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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 991 records · Page 55

Determining Availability Characteristics of DSN Data Systems Using Discrepancy Report Data

A reasonably economical way was developed to determine availability characteristics of Deep Space Network (DSN) data systems, subsystems, and assemblies using the DSN discrepancy report (DR) data base and DSN operating schedule and history data bases. Operating mean time between failures (OMTBF), operating mean time to restore service (OMTTRS), and operating functional availability (OFA) can be computed by year, by system, by subsystem, by assembly, and by station. The effort required to produce the desired reports is described, specific data on the telemetry, command, and tracking systems are presented, and major contributors to system outages are identified. Future improvements in preparing and analyzing DR data are also outlined to enhance their use in correcting conditions that lead to outages.

Ruskin, A. M.↗

The effects of leading edge and downstream film cooling on turbine vane heat transfer

The progress under contract NAS3-24619 toward the goal of establishing a relevant data base for use in improving the predictive design capabilities for external heat transfer to turbine vanes, including the effect of downstream film cooling with and without leading edge showerhead film cooling. Experimental measurements were made in a two-dimensional cascade previously used to obtain vane surface heat transfer distributions on nonfilm cooled airfoils under contract NAS3-22761 and leading edge showerhead film cooled airfoils under contract NAS3-23695. The principal independent parameters (Mach number, Reynolds number, turbulence, wall-to-gas temperature ratio, coolant-to-gas temperature ratio, and coolant-to-gas pressure ratio) were maintained over ranges consistent with actual engine conditions and the test matrix was structured to provide an assessment of the independent influence of parameters of interest, namely, exit Mach number, exit Reynolds number, coolant-to-gas temperature ratio, and coolant-to-gas pressure ratio. Data provide a data base for downstream film cooled turbine vanes and extends the data bases generated in the two previous studies. The vane external heat transfer obtained indicate that considerable cooling benefits can be achieved by utilizing downstream film cooling. The data obtained and presented illustrate the interaction of the variables and should provide the airfoil designer and computational analyst the information required to improve heat transfer design capabilities for film cooled turbine airfoils.

Hylton, L. D.↗

An Ab Initio Based Potential Energy Surface for Water

We report a new determination of the water potential energy surface. A high quality ab initio potential energy surface (PES) and dipole moment function of water have been computed. This PES is empirically adjusted to improve the agreement between the computed line positions and those from the HITRAN 92 data base. The adjustment is small, nonetheless including an estimate of core (oxygen 1s) electron correlation greatly improves the agreement with experiment. Of the 27,245 assigned transitions in the HITRAN 92 data base for H2(O-16), the overall root mean square (rms) deviation between the computed and observed line positions is 0.125/cm. However the deviations do not correspond to a normal distribution: 69% of the lines have errors less than 0.05/cm. Overall, the agreement between the line intensities computed in the present work and those contained in the data base is quite good, however there are a significant number of line strengths which differ greatly.

Partridge, Harry↗

Proactive Data Containers for Scientific Storage (Final Report)

Emerging HPC systems are expected to be deployed with an unprecedented level of complexity, due to a deep system memory/storage hierarchy and heterogeneity of the storage hardware. This hierarchy is expected to range from CPU cache through several levels of volatile memory to nonvolatile memory, traditional hard disks, and tape. Simple and efficient methods of data management and movement through this hierarchy is critical for scientific applications using exascale systems. Existing storage system and I/O (SSIO) technologies face severe challenges in dealing with these requirements. POSIX and MPI I/O standards that are the basis for existing I/O libraries and parallel file systems present fundamental challenges in the areas of scalable metadata operations, semantics-based data movement performance tuning, asynchronous operation, and support for scalable consistency of distributed operations. Moving toward new paradigms for SSIO in the extreme-scale era, we have proposed to investigate novel object-based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these overarching goals, we initiated an effort to develop a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-centric manner. Managing data as objects enables powerful optimization opportunities for data movement and transformations. The R&D focus of this project are: 1) formulation of object-oriented PDCs and their mapping in different levels of the exascale storage hierarchy; 2) efficient strategies for moving data in deep storage hierarchies using PDCs; 3) techniques for transforming and reorganizing data based on application requirements; and 4) novel analysis paradigms for enabling data transformations and user-defined analysis on data in PDCs. Toward achieving these overarching goals, we designed an object-centric application programing interface (API) for HPC, scalable metadata management for object-centric storage systems, and data movement optimizations such as Data Elevator for moving data between two levels of storage devices and TAPIOCA for efficient aggregation of data on compute nodes. We then implemented several components of the PDC system. They include metadata management, data placement services, remote procedure calls, data aggregation, etc. We have put them together into the overall PDC framework.

