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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Impact of Ocean Observations in Seasonal Climate Prediction

The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

Rienecker, Michele↗
NASA NTRS2016

North American Megadroughts in the Common Era: Reconstructions and Simulations

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

atmospheric temperature↗
NASA NTRS2020

Dynamic Medical Risk Assessment Supported by Inference Networks

The Human Research Program's next generation risk model, the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT), provides researchers with estimates of astronaut medical and health risk. MEDPRATs Susceptibility Inference Network (SIN) facilitates the dynamic component of this tool. The SIN provides MEDPRAT with a "memory" that allows the system to use knowledge of what simulation events have occurred to alter the representative probability that future simulation events will occur during a given trial. The SIN allows for the medical events being simulated to be related to, and influence the likelihood of one another, providing a more robust risk estimate. We present initial work of our efforts to mathematically quantify and represent these dependent relationships between medical events.

McIntyre, L.↗
NASA NTRS1974

Future applications of associative processor systems to operational KSC systems for optimizing cost and enhancing performance characteristics

The application of associative memory processor equipment to conventional host processors type systems is discussed. Efforts were made to demonstrate how such application relieves the task burden of conventional systems, and enhance system speed and efficiency. Data cover comparative theoretical performance analysis, demonstration of expanded growth capabilities, and demonstrations of actual hardware in simulated environment.

Perkinson, J. A.↗
NASA NTRS1990

Rule-based mechanisms of learning for intelligent adaptive flight control

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Handelman, David A.↗
NASA NTRS1988

Fast Data Acquisition For Mass Spectrometer

New equipment has speed and capacity to process time-of-flight data. System relies on fast, compact waveform digitizer with 32-k memory coupled to personal computer. With digitizer, system captures all mass peaks on each 25- to 35-microseconds cycle of spectrometer.

Lincoln, K. A.↗
NASA NTRS1995

Solar Particle Induced Upsets in the TDRS-1 Attitude Control System RAM During the October 1989 Solar Particle Events

The three large solar particle events, beginning on October 19, 1989 and lasting approximately six days, were characterized by high fluences of solar protons and heavy ions at 1 AU. During these events, an abnormally large number of upsets (243) were observed in the random access memory of the attitude control system (ACS) control processing electronics (CPE) on-board the geosynchronous TDRS-1 (Telemetry and Data Relay Satellite). The RAM unit affected was composed of eight Fairchild 93L422 memory chips. The Galileo spacecraft, launched on October 18, 1989 (one day prior to the solar particle events) observed the fluxes of heavy ions experienced by TDRS-1. Two solid-state detector telescopes on-board Galileo, designed to measure heavy ion species and energy, were turned on during time periods within each of the three separate events. The heavy ion data have been modeled and the time history of the events reconstructed to estimate heavy ion fluences. These fluences were converted to effective LET spectra after transport through the estimated shielding distribution around the TDRS-1 ACS system. The number of single event upsets (SEU) expected was calculated by integrating the measured cross section for the Fairchild 93L422 memory chip with average effective LET spectrum. The expected number of heavy ion induced SEU's calculated was 176. GOES-7 proton data, observed during the solar particle events, were used to estimate the number of proton-induced SEU's by integrating the proton fluence spectrum incident on the memory chips, with the two-parameter Bendel cross section for proton SEU'S. The proton fluence spectrum at the device level was gotten by transporting the protons through the estimated shielding distribution. The number of calculated proton-induced SEU's was 72, yielding a total of 248 predicted SEU'S, very dose to the 243 observed SEU'S. These calculations uniquely demonstrate the roles that solar heavy ions and protons played in the production of SEU's during the October 1989 solar particle events.

Croley, D. R.↗
NASA NTRS1985

Error control for reliable digital data transmission and storage systems

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256K-bit DRAM's are organized in 32Kx8 bit-bytes. Byte oriented codes such as Reed Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. In this paper we present some special decoding techniques for extended single-and-double-error-correcting RS codes which are capable of high speed operation. These techniques are designed to find the error locations and the error values directly from the syndrome without having to use the iterative alorithm to find the error locator polynomial. Two codes are considered: (1) a d sub min = 4 single-byte-error-correcting (SBEC), double-byte-error-detecting (DBED) RS code; and (2) a d sub min = 6 double-byte-error-correcting (DBEC), triple-byte-error-detecting (TBED) RS code.

