Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “low 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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

High level tritiated water monitoring by Bremsstrahlung counting using a silicon drift detector

The β-ray induced X-ray spectrometry (BIXS) is a promising technique to monitor the tritium concentration in a fuel cycle of a fusion reactor. For in-situ measurements of high level tritiated water by Bremsstrahlung counting, the characteristics of a low-noise silicon drift detector (SDD) have been examined at the Tritium Laboratory Karlsruhe (TLK). In static measurements with constant sample volume and tritium concentration, the Bremsstrahlung spectra of tritiated water samples in a concentration range of 0.02 to 15 MBq/ml have been obtained. The volume has been kept constant at 5 cm{sup 3}. The observed spectra are well above the noise threshold. In addition to X-rays induced by β-rays, the spectra feature X-ray fluorescence peaks of the surrounding materials. No indications of memory effects have been observed. A linear relation between the X-ray intensity and the tritium concentration was obtained and the lower detection limit of the setup has been determined to 1 MBq ml{sup -1}, assessed by the Curie criterion. In addition, the spectra obtained experimentally could be reproduced with high agreement by Monte-Carlo simulations using the GEANT4-tool-kit. It was found that the present detection system is applicable to non-invasive measurements of high-level tritiated water and the SDD is a convenient tool to detect the low energy Bremsstrahlung X-rays. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Improving energy efficiency of Embedded DRAM Caches for High-end Computing Systems

With increasing system core-count, the size of last level cache (LLC) has increased and since SRAM consumes high leakage power, power consumption of LLCs is becoming a significant fraction of processor power consumption. To address this, researchers have used embedded DRAM (eDRAM) LLCs which consume low-leakage power. However, eDRAM caches consume a significant amount of energy in the form of refresh energy. In this paper, we propose ESTEEM, an energy saving technique for embedded DRAM caches. ESTEEM uses dynamic cache reconfiguration to turn-off a portion of the cache to save both leakage and refresh energy. It logically divides the cache sets into multiple modules and turns-off possibly different number of ways in each module. Microarchitectural simulations confirm that ESTEEM is effective in improving performance and energy efficiency and provides better results compared to a recently-proposed eDRAM cache energy saving technique, namely Refrint. For single and dual-core simulations, the average saving in memory subsystem (LLC+main memory) on using ESTEEM is 25.8% and 32.6%, respectively and average weighted speedup are 1.09X and 1.22X, respectively. Additional experiments confirm that ESTEEM works well for a wide-range of system parameters.

cache reconfiguration↗
DOE OSTI2014

High speed finite element simulations on the graphics card

A software package is developed to perform explicit time domain finite element simulations of ultrasonic propagation on the graphical processing unit, using Nvidia’s CUDA. Of critical importance for this problem is the arrangement of nodes in memory, allowing data to be loaded efficiently and minimising communication between the independently executed blocks of threads. The initial stage of memory arrangement is partitioning the mesh; both a well established ‘greedy’ partitioner and a new, more efficient ‘aligned’ partitioner are investigated. A method is then developed to efficiently arrange the memory within each partition. The technique is compared to a commercial CPU equivalent, demonstrating an overall speedup of at least 100 for a non-destructive testing weld model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Big Advances at the Nano Scale in the Nanocarbons Division

In this issue of ECS Interface, we highlight some exciting success stories for low-dimensional materials in technologically critical fields. These are areas where emergent properties and processes within quantum-confined low-dimensional materials (and heterostructures) enable novel applications beyond what can be achieved in bulk materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Materials for the biorefinery: high bio-content, shape memory Kraft lignin-derived non-isocyanate polyurethane foams using a non-toxic protocol

Polyurethanes are among the top six polymers produced in the world and are widely used in the automotive, furniture, construction and appliance industry for their light weight, impact resistance, and insulating properties. However, the use of hazardous diisocyanates used in polyurethane formulations has led many to search for more sustainable alternatives. The lignin component of biomass has been targeted to replace the often toxic and petroleum-derived precursors to polymer synthesis in support of the biorefinery concept where natural materials are used as the feedstock for commodity plastics. The use of lignin is often hampered due to its low reactivity, heterogeneity and the necessity of employing extensive purification and/or functionalization measures to ensure materials are of comparable quality. In this report, a unique method is presented for the synthesis and processing of a non-toxic, non-isocyanate polyurethane foam utilizing unmodified Kraft lignin and a biobased curing agent. Here, raw Kraft lignin is functionalized with green organic carbonates and a non-toxic approach is taken to solubilize the precursors with a curing agent from renewable fatty acids enabling rapid gel-times. For the first time, a NIPU foam from lignin is synthesized while the structure–property relationship of different reaction mixtures is studied demonstrating shape memory capacity and 100% biobased carbon content.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Realization of write-once-read-many-times memory device with O{sub 2} plasma-treated indium gallium zinc oxide thin film

