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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 NTRS2012

NASA Tech Briefs, April 2012

Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.

Source record↗
NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗
NASA NTRSDate not supplied

Scalability of GlennICE in a Parallel Environment

GlennICE (Glenn Icing Computational Environment) is a comptational tool designed to calculate ice growth on complex three- dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for tractability in a practical engineering application. Although studies have demonstrated a reduction in the amount of work (memory footprint) required, research has yet to systematically investigate the effects of scaling GlennICE. This paper sets out to benchmark the scalability of GlennICE within a parallel environment and investigate if an increase in the number of processors result in a linear speed up.

Computational Icing↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS1977

Efficient bit-error detecting code

Two highly reliable codes termed "Modified b-adjacent interleaving codes" provide fail-safe operation of launch processing and control system in which common memory is coordination point for interconnection of up to 64 minicomputers. Codes detect and correct bit errors in computer data transmission.

Hockenberger, R. W.↗
NASA NTRS2014

Computationally Efficient Modeling and Simulation of Large Scale Systems

A system for simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof, including a processor, and a memory, the processor configured to perform obtaining a matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure, the element values for each matrix including inductance L and inverse capacitance P, obtaining an adjacency matrix A associated with the interconnect structure, storing the matrices X, Y, and A in the memory, and performing numerical integration to solve first and second equations.

Jain, Jitesh↗
NASA NTRS2001

A High-Order Finite Spectral Volume Method for Conservation Laws on Unstructured Grids

A time accurate, high-order, conservative, yet efficient method named Finite Spectral Volume (FSV) is developed for conservation laws on unstructured grids. The concept of a 'spectral volume' is introduced to achieve high-order accuracy in an efficient manner similar to spectral element and multi-domain spectral methods. In addition, each spectral volume is further sub-divided into control volumes (CVs), and cell-averaged data from these control volumes is used to reconstruct a high-order approximation in the spectral volume. Riemann solvers are used to compute the fluxes at spectral volume boundaries. Then cell-averaged state variables in the control volumes are updated independently. Furthermore, TVD (Total Variation Diminishing) and TVB (Total Variation Bounded) limiters are introduced in the FSV method to remove/reduce spurious oscillations near discontinuities. A very desirable feature of the FSV method is that the reconstruction is carried out only once, and analytically, and is the same for all cells of the same type, and that the reconstruction stencil is always non-singular, in contrast to the memory and CPU-intensive reconstruction in a high-order finite volume (FV) method. Discussions are made concerning why the FSV method is significantly more efficient than high-order finite volume and the Discontinuous Galerkin (DG) methods. Fundamental properties of the FSV method are studied and high-order accuracy is demonstrated for several model problems with and without discontinuities.

Wang, Z. J.↗
NASA NTRS2004

FPGA-Based, Self-Checking, Fault-Tolerant Computers

A proposed computer architecture would exploit the capabilities of commercially available field-programmable gate arrays (FPGAs) to enable computers to detect and recover from bit errors. The main purpose of the proposed architecture is to enable fault-tolerant computing in the presence of single-event upsets (SEUs). [An SEU is a spurious bit flip (also called a soft error) caused by a single impact of ionizing radiation.] The architecture would also enable recovery from some soft errors caused by electrical transients and, to some extent, from intermittent and permanent (hard) errors caused by aging of electronic components. A typical FPGA of the current generation contains one or more complete processor cores, memories, and highspeed serial input/output (I/O) channels, making it possible to shrink a board-level processor node to a single integrated-circuit chip. Custom, highly efficient microcontrollers, general-purpose computers, custom I/O processors, and signal processors can be rapidly and efficiently implemented by use of FPGAs. Unfortunately, FPGAs are susceptible to SEUs. Prior efforts to mitigate the effects of SEUs have yielded solutions that degrade performance of the system and require support from external hardware and software. In comparison with other fault-tolerant- computing architectures (e.g., triple modular redundancy), the proposed architecture could be implemented with less circuitry and lower power demand. Moreover, the fault-tolerant computing functions would require only minimal support from circuitry outside the central processing units (CPUs) of computers, would not require any software support, and would be largely transparent to software and to other computer hardware. There would be two types of modules: a self-checking processor module and a memory system (see figure). The self-checking processor module would be implemented on a single FPGA and would be capable of detecting its own internal errors. It would contain two CPUs executing identical programs in lock step, with comparison of their outputs to detect errors. It would also contain various cache local memory circuits, communication circuits, and configurable special-purpose processors that would use self-checking checkers. (The basic principle of the self-checking checker method is to utilize logic circuitry that generates error signals whenever there is an error in either the checker or the circuit being checked.) The memory system would comprise a main memory and a hardware-controlled check-pointing system (CPS) based on a buffer memory denoted the recovery cache. The main memory would contain random-access memory (RAM) chips and FPGAs that would, in addition to everything else, implement double-error-detecting and single-error-correcting memory functions to enable recovery from single-bit errors.

