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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Effect of Fe{sub 3}O{sub 4} nanoparticles on space charge distribution in propylene carbonate under impulse voltage

Addition of nanoparticles of the ferromagnetic material Fe{sub 3}O{sub 4} can increase the positive impulse breakdown voltage of propylene carbonate by 11.65%. To further investigate the effect of ferromagnetic nanoparticles on the space charge distribution in the discharge process, the present work set up a Kerr electro-optic field mapping measurement system using an array photodetector to carry out time-continuous measurement of the electric field and space charge distribution in propylene carbonate before and after modification. Test results show that fast electrons can be captured by Fe{sub 3}O{sub 4} nanoparticles and converted into relatively slow, negatively charged particles, inhibiting the generation and transportation of the space charge, especially the negative space charge.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors

This report is a revision of the original report, INL/LTD-17-43723. Distribution of the original report was to the Nuclear Regulatory Commission (NRC) only, and the report was not made available to the public. The original report was revised as this report for public distribution. This report presents the latest update of generic prior distributions for common cause failure (CCF) alpha factors, as well as the development of new generic prior distributions for CCF causal alpha factors. The history of CCF treatment and parameter estimations is reviewed. The existing process for developing generic prior distributions is reviewed and used to develop new priors for CCF alpha factors and causal alpha factors. For causal alpha factors, different priors are developed for the five different CCF cause groups: Component (GC), Design (GD), Environment (GE), Human (GH), and Other (GO). These generic prior distributions could be used in the Standardized Plant Analysis Risk (SPAR) models for CCF parameter estimation. The issues and preliminary thoughts regarding prior distribution development are documented. Potential future work is then proposed for improving the process of developing priors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Impact of Salinity on Ground Ice Distribution Across an Arctic Coastal Polygonal Tundra Environment

The heterogeneous distribution of ground ice in the Arctic is a key driver of uneven ground subsidence as permafrost thaws, significantly impacting infrastructure and surface/subsurface hydrology. These topographic and hydrological changes contribute to major uncertainties in energy and carbon fluxes and storage in a warming Arctic. This study aims to improve our understanding of the controls on ground ice and organic matter distribution within the top 3 m of permafrost in coastal polygonal tundra near Utqiagvik, Alaska. To this end, we apply a neural network approach to bulk density distributions derived from nondestructive X-ray tomography of soil cores, trained with laboratory analyses, to improve the resolution and spatial coverage of estimates of dry bulk density, ice content, and organic matter content. In addition, we use capacitively coupled geophysical imaging to map soil electrical conductivity and salinity variations. The results show that sedimentary deposits from ocean transgressions, along with subsequent ice wedge polygon geomorphological processes, jointly influence the distribution of ice content at various scales. The impact of the latter decreases with depth, whereas the influence of salinity and sedimentary history increases. Although the controls on the distribution of soil organic matter content (g/cm 3 ) remain unclear, the pronounced heterogeneity in bulk density strongly influences its calculation from laboratory mass fraction measurements (g/g). From a methodological perspective, the interdependencies among soil components and the need for increased data coverage underscore the value of high-resolution density measurements, such as using X-ray tomography. Overall, this study emphasizes the importance of considering salinity constraints on ice content distribution in coastal permafrost regions. The results are expected to aid in the development of data products and process representations in geomorphological and ecosystem models.

Dafflon, Baptiste [Lawrence Berkeley National Labo↗
DOE OSTI2024

Parallel interior-point solver for block-structured nonlinear programs on SIMD/GPU architectures

Here, we investigate how to port the standard interior-point method to new exascale architectures for block-structured nonlinear programs with state equations. Computationally, we decompose the interior-point algorithm into two successive operations: the evaluation of the derivatives and the solution of the associated Karush-Kuhn-Tucker (KKT) linear system. Our method accelerates both operations using two levels of parallelism. First, we distribute the computations on multiple processes using coarse parallelism. Second, each process uses SIMD/GPU accelerators locally to accelerate the operations using fine-grained parallelism. The KKT system is reduced by eliminating the inequalities and the state variables from the corresponding equations. We demonstrate our method's capability on the supercomputer Polaris, a testbed for the future exascale Aurora system. Each node is equipped with four GPUs, a setup amenable to our two-level approach. Our experiments on the stochastic optimal power flow problem show that the reduction method is 50x faster than the sparse linear solver HSL MA57 running in serial on the CPU, and 6x faster than Pardiso running in parallel on CPU on the same number of processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Continental-scale niche differentiation of dominant topsoil archaea in drylands

