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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Graph Neural Networks and Applied Linear Algebra v.1.0

SAND2024-01365O The Graph Neural Networks and Applied Linear Algebra is companion software for the educational article with the same title. The software provides illustrative examples of graph neural networks in Matlab and Python. These stand-alone algorithms are for educational purposes. The software also includes graph neural network-based algorithms for a trainable Jacobi iteration as well as diffusion coefficient estimation. The software provides human-interpretable implementations of Graph Neural Networks in Matlab and Python. These implementations are not optimized for performance and instead emphasize readability. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2021

Local models for scatter estimation and descattering in polyenergetic X-ray tomography

We propose a new modeling approach for scatter estimation and descattering in polyenergetic X-ray computed tomography (CT) based on fitting models to local neighborhoods of a training set. X-ray CT is widely used in medical and industrial applications. X-ray scatter, if not accounted for during reconstruction, creates a loss of contrast in CT reconstructions and introduces severe artifacts including cupping, shading, and streaks. Even when these qualitative artifacts are not apparent, scatter can pose a major obstacle in obtaining quantitatively accurate reconstructions. Our approach to estimating scatter is, first, to generate a training set of 2D radiographs with and without scatter using particle transport simulation software. To estimate scatter for a new radiograph, we adaptively fit a scatter model to a small subset of the training data containing the radiographs most similar to it. We compared local and global (fit on full data sets) versions of several X-ray scatter models, including two from the recent literature, as well as a recent deep learning-based scatter model, in the context of descattering and quantitative density reconstruction of simulated, spherically symmetrical, single-material objects comprising shells of various densities. Our results show that, when applied locally, even simple models provide state-of-the-art descattering, reducing the error in density reconstruction due to scatter by more than half.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

EnCache: A Dynamic Profiling Based Reconfiguration Technique for Improving Cache Energy Efficiency

With each CMOS technology generation, leakage energy consumption has been dramatically increasing and hence, managing leakage power consumption of large last-level caches (LLCs) has become a critical issue in modern processor design. In this paper, we present EnCache, a novel software-based technique which uses dynamic profiling-based cache reconfiguration for saving cache leakage energy. EnCache uses a simple hardware component called profiling cache, which dynamically predicts energy efficiency of an application for 32 possible cache configurations. Using these estimates, system software reconfigures the cache to the most energy efficient configuration. EnCache uses dynamic cache reconfiguration and hence, it does not require offline profiling or tuning the parameter for each application. Furthermore, EnCache optimizes directly for the overall memory subsystem (LLC and main memory) energy efficiency instead of the LLC energy efficiency alone. The experiments performed with an x86-64 simulator and workloads from SPEC2006 suite confirm that EnCache provides larger energy saving than a conventional energy saving scheme. For single core and dual-core system configurations, the average savings in memory subsystem energy over a shared baseline configuration are 30.0% and 27.3%, respectively.

Cache Energy Saving↗
DOE OSTI2021

PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient

We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.

Yoon, Tae-Jun↗
DOE OSTI2017

A learning-based measurement framework for traffic matrix inference in software defined networks

Here, we propose an intelligent framework for Traffic Matrix (TM) inference in Software Defined Networks (SDN) where the Ternary Content Addressable Memory (TCAM) entries of switches are partitioned into two parts to: (1) effectively aggregate part of incoming flows for aggregate measurements, and (2) de-aggregate and directly measure the most informative flows for per-flow measurements. These measurements are then processed to effectively estimate the size of network flows. Under hard resource constraints of limited TCAM sizes, we show how to design the optimal and efficient-compressed flow aggregation matrices. We propose an optimal Multi-Armed Bandit (MAB) based algorithm to adaptively measure the most rewarding flows. We evaluate the performance of our framework using real traffic traces from different network environments and by considering two main applications: TM estimation and Heavy Hitter (HH) detection. Moreover, we have implemented a prototype of our framework in Mininet to demonstrate its effectiveness.

42 ENGINEERING↗
DOE OSTI2016

PEES (Parameter Estimator for Engineering Systems) [SWR-16-38]

This software model generates vehicle parameter sets for downstream modeling applications using real-world data. Value to users is provided through improvements to modeling activities as a result of decreases in time taken during model development and validation. Currently configured for transportation modeling activities, the software provides initial estimates for multiple fundamental vehicle parameters including mass, coefficient of drag, and tire rolling resistance using real-world drive and duty cycle information as inputs.

Miller, Eric↗
DOE OSTI2019

Bifacial PV System Mismatch Loss Estimation & Parameterization

Non-uniform irradiance on the rear-side of bifacial PV systems can cause additional mismatch loss which may not be appropriately captured in PV energy production estimates and software. We have evaluated several rooftop mounted systems over high albedo reflective roofs. Mismatch losses of up to 2% annual loss for very close-mounted (0.15 m) rooftop systems were found, but losses for high ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically the mean absolute difference of irradiance) to the resulting mismatch loss factor, with a R2 fit better than 0.985. This approximate relationship has been validated by experiments on mismatched PV modules, and provides a basis for fast estimation of bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM.