Some, Raphael↗
NASA NTRS1975

Main memory unit

The development of a main memory unit (MMU) for the space ultrareliable module computer (SUMC) model HTC is discussed. The design, fabrication, and test of basic memory modules (BMM) which were to be used in the design and construction of the MMU are described. The BMM was designed from state-of-the-art technologies which included large scale integration devices mounted and interconnected on a substrate to form a functional module to be utilized in the MMU development. A SUMC memory system design study is discussed which addressed itself to the BMM design and analysis to be conducted to determine the most efficient organization of the BMM in order to establish such modularity features as: word length expandability without redesign, high reliability, and fault tolerance. One MMU was designed, fabricated, tested, and delivered which will be electrical and mechanically compatible with the hybrid technology computer (HTC) model of the SUMC family of computers. The MMU will contain a storage capacity of 8196 36 bit words which includes a parity bit for each 8 bit byte of data.

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NASA NTRS1993

Efficiently modeling neural networks on massively parallel computers

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Farber, Robert M.↗
NASA NTRS1993

Monitoring cognitive function and need with the automated neuropsychological assessment metrics in Decompression Sickness (DCS) research

Hypobaric decompression sickness (DCS) research presents the medical monitor with the difficult task of assessing the onset and progression of DCS largely on the basis of subjective symptoms. Even with the introduction of precordial Doppler ultrasound techniques for the detection of venous gas emboli (VGE), correct prediction of DCS can be made only about 65 percent of the time according to data from the Armstrong Laboratory's (AL's) hypobaric DCS database. An AL research protocol concerned with exercise and its effects on denitrogenation efficiency includes implementation of a performance assessment test battery to evaluate cognitive functioning during a 4-h simulated 30,000 ft (9144 m) exposure. Information gained from such a test battery may assist the medical monitor in identifying early signs of DCS and subtle neurologic dysfunction related to cases of asymptomatic, but advanced, DCS. This presentation concerns the selection and integration of a test battery and the timely graphic display of subject test results for the principal investigator and medical monitor. A subset of the Automated Neuropsychological Assessment Metrics (ANAM) developed through the Office of Military Performance Assessment Technology (OMPAT) was selected. The ANAM software provides a library of simple tests designed for precise measurement of processing efficiency in a variety of cognitive domains. For our application and time constraints, two tests requiring high levels of cognitive processing and memory were chosen along with one test requiring fine psychomotor performance. Accuracy, speed, and processing throughout variables as well as RMS error were collected. An automated mood survey provided 'state' information on six scales including anger, happiness, fear, depression, activity, and fatigue. An integrated and interactive LOTUS 1-2-3 macro was developed to import and display past and present task performance and mood-change information.

Nesthus, Thomas E.↗
NASA NTRS1995

Parallel adaptive mesh refinement within the PUMAA3D Project

To enable the solution of large-scale applications on distributed memory architectures, we are designing and implementing parallel algorithms for the fundamental tasks of unstructured mesh computation. In this paper, we discuss efficient algorithms developed for two of these tasks: parallel adaptive mesh refinement and mesh partitioning. The algorithms are discussed in the context of two-dimensional finite element solution on triangular meshes, but are suitable for use with a variety of element types and with h- or p-refinement. Results demonstrating the scalability and efficiency of the refinement algorithm and the quality of the mesh partitioning are presented for several test problems on the Intel DELTA.

Freitag, Lori↗
NASA NTRS2001

Evaluation of Design Concepts for Collapsible Cryogenic Storage Vessels

Future long-duration missions to Mars using in situ resource production to obtain oxygen from the Martian atmosphere for use as a propellant or for life support will require long term oxygen storage facilities. This report describes preliminary analysis of design concepts for lightweight, collapsible liquid oxygen storage tanks to be used on the surface of Mars. With storage at relatively low pressures, an inflatable tank concept in which the cryogen is stored within a fiber-reinforced Teflon FEP bladder is an efficient approach. The technology required for such a tank is well-developed through similar previous applications in positive expulsion bladders for zero-g liquid fuel rocket tanks and inflatable space habitat technology, though the liquid oxygen environment presents unique challenges. The weight of the proposed structure is largely dominated by the support structure needed to hold the tank off the ground and permit a vacuum insulation space to be maintained around the tank. In addition to the inflatable tank concept, telescoping tank concepts are studied. For a telescoping tank, the greatest difficulty is in making effective joints and seals. The use of shape memory alloy to produce a passive clamping ring is evaluated. Although the telescoping tank concepts are a viable option, it appears that inflatable tank concepts will be more efficient and are recommended.

