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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 1,207 records · Page 67

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NASA NTRS1973

PLZT block data composers operated in differential phase mode

The use of PLZT ceramics with the 7/65/35 composition in block data composer (BDC) input devices for holographic memory systems has previously been described for operation in the strain biased, scattering, and edge effect modes. A new and promising mode of BDC operation is the differential phase mode in which each element of a matrix array BDC acts as a phase modulator. The phase modulation results from a phase difference in the optical path length between the electrically poled and depoled states of the PLZT. It is shown that a PLZT BDC can be used as a matrix-type phase modulator to record and process digital data by the differential phase mode in a holographic recording/processing system with readout contrast ratios of between 10:1 and 15:1. The differential phase mode has the advantages that strain bias is not required and that the thickness and strain variations in the PLZT are cancelled out.

Drake, M. D.↗

NASA NTRS1978

An adaptive learning control system for aircraft

A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

Mekel, R.↗

NASA NTRS1984

Application of supercomputers to computational aerodynamics

Computers are playing an increasingly important role in the field of aerodynamics such that they now serve as a major complement to wind tunnels in aerospace research and development. Factors pacing advances in computational aerodynamics are identified, including the amount of computational power required to take the next major step in the discipline. Example results obtained from the successively refined forms of the governing equations are discussed, both in the context of levels of computer power required and the degree to which they either further the frontiers of research or apply to problems of practical importance. Finally, the Numerical Aerodynamic Simulation (NAS) Program - with its 1988 target of achieving a sustained computational rate of 1 billion floating point operations per second and operating with a memory of 240 million words - is discussed in terms of its goals and its projected effect on the future of computational aerodynamics.

Peterson, V. L.↗

NASA NTRS1990

Nonvolatile Ionic Two-Terminal Memory Device

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Williams, Roger M.↗

NASA NTRS1994

On the effects of a weak magnetic field on turbulent transport

We discuss the effects of a weak large-scale magnetic field on turbulent transport. We show by means of a series of two-dimensional numerical experiments that turbulent diffusion can be effectively suppressed by a (large scale) magnetic field whose energy is small compared to equipartition. The suppression mechanism is associated with a subtle modification of the Lagrangian energy spectrum, and it does not require any substantial reduction of the turbulent amplitude. We exploit the relation between diffusion and random walking to emphasize that the effect of a large-scale magnetic field is to induce a long-term memory in the field of turbulence. The implications of the general case of three-dimensional transport are briefly discussed.

Cattaneo, F.↗

NASA NTRS1996

Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation

We study parallel two-level overlapping Schwarz algorithms for solving nonlinear finite element problems, in particular, for the full potential equation of aerodynamics discretized in two dimensions with bilinear elements. The overall algorithm, Newton-Krylov-Schwarz (NKS), employs an inexact finite-difference Newton method and a Krylov space iterative method, with a two-level overlapping Schwarz method as a preconditioner. We demonstrate that NKS, combined with a density upwinding continuation strategy for problems with weak shocks, is robust and, economical for this class of mixed elliptic-hyperbolic nonlinear partial differential equations, with proper specification of several parameters. We study upwinding parameters, inner convergence tolerance, coarse grid density, subdomain overlap, and the level of fill-in in the incomplete factorization, and report their effect on numerical convergence rate, overall execution time, and parallel efficiency on a distributed-memory parallel computer.

Cai, Xiao-Chuan↗

NASA NTRS1997

Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

Sedlak, J.↗

NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗

NASA NTRS2002

A Nonlinear Theory for Smart Composite Structures

The paper discusses the following: (1) Development of a completely coupled thermo-piezoelectric-mechanical theory for the analysis of composite shells with segmented and distributed piezoelectric sensor/actuators and shape memory alloys. The higher order displacement theory will be used to capture the transverse shear effects in anisotropic composites. The original theory will be modified to satisfy the stress continuity at ply interfaces. (2) Development of a finite element technique to implement the mathematical model. (3) Investigation of the coupled structures/controls interaction problem to study the complex trade-offs associated with the coupled problem.

