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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

High Resolution Stereoscopic PIV Measurements in a 5 x 5 Rod Bundle with Mixing Vane

Spacer grids are used in the pressurized water reactor (PWR) to fix, clamp the fuel rods, and enhance the turbulence mixing within the spaces of the rods and overall heat transfer performance. Proper understanding on the thermal-hydraulic characteristics of the turbulent mixing and heat transfer created by the space grids is important. However, spacer grids having complex design structure with dimple, mixing vane and spring have been challenges for computational fluid dynamics (CFD) turbulent models. High fidelity experimental data with spatial-temporal resolutions is essential to validate and assess the performances of CFD models. Baglietto and Ninokata applied an improved realizable anisotropic turbulence models via direct numerical simulation (DNS)-based near-wall formulation data to study the wall shear stresses and flow structures in tight bundle subchannels. These authors have shown that their models are able to capture the stress distribution and velocity field at an acceptable accuracy. The authors numerically studied the flow field characteristics at the region downstream of the spacer grids, and validated their results to particle imagery velocimetry (PIV) measurements. Dominguez and Hassan performed two-dimensional time resolved PIV (TR-PIV) measurements within a 5 x 5 PWR rod bundle with spacer-grids that utilized a matching index of refraction (MIR) approach. Their averaged data showed a rather uniform direction velocity profile after the spacer grid while the downstream illustrated a no slip wall profile. In this paper, we presents flow measurements in the MIR 5 x 5 fuel rod bundle with a spacer grid. Time resolved stereoscopic PIV (TR-SPIV) measurements were performed to obtain high spatial-temporal resolution two-dimensional three-component (2D3C) velocity vector fields in the subchannels between the rods. Flow statistics such as mean velocity, and Reynolds stresses were computed. The obtained experimental data can be used to improve the computational modeling and validate the numerical models that are currently applied to light and pressurized water reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types

Here, a recent assessment that quantified potential impacts of solar energy development on water resources in the southwestern United States necessitated the development of a methodology to identify locations of mountain front recharge (MFR) in order to guide land development decisions. A spatially explicit, slope-based algorithm was created to delineate MFR zones in 17 arid, mountainous watersheds using elevation and land cover data. Slopes were calculated from elevation data and grouped into 100 classes using iterative self-organizing classification. Candidate MFR zones were identified based on slope classes that were consistent with MFR. Land cover types that were inconsistent with groundwater recharge were excluded from the candidate areas to determine the final MFR zones. No MFR reference maps exist for comparison with the study’s results, so the reliability of the resulting MFR zone maps was evaluated qualitatively using slope, surficial geology, soil, and land cover datasets. MFR zones ranged from 74 km2 to 1,547 km2 and accounted for 40% of the total watershed area studied. Slopes and surficial geologic materials that were present in the MFR zones were consistent with conditions at the mountain front, while soils and land cover that were present would generally promote groundwater recharge. Visual inspection of the MFR zone maps also confirmed the presence of well-recognized alluvial fan features in several study watersheds. While qualitative evaluation suggested that the algorithm reliably delineated MFR zones in most watersheds overall, the algorithm was better suited for application in watersheds that had characteristic Basin and Range topography and relatively flat basin floors than areas without these characteristics. Because the algorithm performed well to reliably delineate the spatial distribution of MFR, it would allow researchers to quantify aspects of the hydrologic processes associated with MFR and help local land resource managers to consider protection of critical groundwater recharge regions in their development decisions.

58 GEOSCIENCES↗
DOE OSTI2019

Spatially resolved degradation during startup and shutdown in polymer electrolyte membrane fuel cell operation

Polymer electrolyte membrane fuel cells have durability limitations associated with the startup and shutdown of the fuel cell, which is critical for real-world vehicle commercialization. During startup or shutdown, there exists an active region (hydrogen/air) and a passive region (air/air) between the cell inlet and outlet. Internal currents are generated in the passive region causing high-potential excursion in the cathode leading to accelerated carbon corrosion. In this study, a segmented cathode hardware is used to evaluate the effect of platinum loading on both cathode and anode, and carbon support material on degradation due to repeated series of startups or shutdowns. Here, in situ losses in the performance and electrochemical surface area were measured spatially, and ex situ analysis of the catalyst layer thickness and platinum particle size was performed to understand the effect of startup or shutdown on different membrane electrode assembly materials. Startup degrades the region near anode outlet more, while shutdown degrades the region near anode inlet more compared to the rest of the electrode. While various system mitigation strategies have been reported in the literature to limit this degradation, one materials mitigation strategy is to limit the anode's ability to reduce oxygen to water through increasing the ratio of platinum loading in the cathode to the anode, or by using a bi-functional catalyst.