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. Here, we hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Characterization of an aluminum alloy hemispherical shell fabricated via direct metal laser melting

The ability of additive manufacturing to directly fabricate complex shapes provides characterization challenges for part qualification. The orientation of the microstructures produced by these processes will change relative to the surface normal of a complex part. In this work, the microscopy and x-ray tomography of an AlSi10Mg alloy hemispherical shell fabricated using powder bed metal additive manufacturing are used to illustrate some of these challenges. The shell was manufactured using an EOS M280 system in combination with EOS-specified powder and process parameters. The layer-by-layer process of building the shell with the powder bed additive manufacturing approach results in a position-dependent microstructure that continuously changes its orientation relative to the shell surface normal. X-ray tomography was utilized to examine the position-dependent size and distribution of porosity and surface roughness in the 98.6% dense part. Optical and electron microscopy were used to identify global and local position-dependent structures, grain morphologies, chemistry, and precipitate sizes and distributions. The rapid solidification processes within the fusion zone (FZ) after the laser transit results in a small dendrite size. Cell spacings taken from the structure in the middle of the FZ were used with published relationships to estimate a cooling rate of ~9 × 10 5 K/s. Uniformly-distributed, nanoscale Si precipitates were found within the primary α-Al grains. A thin, distinct boundary layer containing larger α-Al grains and extended regions of the nanocrystalline divorced eutectic material surrounds the FZ. Moreover, subtle differences in the composition between the latter layer and the interior of the FZ were noted with scanning transmission electron microscopy (STEM) spectral imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Ultrahigh throughput plasma processing of free standing silicon nanocrystals with lognormal size distribution

We demonstrate a method for synthesizing free standing silicon nanocrystals in an argon/silane gas mixture by using a remote expanding thermal plasma. Transmission electron microscopy and Raman spectroscopy measurements reveal that the distribution has a bimodal shape consisting of two distinct groups of small and large silicon nanocrystals with sizes in the range 2-10 nm and 50-120 nm, respectively. We also observe that both size distributions are lognormal which is linked with the growth time and transport of nanocrystals in the plasma. Average size control is achieved by tuning the silane flow injected into the vessel. Analyses on morphological features show that nanocrystals are monocrystalline and spherically shaped. These results imply that formation of silicon nanocrystals is based on nucleation, i.e., these large nanocrystals are not the result of coalescence of small nanocrystals. Photoluminescence measurements show that silicon nanocrystals exhibit a broad emission in the visible region peaked at 725 nm. Nanocrystals are produced with ultrahigh throughput of about 100 mg/min and have state of the art properties, such as controlled size distribution, easy handling, and room temperature visible photoluminescence.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Distribution of Resonance Widths and Dynamics of Continuum Coupling

We analyze the statistics of resonance widths in a many-body Fermi system with open decay channels. Depending on the strength of continuum coupling, such a system reveals growing deviations from the standard chi-square (Porter-Thomas) width distribution. The deviations emerge from the process of increasing interaction of intrinsic states through common decay channels; in the limit of perfect coupling this process leads to the superradiance phase transition. The width distribution depends also on the intrinsic dynamics (chaotic versus regular). The results presented here are important for understanding the recent experimental data concerning the width distribution for neutron resonances in nuclei.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Where Might We Be Headed? Signposts from Other States

Presentation on the state of distributed energy resources interconnection in Wisconsin from the Wisconsin Distributed Resources Collaborative (WIDRC) Interconnection Forum for Distributed Generation. It addresses concerns over application submission and processing, lack of visibility into the distribution system, and uncertainty in upgrade costs.

