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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗
DOE OSTI2015

Assessing the use of reflectance spectroscopy in determining CsCl stress in the model species Arabidopsis thaliana

Here, reflectance spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress, and has potential applications for use in remediation. Changes in reflectance such as that due to metal stress may occur before damage is visible, and existing studies have shown that metal stress does cause changes in plant reflectance. To further investigate the potential use of reflectance spectroscopy as a method for assessing metal stress in plants, an exploratory study was conducted in which Arabidopsis thaliana plants were treated twice weekly in a laboratory setting with varying levels (0, 0.5, or 5 mM (millimolar)) of caesium chloride (CsCl) solution, and reflectance spectra were collected every week for three weeks using an Analytical Spectral Devices FieldSpec Pro spectroradiometer with both a contact probe (CP) and a field of view (FOV) probe at 36.8 and 66.7 cm, respectively, above the plant. Plants were harvested each week after spectra collection for determination of relative water content and chlorophyll content. A visual assessment of the plants was also conducted using point observations on a uniform grid of 81 points. A mixed-effects model analysis was conducted for each vegetation index (VI) considered to determine the effects of length of treatment, treatment level, view with which spectra were acquired, and the interactions of these terms. Two-way analyses of variance (ANOVAs) were performed on the aforementioned endpoints (e.g. chlorophyll content) to determine the significance of the effects of treatment level and length of treatment. Multiple linear regression (MLR) was used to develop a predictive model for each endpoint, considering VI acquired at each view (CP, high FOV, and low FOV). Of the 14 VI considered, 8 were included in the MLR models. Contact probe readings and FOV readings differed significantly, but FOV measurements were generally consistent at each height.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Turbine-based Power System Tool

Advanced research tools are essential to illustrate the effects of turbine-based power system operations on the electric grid network. This paper presents the development of an open-source tool to visualize the operation of turbine-based electricity generation. The tool exposes power system models, control parameters, and corresponding values of the turbine model and its electrical system, allowing them to customize the simulation according to their needs. The developed tool enables users to simulate power profiles for different turbinebased energy generation such as wind, tidal, and gas turbines. It allows users to investigate the details of the generated profiles of various types of turbine systems at various scales. It can provide valuable insights into model development and facilitate the analysis of integrated power systems. By enabling access to turbine-based operations visualization, the tool aims to bridge the gap between advanced research tools and users, facilitating broader adoption of renewable energy technologies and aiding in developing sustainable power systems.

Kini, Roshan L.↗
DOE OSTI2019

Smart Proxy Modeling of SACROC CO2-EOR

Large CO2-enhanced oil recovery (EOR) projects usually contain an abundance of geological and good performance data. While this volume of data leads to robust models, it often results in difficult to manage, slow-running numerical flow models. To dramatically reduce the numerical run-times associated with the traditional simulation techniques, this work investigated the feasibility of using artificial intelligence and machine learning technologies to develop a smart proxy model of the Scurry Area Canyon Reef Operators Committee (SACROC) oilfield, located in the Permian Basin, TX, USA. Smart proxy models can be used to facilitate injection-production optimization for CO2-EOR projects. The use of a coupled grid-based, and well-based surrogate reservoir model (SRM) (also known as smart proxy modeling) was investigated as the base of the optimization. A fit-for-purpose coupled SRM, which executes in seconds, was built based on high-resolution numerical reservoir simulation models of the northern platform of the SACROC oilfield. This study is unique as it is the first application of coupled SRM at a large oilfield. The developed SRM was able to identify the dynamic reservoir properties (pressure, saturations, and component mole-fraction) at every grid-block, along with the production characteristics (pressure and rate) at each well. Recent attempts to use machine learning and pattern recognition to build proxy models have been simplistic, with limited predictive capabilities. The geological model used in this study is comprised of more than nine million grid blocks. The high correlation between the actual component and SRM, which can be visualized by mapping the properties, along with the fast footprint of the developed model demonstrate the successful application of this methodology.

