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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2024

DEPLOYING FAST CHARGING INFRASTRUCTURE FOR ELECTRIC VEHICLES IN URBAN NETWORKS: AN ACTIVITY-BASED APPROACH

This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users' daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charge (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. The problem of finding the optimum charging configuration is then formulated as a mixed-integer nonlinear programming problem that considers the dynamics of travel time and travel distance, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.

Chain of Trips↗
DOE OSTI2023

Data for Climate vs Energy Security: Quantifying the Trade-offs of BECCS Deployment and Overcoming Opportunity Costs on Set-Aside Land

Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14–36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year–1 from the atmosphere, deliver up to 16 Tg CE year–1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.

Field Data↗
DOE OSTI2025

Entanglement-based quantum digital signatures over a deployed campus network: erratum

We correct a minor error in Table 1 and a related minor error in the simulations of the improved system. These revisions result in minor changes to Fig. 6 and Table 1 in [ Opt. Express 32 , 7521 ( 2024 ) 10.1364/OE.510787 ]. These changes do not affect the experimental measurements or the conclusions of the work.

Chapman, Joseph C. (ORCID:0000000233460914)↗
DOE OSTI2020

Report on the deployment of the National Geothermal Data System 2.0

This reports includes a video description of recent upgrades and changes to the National Geothermal Data System (geothermaldata.org) and a text report of its relevant security upgrades. Improvements include a new operating system, implementation of HTTPS, implementation of a standard firewall, PostgreSQL upgrades, an ESRI ArcGIS server, new registration policies, and a non-public API.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Deployment of ADTimePix3 areaDetector Driver at Neutron and X-ray User Facilities

TimePix3 is a 65k hybrid pixel readout chip with simultaneous Time-of-Arrival (ToA) and Time-over-Threshold (ToT) recording in each pixel*. The chip operates without a trigger signal with a sparse readout where only pixels containing events are read out. The flexible architecture allows 40 MHits/s/cm² readout throughput, using simultaneous readout and acquisition by sharing readout logic with transport logic of superpixel matrix formed using 2x4 structure. The chip ToA records 1.5625 ns time resolution. The X-ray and charged particle events are counted directly. However, indirect neutron counts use 6Li fission in a scintillator matrix, such as ZnS(Ag). The fission space-charge region is limited to 5-9 um. A photon from scintillator material excites a photocathode electron, which is further multiplied in dual-stack MCP. The neutron count event is a cluster of electron events at the chip. We report on the EPICS areaDetector** ADTimePix3 driver that controls Serval*** using json commands. The driver directs data to storage and to a real-time processing pipeline and configures the chip. The time-stamped data are stored in raw .tpx3 file format and passed through a socket where the clustering software identifies individual neutron events. The conventional 2D images are available as images for each exposure frame, and a preview is useful for sample alignment. The areaDetector driver allows integration of time-enhanced capabilities of this detector into SNS beamlines controls and unprecedented time resolution.

Gofron, Kaz↗
DOE OSTI2020

A guide for deploying Deep Learning in LHC searches: How to achieve optimality and account for uncertainty

Deep learning tools can incorporate all of the available information into a search for new particles, thus making the best use of the available data. This paper reviews how to optimally integrate information with deep learning and explicitly describes the corresponding sources of uncertainty. Simple illustrative examples show how these concepts can be applied in practice.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Oneida Indian Nation Community-Scale Clean Energy Deployment Combined Heat and Power Project. Tribal Renewable Energy (Final Technical Report)

This document reports on the Oneida Indian Nation's to upgrade and improve the operation of the Nation’s Central Utility Plant (CUP) so that previously wasted energy could be captured and utilized to produce electricity. The final technical report contains an overview of the project and the project objectives, which are increased energy efficiency, reduced dependency on fossil fuels, and lower energy costs while maintaining sound environmental stewardship of natural resources. The report describes the specific activities and milestones accomplished, a summary of the current status of the project, including objectives and results achieved, and a description of project management, challenges and lessons learned.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

