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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Inverse Method for Estimation of Composite Kink-Band Toughness from Open-Hole Compression Strength Data

Fiber-reinforced polymer matrix composite materials can fail by kink-band propagation mechanism when subjected to in-plane compressive loading. This mode of failure is especially prevalent in compressive loading of laminates with holes, cut-outs, or impact damage. Most of the successful models for predicting compressive strength of such laminates require “fracture” toughness associated with kink-band propagation under in-plane compression. However, this property is difficult to measure experimentally, limiting the use of such models in design practice. In this paper an inverse method is proposed to estimate the kink-band toughness of the laminate from its open-hole compression strength data, which is an easier property to measure experimentally. Furthermore, a scaling relationship is proposed to estimate kink-band toughness for other laminate configurations of the same material.

Luke Borkowski↗
NASA NTRS2020

Neural Network Repair of Lossy Compression Artifacts in the Sept 2015 – March 2016 Duration of the MMS/FPI Dataset

During the Sept 2015 –March 2016 duration (sometimes referred to as Phase 1A) of the Magnetospheric Multiscale Mission (MMS), the Dual Electron Spectrometers (DES) were configured to generously utilize lossy compression. While this maximized the number of velocity distribution functions downlinked, it cameat the expense of lost information content for a fractionof the frames. Following this period of lossy compression, the DES was re-configured in a way that allowed for 95% of the framesto arrive to the ground without loss. Using this high-quality set offrameson-orbit observations, we compressed and decompressed the frameson the ground to create a side-by-side record of the compression effect. This record was used to drive an optimization method that (a) derived basis functions capable of approximating the lossless sample space and with non-negative coefficients and (b) fitted a function which maps the lossy framesto basis weights that recreate the framewithout compression artifacts. This methodis introduced and evaluated in this paper.Data users should expect a higher level of confidence in the absolute scale of density/temperature measurements andnotice less sinusoidal bias in the velocity X and Y components(GSE).

Magnetosphere, Neural Networks, Image Processing, ↗
DOE OSTI2020

Reliable voltage scaled links for compressed data

Systems, apparatuses, and methods for reliably transmitting data over voltage scaled links are disclosed. A computing system includes at least first and second devices connected via a link. In one implementation, if a data block can be compressed to less than or equal to half the original size of the data block, then the data block is compressed and sent on the link in a single clock cycle rather than two clock cycles. If the data block cannot be compressed to half the original size, but if the data block can be compressed enough to include error correction code (ECC) bits without exceeding the original size, then ECC bits are added to the compressed block which is sent on the link at a reduced voltage. The ECC bits help to correct for any errors that are generated as a result of operating the link at the reduced voltage.

42 ENGINEERING↗
DOE OSTI2020

Electrochemical devices comprising compressed gas solvent electrolytes

Disclosed are novel electrolytes, and techniques for making and devices using such electrolytes, which are based on compressed gas solvents. Unlike conventional electrolytes, disclosed electrolytes are based on “compressed gas solvents” mixed with various salts, referred to as “compressed gas electrolytes.” Various embodiments of a compressed gas solvent includes a material that is in a gas phase and has a vapor pressure above an atmospheric pressure at a room temperature. The disclosed compressed gas electrolytes can have wide electrochemical potential windows, high conductivity, low temperature capability and/or high pressure solvent properties.

25 ENERGY STORAGE↗
DOE OSTI2020

CSB-RNN: A Faster-Than-Realtime RNN Acceleration Framework with Compressed Structured Blocks

Recurrent Neural Networks (RNN) is widely applied to temporal sequence analysis, where real-time performance is usually in demand. However, RNN suffers a heavy computational workload as the model comes with a large weight matrix. To alleviate the pain, model compression (pruning) schemes have been proposed for RNN that pruning the redundant (near-zero) weight-values. On the one hand, the non-structured pruning methods achieve a considerable pruning rate while bringing the computational irregularity, which is un-friendly to parallel-hardware. On the other hand, the existing structured pruning methods consider the hardware parallelism; However, they suffer a poor pruning rate due to the restrict constraints on pruning structure. This paper presents CSB-RNN, an optimized full-stack RNN framework with the novel compressed structured block (CSB) technique. The CSB-pruned RNN model comes with both fine-granularity that benefits the pruning rate and regular structure that facilitates the hardware-parallelism. Further, we propose a novel hardware architecture for inferencing the CSB-pruned model. Different from conventional parallel hardware, this architecture solves the block-workload imbalance issue and achieves an over 95% hardware utilization. With the experiments on 10 RNN models in 5 application domains, the CSB-RNN realizes 7×-20× lossless compression and up to 50× acceptable lossy-compression, which is 2×-7× to the prior art. With the addition of the novel hardware, the compressed-RNN inference reaches a super real-time latency of 10-400µs with FPGA implementation.