Vida, Gholami↗
DOE OSTI2023

Using 3D position sensitivity to reveal response non-uniformities in CdZnTe, TlBr, and CsPbBr 3 detectors

Position sensitivity enables the correction of response non-uniformities in room-temperature semiconductor detectors caused by crystal defects and other factors. It can also be used to pinpoint the exact location of crystal defects responsible for the response variations. This work describes a technique for revealing and visualizing the detector regions affecting the charge collection efficiency in CdZnTe (CZT), TlBr, and CsPbBr 3 detectors configured as position-sensitive virtual Frisch-grid (VFG) devices. The technique correlates the photopeak events in energy spectra with their spatial distributions inside the detectors using the position information. By selecting the events from narrow energy intervals within a photopeak, we can visualize the detector volumes with particular charge collection efficiencies, which, in turn, correlate with the locations of electrode and crystal defects. Here, we demonstrate this technique in several examples. Columnar structures in the volume plots (position distribution maps) are consistent with signal losses near or at the anode in selected samples of CZT and TlBr. Structures exhibiting a distinct depth dependence are consistent with grain boundaries or other crystal defects.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Connectivity, Centrality, and Bottleneckedness: On Graph Theoretic Methods for Power Systems

This report provides an introduction to selected graph theoretic topics with pertinence to the structural analysis of electric power grid and communication systems. We focus on methodologies for defining, scoring, and identifying connectivity, spectral, and bottleneckeness properties in graphs, as well as vertex and edge importance measures such as centrality. We apply these measures to power systems and communications graph data, discuss and visualize the results, and comment on computational aspects of these methods. We show that graph theoretic methods can provide useful insights into grid and communication network structure, leading to tools and methods that could be used by electric utility engineers to improve key grid and communication network characteristics, such as resilience and scalability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Improving FERRY: Visualization, Refactoring, and Testing

The Frontier Experiment RegistRY System (FERRY) is a metadata database that contains information about employees, the groups and experiments they belong to, and grid mapping and quota management for the Fermi National Accelerator Laboratory. It is predominantly used to acquire user information. FERRY is accessed through the use of APIs (Application Programming Interface), shown in Figure 1. Corresponding attributes are then displayed for the user in JSON (Java Script Object Notation) format. The goal of this project has been to build upon and improve aspects of FERRY. Including the refactoring of the code, building a visual interface, and creating a testing system for FERRY’s APIs.

Segura, Antonio Thomas↗
DOE OSTI2023

ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites

Zeolites are one of the most widely used materials in the chemical industry due to their nanometer-sized pores that can adsorb and react upon molecules selectively. With hundreds of known framework topologies and hundreds of thousands of computationally predicted structures, the ability to rapidly predict zeolite performance allows researchers to prioritize their efforts on the most promising structures for a given application. Although the accuracy of forcefield-based atomistic simulations has advanced significantly in the past two decades, these simulations can be computationally expensive, especially for long-chain, complex molecules. Here, we present ZeoNet, a representation learning framework using convolutional neural networks (ConvNets) and 3D volumetric representations for predicting adsorption in zeolites. ZeoNet was trained on the task of predicting Henry's constants for adsorption, k H , of n-octadecane in more than 330 000 known and predicted zeolite materials. Employing a 3D grid based on the distances to solvent-accessible surfaces, a volumetric representation that can be generated efficiently, the best-performing ZeoNet achieved a correlation coefficient r 2 = 0.977 and a mean-squared error MSE = 3.8 in ln k H , which corresponds to an error of 9.3 kJ mol -1 in adsorption free energy. In comparison, a model based on hand-designed geometric features has values of r 2 = 0.783 and MSE = 35.7. ZeoNet is also relatively efficient and can process ≈8 structures per second on an Nvidia RTX 2080TI GPU, orders of magnitude faster than forcefield-based simulations. A systematic analysis was conducted to investigate how the choice of ConvNet architectures, the linear dimension (L) and spatial resolution (Δd) of the distance grids, batch size, optimizer, and learning rate impact the model performance. We found that ConvNets based on the ResNet architecture offer the best tradeoff between expressiveness and efficiency. The performance for all models reaches a plateau at L = 30–45 Å and depends less sensitively on grid resolution, with a small benefit around Δd = 0.30–0.45 Å. Finally, saliency maps were visualized to identify which regions of the materials contributed the most to model predictions. It was found, interestingly, that the predictions are driven primarily by the accessible pore volume rather than the region occupied by the framework atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

1.4.2.402 - Water Risk for the Bulk Power System: Asset to Grid Impacts

Utilities and stakeholders need a standardized mechanism for evaluating how future climate and hydrologic conditions translate to water-related risks for power grid assets and systems to support planning decisions. Yet, no such mechanism exists. To address this need, our goals are to: (1) Develop and execute a state-of-the-art multi-model framework to assess future climate-water impacts and risks to the grid, including sensitivities to varying hydrologic drivers and infrastructure scenarios. (2) Create a standardized interactive visualization platform, using data from the climate-water risk assessments, that enables stakeholders to evaluate climate-water impacts, risks, and adaptation measures for power systems.