NRC Multiphysics Analysis Capability Deployment FY2020: Part 3

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: Task2c: Explicit modeling of pebble transient temperature response. In this simulation, the 400 MWth Pebble-Bed Modular Reactor (PBMR) design, PBMR- 400, experiences a 20-second power ramp from 100% to 150% power. This is followed by a similar reduction in the power back to 100%. Several multiscale pebble coupling approaches are tested with one pebble per mesh element in the active core region. The results show good conservation behavior and the stability of the coupling.; Extended scope part 1: An assessment of the computational efficiency of the Discontinuous Finite Element Method (DFEM) heat transfer solver shows good scalability. The DFEM solver is a factor of 4 more expensive in solution time than the Finite Element Method (FEM) solver for heat transfer problems due to the increased number of degrees of freedom. Nonetheless, the DFEM approach provides the user with the flexibility to model gap heat transfer problems.; Extended scope part 2: The GapHeatTransferInterfaceMaterial was improved to give the user increased flexibility with the modeling of heat transfer through gaps with the DFEM solver. A number of gap parameters can now be coupled both through functions and variables.; Extended scope part 3: Demonstration of how the gap width between hexagonal fuel cells can be calculated during a heat-up transient and used in the GapHeatTransferInterface model. A full-domain DFEM model with gap expansion is coupled to a SubApp that models the thermal expansion of the base plate. The results show the expected physical behavior, although have not been fully bench-marked at this point in time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Deploying Machine Learning Workflows into HPC environment

Outline: Workflows Overview; Common Workflow Language (CWL), Example of a CWL; BEE Overview; Machine Learning Components; Machine Learning Scientific Workflow using CWL → A new test case for BEE; Discussion: Benefits and Caveats of current ML workflow; Conclusion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Automated Mobility District Implementation Catalog: Insights from Ten Early-Stage Deployments

Major disruptive technologies are set to redefine the way in which people view travel, particularly in dense urban areas. Already, ride-hailing services have redefined mobility expectations of a new generation of urban dwellers in some places around the country. Over the next few decades, the proliferation of autonomous vehicles, which are generally referred to in the industry as “automated vehicles (AVs),” will be enhanced by the next generation of shared mobility. This combination of AV operations with on-demand service will provide convenience of mobility similar to that being exhibited in today’s transportation networking companies (TNCs). Shared, automated, public mobility resulting from the cross-hybridization of AVs with on-demand mobility service will bring economic and system efficiencies. Economic efficiencies may be realized by less vehicle ownership and more vehicle “usership.” Many companies are already exploring avenues for shared automated mobility through fleet operations as the wave of the future.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Biopower: Impact of Biofuels Deployment to Replace Petroleum Liquids in Stationary Power Applications

Petroleum-based liquids are used in a portion of power generation applications in the United States, predominantly in the New England, Middle Atlantic, South Atlantic, and Pacific-Noncontiguous regions. Power plants that burn petroleum liquids, such as distillate or residual fuel oils, are generally used for short periods to accommodate peak electricity demands. The Energy Information Administration (EIA) estimated the U.S. consumption of petroleum liquids for electricity generation at 27 million barrels in 2018, representing a cost of $2.4 billion annually. This study assesses the potential to displace all or part of the petroleum liquids in U.S. power generation with biofuels. The biofuels for this application are assumed to be derived from terrestrial feedstocks, with conversion routes of both fast pyrolysis (bio-oil) and hydrothermal liquefaction (bio-crude). Regional models were used to assess the availability and cost of three different base materials: clean wood, forest residues, and corn stover; each was evaluated in the laboratory at small or experimental scales for conversion to bio-oil or bio-crude. The estimated biofuel production quantities depend on equivalent heating versus the current heavy fuel. In this report, the availability of each type of biomass for each section of the U.S. Census division is estimated using a conservative broker price (in each case) of $ 80 per dry tonne. The results show that the petroleum-liquid power generation in each of the Census Divisions could be supplied by one or more of the feedstocks evaluated. For all regions, clean wood supplies (only) could provide ample supply. For all but two regions (Middle Atlantic and New England), forest residues alone are sufficient. Finally, for all regions but three (Middle Atlantic, New England, and South Atlantic), corn stover alone is adequate. The Minimum Fuel Selling Price (MFSP) of bio-oil and bio-crude were also estimated for each feedstock type and Census Division. This analysis showed that fast pyrolysis bio-oil projections to be lower (14% on average) than current wholesale petroleum-based heating oil prices in each of the regions, assuming 100 dry tonnes/day processing capacity. However, bio-crude predictions were significantly higher (2X) in all cases. The effect of biorefinery size was also quantified. Based on the preliminary results in this study, it is apparent the biofuels could be an economical alternative for current petroleum liquids in U.S. power generation. However, additional research is needed to determine the necessary biofuel characteristics to support existing generation equipment. It is recommended that both power generation and biofuel production stakeholders to be engaged to outline the research and testing needed to identify the technical hurdles to enable the opportunity.

