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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Reasoning with case histories of process knowledge for efficient process development

The significance of compiling case histories of empirical process knowledge and the role of such histories in improving the efficiency of manufacturing process development is discussed in this paper. Methods of representing important investigations as cases and using the information from such cases to eliminate redundancy of empirical investigations in analogous process development situations are also discussed. A system is proposed that uses such methods to capture the problem-solving framework of the application domain. A conceptual design of the system is presented and discussed.

Bharwani, Seraj S.↗
NASA NTRS2016

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗
NASA NTRS2003

Efficient Processing of Data for Locating Lightning Strikes

Two algorithms have been devised to increase the efficiency of processing of data in lightning detection and ranging (LDAR) systems so as to enable the accurate location of lightning strikes in real time. In LDAR, the location of a lightning strike is calculated by solving equations for the differences among the times of arrival (DTOAs) of the lightning signals at multiple antennas as functions of the locations of the antennas and the speed of light. The most difficult part of the problem is computing the DTOAs from digitized versions of the signals received by the various antennas. One way (a time-domain approach) to determine the DTOAs is to compute cross-correlations among variously differentially delayed replicas of the digitized signals and to select, as the DTOAs, those differential delays that yield the maximum correlations. Another way (a frequency-domain approach) to determine the DTOAs involves the computation of cross-correlations among Fourier transforms of variously differentially phased replicas of the digitized signals, along with utilization of the relationship among phase difference, time delay, and frequency.

Medelius, Pedro J.↗
NASA NTRSDate not supplied

Deep Learning System for Efficient Processing of Geostationary Satellite Imagery

Improved capabilities of Earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), and Himawari-8/9 (JAXA), we present an interchangeable set of machine models to perform spectral adjustment among sensors, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools on the NASA Earth eXchange (NEX) to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate surface reflectance, surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Thomas Vandal↗
NASA NTRS2018

Development of a Robust, Efficient Process to Produce Scalable, Superconducting Kilopixel Far-IR Detector Arrays

The far-IR band is uniquely suited to study the physical conditions in the interstellar medium from nearby sources out to the highest redshifts. FIR imaging and spectroscopy instrumentation using incoherent superconducting bolometers represents a high sensitivity technology for many future suborbital and space missions, including the Origins Space Telescope. Robust, high sensitivity detector arrays with several 104 pixels, large focal plane filling factors, and low cosmic ray cross sections that operate over the entire far-IR regime are required for such missions. These arrays could consist of smaller sub-arrays, in case they are tileable. The TES based Backshort Under Grid array architecture which our group has fielded in a number of FIR cameras, is a good candidate to meet these requirements: BUGs are tileable, and with the integration of the SQUID multiplexer scaleable beyond wafer sizes; they provide high filling factors, low cosmic cross section and have been demonstrated successfully in far-infrared astronomical instrumentation. However, the production of BUGs with integrated readout multiplexers has many time and resource consuming process steps. In order to meet the requirement of robustness and efficiency on the production of future arrays, we have developed a new method to provide the superconducting connection of BUG detectors to the readout multiplexers or general readout boards behind the detectors. This approach should allow us to reach the goal to produce reliable, very large detector arrays for future FIR missions.

Staguhn, Johannes↗
NASA NTRS1985

Efficient Process for Making Polycrystalline Silicon

Solar cells made with lower capital and operating costs. Process based on chemical-vapor deposition (CVD) of dichlorosilane produces high-grade polycrystalline silicon for solar cells. Process has potential as cost-effective replacement for CVD of trichlorosilane.

Mccormick, J. R.↗
NASA NTRS1996

Efficient Process Migration for Parallel Processing on Non-Dedicated Networks of Workstations

This paper presents the design and preliminary implementation of MpPVM, a software system that supports process migration for PVM application programs in a non-dedicated heterogeneous computing environment. New concepts of migration point as well as migration point analysis and necessary data analysis are introduced. In MpPVM, process migrations occur only at previously inserted migration points. Migration point analysis determines appropriate locations to insert migration points; whereas, necessary data analysis provides a minimum set of variables to be transferred at each migration pint. A new methodology to perform reliable point-to-point data communications in a migration environment is also discussed. Finally, a preliminary implementation of MpPVM and its experimental results are presented, showing the correctness and promising performance of our process migration mechanism in a scalable non-dedicated heterogeneous computing environment. While MpPVM is developed on top of PVM, the process migration methodology introduced in this study is general and can be applied to any distributed software environment.

Chanchio, Kasidit↗
NASA NTRS1973

On the normality and accuracy of simulated random processes.

Efficient methods of simulating stationary and nonstationary random processes and envelopes, by using a series of sine or cosine functions or by using the fast Fourier transform, have been proposed previously. Without applying the central limit theorem, it is shown in this paper that the simulated random processes are asymptotically Gaussian processes as the number of terms, N, of sine or cosine functions approaches infinity. The accuracy of the first-order probability densities of the simulated random processes is investigated by using the fast Fourier transform. Numerical results are computed with respect to the variation of the number of terms, N, of sine or cosine functions used for simulation. It is shown that within the practical range of N, such as 500, the accuracy is remarkably satisfactory even outside the region of 3 standard deviations.