14 SOLAR ENERGY↗
DOE OSTI2019

Bifacial PV System Mismatch Loss Estimation and Parameterization: Preprint

Non-uniform irradiance on the rear-side of bifacial PV systems can cause additional mismatch loss which may not be appropriately captured in PV energy production estimates and software. We have evaluated several scenarios including horizontal single-axis tracking (HSAT) and rooftop mounted systems over high albedo reflective roofs. Mismatch losses of up to 2% annual loss for very close-mounted (0.15 m) rooftop systems were found, but losses for HSAT systems and high ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically the mean absolute difference of irradiance) to the resulting mismatch loss factor, with a R2 fit better than 0.985. This approximate relationship has been validated by experiments on mismatched PV modules, and provides a basis for fast estimation of bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM.

14 SOLAR ENERGY↗
DOE OSTI2020

Estimating and parameterizing mismatch power loss in bifacial photovoltaic systems

Nonuniform irradiance on the rear side of bifacial photovoltaic (PV) systems can cause additional mismatch loss, which may not be appropriately captured in PV energy production estimates and software. We evaluated several scenarios including horizontal single-axis tracking (HSAT) over natural ground-cover and rooftop-mounted systems over high albedo reflective roofs. We found mismatch losses of up to 1.5% annual loss for very close-mounted (0.15 m) rooftop systems, but losses for HSAT systems and high-ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically, the mean absolute difference of irradiance) to the resulting mismatch loss factor, with an R 2 better than .99. Furthermore, this approximate relationship was experimentally validated on mismatched PV modules, and it provides a basis for rapidly estimating bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM. Additional parameters investigated include (a) climate dependence and module orientation, which were not found to have a strong impact on bifacial mismatch losses and (b) PV module fill factor and bifaciality ratio, which did have a strong linear impact on mismatch losses.

14 SOLAR ENERGY↗
DOE OSTI2025

Discerning structure sensitivity of Ni-core Pd-shell nanoparticles for enhanced nitrite reduction

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application. In this work, we synthesize water-suspended, structure-controlled Ni-core/Pd-shell nanoparticles (Ni@Pd NPs) that show Pd-catalyzed nitrite (NO 2 − ) reduction catalysis promoted by Ni. The NPs immobilized on Al 2 O 3 (0.47 wt % Pd and 0.74 wt % Ni) have higher NH 4 + selectivity and higher catalytic activity than wet-impregnated Pd/Al 2 O 3 (1.0 wt % Pd), i.e., 315.4 vs. 132.1 Lg surface Pd −1 min −1 . X-ray photoelectron spectroscopy (XPS) and CO-diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS) analyses show that Ni increases Pd electron density, which is proposed to lower the bond dissociation energy barrier for nitric oxide surface intermediate. Low-coordinated Pd atoms correlate to high activity and low NH 4 + selectivity. Using CatCost software, we estimate Ni@Pd/Al 2 O 3 to have a ∼40% lower manufacturing cost compared to wet-impregnated Pd/Al 2 O 3 . This rationally designed catalyst illustrates how nickel promotes Pd catalysis and how Pd usage can be lowered for denitrification and other hydrogenation reactions.

CO-DRIFTS↗
DOE OSTI2016

Characterization of HPGe gamma spectrometric detectors systems for Instrumental Neutron Activation Analysis (INAA) at the Colombian Geological Survey

This paper presents the progress made by the Neutron Activation Analysis (NAA) laboratory at the Colombian Geological Survey (SGC in its Spanish acronym), towards the characterization of its gamma spectrometric systems for Instrumental Neutron Activation Analysis (INAA), with the aim of introducing corrections to the measurements by variations in sample geometry. Characterization includes the empirical determination of the interaction point of gamma radiation inside the Germanium crystal, through the application of a linear model and the use of a fast Monte Carlo N-Particle (MCNP) software to estimate correction factors for differences in counting efficiency that arise from variations in sample density between samples and standards.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Simulated X-Ray Radiographic Performance of a Bismuth-Loaded PVT Array

Recent material advancements in organic plastic scintillators enable marked increases in material detection efficiency, light yield, and pulse shape discrimination properties. These advances may resolve significant capability gaps for lowcost, portable, and durable dual-particle imaging (DPI) systems for nuclear safety, security, and safeguard purposes. One such material, a 21% bismuth-loaded polyvinyl toluene (BiPVT), is computationally evaluated as a small, pixelated radiographic array using Monte Carlo N-Particle (MCNP) and Zemax OpticStudio, and it is compared to identical evaluations of EJ-200 and EJ-256 arrays. MCNP software enables estimates of particle interaction and energy deposition, while OpticStudio computes optical light transport within each material. Here, computational estimates of spatial resolution and relative light collection at 370 kVp are found to agree with experimental results for both EJ-200 and EJ-256 arrays, thereby validating predictions of the same for the BiPVT array. As such, for equivalent exposures at 370 kVp, a BiPVT array may provide ~20× the light collection expected from EJ-200 and ~10× that expected from EJ-256. Similar comparisons of estimated light collection are also computed at 150 and 270 kVp, and these results suggest that BiPVT will provide significantly improved performance over EJ-200 and EJ-256 across all energies practical for portable X-ray radiography.

