Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “idaho”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

Federal Automotive Statisical Tool: FAST Changes & Data Call Preparation (INTERFUEL - September 2023) [Slides]

This presentation presents an overview of and timeline for coming changes to how federal agencies with motor vehicles will submit required information about the motor vehicles, fueling centers, and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation provides information on changes throughout the FAST system as well as changes planned for implementation in FY 2023 and later. This presentation is intended for delivery via WebEx/GoToMeeting at the September 13, 2023 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗

Federal Automotive Statistical Tool: FY 2022 Federal Fleet Trends and Data Quality [Slides]

This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2022 and discusses quality of the submitted data. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

33 ADVANCED PROPULSION SYSTEMS↗

FedFleet 2024: Fleet Data Quality - Understanding and Improving Your Agency's FAST Fleet Data Quality Metric? [Slides]

This presentation presents an overview of how the team supporting the Federal Automotive Statistical Tool (FAST) project for DOE and GSA view and assess the quality of fleet data submissions from federal agencies. It also discusses ways in which agencies can improve the quality of their fleet data and of their fleet data submissions. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗

Creation Synthetic Data to Train a Digital Twin to Predict Reactor Operations

Understanding techniques to strengthen the nuclear safeguards regime is crucial in preventing nuclear proliferation due to recent advancements in the nuclear energy industry such as Generation IV reactors and microreactors. Prior to the construction of a nuclear power plant, it is necessary to understand the proliferation potential of the plant's reactor. Digital twins serve as a unique solution to recognizing reactor behavior indicative of nuclear proliferation. A digital twin is defined as a virtual model that works in unison to represent a physical asset, with a transference of data between the virtual and physical assets [1]. This work serves as validation for training a digital twin on synthetic data fabricated via means of Serpent reactor physics and point kinetics equations simulations. In this case this work is based on parameters of Idaho State University's AGN-201 reactor. The synthetic data can then be utilized to train machine learning models in the future to further investigate the utility of these methods. The accuracy of the predicted data is measured against real operational data to verify the reliability of the synthetic data creation methods and decide whether these methods should be used in the future to inform inspectors of a reactor's proliferation potential.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Development of INL Ultrasonic Thermometer

This document summarizes the development at Idaho National Laboratory of an ultrasonic thermometer. The ultrasonic thermometer is a temperature sensor capable of multi-point measurements at very high temperatures with a high level of radiation tolerance. All of the components of the ultrasonic thermometer have been improved over the course of this work. The base technology, a magnetosrictive transducer, has been shown to be highly radiation tolerant. The solenoidal coil used in the transducer has been redesigned to operate at higher frequencies that previously possible. Materials used for the acoustic waveguide (the sensing portion of the device) have been tested and ideal candidates identified. Finally, a solution to the sticking issue (diffusion bonding between the waveguide and a protective sheath) has been developed and tested.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

FedFleet 2024: Federal Fleet Boot Camp - Federal Motor Vehicle Fleet Data Reporting [Slides]

This presentation is intended as a 15-minute overview of federal motor vehicle fleet data reporting using the Federal Automotive Statistical Tool, presented as part of a half-day pre-conference workshop led by GSA's Office of Government-wide Policy for federal fleet managers at FedFleet 2024. This presentation covers what FAST is, what types of information agencies report through FAST, and where fleet managers can turn for assistance with fleet data reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗

Utilizing Physics-Informed Synthetic Data to Train a Digital Twin for Predicting Reactor Operations

Understanding techniques to strengthen the nuclear nonproliferation regime is crucial in reducing the creation of nuclear weaponry on the basis of advancements in the nuclear energy industry. Prior to construction of a nuclear power plant, it is necessary to understand the proliferation potential of the plant’s reactor. Digital twins serve as a unique solution to recognizing reactor behavior indicative of nuclear proliferation. The following research conducted serves as a validation to training a digital twin on synthetic data fabricated via means of reactor physics simulations based on parameters of Idaho State University’s AGN-201 reactor. The synthetic data is utilized to train a long short-term memory (LSTM) recurrent neural network model. The accuracy of the predicted data is measured against real operational data to verify the reliability of the synthetic data creation methods and if these methods should be used in the future to inform inspectors of a reactor’s proliferation capabilities.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Status Report on Thermal Extraction Modeling within HYBRID