25 ENERGY STORAGE↗
DOE OSTI2020

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Minimum detectable activity for tomographic gamma scanning system - 15648

For any radiation measurement system, it is useful to explore and establish the detection limits and a minimum detectable activity (MDA) for the radionuclides of interest, even if the system is to be used at far higher values. The MDA serves as an important figure of merit, and often a system is optimized and configured so that it can meet the MDA requirements of a measurement campaign. The non-destructive assay (NDA) systems based on gamma ray analysis are no exception and well established conventions, such the Currie method, exist for estimating the detection limits and the MDA. However, the Tomographic Gamma Scanning (TGS) technique poses some challenges for the estimation of detection limits and MDAs. The TGS combines high resolution gamma ray spectrometry (HRGS) with low spatial resolution image reconstruction techniques. In non-imaging gamma ray based NDA techniques measured counts in a full energy peak can be used to estimate the activity of a radionuclide, independently of other counting trials. However, in the case of the TGS each 'view' is a full spectral grab (each a counting trial), and each scan consists of 150 spectral grabs in the transmission and emission scans per vertical layer of the item. The set of views in a complete scan are then used to solve for the radionuclide activities on a voxel by voxel basis, over 16 layers of a 10x10 voxel grid. Thus, the raw count data are not independent trials any more, but rather constitute input to a matrix solution for the emission image values at the various locations inside the item volume used in the reconstruction. So, the validity of the methods used to estimate MDA for an imaging technique such as TGS warrant a close scrutiny, because the pair-counting concept of Currie is not directly applicable. One can also raise questions as to whether the TGS, along with other image reconstruction techniques which heavily intertwine data, is a suitable method if one expects to measure samples whose activities are at or just above MDA levels. The paper examines methods used to estimate MDAs for a TGS system, and explores possible solutions that can be rigorously defended. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs

Fully distributed, integrated surface–subsurface hydrological models (ISSHMs) have seen renewed interest due to availability of better software, high performance computing facilities, and high-resolution, spatially extensive data products. ISSHMs are valuable as tools for advancing system understanding as they can resolve multiple processes defined on the plot scale including three-dimensional interaction of surface water and groundwater. Here, we evaluated the performance of an ISSHM, the Advanced Terrestrial Simulator (ATS), on seven diverse catchments across the continental US using widely available data products to define model inputs without calibration. We compare the ATS-simulated streamflow and evapotranspiration with gauge observations and MODIS-derived evapotranspiration, respectively. Using the Kling-Gupta Efficiency (KGE) as metric, ATS with default data products performed reasonably well at 6 of 7 catchments for streamflow. However, in one of those 6 catchments ATS had poor performance on baseflow and ATS’s overall performance was thus judged to be inadequate despite the acceptable KGE. ATS performance for evapotranspiration was good in all 7 catchments using default data products. In the two catchments where ATS streamflow performance using default data products was not acceptable, the performance was significantly improved by using local information on subsurface properties below the soil. We also compare the model-simulated streamflow and evapotranspiration with the Sacramento soil moisture accounting (SAC-SMA) model, a semi-distributed model that was calibrated on a catchment-by-catchment basis. Uncalibrated ATS performance is comparable to the calibrated SAC-SMA model in terms of streamflow while ATS performance is similar to or better (much better in certain catchments) in reproducing MODIS-derived evapotranspiration. Reasonably good performance of ATS without catchment-specific calibration provides new confidence in the ISSHM class of models and community data products as tools for advancing understanding of watershed function in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Molecular Breast Imaging Using Emission Tomosynthesis

Purpose: Tour objective is to design a novel SPECT system for molecular breast imaging (MBI) and evaluate its performance. The limited angle SPECT system, or emission tomosynthesis, is designed to achieve 3D images of the breast with high spatial resolution/sensitivity. The system uses a simplified detector motion and is conducive to on-board biopsy and mult-modal imaging with mammography. Methods: The novel feature of the proposed gamma camera is a variable-angle, slant-hole (VASH) collimator, which is well suited for limited angle SPECT of a mildly compressed breast. The collimator holes change slant angle while the camera surface remains flush against the compression paddle. This allows the camera to vary the angular view ({+-}30{degrees}, {+-}45{degrees}) for tomographic imaging while keeping the camera close to the object for high spatial resolution and/or sensitivity. Theoretical analysis and Monte Carlo simulations were performed assuming a point source and isolated breast phantom. Spatial resolution, sensitivity, contrast and SNR were measured. Results were compared to single-view, planar images and conventional SPECT. For both conventional SPECT and VASH, data were reconstructed using iterative algorithms. Finally, a proof-of-concept VASH collimator was constructed for experimental evaluation. Results: Measured spatial resolution/sensitivity with VASH showed good agreement with theory including depth-of-interaction (DOI) effects. The DOI effect diminished the depth resolution by approximately 2 mm. Increasing the slant angle range from {+-}30{degrees} to {+-}45{degrees} resulted in an approximately 1 mm improvement in the depth resolution. In the breast phantom images, VASH showed improved contrast and SNR over conventional SPECT and improved contrast over planar scintimmammography. Reconstructed images from the proof-of-concept VASH collimator demonstrated reasonable depth resolution capabilities using limited angle projection data. Conclusion: We conclude that this limited angle SPECT approach using a VASH collimator can achieve superior 3D image quality for MBI in a design that has attractive characteristics for clinical imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task-based optimization framework provides a promising approach that maximizes imaging performance under the same total dose constraint.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modeling approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.