Chattopadhyay, Aditi↗

NASA NTRS2011

Energy Usage in an Embedded Space Vision Application on a Tiled Architecture

The need for greater autonomy in platforms such as planetary rovers is driving rapidly to codes that far overwhelm the capabilities of conventional space-qualified single core processors to run them in real-time. However, a new generation of potentially space-qualified 2D "tiled" multi-core microprocessor chips is emerging with significant performance potential. Leveraging such inherently parallel hardware for space platforms requires consideration of both time and power limitations - the latter of which is not normally done in conventional parallel computing. This paper takes one such application, Rockster, and analyzes it for energy usage when ported to a multi-core tiled chip such as may come from the Maestro program. The results demonstrate not only the criticality of memory and interconnect in the energy of real-time parallel codes, but also the effects of possible "energy-aware" changes in partitioning and algorithm design.

multi-core processors↗

DOE OSTI2024

Local structure effects of carbon-doping on the phase change material Ge 2 Sb 2 Te 5

Ge 2 Sb 2 Te 5 is used in phase change memory, a nonvolatile memory technology, due to its phase change properties. The primary advantage of phase change memory over the state-of-the-art (flash memory) is its simple and small device geometry, which allows for denser nodes and lower power consumption. In phase change memory, resistive heating induces fast switching between the high resistance amorphous and low resistance crystalline phases, corresponding to storage of low and high digital states, respectively. However, the instability of the amorphous phase of Ge 2 Sb 2 Te 5 presents issues with processing and long-term data storage; such issues can be resolved by C doping, which stabilizes the amorphous phase and raises the crystallization temperature. To better understand the local structural effects of C doping on Ge 2 Sb 2 Te 5 , in situ Ge K-edge X-ray absorption spectroscopy measurements were taken during heating of films with various C doping concentrations. Here, the range of structural transformation temperatures derived from X-ray absorption near-edge structure analysis across the C doping series proved narrower than crystallization temperatures reported in similar in situ X-ray diffraction experiments, which may reflect changes in local structure that precede long-range ordering during crystallization. In addition, rigorous extended X-ray absorption fine structure fitting across and between temperature series revealed effects of C doping on the rigidity of Ge–Te bonds at low (2 at% and 4 at%) C concentrations.

Langhout, John D.↗

NASA NTRS1992

Study on advanced information processing system

Issues related to the reliability of a redundant system with large main memory are addressed. In particular, the Fault-Tolerant Processor (FTP) for Advanced Launch System (ALS) is used as a basis for our presentation. When the system is free of latent faults, the probability of system crash due to nearly-coincident channel faults is shown to be insignificant even when the outputs of computing channels are infrequently voted on. In particular, using channel error maskers (CEMs) is shown to improve reliability more effectively than increasing the number of channels for applications with long mission times. Even without using a voter, most memory errors can be immediately corrected by CEMs implemented with conventional coding techniques. In addition to their ability to enhance system reliability, CEMs--with a low hardware overhead--can be used to reduce not only the need of memory realignment, but also the time required to realign channel memories in case, albeit rare, such a need arises. Using CEMs, we have developed two schemes, called Scheme 1 and Scheme 2, to solve the memory realignment problem. In both schemes, most errors are corrected by CEMs, and the remaining errors are masked by a voter.

Shin, Kang G.↗

DOE OSTI2014

Effect of silver doping on the surface of La{sub 5/8}Ca{sub 3/8}MnO{sub 3} epitaxial films

Thin film manganese oxides (manganites) display remarkable properties, such as colossal magnetoresistance and charge ordered phases, and became a focal point of research in the past two decades owing to potential applications ranging from oxide spintronics to resistive switching-based memories. La{sub x}Ca{sub 1−x}MnO{sub 3} (LCMO), a widely studied manganite, is known to substantially improve its transport properties when doped with Ag. However, despite the abundance of studies on LCMO, the effect of silver on the surface structure is unknown. Here, through in-situ methods, scanning tunneling microscopy (STM) is performed on La{sub 5/8}Ca{sub 3/8}MnO{sub 3} films grown by pulsed laser deposition. Films doped by silver, as confirmed by in-situ X-ray photoelectron spectroscopy, display large-scale reconstructions, interpreted as being of type (√10 × √10)R18.4°, while films lacking silver display a (√2 × √2)R45° reconstruction that may be associated with a surface charge-ordered state. It is posited that the possible cause of the varied reconstructions is due to a vacancy ordering on top of the existing (√2 × √2)R45° reconstruction. These studies highlight the influence of Ag on the surface structure, and therefore a route towards modifying the surface properties of manganites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1988

Simulation of proton-induced energy deposition in integrated circuits

A time-efficient simulation technique was developed for modeling the energy deposition by incident protons in modern integrated circuits. To avoid the excessive computer time required by many proton-effects simulators, a stochastic method was chosen to model the various physical effects responsible for energy deposition by incident protons. Using probability density functions to describe the nuclear reactions responsible for most proton-induced memory upsets, the simulator determines the probability of a proton hit depositing the energy necessary for circuit destabilization. This factor is combined with various circuit parameters to determine the expected error-rate in a given proton environment. An analysis of transient or dose-rate effects is also performed. A comparison to experimental energy-disposition data proves the simulator to be quite accurate for predicting the expected number of events in certain integrated circuits.

