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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Combining the mapping Hamiltonian linearized semiclassical approach with the generalized quantum master equation to simulate electronically nonadiabatic molecular dynamics

The generalized quantum master equation (GQME) provides a powerful framework for simulating electronically nonadiabatic molecular dynamics. Within this framework, the effect of the nuclear degrees of freedom on the time evolution of the electronic reduced density matrix is fully captured by a memory kernel superoperator. In this paper, we consider two different procedures for calculating the memory kernel of the GQME from projection-free inputs obtained via the combination of the mapping Hamiltonian (MH) approach and the linearized semiclassical (LSC) approximation. Here, the accuracy and feasibility of the two procedures are demonstrated on the spin-boson model. We find that although simulating the electronic dynamics by direct application of the two LSC-based procedures leads to qualitatively different results that become increasingly less accurate with increasing time, restricting their use to calculating the memory kernel leads to an accurate description of the electronic dynamics. Comparison with a previously proposed procedure for calculating the memory kernel via the Ehrenfest method reveals that MH/LSC methods produce memory kernels that are better behaved at long times and lead to more accurate electronic dynamics

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Modal interactions between a large-wavelength inclined interface and small-wavelength multimode perturbations in a Richtmyer-Meshkov instability

The interaction of a small-wavelength multimodal perturbation with a large-wavelength inclined interface perturbation is investigated for the reshocked Richtmyer-Meshkov instability using three-dimensional simulations. The ares code, developed at Lawrence Livermore National Laboratory, was used for these simulations and a detailed comparison of simulation results and experiments performed at the Georgia Tech Shock Tube facility is presented first for code validation. Simulation results are presented for four cases that vary in large-wavelength perturbation amplitude and the presence of secondary small-wavelength multimode perturbations. Previously developed measures of mixing and turbulence quantities are presented that highlight the large variation in perturbation length scales created by the inclined interface and the multimode complex perturbation. Measures are developed for entrainment, and turbulence anisotropy that help to identify the effects of and competition between each perturbations type. It is shown through multiple measures that before reshock the flow processes a distinct memory of the initial conditions that is present in both large-scale-driven entrainment measures and small-scale-driven mixing measures. After reshock the flow develops to a turbulentlike state that retains a memory of high-amplitude but not low-amplitude large-wavelength perturbations. As a result, it is also shown that the high-amplitude large-wavelength perturbation is capable of producing small-scale mixing and turbulent features similar to the small-wavelength multimode perturbations.

42 ENGINEERING↗
DOE OSTI2019

Single-Net Continual Learning with Progressive Segmented Training

There is an increasing need of continual learning in dynamic systems, such as the self-driving vehicle, the surveillance drone, and the robotic system. Such a system requires learning from the data stream, training the model to preserve previous information and adapt to a new task, and generating a single-headed vector for future inference. Different from previous approaches with dynamic structures, this work focuses on a single network and model segmentation to prevent catastrophic forgetting. Leveraging the redundant capacity of a single network, model parameters for each task are separated into two groups: one important group which is frozen to preserve current knowledge, and secondary group to be saved (not pruned) for a future learning. A fixed-size memory containing a small amount of previously seen data is further adopted to assist the training. Without additional regularization, the simple yet effective approach of Progressive Segmented Training (PST) successfully incorporates multiple tasks and achieves the state-of-the-art accuracy in the single-head evaluation on CIFAR-10 and CIFAR-100 datasets. Moreover, the segmented training significantly improves computation efficiency in continual learning at the edge.

Du, Xiaocong↗
DOE OSTI2024

Development of message passing-based graph convolutional networks for classifying cancer pathology reports

Abstract Background Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language texts. However, the text classification models based on the TextGCN possess weaknesses in terms of memory consumption and model dissemination and distribution. In this paper, we present a fast message passing network (FastMPN), implementing a GCN with message passing architecture that provides versatility and flexibility by allowing trainable node embedding and edge weights, helping the GCN model find the better solution. We applied the FastMPN model to the task of clinical information extraction from cancer pathology reports, extracting the following six properties: main site, subsite, laterality, histology, behavior, and grade. Results We evaluated the clinical task performance of the FastMPN models in terms of micro- and macro-averaged F1 scores. A comparison was performed with the multi-task convolutional neural network (MT-CNN) model. Results show that the FastMPN model is equivalent to or better than the MT-CNN. Conclusions Our implementation revealed that our FastMPN model, which is based on the PyTorch platform, can train a large corpus (667,290 training samples) with 202,373 unique words in less than 3 minutes per epoch using one NVIDIA V100 hardware accelerator. Our experiments demonstrated that using this implementation, the clinical task performance scores of information extraction related to tumors from cancer pathology reports were highly competitive.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Accuracy of estimating the masses of Phobos and Deimos from multiple Viking orbiter encounters