A write-once-read-many-times (WORM) memory devices based on O{sub 2} plasma-treated indium gallium zinc oxide (IGZO) thin films has been demonstrated. The device has a simple Al/IGZO/Al structure. The device has a normally OFF state with a very high resistance (e.g., the resistance at 2 V is ∼10{sup 9} Ω for a device with the radius of 50 μm) as a result of the O{sub 2} plasma treatment on the IGZO thin films. The device could be switched to an ON state with a low resistance (e.g., the resistance at 2 V is ∼10{sup 3} Ω for the radius of 50 μm) by applying a voltage pulse (e.g., 10 V/1 μs). The WORM device has good data-retention and reading-endurance capabilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Improvements to a class of hybrid methods for radiation transport: Nyström reconstruction and defect correction methods

In this study, two modifications are introduced for improving the accuracy, versatility, and robustness of a class of hybrid methods for radiation transport. In general, such methods are constructed by splitting the radiative flux into collided and uncollided components to which low- and high-resolution angular approximations are applied, respectively. In this work we focus on discrete ordinates discretizations of high and low order. The first modification we introduce changes the way in which the collided component is mapped into the uncollided component at the end of each time step in a simulation. The new mapping is a Nyström-type reconstruction that is applicable to arbitrary discrete ordinates quadratures, is guaranteed to preserve positivity of the solution provided that all ordinate weights are positive, is significantly more accurate than previous methods, and can be readily extended to other discretizations such as moment methods, finite element methods, and diffusion approximations. The second modification leverages integral deferred correction (IDC) to iteratively correct for the splitting error introduced by the inconsistency in angular discretization between the collided and uncollided components, in addition to improving the accuracy of the low-order temporal error that is treated by traditional IDC methods. Numerical tests in one- and two-dimensional geometries are used to demonstrate the increased accuracy and efficiency of the proposed modifications. It is found that the two techniques combined yield methods with solution accuracy and memory requirements comparable to that of monolithic discrete ordinates methods while reducing runtime by as much as a factor of between two and ten, depending on the problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Efficient Ab Initio Auxiliary-Field Quantum Monte Carlo Calculations in Gaussian Bases via Low-Rank Tensor Decomposition

We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While the cost of conventional AFQMC calculations in Gaussian bases scales as O(N 4 ), where N is the size of the basis, we show that ground-state energies can be computed through tensor decomposition with reduced memory requirements and subquartic scaling. Here, the algorithm is applied to hydrogen chains and square grids, water clusters, and hexagonal BN. In all cases, we observe significant memory savings and, for larger systems, reduced, subquartic simulation time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

ADVERT: An Asynchronous Runtime for Fine-Grained Network Systems

The Data Vortex Network, a novel fine-grained high-radix interconnect, provides the performance and injection rates required by the fine-grained, unpredictable communication patterns of irregular applications. This paper presents ADVERT, an asynchronous runtime system that provides performance and productivity for the fine-grained Data Vortex Network. ADVERT integrates a lightweight memory manager (DVMem) for the user accessible SRAM integrated in the network interface, and a communication library (DVComm) that implements active messaging primitives (remote execution, and, based on this, get and put routines). ADVERT hides the complexity of controlling all the network hardware features through the low-level Data Vortex programming interface, while providing comparable performance. We discuss ADVERT's design and present an analysis of three exemplar irregular kernels (Triangle Count, Page Rank, and GUPS). ADVERT can provide the communication substrate required to build emerging higher level asynchronous many tasking runtimes and partitioned global address space libraries on top of the Data Vortex Network.