Tesfa, Teklu K.↗
DOE OSTI2021

Controlling hydrocarbon transport and electron beam induced deposition on single layer graphene: Toward atomic scale synthesis in the scanning transmission electron microscope

Abstract Focused electron beam induced deposition (FEBID) is a direct write technique for depositing materials on a support substrate akin to 3D printing with an electron beam (e‐beam). Opportunities exist for merging this existing technique with aberration‐corrected scanning transmission electron microscopy to achieve molecular‐ or atomic‐level spatial precision. Several demonstrations have been performed using graphene as the support substrate. A common challenge that arises during this process is e‐beam‐induced hydrocarbon deposition, suggesting greater control over the sample environment is needed. Various strategies exist for cleaning graphene in situ. One of the most effective methods is to rapidly heat to high temperatures, for example, 600℃ or higher. While this can produce large areas of what appears to be atomically clean graphene, mobile hydrocarbons can still be present on the surfaces. Here, we show that these hydrocarbons are primarily limited to surface migration and demonstrate an effective method for interrupting the flow using e‐beam deposition to form corralled hydrocarbon regions. This strategy is effective for maintaining atomically clean graphene at high temperatures where hydrocarbon mobility can lead to substantial accumulation of unwanted e‐beam deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images

Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997–2016). Satellite-derived results showed that on average about 3.47 - 4.53 x 10 4 km 2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 10 4 km 2 , accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High spatial resolution neutron imaging of lithium-ion batteries: Correlating microstructure and lithium transport

Thick electrodes for lithium-ion batteries can increase the overall energy density, but increasing the electrode thickness introduces charge transport limitations. These limitations may be mitigated through proper electrode structuring. Here, high spatial resolution neutron imaging was used to understand the correlation between microstructure and lithium transport in lithium-ion anodes. Batteries with distinct graphite anode microstructures were produced and studied with high spatial resolution in operando neutron radiography to observe the effects of structure on transport. High spatial resolution neutron computed tomography was performed following in operando neutron radiography. X-ray computed tomography and scanning electron microscopy were used to observe the finer scale anode structure to complement neutron imaging. Solvent-free anodes containing a tightly-packed layered structure confined lithium movement close to the separator. This structure limited capacity, but supported better rate capability. Conversely, a more open pore structure in the wet cast anodes yielded higher capacity with reduced rate capability. Together, these results show that lithium distributions can be controlled by the macroscopic structure of the electrodes, the microstructural pore network, and the microscale active areas that support electrochemical reactions. Furthermore, multimodal imaging applying the complementary strengths of neutron and X-ray methods is shown as a tool for advancing battery design.

25 ENERGY STORAGE↗
DOE OSTI2025

Angular-spatial hp -adaptivity for radiative transfer with discontinuous Galerkin spectral element methods

Radiative transfer is important for many science and engineering applications, and numerical simulations of radiative transfer can be challenging. For instance, the radiation field is seven-dimensional – three spatial, two angular, one wavelength, and one temporal – and often features steep gradients. Therefore, memory usage is a key issue. To reduce memory, some past work has investigated the use of adaptive mesh refinement (AMR), typically for either the spatial or angular coordinate, and typically for only h -adaptivity. Here, we propose the use of AMR for the spatial and angular coordinates together, and the use of h - and p -adaptivity together as hp -AMR for the potential for further memory savings. We implemented the proposed method for several test cases in two spatial and one angular dimension, with the discontinuous Galerkin spectral element method. These test cases featured highly anisotropic angular radiation, with or without steep spatial gradients. Our primary findings from these test cases were: (1) Angular hp -adaptivity can deliver the radiation solution with the same accuracy as, and with much less computational memory than, uniform angular h - or p -refinements, or angular h -adaptivity alone. This is most obvious when the incoming radiation is highly anisotropic, in which case the savings can be orders of magnitude. (2) Full spatial-angular hp -adaptivity is more efficient in solution representation, compared to solely spatial or solely angular -adaptivity. This is most evident when steep gradients are present in both the spatial and angular distribution. These results suggest that adaptive spatial- hp angular-refinement may perform well in large-scale seven-dimensional applications.

Adaptive refinement↗
DOE OSTI2023

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