temperature. The flight data were reduced and analyzed against math models established from an extensive wind tunnel data base and empirical heat-transfer relationships. This analysis has supported the validity of the current aeroheating methodology and existing data base, but has also identified some problem areas which require methodology modifications.

Praharaj, S. C.↗

Orbital flight test shuttle external tank aerothermal flight evaluation, volume 1

This 3-volume report discusses the evaluation of aerothermal flight measurements made on the orbital flight test Space Shuttle External Tanks (ETs). Six ETs were instrumented to measure various quantities during flight; including heat transfer, pressure, and structural temperature. The flight data was reduced and analyzed against math models established from an extensive wind tunnel data base and empirical heat-transfer relationships. This analysis has supported the validity of the current aeroheating methodology and existing data base; and, has also identified some problem areas which require methodology modifications. This is Volume 1, an Executive Summary. Volume 2 contains Appendices A (Aerothermal Comparisons) and B (Flight Derived h sub 1/h sub u vs. M sub inf. Plots), and Volume 3 contains Appendix C (Comparison of Interference Factors among OFT Flight, Prediction and 1H-97A Data), Appendix D (Freestream Stanton Number and Reynolds Number Correlation for Flight and Tunnel Data), and Appendix E (Flight-Derived h sub i/h sub u Tables).

Praharaj, Sarat C.↗

Orbital flight test shuttle external tank aerothermal flight evaluation, volume 3

This 3-volume report discusses the evaluation of aerothermal flight measurements made on the orbital flight test Space Shuttle External Tanks (ETs). Six ETs were instrumented to measure various quantities during flight; including heat transfer, pressure, and structural temperature. The flight data was reduced and analyzed against math models established from an extensive wind tunnel data base and empirical heat-transfer relationships. This analysis has supported the validity of the current aeroheating methodology and existing data base; and, has also identified some problem areas which require methodology modifications. Volume 1 is the Executive Summary. Volume 2 contains Appendix A (Aerothermal Comparisons), and Appendix B (Flight-Derived h sub 1/h sub u vs. M sub inf. Plots). This is Volume 3, containing Appendix C (Comparison of Interference Factors between OFT Flight, Prediction and 1H-97A Data), Appendix D (Freestream Stanton Number and Reynolds Number Correlation for Flight and Tunnel Data), and Appendix E (Flight-Derived h sub i/h sub u Tables).

Praharaj, Sarat C.↗

Orbital flight test shuttle external tank aerothermal flight evaluation, volume 2

This 3-volume report discusses the evaluation of aerothermal flight measurements made on the orbital flight test Space Shuttle External Tanks (ETs). Six ETs were instrumented to measure various quantities during flight; including heat transfer, pressure, and structural temperature. The flight data was reduced and analyzed against math models established from an extensive wind tunnel data base and empirical heat-transfer relationships. This analysis has supported the validity of the current aeroheating methodology and existing data base; and, has also identified some problem areas which require methodology modifications. Volume 1 is the Executive Summary. This is volume 2, containing Appendix A (Aerothermal Comparisons), and Appendix B (Flight-Derived h sub i/h sub u vs. M sub inf. Plots). Volume 3 contains Appendix C (Comparison of Interference Factors between OFT Flight, Prediction and 1H-97A Data), Appendix D (Freestream Stanton Number and Reynolds Number Correlation for Flight and Tunnel Data), and Appendix E (Flight-Derived h sub i/h sub u Tables).

Praharaj, Sarat C.↗

Heat transfer rate distribution on North American Rockwell delta wing orbiter determined by phase change paint technique at a Mach number of 8, volume 1

The results of a wind tunnel test program to determine aerodynamic heat transfer distributions on an orbiter configuration are presented. Heat-transfer rates were determined by the phase change paint technique on 0.013-scale Stycast models using Tempilaq as the surface temperature indicator. The nominal test conditions were; Mach 8, length Reynolds numbers of 6.0 x 1 million and 8.9 x 1 million, and angles of attack from 10 to 50 deg in 10-deg increments. At the higher Reynolds number, data were obtained with and without boundary layer trips. Model details, test conditions, and reduced heat-transfer data are presented. Data reduction of the phase-change paint photographs was performed by utilizing a new technique which is described in the data presentation section.