bulk power system↗
DOE OSTI2016

SU-F-J-28: Development of a New Imaging Filter to Remove the Shadows From the Carbon Fiber Grid Table Top

Purpose: For the image guided radiation therapy (IGRT), the shadows caused by the construction of the treatment couch top adversely affect the visual evaluation. Therefore, we developed the new imaging filter in order to remove the shadows. The performance of the new filter was evaluated using the clinical images. Methods: The new filter was composed of the band-pass filter (BPF) weighted by the k factor and the low-pass filter (LPF). In the frequency region, the stop bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the BPF, and the pass bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the LPF. After adding the filter, the shadows from the carbon fiber grid table top (CFGTT, Varian) on the kV-image was removed. To check the filter effect, we compared the clinical images, which are thorax and thoracoabdominal region, with to without the filter. The subjective evaluation tests was performed by adapting a three-point scale (agree, neither agree nor disagree, disagree) about the 15 persons in the department of radiation oncology. Results: We succeeded in removing all shadows of CFGTT using the new filter. This filter is very useful shown by the results of the subjective evaluation having the 23/30 persons agreed to the filtered clinical images. Conclusion: We concluded that the proposed method was useful tool for the IGRT and the new filter leads to improvement of the accuracy of radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Using Micro-Synchrophasor Data for Advanced Distribution Grid Planning and Operations Analysis

This report reviews the potential for distribution-grid phase-angle data that will be available from new micro-synchrophasors (µPMUs) to be utilized in existing distribution-grid planning and operations analysis. This data could augment the current diagnostic capabilities of grid analysis software, used in both planning and operations for applications such as fault location, and provide data for more accurate modeling of the distribution system. µPMUs are new distribution-grid sensors that will advance measurement and diagnostic capabilities and provide improved visibility of the distribution grid, enabling analysis of the grid’s increasingly complex loads that include features such as large volumes of distributed generation. Large volumes of DG leads to concerns on continued reliable operation of the grid, due to changing power flow characteristics and active generation, with its own protection and control capabilities. Using µPMU data on change in voltage phase angle between two points in conjunction with new and existing distribution-grid planning and operational tools is expected to enable model validation, state estimation, fault location, and renewable resource/load characterization. Our findings include: data measurement is outstripping the processing capabilities of planning and operational tools; not every tool can visualize a voltage phase-angle measurement to the degree of accuracy measured by advanced sensors, and the degree of accuracy in measurement required for the distribution grid is not defined; solving methods cannot handle the high volumes of data generated by modern sensors, so new models and solving methods (such as graph trace analysis) are needed; standardization of sensor-data communications platforms in planning and applications tools would allow integration of different vendors’ sensors and advanced measurement devices. In addition, data from advanced sources such as µPMUs could be used to validate models to improve/ensure accuracy, providing information on normally estimated values such as underground conductor impedance, and characterization of complex loads. Although the input of high-fidelity data to existing tools will be challenging, µPMU data on phase angle (as well as other data from advanced sensors) will be useful for basic operational decisions that are based on a trend of changing data.

25 ENERGY STORAGE↗
DOE OSTI2015

Challenges in the separation and analysis of scattered waves in angle-beam wavefield data

The measurement of ultrasonic signals on a 2-D rectilinear grid resulting from a fixed source, referred to as wavefield imaging, is a powerful tool for visualizing wave propagation and scattering. Wavefield imaging provides a more complete picture of wave propagation than conventional single-point measurements, but creates more challenges for analysis. This work considers the development of wavefield-based methods for analyzing angle-beam wave propagation and scattering in plates. Methods of analysis focus on the separation of scattered waves from the total wavefield with the eventual goal of quantitative scatterer characterization in a laboratory environment. Two methods for wave separation are considered: frequency-wavenumber filtering and wavefield baseline subtraction. Frequency-wavenumber filtering is applied to wavefield data that are finely sampled in both space and time, whereas baseline subtraction is a technique that has typically been applied to individual signals recorded from fixed transducers rather than to full wavefield data. Baseline subtraction of wavefields, particularly for the frequency range considered here, is sensitive to both specimen alignment and temperature variations, whereas frequency-wavenumber methods are limited in their ability to separate waves traveling in the same direction. Results are shown for both methods with a focus on investigating and overcoming the challenges to full wavefield baseline subtraction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

58 GEOSCIENCES↗
DOE OSTI2021

Review of Design Elements within Power Infrastructure Cyber–Physical Test Beds as Threat Analysis Environments