02 PETROLEUM↗
DOE OSTI2020

NRC Multiphysics Analysis Capability Deployment FY2020 - Part 4

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: • Task 3a: This task demonstrates the effectiveness of Griffin’s methods for interpolating cross sections and SPH correction factors as a function of control drum rotation. The Monte Carlo code Serpent is used to generate reference results. The accuracy of Griffin-calculated eigenvalues and reaction rates are studied as a function of control drum rotation for cross section and SPH factor libraries of varying fidelity. Higher-fidelity libraries require less interpolation and are therefore inherently more accurate; however, they require more computational resources to create. Overall, Griffin is able to accurately model eigenvalue and reaction rates over the full range of drum rotation using a library generated from three to five discrete drum rotations for a particular microreactor design. • Task 3c: This preliminary task successfully demonstrates the performance of a coupled neutron-photon transport calculation with Griffin using the spherical harmonics approximation. The Griffin solutions are compared to reference solutions from the continuous energy Monte Carlo codes MCNP and Serpent. Furthermore, this work also demonstrates how to prepare the neutron and photon libraries using NJOY, MCNP, and Serpent with the latest ENDF/B-VIII data for 235 U and graphite. The Griffin total energy deposition in the active core region is calculated within 0.3% of the reference, but it degrades in the reflector regions with a maximum difference of -1.5%. Overall, the results look promising and future analysis should use an improved data stream and focus on determining the potential cancellation of error within each energy group.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Scat Detection Dog Surveys for the San Joaquin Kit Fox on the Lawrence Livermore National Laboratory's Experimental Test Site (Site 300) and the Corral Hollow Ecological Reserve: 2020 Deployment

The San Joaquin kit fox (Vulpes macrotis mutica) historically occupied an extensive range in the San Joaquin Valley, California; however, their populations and habitat have since been significantly reduced by human impacts (United States Fish and Wildlife Service [USFWS] 1998). More than 95% of the potential habitat for kit foxes on the San Joaquin Valley floor has been converted to irrigated agriculture, urbanized, or industrialized lands. The San Joaquin kit fox was listed as endangered by the USFWS in 1967 and as threatened by the State of California in 1971. Records from local surveys, research projects, and incidental sightings indicate the present distribution of kit foxes extends from 1) southern Kern County north to Contra Costa, Alameda, and San Joaquin counties on the west side of the valley and to Stanislaus County on the east side; 2) into some of the larger, uncultivated valley-floor land parcels in Kern, Tulare, Kings, Fresno, Madera, and Merced counties; and 3) westward within 5 counties in the interior coastal range (USFWS 1998). Kit foxes have been denoted to occur in 3 geographically distinct core and several satellite populations in a heavily fragmented landscape, with the largest extant populations concentrated in the southern part of the range and smaller populations and isolated sightings in the central and northern portions (USFWS 1998, 2010).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Deployment of Energy Efficiency and Clean Energy on Indians Lands – A Community Solar Project

The Eastern Band of Cherokee Indians (EBCI or Tribe) is a federally recognized Indian Tribe located on ancestral homelands in western North Carolina. The Tribe is comprised of just over 16,000 enrolled members, with an estimated 8,000 – 10,000 residing on tribal lands. The Qualla Boundary is comprised of over 56,000 acres of contiguous trust land adjacent to the Great Smoky Mountain National Park. The EBCI also possess an assortment of scattered parcels of varying sizes across western North Carolina, some in trust status and others in deeded or fee simple. This project was implemented on a trust parcel in Cherokee County, NC. The Tribe was awarded the maximum amount of $\$ $1,000,000 for the installation of a 705.6 kilowatt (kW) solar PV array to supplement the power consumed and reduce annual utility costs at the Harrah’s Cherokee Valley River (HCVR) casino and hotel in Murphy, NC. The casino is a tribal entity of the Tribe. The total cost of the project was $\$ $2.364 million. The system was officially commissioned on April 12, 2019. For the purpose of calculating the amount of power produced and reduction in utility costs, the time frame assessed is May 2019 through April 2020. All power generated was consumed onsite.Based on the first full year of data, the project achieved the estimated 8.3% reduction in utility costs. A total of six casino and tribal staff were trained and received a North American Board of Certified Energy Practitioners (NABCEP) certification, giving our staff the resources and skills to manage and operate the solar PV array. Based on the Tribal match of $\$ $1,377,797 and estimated net annual benefit of $89,000, the estimated return on investment (ROI) is 15.48 years.

14 SOLAR ENERGY↗