Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “memory”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Characterization of the microstructures and the shape memory properties of the Fe-Mn-Si-Cr-Ni-C shape memory alloy after severe plastic deformation by differential speed rolling and subsequent annealing

Highlights: • The Fe-SMA was subjected to severe plastic deformation and then annealed. • Recovery strain increased with increasing grain size. • An optimum grain size existed for the largest recovery stress. • Grain reduction is useful for having a high recovery stress. - Abstract: The Fe-13.51Mn-4.82Si-8.32Cr-3.49Ni-0.15C shape memory alloy was subjected to severe plastic deformation by high-ratio differential speed rolling and subsequent annealing (between 873 and 1373 K) to find the factors that affect recovery stress and recovery strain. As the annealing temperature increased (i. e., as grain size increased), the recovery strain increased. This was attributed to decrease in the density of grain boundaries and the density of twins with increasing grain size. The recovery stress, however, showed a different behavior. It increased with annealing temperature up to 973 K, at which an ultrafine grain size near 1.6 μm was obtained, and then decreased with further increase in the temperature. The difference between the recovery strain and the plastic strain induced by recovery stress under constrained displacement during cooling was proposed to determine the amount of recovery stress. There was an optimum grain size for the largest difference between the recovery strain and the plastic strain. The current study shows that grain-size reduction is not good for having a high recovery strain but it is beneficial for having a high recovery stress in the Fe-Mn-Si shape memory alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.

dynamic simulation↗
DOE OSTI2015

Memory operation mechanism of fullerene-containing polymer memory

The memory operation mechanism in fullerene-containing nanocomposite gate insulators was investigated while varying the kind of fullerene in a polymer gate insulator. It was cleared what kind of traps and which positions in the nanocomposite the injected electrons or holes are stored in. The reason for the difference in the easiness of programming was clarified taking the role of the charging energy of an injected electron into account. The dependence of the carrier dynamics on the kind of fullerene molecule was investigated. A nonuniform distribution of injected carriers occurred after application of a large magnitude programming voltage due to the width distribution of the polystyrene barrier between adjacent fullerene molecules. Through the investigations, we demonstrated a nanocomposite gate with fullerene molecules having excellent retention characteristics and a programming capability. This will lead to the realization of practical organic memories with fullerene-containing polymer nanocomposites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Direct in situ measurement of coupled magnetostructural evolution in a ferromagnetic shape memory alloy and its theoretical modeling

Ferromagnetic shape memory alloys (FSMAs) have shown great potential as active components in next generation smart devices due to their exceptionally large magnetic-field-induced strains and fast response times. During application of magnetic fields in FSMAs, as is common in several magnetoelastic smart materials, there occurs simultaneous rotation of magnetic moments and reorientation of twin variants, resolving which, although critical for design of new materials and devices, has been difficult to achieve quantitatively with current characterization methods. At the same time, theoretical modeling of these phenomena also faced limitations due to uncertainties in values of physical properties such as magnetocrystalline anisotropy energy (MCA), especially for off-stoichiometric FSMA compositions. Here, in situ polarized neutron diffraction is used to measure directly the extents of both magnetic moments rotation and crystallographic twin-reorientation in an FSMA single crystal during the application of magnetic fields. Additionally, high-resolution neutron scattering measurements and first-principles calculations based on fully relativistic density functional theory are used to determine accurately the MCA for the compositionally disordered alloy of Ni 2 Mn 1.14 Ga 0.86 . The results from these state-of-the-art experiments and calculations are self-consistently described within a phenomenological framework, which provides quantitative insights into the energetics of magnetostructural coupling in FSMAs. Furthermore, based on the current model, the energy for magnetoelastic twin boundaries propagation for the studied alloy is estimated to be ~150 kJ/m 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2016

NANDFlashSim: High-Fidelity, Microarchitecture-Aware NAND Flash Memory Simulation [NANDFlashSim: Intrinsic Latency Variation Aware NAND Flash Memory System Modeling and Simulation at Microarchitecture Level]

As the popularity of NAND flash expands in arenas from embedded systems to high-performance computing, a high-fidelity understanding of its specific properties becomes increasingly important. Further, with the increasing trend toward multiple-die, multiple-plane architectures and high-speed interfaces, flash memory systems are expected to continue to scale and cheapen, resulting in their broader proliferation. However, when designing NAND-based devices, making decisions about the optimal system configuration is nontrivial, because flash is sensitive to a number of parameters and suffers from inherent latency variations, and no available tools suffice for studying these nuances. The parameters include the architectures, such as multidie and multiplane, diverse node technologies, bit densities, and cell reliabilities. Therefore, we introduce NANDFlashSim, a high-fidelity, latency-variation-aware, and highly configurable NAND-flash simulator, which implements a detailed timing model for 16 state-of-the-art NAND operations. Using NANDFlashSim, we notably discover the following. First, regardless of the operation, reads fail to leverage internal parallelism. Second, MLC provides lower I/O bus contention than SLC, but contention becomes a serious problem as the number of dies increases. Third, many-die architectures outperform many-plane architectures for disk-friendly workloads. Lastly, employing a high-performance I/O bus or an increased page size does not enhance energy savings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The microstructure of a selective laser melting (SLM)-fabricated NiTi shape memory alloy with superior tensile property and shape memory recoverability