Cyber–physical systems (CPSs) are an integral part of modern society; thus, enhancing these systems’ reliability and resilience is paramount. Cyber–physical testbeds (CPTs) are a safe way to test and explore the interplay between the cyber and physical domains and to cost-effectively enhance the reliability and resilience of CPSs. Here a review of CPT elements, broken down into physical components (simulators, emulators, and physical hardware), soft components (communication protocols, network timing protocols), and user interfaces (visualization-dashboard design considerations) is presented. Various methods used to validate CPS performance are reviewed and evaluated for potential applications in CPT performance validation. Last, initial simulated results for a CPT design, based on the IEEE 33 bus system, are presented, along with a brief discussion on how model-based testing and fault–injection-based testing (using scaling and ramp-type attacks) may be used to help validate CPT performance.

14 SOLAR ENERGY↗
DOE OSTI2013

Westinghouse Fuel Assemblies Performance after Operation in South-Ukraine NPP Mixed Core

The evaluation of WWER-1000 Westinghouse fuel performance was done using the results of post–irradiation examinations of six LTAs and the WFA reload batches that have operated normally in mixed cores at South-Ukraine NPP, Unit-3 and Unit-2. The data on WFA/LTA elongation, FR growth and bow, WFA bow and twist, RCCA drag force and drag work, RCCA drop time, FR cladding integrity as well as the visual observation of fuel assemblies obtained during the 2006-2012 outages was utilized. The analysis of the measured data showed that assembly growth, FR bow, irradiation growth, and Zr-1%Nb grid and ZIRLO cladding corrosion lies within the design limits. The RCCA drop time measured for the LTA/WFA is about 1.9 s at BOC and practically does not change at EOC. The measured WFA bow and twist, and data of drag work on RCCA insertion showed that the WFA deformation in the mixed core is mostly controlled by the distortion of Russian FAs (TVSA) having the higher lateral stiffness. The visual inspection of WFAs carried out during the 2012 outages revealed some damage to the Zr-1%Nb grid outer strap for some WFAs during the loading sequence. The performed fundamental investigations allowed identifying the root cause of grid outer strap deformation and proposing the WFA design modifications for preventing damage to SG at a 225 kg handling trip limit.

assembly distortion↗
DOE OSTI2012

Methods for Data-based Delineation of Spatial Regions

In data analysis, it is often useful to delineate or segregate areas of interest from the general population of data in order to concentrate further analysis efforts on smaller areas. Three methods are presented here for automatically generating polygons around spatial data of interest. Each method addresses a distinct data type. These methods were developed for and implemented in the sample planning tool called Visual Sample Plan (VSP). Method A is used to delineate areas of elevated values in a rectangular grid of data (raster). The data used for this method are spatially related. Although VSP uses data from a kriging process for this method, it will work for any type of data that is spatially coherent and appears on a regular grid. Method B is used to surround areas of interest characterized by individual data points that are congregated within a certain distance of each other. Areas where data are “clumped” together spatially will be delineated. Method C is used to recreate the original boundary in a raster of data that separated data values from non-values. This is useful when a rectangular raster of data contains non-values (missing data) that indicate they were outside of some original boundary. If the original boundary is not delivered with the raster, this method will approximate the original boundary.

Algorithm↗
DOE OSTI2014

A high-performance workflow system for subsurface simulation

Subsurface modeling applications typically neglect uncertainty in the conceptual models, past or future scenarios, and attribute most or all uncertainty to errors in model parameters. In this contribution, uncertainty in technetium-99 transport in a heterogeneous, deep vadose zone is explored with respect to the conceptual model using a next generation user environment called Akuna. Akuna provides a range of tools to manage environmental modeling projects, from managing simulation data to visualizing results from high-performance computational simulators. Core toolsets accessible through the user interface include model setup, grid generation, parameter estimation, and uncertainty quantification. The BC Cribs site at Hanford in southeastern Washington State is used to demonstrate Akuna capabilities. At the BC Cribs site, conceptualization of the system is highly uncertain because only sparse information is available for the geologic conceptual model, the physical and chemical properties of the sediments, and the history of waste disposal operations. Using the Akuna toolset to perform an analysis of conservative solute transport, significant prediction uncertainty in simulated concentrations is demonstrated by conceptual model variation. This demonstrates that conceptual model uncertainty is an important consideration in sparse data environments such as BC Cribs. It is also demonstrated that Akuna and the underlying toolset provides an integrated modeling environment that streamlines model setup, parameter optimization, and uncertainty analyses for high-performance computing applications.

Akuna↗