Shi, Runbin↗
DOE OSTI2023

Device and method for data compression using a metadata cache

A processing device is provided which includes memory comprising data cache memory configured to store compressed data and metadata cache memory configured to store metadata, each portion of metadata comprising an encoding used to compress a portion of data. The processing device also includes at least one processor configured to compress portions of data and select, based on one or more utility level metrics, portions of metadata to be stored in the metadata cache memory. The at least one processor is also configured to store, in the metadata cache memory, the portions of metadata selected to be stored in the metadata cache memory, store, in the data cache memory, each portion of compressed data having a selected portion of corresponding metadata stored in the metadata cache memory. Each portion of compressed data, having the selected portion of corresponding metadata stored in the metadata cache memory, is decompressed.

Das, Shomit N.↗
DOE OSTI2025

Compressed Air Scoping Tool Teaches Energy Efficiency Best Practices

Standards and practices around compressed air systems are evolving as previous golden rules become outdated and unhelpful. One of the most referenced guidelines gives us the perfect example: The previous rule of thumb for compressed air storage – 1-3 gal/cfm1,2 – is now accepted to be 3-5 gal/cfm. This change in recommended storage is only one of many in the industry, resulting in industrial users lost in a sea of contradictory best practices. To help combat confusion and poor information sharing, a collaborative effort between Oak Ridge National Laboratory (ORNL) and the Department of Energy’s (DOE’s) Better Plants program created the Compressed Air (CA) Scoping Tool with the most up-to-date best practices in the industry (as of 2023). It can be used as a nonbiased, one-stop shop for best practice recommendations. The Excelbased tool is designed to be an initial step in understanding the operation of a compressed air system, a baselining tool enabling users to comprehend various aspects of a facility’s system from the production of compressed air to its application by end users.

42 ENGINEERING↗
DOE OSTI2023

Development and characterization of a low-density TiNbZrAlTa refractory high entropy alloy with enhanced compressive strength and plasticity

A new refractory high entropy alloy (RHEA) is designed by combining refractory elements Nb and Ta with Ti, Zr, and Al, resulting in a (TiNbZr) 89 (AlTa) 11 alloy composition with a low-density of 6.0 g/cm 3 . The novel RHEA features a BCC matrix with B2 and Zr 5 Al 3 nano precipitates, exhibiting a compressive yield strength of ~890 MPa and specific yield strength of ~148.3 MPa g -1 cm 3 . Remarkably, the alloy demonstrates excellent compressive plasticity of ~70% at 298 K. As the temperature increases to 873 K, 1073 K, and 1273 K, the yield strength of the RHEA gradually decreases to ~610 MPa, ~ 210 MPa, and ~ 60 MPa, respectively. These results indicate that this novel RHEA showcases a combination of good specific strength and plasticity. Post-compression, B2, and Zr 5 Al 3 phases are observed. In conclusion, the second-phase particles dispersed throughout the grains hinder dislocation motion and contribute to the formation of sub-grain boundaries during hot compression.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Negative linear compressibility in common materials

Negative linear compressibility (NLC) is still considered an exotic property, only observed in a few obscure crystals. The vast majority of materials compress axially in all directions when loaded in hydrostatic compression. However, a few materials have been observed which expand in one or two directions under hydrostatic compression. At present, the list of materials demonstrating this unusual behaviour is confined to a small number of relatively rare crystal phases, biological materials, and designed structures, and the lack of widespread availability hinders promising technological applications. Using improved representations of elastic properties, this study revisits existing databases of elastic constants and identifies several crystals missed by previous reviews. More importantly, several common materials-drawn polymers, certain types of paper and wood, and carbon fibre laminates-are found to display NLC. We show that NLC in these materials originates from the misalignment of polymers/fibres. Using a beam model, we propose that maximum NLC is obtained for misalignment of 26°. The existence of such widely available materials increases significantly the prospects for applications of NLC.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP

With ever-increasing volumes of scientific data produced by high-performance computing applications, significantly reducing data size is critical because of limited capacity of storage space and potential bottlenecks on I/O or networks in writing/reading or transferring data. SZ and ZFP are two leading BSD licensed open source C/C++ libraries for compressed floating-point arrays that support high throughput read and write random access. However, their performance is not consistent across different data sets and across different fields of some data sets, which raises the need for an automatic online (during compression) selection between SZ and ZFP, with minimal overhead. In this paper, the automatic selection optimizes the rate-distortion, an important statistical quality metric based on the signal-to-noise ratio. To optimize for rate-distortion, we investigate the principles of SZ and ZFP. We then propose an efficient online, low-overhead selection algorithm that predicts the compression quality accurately for two compressors in early processing stages and selects the best-fit compressor for each data field. Here, we implement the selection algorithm into an open-source library, and we evaluate the effectiveness of our proposed solution against plain SZ and ZFP in a parallel environment with 1,024 cores. Evaluation results on three data sets representing about 100 fields show that our selection algorithm improves the compression ratio up to 70 percent with the same level of data distortion because of very accurate selection (around 99 percent) of the bestfit compressor, with little overhead (less than 7 percent in the experiments).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Compressed glassy carbon: An ultrastrong and elastic interpenetrating graphene network

Carbon’s unique ability to have both sp 2 and sp 3 bonding states gives rise to a range of physical attributes, including excellent mechanical and electrical properties. We show that a series of lightweight, ultrastrong, hard, elastic, and conductive carbons are recovered after compressing sp 2 -hybridized glassy carbon at various temperatures. Compression induces the local buckling of graphene sheets through sp 3 nodes to form interpenetrating graphene networks with long-range disorder and short-range order on the nanometer scale. The compressed glassy carbons have extraordinary specific compressive strengths—more than two times that of commonly used ceramics—and simultaneously exhibit robust elastic recovery in response to local deformations. Finally, this type of carbon is an optimal ultralight, ultrastrong material for a wide range of multifunctional applications, and the synthesis methodology demonstrates potential to access entirely new metastable materials with exceptional properties.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exploring the feasibility of lossy compression for PDE simulations

Checkpoint restart plays an important role in high-performance computing (HPC) applications, allowing simulation runtime to extend beyond a single job allocation and facilitating recovery from hardware failure. Yet, as machines grow in size and in complexity, traditional approaches to checkpoint restart are becoming prohibitive. Current methods store a subset of the application’s state and exploit the memory hierarchy in the machine. However, as the energy cost of data movement continues to dominate, further reductions in checkpoint size are needed. Lossy compression, which can significantly reduce checkpoint sizes, offers a potential to reduce computational cost in checkpoint restart. This article investigates the use of numerical properties of partial differential equation (PDE) simulations, such as bounds on the truncation error, to evaluate the feasibility of using lossy compression in checkpointing PDE simulations. Restart from a checkpoint with lossy compression is considered for a fail-stop error in two time-dependent HPC application codes: PlasComCM and Nek5000. Results show that error in application variables due to a restart from a lossy compressed checkpoint can be masked by the numerical error in the discretization, leading to increased efficiency in checkpoint restart without influencing overall accuracy in the simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

StimuFrac Compressibility as a Function of CO2 Molar Fraction

Compressibility values were obtained in a range of pressures at 250degC by employing a fixed volume view cell completely filled with PAA aqueous solution and injecting CO2 at constant flow rate (0.3mL/min). Pressure increase as a function of supercritical CO2 (scCO2) mass fraction in the mixture was monitored. The plot shows the apparent compressibility of Stimufrac as a function of scCO2 mass fraction obtained in a pressure range between 2100-7000 psi at 250degC. At small mass fractions of scCO2 the compressibility increases probably due to the dissolution/reaction of CO2 in aqueous PAA and reaches a maximum at mCO2/mH2O = 0.06. Then, compressibility decreases showing a linear relationship with scCO2 mass fraction due to the continuous increase in density of the binary fluid associated to the pressure increase.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

A Framework of Hyperspectral Image Compression using Neural Networks

Hyperspectral image analysis has gained considerable attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows us to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. This paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

Application of Compressive Sensing for Gravitational Microlensing Events

Compressive sensing is a novel mathematical technique for simultaneous data acquisition and compression. This technique is particularly apt for time-series photometric measurements. In this work we apply compressive sensing to time-series photometric measurements specifically obtained due to gravitational microlensing events. We show through simulation modelling the error sensitivity for detecting microlensing event parameters. Particularly, we show the relation of the amount of error and its impact on the microlensing parameters of interest. We derive statistical error bounds to apply those as a baseline for analyzing the effectiveness of compressive sensing application. Our results conclude that for single and binary microlensing events we can obtain error less than 1% over a 3-pixel radius of the center of the microlensing star by using 25% Nyquist rate measurements.