97 MATHEMATICS AND COMPUTING↗

Solar heating and cooling technical data and systems analysis

The acquisition and processing of selected parametric data for inclusion in a computerized Data Base using the Marshall Information Retrieval and Data System (MIRADS) developed by NASA-MSFC is discussed. This data base provides extensive technical and socioeconomic information related to solar energy heating and cooling on a national scale. A broadly based research approach was used to assist in the support of program management and the application of a cost-effective program for solar energy development and demonstration.

Christensen, D. L.↗

High-Level Data-Abstraction System

Communication with data-base processor flexible and efficient. High Level Data Abstraction (HILDA) system is three-layer system supporting data-abstraction features of Intel data-base processor (DBP). Purpose of HILDA establishment of flexible method of efficiently communicating with DBP. Power of HILDA lies in its extensibility with regard to syntax and semantic changes. HILDA's high-level query language readily modified. Offers powerful potential to computer sites where DBP attached to DEC VAX-series computer. HILDA system written in Pascal and FORTRAN 77 for interactive execution.

Fishwick, P. A.↗

Large angle transient dynamics (LATDYN) documentation. Post-processor manual

The post processor program was developed to view Large Angle Transient Dynamics (LATDYN) output data in predefined, predetermined formats. The post processor is used for plotting data, creating and maintaining a data base of plotting requests, comparing and manipulating data sets in the data base, and the preparing plots for documentation.

Mitchum, Maria V.↗

The Columbus logistics support at the APMC: Requirements and implementation aspects

This paper focuses on the logistics support to be provided by the APM Center (APMC). Among the Columbus ground infrastructures, this center is tasked to provide logistics, sustaining engineering and P/L integration support to the ongoing missions of the APM, i.e. the Columbus Laboratory attached to the Freedom Space Station. The following is illustrated: an analysis of the requirements that are levied on the logistics support of the APM; how such requirements are reflected in the corresponding support to be available on-ground and at APMC; the functional components of the APMC logistics support and how such components interact each other; how the logistics support function interfaces with the other functions of the ground support; and how the logistics support is being designed in terms of resources (such as hardware, data bases, etc.). Emphasis is given to the data handling aspects and to the related data bases that will constitute for the logistics activities the fundamental source of information during the APM planned lifetime. Functional and physical architectures, together with trades for possible implementation, are addressed. Commonalities with other centers are taken into account and recommendations are made for possible reuse of tools already developed in the C/D phase. Finally, programmatic considerations are discussed for the actual implementation of the center.

Canu, C.↗

CINDOC, CSIC, and Spanish R and D

The organizational structure and functional activities of the Spanish Center for Scientific Information and Documentation (CINDOC) are discussed. The library holds 8,500 journals, including all the Spanish scientific journals; 16,000 books and 20 CD-ROM data bases. CINDOC creates and distributes its own data bases that include all the articles published in Spanish scientific journals.

Delaviesca, Rosa↗

Changes in the TRMM Version 7 Space/Time Averaged Level 3 Data Products Based on GPROF TMI Swath-Based Precipitation Retrievals

TRMM has three level 3 (space/time averaged) data products that aggregate level 2 TRMM Microwave Imager (TMI) GPROF precipitation retrievals. These three products are TRMM 3A12, which is a monthly accumulation of 2A12 the GPROF swath retrieval product; TRMM 3B31, which is a monthly accumulation of 2A12 and 2B31 the combined retrieval product that uses both Precipitation Radar (PR) and TMI data; and 3G68 and its variants, which provide hourly retrievals for TMI, PR and combined. The 3G68 products are packaged as daily files but provide hourly information at 0.5 deg x 0.5 deg resolution globally, 0.25 deg x 0.25 deg globally, or 0.1 deg x 0.1 deg over Africa, Australia and South America. This paper will present early information of the changes in the v7 TMI GPROF level 2 retrievals that have an impact on the level 3 accumulations. This paper provides an analysis of the effect the 2A12 GPROF changes have on 3G68 products. In addition, it provides a comparison between the TRMM level 3 products that use the TMI GPROF swath retrievals.

Stocker, Erich↗

A review of propeller noise prediction methodology: 1919-1994

This report summarizes a review of the literature regarding propeller noise prediction methods. The review is divided into six sections: (1) early methods; (2) more recent methods based on earlier theory; (3) more recent methods based on the Acoustic Analogy; (4) more recent methods based on Computational Acoustics; (5) empirical methods; and (6) broadband methods. The report concludes that there are a large number of noise prediction procedures available which vary markedly in complexity. Deficiencies in accuracy of methods in many cases may be related, not to the methods themselves, but the accuracy and detail of the aerodynamic inputs used to calculate noise. The steps recommended in the report to provide accurate and easy to use prediction methods are: (1) identify reliable test data; (2) define and conduct test programs to fill gaps in the existing data base; (3) identify the most promising prediction methods; (4) evaluate promising prediction methods relative to the data base; (5) identify and correct the weaknesses in the prediction methods, including lack of user friendliness, and include features now available only in research codes; (6) confirm the accuracy of improved prediction methods to the data base; and (7) make the methods widely available and provide training in their use.