Fleming, David C.↗
NASA NTRS1999

Parallel Grid Manipulations in Earth Science Calculations

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center is moving its data assimilation system to massively parallel computing platforms. This parallel implementation of GEOS DAS will be used in the DAO's normal activities, which include reanalysis of data, and operational support for flight missions. Key components of GEOS DAS, including the gridpoint-based general circulation model and a data analysis system, are currently being parallelized. The parallelization of GEOS DAS is also one of the HPCC Grand Challenge Projects. The GEOS-DAS software employs several distinct grids. Some examples are: an observation grid- an unstructured grid of points at which observed or measured physical quantities from instruments or satellites are associated- a highly-structured latitude-longitude grid of points spanning the earth at given latitude-longitude coordinates at which prognostic quantities are determined, and a computational lat-lon grid in which the pole has been moved to a different location to avoid computational instabilities. Each of these grids has a different structure and number of constituent points. In spite of that, there are numerous interactions between the grids, e.g., values on one grid must be interpolated to another, or, in other cases, grids need to be redistributed on the underlying parallel platform. The DAO has designed a parallel integrated library for grid manipulations (PILGRIM) to support the needed grid interactions with maximum efficiency. It offers a flexible interface to generate new grids, define transformations between grids and apply them. Basic communication is currently MPI, however the interfaces defined here could conceivably be implemented with other message-passing libraries, e.g., Cray SHMEM, or with shared-memory constructs. The library is written in Fortran 90. First performance results indicate that even difficult problems, such as above-mentioned pole rotation- a sparse interpolation with little data locality between the physical lat-lon grid and a pole rotated computational grid- can be solved efficiently and at the GFlop/s rates needed to solve tomorrow's high resolution earth science models. In the subsequent presentation we will discuss the design and implementation of PILGRIM as well as a number of the problems it is required to solve. Some conclusions will be drawn about the potential performance of the overall earth science models on the supercomputer platforms foreseen for these problems.

Sawyer, W.↗
NASA NTRS1984

Minimum wafer thickness by rotated ingot ID wafering

The efficient utilization of materials is critical to certain device applications such as silicon for photovoltaics or diodes and gallium-gadolinium-garnet for memories. A variety of slicing techniques has been investigated to minimize wafer thickness and wafer kerf. This paper presents the results of analyses of ID wafering of rotated ingots based on predicted fracture behavior of the wafer as a result of forces during wafering and the properties of the device material. The analytical model indicated that the minimum wafer thickness is controlled by the depth of surface damage and the applied cantilever force. Both of these factors should be minimized. For silicon, a minimum thickness was found to be approximately 200 x 10 - 6th m for conventional sizes of rotated ingot wafering. Fractures through the thickness of the wafer rather than through the center supporting column were found to limit the minimum wafer thickness. The model suggested that the use of a vacuum chuck on the wafer surface to enhance cleavage fracture of the center supporting core and, with silicon, by using 111-line-type ingots could have potential for reducing minimum wafer thickness.

Chen, C. P.↗
NASA NTRS1986

Performance measurements of a data link protocol

The end-to-end performance of a program implementing IEEE Std 802.2 logical link control protocol, which provides virtual circuit and datagram service and which constitutes the top sublayer of the data link layer of the reference model for Local Area Networks is studied. The measurements of relative execution times of various functions required in transferring data, over virtual circuits or as datagrams, showed that most of the program execution time is spent in a few relatively low-level functions. One of these functions performs block movement of data in memory, and two other functions provide access to various queues. Based on this result, two alternative versions of the program which move data efficiently were written and measured. In this paper the results of the study are reported and their impact on designing hardware and software systems for a network interface are discussed.

Kanakia, Hemant↗
NASA NTRS1995

Heterogeneous concurrent computing with exportable services

Heterogeneous concurrent computing, based on the traditional process-oriented model, is approaching its functionality and performance limits. An alternative paradigm, based on the concept of services, supporting data driven computation, and built on a lightweight process infrastructure, is proposed to enhance the functional capabilities and the operational efficiency of heterogeneous network-based concurrent computing. TPVM is an experimental prototype system supporting exportable services, thread-based computation, and remote memory operations that is built as an extension of and an enhancement to the PVM concurrent computing system. TPVM offers a significantly different computing paradigm for network-based computing, while maintaining a close resemblance to the conventional PVM model in the interest of compatibility and ease of transition Preliminary experiences have demonstrated that the TPVM framework presents a natural yet powerful concurrent programming interface, while being capable of delivering performance improvements of upto thirty percent.

Sunderam, Vaidy↗