42 ENGINEERING↗
DOE OSTI2018

Determining the Concentration of Free Electrons in n-InSb from Far-Infrared Reflectance Spectra with Allowance for Plasmon–Phonon Coupling

Contactless nondestructive testing is a means for determining the concentration of free electrons N in indium antimonide (InSb) samples from far-infrared reflectance spectra recorded at room temperature. A computer program capable of determining the characteristic wave number from the Kramers–Kronig relation is developed. The calculated calibration dependence makes it possible to determine the electron concentration from the known characteristic wave number. It is shown that this dependence is described by a cubic polynomial. In the calculations, the energy dependence of the electron effective mass is taken into account. It is established that, in determining the electron concentration, account must be taken of plasmon–phonon coupling, specifically at N ≤ 5 × 10{sup 17} cm{sup –3}. The systematic error introduced into the determination of N by disregard of plasmon–phonon coupling is estimated. The software elaborated here makes it possible to calculate the electron concentration N from experimental reflectance spectra and to store and process the results. The software is tested by the example of the reflectance spectrum of heavily doped n-InSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

There goes the neighborhood: performance degradation due to nearby jobs

Predictable performance is important for understanding and alleviating application performance issues; quantifying the effects of source code, compiler, or system software changes; estimating the time required for batch jobs; and determining the allocation requests for proposals. Our experiments show that on a Cray XE system, the execution time of a communication-heavy parallel application ranges from 28% faster to 41% slower than the average observed performance. Blue Gene systems, on the other hand, demonstrate no noticeable run-to-run variability. In this paper, we focus on Cray machines and investigate potential causes for performance variability such as OS jitter, shape of the allocated partition, and interference from other jobs sharing the same network links. Reducing such variability could improve overall throughput at a computer center and save energy costs.

Computer Science↗
DOE OSTI2022

2-D Surface Temperature Simulation Data and Matlab Scripts

SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sjoberg, Carl Magnus↗
DOE OSTI2020

Framework For Spatial Agricultural Crop Yield Prediction Model Development

This framework was developed to provide data preprocessing for spatiotemporal agricultural yield data and remote sensing data for modelling using artificial neural networks (ANNs) to predict subfield crop yield estimates. The software includes methods to train, validate, and test ANN models. It also include methods to infer on new remote sensing data.

Griffel, LloydM.↗
DOE OSTI2014

Direct Liquid Cooling for Electronic Equipment

This report documents a demonstration of an electronic-equipment cooling system in the engineering prototype development stage that can be applied in data centers. The technology provides cooling by bringing a water-based cooling fluid into direct contact with high-heat-generating electronic components. This direct cooling system improves overall data center energy efficiency in three ways: 1) High-heat-generating electronic components are more efficiently cooled directly using water, capturing a large portion of the total electronic equipment heat generated. This captured heat reduces the load on the less-efficient air-based data center room cooling systems. The combination contributes to the overall savings. 2) The power consumption of the electronic equipment internal fans is significantly reduced when equipped with this cooling system. 3) The temperature of the cooling water supplied to the direct cooling system can be much higher than that commonly provided by facility chilled water loops, and therefore can be produced with lower cooling infrastructure energy consumption and possibly compressor-free cooling. Providing opportunities for heat reuse is an additional benefit of this technology. The cooling system can be controlled to produce high return water temperatures while providing adequate component cooling. The demonstration was conducted in a data center located at Lawrence Berkeley National Laboratory in Berkeley, California. Thirty-eight servers equipped with the liquid cooling system and instrumented for energy measurements were placed in a single rack. Two unmodified servers of the same configuration, located in an adjacent rack, were used to provide a baseline. The demonstration characterized the fraction of heat removed by the direct cooling technology, quantified the energy savings for a number of cooling infrastructure scenarios, and provided information that could be used to investigate heat reuse opportunities. Thermal measurement data were used with data center energy use modeling software to estimate overall site energy use. These estimates show that an overall data center energy savings of approximately 20 percent can be expected if a center is retrofitted as specified in the models used. Increasing the portion of heat captured by this technology is an area suggested for further development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Geochemical Model of E h and pH Transitions in Pore Fluids during Saltstone and SDU Concrete Aging: Saltstone Disposal Facility PA Revision

The chemical and physical properties of the cementitious materials (dry cement, blast furnace slag, and fly ash) used to construct the Saltstone Disposal Units (SDUs) and saltstone waste form play a key role in the design and long-term performance of the Saltstone Disposal Facility. Chemical degradation of the reducing saltstone and concrete over time will impact radionuclide release and transport due to the changing chemical composition of groundwater (GW) percolating through the porous saltstone waste form. An equilibrium reaction path model was developed using The Geochemist’s Workbench® (GWB) software to estimate the timescales (expressed as number of pore volumes) for chemical degradation of the reducing cementitious materials as indicated by changes in redox potential (E h ) and pH.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