Metzger, F. Bruce↗

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗

Testing of ENDF71x: A new ACE-formatted neutron data library based on ENDF/B-VII.1

The ENDF71x library [1] is the most thoroughly tested set of ACE-format data tables ever released by the Nuclear Data Team at Los Alamos National Laboratory (LANL). It is based on ENDF/B-VII. 1, the most recently released set of evaluated nuclear data files produced by the US Cross Section Evaluation Working Group (CSEWG). A variety of techniques were used to test and verify the ENDF7 1x library before its public release. These include the use of automated checking codes written by members of the Nuclear Data Team, visual inspections of key neutron data, MCNP6 calculations designed to test data for every included combination of isotope and temperature as comprehensively as possible, and direct comparisons between ENDF71x and previous ACE library releases. Visual inspection of some of the most important neutron data revealed energy balance problems and unphysical discontinuities in the cross sections for some nuclides. Doppler broadening of the total cross sections with increasing temperature was found to be qualitatively correct. Test calculations performed using MCNP prompted two modifications to the MCNP6 source code and also exposed bad secondary neutron yields for {sup 231,233}Pa that are present in both ENDF/B-VII.1 and ENDF/B-VII.0. A comparison of ENDF71x with its predecessor ACE library, ENDF70, showed that dramatic changes have been made in the neutron cross section data for a number of isotopes between ENDF/B-VII.0 and ENDF/B-VII.1. Based on the results of these verification tests and the validation tests performed by Kahler, et al. [2], the ENDF71x library is recommended for use in all Monte Carlo applications. (authors)

97 MATHEMATICS AND COMPUTING↗

The Final Approach Spacing Tool

A system for assisting terminal area air traffic controllers in the management and control of arrival traffic, referred to as the Final Approach Spacing Tool (FAST), is being developed at NASA Ames Research Center. In a cooperative program, NASA and FAA have efforts underway to install and evaluate the system at the Dallas/Fort Worth Terminal Radar Approach Control facility. This paper will review the software architecture, the algorithms components, and the human-machine interface. The system is based on continuous updates of a detailed trajectory analyses of all arrival aircraft. FAST interprets the results of these trajectory analyses to build an efficient and procedurally acceptable plan for the arrival traffic that consists of a sequence, schedule, and runway assignment. The system utilizes a heuristically-based conflict resolution algorithm to build a solution trajectory that satisfies the plan, It extracts a series of speed and heading advisories from the solution trajectory to assist the controller in efficiently managing and controlling the arrival traffic down to the runway. The advisories are displayed in a graphical format to the controller. In addition to the radar tracking data, the system also relies on a series of data bases. These data bases contain aircraft performance models, airline preferred operational procedures, airspace structure, air traffic procedural models, and a three dimensional wind model. Field evaluation of FAST is expected to begin in 1994.

Davis, Thomas J.↗

Critical issues in NASA information systems

The National Aeronautics and Space Administration has developed a globally-distributed complex of earth resources data bases since LANDSAT 1 was launched in 1972. NASA envisages considerable growth in the number, extent, and complexity of such data bases, due to the improvements expected in its remote sensing data rates, and the increasingly multidisciplinary nature of its scientific investigations. Work already has begun on information systems to support multidisciplinary research activities based on data acquired by the space station complex and other space-based and terrestrial sources. In response to a request from NASA's former Associate Administrator for Space Science and Applications, the National Research Council convened a committee in June 1985 to identify the critical issues involving information systems support to space science and applications. The committee has suggested that OSSA address four major information systems issues; centralization of management functions, interoperability of user involvement in the planning and implementation of its programs, and technology.

Source record↗

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗

Space shuttle natural environment analysis

Five major tasks are briefly outlined: development of detailed wind profile measurements for Kennedy Space Center (KSC) and Vandenberg Air Force Base (VAFB): development of software to construct meteorological data tapes for use in the STS Post Ascent Analysis; development of storage, access, and utilization codes for Global Cloud Cover data; development of software and meteorological data bases to establish launch delay risks at KSC and VAFB; and development of the meteorological tower 301 climatological data base at VAFB.

Batts, Wade↗