Matthews, R. K.↗

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗

Data processing 2: Advancements in large scale data processing systems for remote sensing

The development of large scale data processing systems for remote sensing is studied by evaluating: (1) the suitability of several sensor types with regard to producing data required for multispectral machine analysis; (2) various types of data preprocessing necessary to prepare such data for analysis; and (3) transfer of machine processing techniques for earth resources data to user community.

Landgrebe, D. A.↗

Design of an Improved Heater Array to Measure Microscale Wall Heat Transfer

An improved array of microscale heaters is being developed to measure the heat transfer coefficient at many points underneath individual bubbles during boiling as a function of space and time. This heater array enables the local heat transfer from a surface during the bubble growth and departure process to be measured with very high temporal and spatial resolution, and should allow better understanding of the boiling heat transfer mechanisms by pin-pointing when and where in the bubble departure cycle large amounts of wall heat transfer occur. Such information can provide much needed data regarding the important heat transfer mechanisms during the bubble departure cycle, and can serve as benchmarks to validate many of the analytical and numerical models used to simulate boiling. The improvements to the heater array include using a silicon-on-quartz substrate to reduce thermal cross-talk between the heaters, decreased space between the heaters, increased pad sizes on the heaters, and progressive heater sizes. Some results using the present heater array are discussed.

Kim, Jungho↗

Remote Data Exploration with the Interactive Data Language (IDL)

A difficulty for many NASA researchers is that often the data to analyze is located remotely from the scientist and the data is too large to transfer for local analysis. Researchers have developed the Data Access Protocol (DAP) for accessing remote data. Presently one can use DAP from within IDL, but the IDL-DAP interface is both limited and cumbersome. A more powerful and user-friendly interface to DAP for IDL has been developed. Users are able to browse remote data sets graphically, select partial data to retrieve, import that data and make customized plots, and have an interactive IDL command line session simultaneous with the remote visualization. All of these IDL-DAP tools are usable easily and seamlessly for any IDL user. IDL and DAP are both widely used in science, but were not easily used together. The IDL DAP bindings were incomplete and had numerous bugs that prevented their serious use. For example, the existing bindings did not read DAP Grid data, which is the organization of nearly all NASA datasets currently served via DAP. This project uniquely provides a fully featured, user-friendly interface to DAP from IDL, both from the command line and a GUI application. The DAP Explorer GUI application makes browsing a dataset more user-friendly, while also providing the capability to run user-defined functions on specified data. Methods for running remote functions on the DAP server were investigated, and a technique for accomplishing this task was decided upon.

Galloy, Michael↗

Low-thrust chemical rocket engine study

An analytical study evaluating thrust chamber cooling engine cycles and preliminary engine design for low thrust chemical rocket engines for orbit transfer vehicles is described. Oxygen/hydrogen, oxygen/methane, and oxygen/RP-1 engines with thrust levels from 444.8 N to 13345 N, and chamber pressures from 13.8 N/sq cm to 689.5 N/sq cm were evaluated. The physical and thermodynamic properties of the propellant theoretical performance data, and transport properties are documented. The thrust chamber cooling limits for regenerative/radiation and film/radiation cooling are defined and parametric heat transfer data presented. A conceptual evaluation of a number of engine cycles was performed and a 2224.1 N oxygen/hydrogen engine cycle configuration and a 2224.1 N oxygen/methane configuration chosen for preliminary engine design. Updated parametric engine data, engine design drawings, and an assessment of technology required are presented.

Shoji, J. M.↗

Forced convection heat transfer to air/water vapor mixtures

Heat transfer coefficients were measured using both dry and humid air in the same forced convection cooling scheme and were compared using appropriate nondimensional parameters (Nusselt, Prandtl and Reynolds numbers). A forced convection scheme with a complex flow field, two dimensional arrays of circular jets with crossflow, was utilized with humidity ratios (mass ratio of water vapor to air) up to 0.23. The dynamic viscosity, thermal conductivity and specific heat of air, steam and air/steam mixtures are examined. Methods for determining gaseous mixture properties from the properties of their pure components are reviewed as well as methods for determining these properties with good confidence. The need for more experimentally determined property data for humid air is discussed. It is concluded that dimensionless forms of forced convection heat transfer data and empirical correlations based on measurements with dry air may be applied to conditions involving humid air with the same confidence as for the dry air case itself, provided that the thermophysical properties of the humid air mixtures are known with the same confidence as their dry air counterparts.

Richards, D. R.↗

The Role of Mobility Data Hubs in an Integrated Decarbonized Transportation Future

The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