14 SOLAR ENERGY↗
DOE OSTI2015

Uncertainty quantification for nuclear density functional theory and information content of new measurements

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors using routine measurement of electron beam energy constancy.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Hydrogeological and multi-isotopic approach to define nitrate pollution and denitrification processes in a coastal aquifer (Sardinia, Italy)

Agricultural coastal areas are frequently affected by the superimposition of various processes, with a combination of anthropogenic and natural sources, which degrade groundwater quality. In the coastal multi-aquifer system of Arborea (Italy)—a reclaimed morass area identified as a nitrate vulnerable zone, according to Nitrate Directive 91/676/EEC—intensive agricultural and livestock activities contribute to substantial nitrate contamination. For this reason, the area can be considered a bench test for tuning an appropriate methodology aiming to trace the nitrate contamination in different conditions. An approach combining environmental isotopes, water quality and hydrogeological indicators was therefore used to understand the origins and attenuation mechanisms of nitrate pollution and to define the relationship between contaminant and groundwater flow dynamics through the multi-aquifer characterized by sandy (SHU), alluvial (AHU), and volcanic hydrogeological (VHU) units. Various groundwater chemical pathways were consistent with both different nitrogen sources and groundwater dynamics. Isotope composition suggests a mixed source for nitrate (organic and synthetic fertilizer), especially for the AHU and SHU groundwater. Moreover, marked heterotrophic denitrification and sulfate reduction processes were detected; although, for the contamination related to synthetic fertilizer, the attenuation was inefficient at removing NO{sub 3}{sup −} to less than the human consumption threshold of 50 mg/L. Various factors contributed to control the distribution of the redox processes, such as the availability of carbon sources (organic fertilizer and the presence of lagoon-deposited aquitards), well depth, and groundwater flow paths. The characterization of these processes supports water-resource management plans, future actions, and regulations, particularly in nitrate vulnerable zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Heterogeneous scalable framework for multiphase flows

Two categories of challenges confront the developer of computational spray models: those related to the computation and those related to the physics. Regarding the computation, the trend towards heterogeneous, multi- and many-core platforms will require considerable re-engineering of codes written for the current supercomputing platforms. Regarding the physics, accurate methods for transferring mass, momentum and energy from the dispersed phase onto the carrier fluid grid have so far eluded modelers. Significant challenges also lie at the intersection between these two categories. To be competitive, any physics model must be expressible in a parallel algorithm that performs well on evolving computer platforms. This work created an application based on a software architecture where the physics and software concerns are separated in a way that adds flexibility to both. The develop spray-tracking package includes an application programming interface (API) that abstracts away the platform-dependent parallelization concerns, enabling the scientific programmer to write serial code that the API resolves into parallel processes and threads of execution. The project also developed the infrastructure required to provide similar API s to other application. The API allow object-oriented Fortran applications direct interaction with Trilinos to support memory management of distributed objects in central processing units (CPU) and graphic processing units (GPU) nodes for applications using C++.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Distribution Model Creation using Circuit Maps for Applied PV Impact Studies

Photovoltaic (PV) generation is becoming increasingly common on power distribution systems. The output fluctuations of this variable resource necessitate the creation of an accurate model to ensure that any adverse impacts to the distribution system are properly addressed. To reduce model creation time, a method of extracting data from AutoCAD drawings using scripted methods was developed. This paper will present a distribution model creation and validation process, document case studies of evaluating the impact of PV interconnections on utility distribution feeders, and discuss future applications. PV integration was found to be easier on 23 kV circuits compared to 4.16 kV circuits.

integrated circuit modeling↗
DOE OSTI2017

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

A generalized parallel replica dynamics

Metastability is a common obstacle to performing long molecular dynamics simulations. Many numerical methods have been proposed to overcome it. One method is parallel replica dynamics, which relies on the rapid convergence of the underlying stochastic process to a quasi-stationary distribution. Two requirements for applying parallel replica dynamics are knowledge of the time scale on which the process converges to the quasi-stationary distribution and a mechanism for generating samples from this distribution. By combining a Fleming–Viot particle system with convergence diagnostics to simultaneously identify when the process converges while also generating samples, we can address both points. This variation on the algorithm is illustrated with various numerical examples, including those with entropic barriers and the 2D Lennard-Jones cluster of seven atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