Compressive Sensing↗
DOE OSTI2017

Compression-based integral curve data reuse framework for flow visualization

Currently, by default, integral curves are repeatedly re-computed in different flow visualization applications, such as FTLE field computation, source-destination queries, etc., leading to unnecessary resource cost. We present a compression-based data reuse framework for integral curves, to greatly reduce their retrieval cost, especially in a resource-limited environment. In our design, a hierarchical and hybrid compression scheme is proposed to balance three objectives, including high compression ratio, controllable error, and low decompression cost. Specifically, we use and combine digitized curve sparse representation, floating-point data compression, and octree space partitioning to adaptively achieve the objectives. Results have shown that our data reuse framework could acquire tens of times acceleration in the resource-limited environment compared to on-the-fly particle tracing, and keep controllable information loss. Moreover, our method could provide fast integral curve retrieval for more complex data, such as unstructured mesh data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Observed compression of in situ tree stems during freezing

Freezing temperatures can influence the material properties of trees. Understanding how forest biometeorological interactions respond to freezing temperatures is important for forest science and management, as its effects can cascade through coupled hydrological and ecological processes including limitations on tree growth, changes to canopy interception, and influences on atmospheric turbulence. This short communication details the effect of sub-freezing temperatures on the mechanical displacement of three in situ Pinus contorta Douglas (lodgepole pine) stems during a winter season (2013–2014) at Niwot Ridge Mountain Research Station (CO, USA). Although previous research on harvested trees suggests longitudinal stem expansion should occur as temperatures decrease below freezing, we observed longitudinal compression in live stems below -3 °C that linearl y correlated with sub-zero air temperatures ranging down to -22 °C. Freeze-related compression of stems frequently achieved displacement magnitudes comparable to applying 55 kN of compressive force (800 μm). Hypotheses are proposed to explain the significant mechanical displacement observed due to freezing: (1) internal gas release as freezing fronts propagate through stems; (2) short-term relocation of water via sap exudation or preferential ice crystal growth. As the observed stem compression response to freezing is substantial, future work on underlying processes and consequences is merited. The measurement technique used here may prove useful to others interested in the dynamics of stem freezing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Numerical investigation of a joint approach to thermal energy storage and compressed air energy storage in aquifers

Different from conventional compressed air energy storage (CAES) systems, the advanced adiabatic compressed air energy storage (AA-CAES) system can store the compression heat which can be used to reheat air during the electricity generation stage. Thus, AA-CAES system can achieve a higher energy storage efficiency. Similar to the AA-CAES system, a compressed air energy storage in aquifers (CAESA) system, which is integrated with an aquifer thermal energy storage (ATES) could possibly achieve the same objective. In order to investigate the impact of ATES on the performance of CAESA, different injection air temperature schemes are designed and analyzed by using numerical simulations. Key parameters relative to energy recovery efficiencies of the different injection schemes, such as pressure distribution and temperature variation within the aquifers as well as energy flow rate in the injection well, are also investigated in this study. The simulations show that, although different injection schemes have a similar overall energy recovery efficiency (~97%) as well as a thermal energy recovery efficiency (~79.2%), the higher injection air temperature has a higher energy storage capability. Our results show the total energy storage for the injection air temperature at 80 °C is about 10% greater than the base model scheme at 40 °C. Sensitivity analysis reveal that permeability of the reservoir boundary could have significant impact on the system performance. However, other hydrodynamic and thermodynamic properties, such as the storage reservoir permeability, thermal conductivity, rock grain specific heat and rock grain density, have little impact on storage capability and the energy flow rate. Our study suggests that the combination of ATES and CAESA can help keep the high efficiency of energy storage so as to make CAESA system more efficiency.

25 ENERGY STORAGE↗