Costello, D. J., Jr.↗
NASA NTRS1994

Precision waveform shaping and precompensation for high data rate space coomunications systems

This paper studies a memory-based pulse shaping and traveling wave tube precompensation technique applied to high data rate satellite communications. Baseband I and Q waveforms are synthesized from data stored in a distributed arithmetic architecture. The waveforms are adjusted to minimize intersymbol interference spectral bandwidth and traveling wave tube distortion. We evaluate its performance in a simulated bi-phase shift keying (BPSK) link. The results show that memory-based precompensation has great potential to improve link performance.

Tague, John A.↗
NASA NTRS1972

C-MOS array design techniques: SUMC multiprocessor system study

The current capabilities of LSI techniques for speed and reliability, plus the possibilities of assembling large configurations of LSI logic and storage elements, have demanded the study of multiprocessors and multiprocessing techniques, problems, and potentialities. Evaluated are three previous systems studies for a space ultrareliable modular computer multiprocessing system, and a new multiprocessing system is proposed that is flexibly configured with up to four central processors, four 1/0 processors, and 16 main memory units, plus auxiliary memory and peripheral devices. This multiprocessor system features a multilevel interrupt, qualified S/360 compatibility for ground-based generation of programs, virtual memory management of a storage hierarchy through 1/0 processors, and multiport access to multiple and shared memory units.

Clapp, W. A.↗
NASA NTRS1973

The data processor from the small scientific satellite

A reprogrammable data system aboard a small scientific satellite is described that samples and processes magnetospheric measurements for transmission to the ground. The lightweight configuration of the data system is made up of the program memory, data storage, input/output module, and a central processing unit. The system is designed for multiple missions.

Mccain, H. G.↗
NASA NTRS2004

Parallel 3D Mortar Element Method for Adaptive Nonconforming Meshes

High order methods are frequently used in computational simulation for their high accuracy. An efficient way to avoid unnecessary computation in smooth regions of the solution is to use adaptive meshes which employ fine grids only in areas where they are needed. Nonconforming spectral elements allow the grid to be flexibly adjusted to satisfy the computational accuracy requirements. The method is suitable for computational simulations of unsteady problems with very disparate length scales or unsteady moving features, such as heat transfer, fluid dynamics or flame combustion. In this work, we select the Mark Element Method (MEM) to handle the non-conforming interfaces between elements. A new technique is introduced to efficiently implement MEM in 3-D nonconforming meshes. By introducing an "intermediate mortar", the proposed method decomposes the projection between 3-D elements and mortars into two steps. In each step, projection matrices derived in 2-D are used. The two-step method avoids explicitly forming/deriving large projection matrices for 3-D meshes, and also helps to simplify the implementation. This new technique can be used for both h- and p-type adaptation. This method is applied to an unsteady 3-D moving heat source problem. With our new MEM implementation, mesh adaptation is able to efficiently refine the grid near the heat source and coarsen the grid once the heat source passes. The savings in computational work resulting from the dynamic mesh adaptation is demonstrated by the reduction of the the number of elements used and CPU time spent. MEM and mesh adaptation, respectively, bring irregularity and dynamics to the computer memory access pattern. Hence, they provide a good way to gauge the performance of computer systems when running scientific applications whose memory access patterns are irregular and unpredictable. We select a 3-D moving heat source problem as the Unstructured Adaptive (UA) grid benchmark, a new component of the NAS Parallel Benchmarks (NPB). In this paper, we present some interesting performance results of ow OpenMP parallel implementation on different architectures such as the SGI Origin2000, SGI Altix, and Cray MTA-2.

Feng, Huiyu↗
NASA NTRS2001

Requirements and Usage of NVM in Advanced Onboard Data Processing Systems

This viewgraph presentation gives an overview of the requirements and uses of non-volatile memory (NVM) in advanced onboard data processing systems. Supercomputing in space presents the only viable approach to the bandwidth problem (can't get data down to Earth), controlling constellations of cooperating satellites, reducing mission operating costs, and real-time intelligent decision making and science data gathering. Details are given on the REE vision and impact on NASA and Department of Defense missions, objectives of REE, baseline architecture, and issues. NVM uses and requirements are listed.

Some, R.↗
NASA NTRS1990

Sparse distributed memory overview

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Raugh, Mike↗