A selective laser melting (SLM)-fabricated NiTi with superior tensile property and shape memory recoverability was obtained by using a unique stripe rotation scanning strategy. Here, the alloy characteristics, formation mechanisms and evolution in terms of twins, dislocations and precipitations of the alloy were systematically studied. Compared to the conventional smelting-followed-by-machining, the SLM fabrication process involves rapid solidification and repeated heating, which confer distinctive characteristics to the microstructures of SLM-fabricated NiTi alloys. Rapid solidification promotes the formation of a supersaturation solid solution matrix containing a high concentration vacancies, which in turn aggregate to generate a high density of dislocations. During subsequent repeated heating stages, these dislocations occur thermal motion along three directions of <001 > , <111> and <110 >, leading to the formation of thermal kinks, helical dislocations and wave morphology. Simultaneously, precipitated particles Ti 3 Ni 4 repeatedly nucleate and heterogeneous grow with the movement of dislocation. Such precipitation behavior, termed repeated precipitation, has not been previously reported in the conventional NiTi alloys, suggesting that it could be a unique characteristic of such alloy. After martensitic transformation, only two twins, {1 1¯ 1} type I twin and compound twin, are detected. The twinning lamellae of these two twins, where precipitation and dislocation pile-ups exist, often have uneven thickness and chaotic arrangement. Besides, the unique self-accommodated microstructures, such as secondary {1 1¯ 1} type I twin and compound twin with “herring-bone’’ lamellae, which often appear in the deformed or nanocrystalline NiTi, can also be observed. These unique microstructures may confer the distinctive properties to the SLM-fabricated NiTi.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ScaWL: Scaling k-WL (Weisfeiler-Lehman) Algorithms in Memory and Performance on Shared and Distributed-Memory Systems

The k-dimensional Weisfeiler-Lehman (k-WL) algorithm—developed as an efficient heuristic for testing if two graphs are isomorphic—is a fundamental kernel for node embedding in the emerging field of graph neural networks. Unfortunately, the k-WL algorithm has exponential storage requirements, limiting the size of graphs that can be handled. This work presents a novel k-WL scheme with a storage requirement orders of magnitude lower while maintaining the same accuracy as the original k-WL algorithm. Due to the reduced storage requirement, our scheme allows for processing much bigger graphs than previously possible on a single compute node. For even bigger graphs, we provide the first distributed-memory implementation. Our k-WL scheme also has significantly reduced communication volume and offers high scalability. Our experimental results demonstrate that our approach is significantly faster and has superior scalability compared to five other implementations employing state-of-the-art techniques.

algorithims↗
DOE OSTI2019

Photo‐/Thermal‐Responsive Field‐Effect Transistor upon Blending Polymeric Semiconductor with Hexaarylbiimidazole toward Photonically Programmable and Thermally Erasable Memory Device

Abstract It is shown that the semiconducting performance of field‐effect transistors (FETs) with PDPP4T (poly(diketopyrrolopyrrole‐quaterthiophene)) can be reversibly tuned by UV light irradiation and thermal heating after blending with the photochromic hexaarylbiimidazole compound ( p ‐NO 2 ‐HABI). A photo‐/thermal‐responsive FET with a blend thin film of PDPP4T and p ‐NO 2 ‐HABI is successfully fabricated. The transfer characteristics are altered significantly with current enhanced up to 10 6 ‐fold at V G = 0 V after UV light irradiation. However, further heating results in the recovery of the transfer curve. This approach can be extended to other semiconducting polymers such as P3HT (poly(3‐hexyl thiophene)), PBTTT (poly(2,5‐bis(3‐tetradecylthiophen‐2‐yl)thieno[3,2‐b] thiophene)) and PDPPDTT (poly(diketopyrrolopyrrole‐dithienothiophene)). It is hypothesized that TPIRs (2,4,5‐triphenylimidazolyl radicals) formed from p ‐NO 2 ‐HABI after UV light irradiation can interact with charge defects at the gate dielectric–semiconductor interface and those in the semiconducting layer to induce more hole carriers in the semiconducting channel. The application of the blend thin film of PDPP4T and p ‐NO 2 ‐HABI is further demonstrated to fabricate the photonically programmable and thermally erasable FET‐based nonvolatile memory devices that are advantageous in terms of i) high ON/OFF current ratio, ii) nondestructive reading at low electrical bias, and iii) reasonably highly stable ON‐state and OFF‐state.

Liu, Yidong↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗
DOE OSTI2015

H-treatment impact on conductive-filament formation and stability in Ta{sub 2}O{sub 5}-based resistive-switching memory cells

In this article, we evidence the lower formation energy and improved stability of the conductive filament (CF) formed in TiN\Ta{sub 2}O{sub 5}\Ta resistive-switching memory cells treated in NH{sub 3} atmosphere at 400 °C. This annealing treatment results in (i) lower forming voltage, (ii) lower CF resistance, and (iii) longer retention lifetime of the oxygen-vacancy (V{sub o}) chain constituting the CF. Atomistic insights into these processes are provided by ab initio calculations performed for hydrogen (H) species incorporated in non-stoichiometric Ta{sub 2}O{sub 5} supercells: (i) V{sub o} formation energy is reduced by the presence of H, (ii) V{sub o}-chain CF conductivity is increased by V{sub o} + OH complex formation, and (iii) V{sub o}-chain retention is strengthened by the stable V{sub o} + OH complex. As a result, efficient CF formation and excellent state stability are obtained after 15 days at 250 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2018

BMS symmetry, soft particles and memory

Here, in this work, we revisit unitary irreducible representations of the Bondi–Metzner–Sachs (BMS) group discovered by McCarthy. Representations are labelled by an infinite number of supermomenta in addition to 4-momentum. Tensor products of these irreducible representations lead to particle-like states dressed by soft gravitational modes. Conservation of 4-momentum and supermomentum in the scattering of such states leads to a memory effect encoded in the outgoing soft modes. We note there exist irreducible representations corresponding to soft states with strictly vanishing 4-momentum, which may nevertheless be produced by scattering of particle-like states. This fact has interesting implications for the S-matrix in gravitational theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