This paper addresses the problem of estimating the masses of Phobos and Deimos from Doppler and onboard optical measurements during the Viking extended mission. A Kalman filter is used to analyze the effects of gravitational uncertainties and nongravitational accelerations. These accelerations destroy the dynamical integrity of the orbit and multi-batch or limited memory filtering is preferred to single batch processing. Optical tracking is essential to improve the relative orbit geometry. The masses can be determined to about 10% and 25% respectively for Phobos and Deimos, assuming satellite densities of about 3 g per cu cm.

Tolson, R. H.↗
NASA NTRS1978

On-board landmark navigation and attitude reference parallel processor system

An approach to autonomous navigation and attitude reference for earth observing spacecraft is described along with the landmark identification technique based on a sequential similarity detection algorithm (SSDA). Laboratory experiments undertaken to determine if better than one pixel accuracy in registration can be achieved consistent with onboard processor timing and capacity constraints are included. The SSDA is implemented using a multi-microprocessor system including synchronization logic and chip library. The data is processed in parallel stages, effectively reducing the time to match the small known image within a larger image as seen by the onboard image system. Shared memory is incorporated in the system to help communicate intermediate results among microprocessors. The functions include finding mean values and summation of absolute differences over the image search area. The hardware is a low power, compact unit suitable to onboard application with the flexibility to provide for different parameters depending upon the environment.

Gilbert, L. E.↗
NASA NTRS1986

An economical semi-analytical orbit theory for micro-computer applications

An economical algorithm is presented for predicting the position of a satellite perturbed by drag and zonal harmonics J2 through J4. Simplicity being of the essence, drag is modeled as a secular decay rate in the semimajor axis (retarded motion) with the zonal perturbations modeled from a modified version of Brouwers formulas. The algorithm is developed as an alternative on-board orbit predictor; a back up propagator requiring low energy consumption; or a ground based propagator for microcomputer applications (e.g., at the foot of an antenna). An O(J2) secular retarded state partial matrix (matrizant) is also given to employ with state estimation. The theory has been implemented in BASIC on an inexpensive microcomputer, the program occupying under 8K bytes of memory. Simulated trajectory data and real tracking data are employed to illustrate the theory's ability to accurately accommodate oblateness and drag effects.

Gordon, R. A.↗
NASA NTRS1987

Applications considerations in the system design of highly concurrent multiprocessors

A flow model processor approach to parallel processing is described, using very-high-performance individual processors, high-speed circuit switched interconnection networks, and a high-speed synchronization capability to minimize the effect of the inherently serial portions of applications on performance. Design studies related to the determination of the number of processors, the memory organization, and the structure of the networks used to interconnect the processor and memory resources are discussed. Simulations indicate that applications centered on the large shared data memory should be able to sustain over 500 million floating point operations per second.

Lundstrom, Stephen F.↗
NASA NTRS1988

An economical semi-analytical orbit theory for micro-computer applications

An economical algorithm is presented for predicting the position of a satellite perturbed by drag and zonal harmonics J sub 2 through J sub 4. Simplicity being of the essence, drag is modeled as a secular decay rate in the semi-axis (retarded motion); with the zonal perturbations modeled from a modified version of the Brouwers formulas. The algorithm is developed as: an alternative on-board orbit predictor; a back up propagator requiring low energy consumption; or a ground based propagator for microcomputer applications (e.g., at the foot of an antenna). An O(J sub 2) secular retarded state partial matrix (matrizant) is also given to employ with state estimation. The theory was implemented in BASIC on an inexpensive microcomputer, the program occupying under 8K bytes of memory. Simulated trajectory data and real tracking data are employed to illustrate the theory's ability to accurately accommodate oblateness and drag effects.

Gordon, R. A.↗
NASA NTRS1991

One GHz digitizer for space based laser altimeter

This is the final report for the research and development of the one GHz digitizer for space based laser altimeter. A feasibility model was designed, built, and tested. Only partial testing of essential functions of the digitizer was completed. Hybrid technology was incorporated which allows analog storage (memory) of the digitally sampled data. The actual sampling rate is 62.5 MHz, but executed in 16 parallel channels, to provide an effective sampling rate of one GHz. The average power consumption of the one GHz digitizer is not more than 1.5 Watts. A one GHz oscillator is incorporated for timing purposes. This signal is also made available externally for system timing. A software package was also developed for internal use (controls, commands, etc.) and for data communication with the host computer. The digitizer is equipped with an onboard microprocessor for this purpose.