Yang, J.-N.↗
NASA NTRS1972

Simulation of random envelope processes.

Efficient and practical methods of simulating stationary and nonstationary random envelope processes are presented. The stationary envelope processes are simulated by using the fast Fourier transform while the nonstationary envelope processes are simulated as the square root of the sum of a series of cosine functions and a series of sine functions with random phase angles. Typical applications of the envelope simulation are the simulations of peaks and troughs which play an important role in the analyses of the first excursion probability, fatigue and crack propagation. In particular, applications to the crack propagation under random loadings are demonstrated in detail.

Yang, J.-N.↗
NASA NTRS1980

Reduced product yield in chemical processes by second law effects

An analysis of second law effects in chemical processes, where product yield is explicitly related to the individual irreversibilities within the process to indicate a maximum theoretical yield, is presented. Examples are given that indicate differences between first and second law approaches toward process efficiency and process yield. This analysis also expresses production capacity in terms of the heating value of a product. As a result, it is particularly convenient in analyzing fuel conversion plants and their potential for improvement. Relationships are also given for the effects of irreversibilities on requirements for process heat and for feedstocks.

England, C.↗
NASA NTRS1990

Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing

Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.

Liu, Kuojuey Ray↗
NASA NTRS1976

Hydrogen production from coal using a nuclear heat source

A strong candidate for hydrogen production in the intermediate time frame of 1985 to 1995 is a coal-based process using a high-temperature gas-cooled reactor (HTGR) as a heat source. Expected process efficiencies in the range of 60 to 70% are considerably higher than all other hydrogen production processes except steam reforming of a natural gas. The process involves the preparation of a coal liquid, hydrogasification of that liquid, and steam reforming of the resulting gaseous or light liquid product. A study showing process efficiency and cost of hydrogen vs nuclear reactor core outlet temperature has been completed, and shows diminishing returns at process temperatures above about 1500 F. A possible scenario combining the relatively abundant and low-cost Western coal deposits with the Gulf Coast hydrogen users is presented which provides high-energy density transportation utilizing coal liquids and uranium.

Quade, R. N.↗
NASA NTRS1998

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Maly, K.↗
NASA NTRS2002

Computed Tomography and Thermography Increases CMC Material and Process Development Efficiency and Testing Effectiveness

Nondestructive characterization techniques have been used to steer development and testing of CMCs. Computed tomography is used to determine the volumetric integrity of the CMC plates and components. Thermography is used to determine the near surface integrity of the CMC plates and components. For process and material development, information such as density uniformity, part delamination, and dimensional tolerance conformity is generated. The information from the thermography and computed tomography is correlated and then specimen cutting maps are superimposed on the thermography images. This enables for tighter data and potential explanation of off nominal test data. Examples of nondestructive characterization utilization to make decisions in process and material development and testing are presented.

Effinger, Michael↗
NASA NTRS2012

Application of System Operational Effectiveness Methodology to Space Launch Vehicle Development and Operations

The Department of Defense (DoD) defined System Operational Effectiveness (SOE) model provides an exceptional framework for an affordable approach to the development and operation of space launch vehicles and their supporting infrastructure. The SOE model provides a focal point from which to direct and measure technical effectiveness and process efficiencies of space launch vehicles. The application of the SOE model to a space launch vehicle's development and operation effort leads to very specific approaches and measures that require consideration during the design phase. This paper provides a mapping of the SOE model to the development of space launch vehicles for human exploration by addressing the SOE model key points of measurement including System Performance, System Availability, Technical Effectiveness, Process Efficiency, System Effectiveness, Life Cycle Cost, and Affordable Operational Effectiveness. In addition, the application of the SOE model to the launch vehicle development process is defined providing the unique aspects of space launch vehicle production and operations in lieu of the traditional broader SOE context that examines large quantities of fielded systems. The tailoring and application of the SOE model to space launch vehicles provides some key insights into the operational design drivers, capability phasing, and operational support systems.

Watson, Michael D.↗
NASA NTRS1992

Equivalent GPS measurements for efficient estimation process

Dual-frequency pseudorange and carrier phase data streams can be analytically combined into a single equivalent data stream, reducing the data volume and computing time in the filtering process for parameter estimation by a factor of 2 to 4. The resulting single data stream is that of carrier phase measurements with both data noise and bias uncertainty strictly defined. Based on these analytical formulas the equivalent GPS measurements can be formed by simple and efficient numerical calculations without any degradation in data strength. Formulation for the equivalent GPS measurements and their covariances are given in closed form; and a numerical simulation is performed to demonstrate the validity and effectiveness of the equivalent measurements.

Wu, S. C.↗