Idaho National Laboratory continues to be at the forefront of advanced reactor systems and integrated energy systems (IES) research. The HYBRID modeling repository is the computational modeling repository used to evaluate potential IES configurations. To support IES analysis, it is necessary to develop models that can evaluate a range of thermal integration points within given energy conversion systems. This work includes as many technologies as possible anticipating that many technologies will be deployed to broadly reduce climate impacts of energy intensive processes. To provide this analysis, a new balance of plant model has been generated. This report will discuss progress on this new main model and discuss nominal conditions for the primary reactor types contained within HYBRID.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

INTERFUEL: FY22 Federal Fleet Reporting [Slides]

This presentation presents an overview of and timeline for coming changes to how federal agencies with motor vehicles will submit required information about the motor vehicles, fueling centers, and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation provides information on changes throughout the FAST system as well as changes planned for implementation in FY 2023 and later. This presentation is intended for delivery via WebEx/GoToMeeting at the September 14, 2022 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

99 GENERAL AND MISCELLANEOUS↗

Annual Summary Report for the Remote-Handled Low-Level Waste Disposal Facility—FY 2023

This Fiscal Year (FY) 2023 annual summary report (ASR) documents the continued adequacy of the performance assessment (PA), the composite analysis (CA) and associated operating disposal-authorization statement (ODAS) technical-basis documents for the Remote-Handled (RH) Low-Level Waste (LLW) Disposal Facility at Idaho National Laboratory. Annual review of the adequacy of the PA and CA for the RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of Department of Energy (DOE) Order 435.1, “Radioactive Waste Management.” In FY 2023, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility-closure design, or institutional controls. Eleven waste canister shipments were received at the RHLLW Disposal Facility, and ten waste canisters were emplaced in disposal vaults.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NRC Multiphysics Analysis Capability Deployment FY21: Part 3

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” The deliverables completed for this report are: Deliverable 1c: the capability to model gas mixtures was added to Pronghorn. A test problem mimicking the conditions achieved in a depressurized loss of forced cooling (DLOFC) event was solved with both RELAP-5 and Pronghorn. Pronghorn employed a finite vol ume method with the Kurganov-Tadmor discretization. The comparison between the mass fraction spatial profiles computed with RELAP-5 and Pronghorn clearly shows the presence of numerical artifacts (i.e., overly diffusive behavior at low Mach numbers). We confirmed that the problem disappears at higher Mach numbers. We recommend future work on the implementation of a low Mach finite volume formulation to better treat low Mach number problems. Deliverable 2a: we demonstrated two approaches to model the radiation/conduction/natural convection heat transfer across a stagnant gas for the PBMR-400 design using Pronghorn. The first approach is based on the net radiation method, which relies on the computation of view factors with the Multiphysics Object-Oriented Simulation Environment (MOOSE) ray tracing capability. The second method is a traditional thermal resistance approach. The test problems include both 2D and 3D geometries. In all cases, the results show very good agreement during a DLOFC transient. This confirms that the faster thermal resistance method produces solutions that are equivalent to the net radiation method for this geometry. Deliverable 3d: we demonstrated the use of the advection kernel for the delayed neutron precursor equation in Griffin with a 2D MSFR model. The results appear physical but further verification is recommended. We also recommend the addition of conjugate heat transfer to compute the temperatures and model the thermomechanic behavior of the reflectors and other structures. Significant memory and performance issues were encountered in the 3D axisymmetric model. Future work is recommended in this area. Task 8g: this task allows multidimensional MOOSE applications to be coupled to system codes (RELAP-7 and SAM). We implemented a faster multiphysics iteration coupling algorithm, which provides an overall 6× acceleration of the 3D-1D coupling of the core multidi- mensional fluid flow solver and the 1D primary and secondary loop model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Generalized Nuclear Code of Accounts for Cost Estimation Standardization