Staples, Edward J.↗
NASA NTRS1929

Wind Tunnel Tests on an Airfoil Equipped with a Split Flap and a Slot

The investigation described in this report is concerned with the changes in the aerodynamic characteristics of an airfoil which are produced by a gauze-covered suction slot, located near the leading edge, and connected by an air passage to a split flap at the trailing edge. The tests were conducted at the Langley Memorial Aeronautical Laboratory. At the larger values of lift coefficient where the action of the slot might be expected to be most effective, the pressure differences were such that the air flowed out of the slot rather than in through it, and in consequence, the maximum lift coefficient was decreased.

Bamber, Millard J↗
NASA NTRS1996

Mass Storage and Retrieval at Rome Laboratory

As the speed and power of modern digital computers continues to advance, the demands on secondary mass storage systems grow. In many cases, the limitations of existing mass storage reduce the overall effectiveness of the computing system. Image storage and retrieval is one important area where improved storage technologies are required. Three dimensional optical memories offer the advantage of large data density, on the order of 1 Tb/cm(exp 3), and faster transfer rates because of the parallel nature of optical recording. Such a system allows for the storage of multiple-Gbit sized images, which can be recorded and accessed at reasonable rates. Rome Laboratory is currently investigating several techniques to perform three-dimensional optical storage including holographic recording, two-photon recording, persistent spectral-hole burning, multi-wavelength DNA recording, and the use of bacteriorhodopsin as a recording material. In this paper, the current status of each of these on-going efforts is discussed. In particular, the potential payoffs as well as possible limitations are addressed.

Kann, Joshua L.↗
NASA NTRS2000

Evaluation of Data Retention and Imprint Characteristics of FRAMs Under Environmental Stresses for NASA Applications

A major reliability issue for all advanced nonvolatile memory (NVM) technology devices including FRAMs (Ferroelectric random access memories) is the data retention characteristics over extended period of time, under environmental stresses and exposure to total ionizing dose (TID) radiation effects. For this testing, 256 Kb FRAMs in 28-pin plastic DIPS, rated for industrial grade temperature range of -40 C to +85 C, were procured. These are two-transistor, two-capacitor (2T-2C) design FRAMs. In addition to data retention characteristics, the parts were also evaluated for imprint failures, which are defined as the failure of cells to change from a "preferred" state, where it has been for a significant period of time to an opposite state (e.g., from 1 to 0, or 0 to 1). These 256 K FRAMs were subjected to scanning acoustic microscopy (C-SAM); 1,000 temperature cycles from -65 C to +150 C; high temperature aging at 150 C, 175 C, and 200 C for 1,000 hours; highly accelerated stress test (HAST) for 500 hours; 1,000 hours of operational life test at 125 C; and total ionizing dose radiation testing. As a preconditioning, 10 K read/write cycles were performed on all devices. Interim electrical measurements were performed throughout this characterization, including special imprint testing and final electrical testing. Some failures were observed during high temperature aging test at 200 C, during HAST testing, and during 1,000 hours of operational life at 125 C. The parts passed 10 Krad exposure, but began showing power supply current increases during the dose increment from 10 Krad to 30 Krad, and at 40 Krad severe data retention and parametric failures were observed. Failures from various environmental group testing are currently being analyzed.

Sharma, Ashok K.↗
DOE OSTI2015

Threshold-voltage modulated phase change heterojunction for application of high density memory

Phase change random access memory is one of the most important candidates for the next generation non-volatile memory technology. However, the ability to reduce its memory size is compromised by the fundamental limitations inherent in the CMOS technology. While 0T1R configuration without any additional access transistor shows great advantages in improving the storage density, the leakage current and small operation window limit its application in large-scale arrays. In this work, phase change heterojunction based on GeTe and n-Si is fabricated to address those problems. The relationship between threshold voltage and doping concentration is investigated, and energy band diagrams and X-ray photoelectron spectroscopy measurements are provided to explain the results. The threshold voltage is modulated to provide a large operational window based on this relationship. The switching performance of the heterojunction is also tested, showing a good reverse characteristic, which could effectively decrease the leakage current. Furthermore, a reliable read-write-erase function is achieved during the tests. Phase change heterojunction is proposed for high-density memory, showing some notable advantages, such as modulated threshold voltage, large operational window, and low leakage current.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Analyzing the Energy and Power Consumption of Remote Memory Accesses in the OpenSHMEM Model