Friese, Ryan D.↗
DOE OSTI2015

Memory-Efficient Simulation of Frequency-Dependent Q

Memory-variable methods have been widely applied to approximate frequency-independent quality factor Q in numerical simulation of wave propagation. The frequency-independent model is often appropriate for frequencies up to about 1 Hz but at higher frequencies is inconsistent with some regional studies of seismic attenuation. We apply the memory-variable approach to frequency-dependent Q models that are constant below, and follow a power-law above, a chosen transition frequency. We present numerical results for the corresponding memory-variable relaxation times and weights, obtained by nonnegative least-squares fitting of the Q(f) function, for a range of exponent values; these times and weights can be scaled to an arbitrary transition frequency and a power-law prefactor, respectively. The resulting memory-variable formulation can be used with numerical wave-propagation solvers based on methods such as finite differences (FDs) or spectral elements and may be implemented in either conventional or coarse-grained form. In the coarse-grained approach, we fit effective Q for low-Q values (<200) using a nonlinear inversion technique and use an interpolation formula to find the corresponding weighting coefficients for arbitrary Q. A 3D staggered-grid FD implementation closely approximates the frequency–wavenumber solution to both a half-space and a layered model with a shallow dislocation source for Q as low as 20 over a bandwidth of two decades. We compare the effects of different power-law exponents using a finite-fault source model of the 2008 Mw 5.4 Chino Hills, California, earthquake and find that Q(f) models generally better fit the strong-motion data than the constant Q models for frequencies above 1 Hz.

Geochemistry & Geophysics↗
DOE OSTI2016

UDCM Operating Procedure (Limited Functionality prototype)

The UDCM is a two channel low current measurement device designed to record sub-nano-amp to micro-amp currents from radiation detectors. The UDCM incorporates a Commercial-Off-The- Shelf (COTS) processor enabling both serial over USB as well as Ethernet communications. The instrument includes microSD and USB flash memory for data storage as well as a programmable High Voltage (HV) power supply for detector bias. The UDCM incorporates a unique TTL output feature first used in the LANL Current to Pulse Converter (CPC). Two SMA connectors on the UDCM provide TTL pulses at a frequency proportional to the input currents.

47 OTHER INSTRUMENTATION↗
NASA NTRS1998

Anisotropic Optical-Response of Eu-doped Yttrium Orthosilicate

Eu-doped yttrium orthosilicate (Eu(3+) : Y2SiO5) had been a subject being investigated for coherent time-domain optical memory and information processing applications since its ultraslow optical dephasing was discovered several years ago. In this crystal the weakly allowed (7)F0 - (5)D0 transition of europium ions exhibits a sufficient long dephasing time and no spectral difli.usion on a time scale of several hours at low temperature, thus an information pattern or data can be stored as a population grating in the ground state hyperfine levels. On the other hand, the study on photon-echo relaxation shows that the dephasing time T2 of Eu (3+) and other rare-earth ions doped YAG, YAlO3 strongly depends on the intensity of the excitation pulses. In Eu (3+) :YAlO3, an exponential decay of photon-echo with T2 = 53 microseconds if the excitation pulses are weak (5 vJ/pulse) was observed. However, when the excitation pulses are strong (80 pJ/pulse) they observed a much shortened T2 with a highly nonexponential decay pattern. The conclusion they derived is that the intensity-dependent dephasing rate effects are quite general, and it depends on how much the excitation intensity varies. In this paper we use transient grating formation technique showing that a temporal lattice distortion may only occur along crystal c axis, caused by EU (3+) excitation. At high excitation level the produced exciton in conduction band may also couple to the dynamical lattice relaxation process, giving rise to an apparently much shortened dephasing time.

Liu, Huimin↗
NASA NTRS2007

Design of Low Power CMOS Read-Out with TDI Function for Infrared Linear Photodiode Array Detectors

A new low voltage CMOS infrared readout circuit using the buffer-direct injection method is presented. It uses a single supply voltage of 1.8 volts and a bias current of 1uA. The time-delay integration technique is used to increase the signal to noise ratio. A current memory circuit with faulty diode detection is used to remove dark current for background compensation and to disable a photodiode in a cell if detected as faulty. Simulations are shown that verify the circuit that is currently in fabrication in 0.5ym CMOS technology.