Fernald, Kenneth W.↗

DOE OSTI2023

Polarity effects on wake–up behavior of Al 0.94 B 0.06 N ferroelectrics

Wurtzite ferroelectric materials are promising candidates for energy-efficient memory technologies, particularly for applications requiring high operating temperatures. Asymmetric wake-up behaviors, in which the polarization reversal depends both on polarity and cycle number for the first few dozen cycles, must be better understood for reliable device operation. Here, the detailed analysis of the asymmetric wake-up behavior of thin film Al 0.94 B 0.06 N was performed combining time-resolved switching measurements with Rayleigh analysis, piezoelectric measurements, and etching experiments of progressively switched samples. Furthermore, the analysis shows that the gradual opening of the polarization hysteresis loops associated with wake-up is driven by a gradual increase in the domain-wall density and/or domain-wall mobility with electric field cycle to the polarity opposite to the growth polarity. The insights of this discovery will help to guide interface and polarity design in the eventual deployment of reliable devices based on these materials.

36 MATERIALS SCIENCE↗

NASA NTRS1928

The Effect of a Flap and Ailerons on the N.A.C.A. M-6 Airfoil Section

This report contains the results obtained at the Langley Memorial Aeronautical Laboratory on an N. A. C. A. M-6 airfoil, fitted with a flap and ailerons, and tested in the variable density wind tunnel at a density of 20 atmospheres. Airfoil characteristics are given for the model up to 48 degree angle of attack with the flap set at various angles, and also with the ailerons set at similar angles. The approximate lift distribution and the center of pressure variation along the span are determined with the model at 18 degree angle of attack and with the ailerons displaced at 20 degrees. Approximate rolling moment and yawing moment coefficients are determined for the various aileron settings. A comparison of the calculated angles of zero lift and the calculated lift and moment coefficiencies with those observed is given in the appendix.

Higgins, George J↗

NASA NTRS1993

Single event effects and laser simulation studies

The single event upset (SEU) linear energy transfer threshold (LETTH) of radiation hardened 64K Static Random Access Memories (SRAM's) was measured with a picosecond pulsed dye laser system. These results were compared with standard heavy ion accelerator (Brookhaven National Laboratory (BNL)) measurements of the same SRAM's. With heavy ions, the LETTH of the Honeywell HC6364 was 27 MeV-sq cm/mg at 125 C compared with a value of 24 MeV-sq cm/mg obtained with the laser. In the case of the second type of 64K SRAM, the IBM640lCRH no upsets were observed at 125 C with the highest LET ions used at BNL. In contrast, the pulsed dye laser tests indicated a value of 90 MeV-sq cm/mg at room temperature for the SEU-hardened IBM SRAM. No latchups or multiple SEU's were observed on any of the SRAM's even under worst case conditions. The results of this study suggest that the laser can be used as an inexpensive laboratory SEU prescreen tool in certain cases.

Kim, Q.↗

DOE OSTI2022

Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression

Computer models play a key role in many scientific and engineering problems. One major source of uncertainty in computer model experiments is input parameter uncertainty. Computer model calibration is a formal statistical procedure to infer input parameters by combining information from model runs and observational data. The existing standard calibration framework suffers from inferential issues when the model output and observational data are high-dimensional dependent data, such as large time series, due to the difficulty in building an emulator and the nonidentifiability between effects from input parameters and data-model discrepancy. To overcome these challenges, we, in this work, propose a new calibration framework based on a deep neural network (DNN) with long short-term memory layers that directly emulates the inverse relationship between the model output and input parameters. Adopting the “learning with noise” idea, we train our DNN model to filter out the effects from data-model discrepancy on input parameter inference. We also formulate a new way to construct interval predictions for DNN using quantile regression to quantify the uncertainty in input parameter estimates. Through a simulation study and real data application with the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro), we show our approach can yield accurate point estimates and well-calibrated interval estimates for input parameters.

97 MATHEMATICS AND COMPUTING↗