PGAS models like OpenSHMEM provide interfaces to explicitly initiate one-sided remote memory accesses among processes. In addition, the model also provides synchronizing barriers to ensure a consistent view of the distributed memory at different phases of an application. The incorrect use of such interfaces affects the scalability achievable while using a parallel programming model. This study aims at understanding the effects of these constructs on the energy and power consumption behavior of OpenSHMEM applications. Our experiments show that cost incurred in terms of the total energy and power consumed depends on multiple factors across the software and hardware stack. We conclude that there is a significant impact on the power consumed by the CPU and DRAM due to multiple factors including the design of the data transfer patterns within an application, the design of the communication protocols within a middleware, the architectural constraints laid by the interconnect solutions, and also the levels of memory hierarchy within a compute node. This work motivates treating energy and power consumption as important factors while designing compute solutions for current and future distributed systems.

Jana, Siddhartha↗
DOE OSTI2014

Analyzing the Energy and Power Consumption of Remote Memory Accesses in the OpenSHMEM Model

PGAS models like OpenSHMEM provide interfaces to explicitly initiate one-sided remote memory accesses among processes. In addition, the model also provides synchronizing barriers to ensure a consistent view of the distributed memory at different phases of an application. The incorrect use of such interfaces affects the scalability achievable while using a parallel programming model. This study aims at understanding the effects of these constructs on the energy and power consumption behavior of OpenSHMEM applications. Our experiments show that cost incurred in terms of the total energy and power consumed depends on multiple factors across the software and hardware stack. We conclude that there is a significant impact on the power consumed by the CPU and DRAM due to multiple factors including the design of the data transfer patterns within an application, the design of the communication protocols within a middleware, the architectural constraints laid by the interconnect solutions, and also the levels of memory hierarchy within a compute node. This work motivates treating energy and power consumption as important factors while designing compute solutions for current and future distributed systems.

Jana, Siddhartha↗
DOE OSTI2023

Atomic scale interface engineering for realizing a perpendicularly magnetized CoFeB-based skyrmion hosting material

Néel-type magnetic skyrmions in perpendicularly magnetized systems have attracted considerable interest due to their potential in fundamental research on topological objects and spintronics applications. Various systems have been explored to study Néel-type magnetic skyrmions, including repeated magnetic multilayers, two-dimensional materials, and single magnetic thin-films. Among these, single magnetic thin-films, especially a CoFeB single layer, offers multiple benefits, such as reduced defect energy, high mobility, and easy integration with existing magnetoresistive random access memory technology. However, optimizing CoFeB-based skyrmion hosting materials remains challenging and requires further systematic and comprehensive investigation. Here, in this study, we examine the effect of atomic-scale interface engineering by inserting a Ta layer between the CoFeB/MgO interface on perpendicular magnetic anisotropy, saturation magnetization, and Dzyaloshinskii–Moriya interaction. Moreover, we provide a guideline for engineering material parameters and demonstrate the validity of atomic-scale interface engineering. Our findings contribute to the development of optimized CoFeB-based skyrmion hosting materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A New Evaluation Metric for Demand Response-Driven Real-Time Price Prediction Towards Sustainable Manufacturing

Abstract The increasing industry energy demand highlights the urgency of demand response management, while the emerging smart manufacturing technologies pave the way for the implementation of real-time price (RTP)-based demand response management towards sustainable manufacturing. The demand response management requires scheduling of manufacturing systems based on RTP predictions, and thus the prediction quality can directly alter the effectiveness of demand response. However, since the general price prediction algorithms and prediction evaluation metrics are not specifically designed for RTP in demand response problems, a good RTP prediction obtained and evaluated by these algorithms and metrics may not be suitable for demand response scheduling. Therefore, in this study, the relationships between the effectiveness of demand response for manufacturing systems and evaluation results from six commonly used metrics are investigated. Meanwhile, a new metric called k-peak distance (KPD), considering the characteristics of the demand response problem, is proposed and compared with the other six metrics. Furthermore, an encoder-decoder long short-term memory recurrent neural network with KPD is proposed to provide better RTP prediction for manufacturing demand response problems. The case studies indicate that the proposed KPD metric shows a 1.8–3.6 times higher correlation with the demand response effectiveness compared to the other metrics. In addition, the production schedule based on the RTP prediction obtained from the proposed algorithm can improve the effectiveness of demand response by 23.4% on average.

Engineering↗