Vizcaino, Paul↗
DOE OSTI2024

Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching

Diffusion MRI (dMRI) non-invasively maps brain white matter yet necessitates denoising due to low signal-to-noise ratios. Patch2Self (P2S) employing self-supervised techniques and regression on a Casorati matrix effectively denoises dMRI images and has become the new de-facto standard in this field. P2S however is resource intensive both in terms of running time and memory usage as it uses all voxels (n) from all-but-one held-in volumes (d-1) to learn a linear mapping Phi : \mathbb R ^ n x(d-1) \mapsto \mathbb R ^ n for denoising the held-out volume. The increasing size and dimensionality of higher resolution dMRI acquisitions can make P2S infeasible for large-scale analyses. This work exploits the redundancy imposed by P2S to alleviate its performance issues and inspect regions that influence the noise disproportionately. Specifically this study makes a three-fold contribution: (1) We present Patch2Self2 (P2S2) a method that uses matrix sketching to perform self-supervised denoising. By solving a sub-problem on a smaller sub-space so called coreset we show how P2S2 can yield a significant speedup in training time while using less memory. (2) We present a theoretical analysis of P2S2 focusing on determining the optimal sketch size through rank estimation a key step in achieving a balance between denoising accuracy and computational efficiency. (3) We show how the so-called statistical leverage scores can be used to interpret the denoising of dMRI data a process that was traditionally treated as a black-box. Experimental results on both simulated and real data affirm that P2S2 maintains denoising quality while significantly enhancing speed and memory efficiency achieved by training on a reduced data subset.

Fadnavis, Shreyas↗
DOE OSTI2018

New Insights into Shape Memory Alloy Bimorph Actuators Formed by Electron Beam Evaporation

In order to create shape memory alloy (SMA) bimorph microactuators with high-precision features, a novel fabrication process combined with electron beam (E-beam) evaporation, lift-off resist and isotropic XeF2 dry etching method was developed. To examine the effect of E-beam deposition and annealing process on nitinol (NiTi) characteristics, the NiTi thin film samples with different deposition rate and overflow conditions during annealing process were investigated. With the characterizations using scanning electron microscope and x-ray diffraction, the results indicated that low E-beam deposition rate and argon employed annealing process could benefit the formation of NiTi crystalline structure. In addition, SMA bimorph microactuators with high-precision features as small as 5 microns were successfully fabricated. Furthermore, the thermomechanical performance was experimentally verified and compared with finite element analysis simulation results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Permanently Magnetized Insulating Thin-Film Devices by Reduction

A reduction-based manufacturing process for creating technologically important multilayer structures from lattice-matched ferromagnetic insulators and ferromagnetic conductors is reported. The process is demonstrated by growing a permanently magnetized double-layer structure, consisting of lattice-matched conducting (Ni,Co) and insulating (Ni 0.4 Co 0.6 ) 3 O 3 layers, through a single deposition cycle. The orientation of the metal cation network is preserved after reduction. Close-packing displacements of Ni and Co take place in such a manner that the in-plane hexagonal arrangement is preserved. This is critical for ensuring high-quality interfaces joining the layers. At room temperature the hysteresis loop is centered. At low temperature the oxide layer becomes ferrimagnetically ordered, accompanied by a shift of the hysteresis loop along the magnetic field axis. The shift is assigned to exchange bias phenomenon. Biaxial compressive strain is responsible for the required ferrimagnetic ordering. Finally, spin valves and closely related magnetoresistance random access memory and spin-transfer-torque magnetic random access memory devices are addressed as potential applications.

42 ENGINEERING↗
DOE OSTI2019

Understanding the switching mechanism of interfacial phase change memory

Phase Change Memory (PCM) is a top candidate for next generation data storage, but it typically suffers from high switching (RESET) current density (20–30 MA/cm 2 ). Interfacial Phase Change Memory (IPCM) is a type of PCM using multilayers of Sb 2 Te 3 /GeTe, with up to 100× lower reported RESET current compared to the standard Ge 2 Sb 2 Te 5 -based PCM. Several hypotheses involving fundamentally new switching mechanisms have been proposed to explain the low switching current densities, but consensus is lacking. Here, we investigate IPCM switching by analyzing its thermal, electrical, and fabrication dependencies. First, we measure the effective thermal conductivity (~0.4 W m -1 K -1 ) and thermal boundary resistance (~3.4 m 2 K GW -1 ) of Sb 2 Te 3 /GeTe multilayers. Simulations show that IPCM thermal properties account only for an ~13% reduction of current vs standard PCM and cannot explain previously reported results. Interestingly, electrical measurements reveal that our IPCM RESET indeed occurs by a melt-quench process, similar to PCM. Finally, we find that high deposition temperature causes defects including surface roughness and voids within the multilayer films. Thus, the substantial RESET current reduction of IPCM appears to be caused by voids within the multilayers, which migrate to the bottom electrode interface by thermophoresis, reducing the effective contact area. These results shed light on the IPCM switching mechanism, indicating that an improved control of layer deposition is necessary to obtain reliable switching.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