This is a joint INL-EPRI study. Link to corresponding page at the Electric Power Research Institute (EPRI): https://www.epri.com/research/products/000000003002028937 Recent Advanced Reactor (AR) designs typically offer features and attributes that depart from traditional water-cooled reactors in terms of fuel forms, coolants, structural materials, size, safety margins, and other important design and operational aspects. These departures, relative to the industry experience, will likely present a challenge for potential owner-operators when evaluating one or more AR designs for commercial deployment on a like-for-like basis. This is further exacerbated with new classes of reactors gaining prominence (e.g., microreactors) and new emerging applications (e.g., floating barge reactors or space propulsion reactors). The differences in design-specific technologies are compounded by the differences in approach to cost estimation. The lack of consistency in build up toward cost estimates creates a challenge when comparing competing concepts and evaluating their associated cost drivers. The outcome of a 2019 Scoping Study conducted by the Electric Power Research Institute (EPRI) indicated the need for a cost modeling guide (CMG), which would be underpinned by a technology-neutral and inclusive Generalized Nuclear Code of Accounts (GN-COA). A code of accounts (COA) is a tool by which costs are identified in even more specific categories, providing clarity on what specific costs are included in an estimate. A parallel independent effort was meanwhile taking place at Idaho National Laboratory via funding by the Systems Analysis Integration (SA&I) campaign of the Office of Nuclear Energy under the U.S. Department of Energy (U.S. DOE-NE) to also update the COA structure to enable more flexibility and encompass a wider variety of reactor technologies. After being made aware of these synergistic efforts, the two parties decided to combine efforts and develop a joint new standard format for nuclear cost estimation that builds on previous structures. This document describes the development of this joint GN-COA and provides guidance on the implementation of the tool, which is provided as the associated GN-COA Excel document. The main attributes of this novel COA format are that all items are functionally defined (in order to be technology and application agnostic) and grouped into logical arrangements that facilitate the tabulation of costs for reactor constructions under consideration. The intent is for the GN-COA to form a standard that is endorsed by future vendors and customers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

EVSE Characterization, A Next-Gen Profiles Project Report

As part of the U.S. DOE EVs@Scale consortium Next-Generation Profiles project, results and analysis from the characterization of high-power conductive and wireless charging infrastructure are presented. This characterization was conducted over a wide range of DC output current and DC voltage charging for nominal test conditions and off-nominal test conditions. Test plans and procedures were developed to define the test configurations and requirements, measurement parameters, and test procedures used throughout testing. Results from a 2023 study conducted on electric vehicle supply equipment (EVSE) characterization by Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) include one 350 kW capable EVSE using a liquid-cooled combined charging system-1 (CCS-1, North American version) cable and connector and an ORNL-developed 100-kW polyphase wireless charger. Characterization results during nominal operation show the AC-to-DC power transfer efficiency for the 350kW conductive EVSE is 95.1% peak and is >92% when the AC power is at least 50 kW. The power quality of the 350 kW conductive EVSE is also measured during nominal conditions. The power factor is >0.91 for power transfer above 50 kW AC input during nominal conditions with a maximum power factor of 0.975. The AC current harmonics produced by the EVSE as measured at the AC input connection to the EVSE is <25% harmonics for power transfer greater than 50 kW and <10% harmonics for power transfer greater than 180 kW.

25 ENERGY STORAGE↗

Characterization Report for the MP-1 Experiment Fabrication Campaign (Rev.1)

This report covers the results of MP 1 fuel characterization analysis to provide a detailed understanding of the as-fabricated fuel that would be irradiated in the MP 1 (Mini-Plate 1) experiment. The work was performed at Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), and Los Alamos National Laboratory (LANL). Characterization of the as-fabricated fuel was performed in accordance with Characterization Plan for the Fabrication of U 10Mo for the MP 1 Experiment, hereinafter the MP 1 Characterization Plan (MAQP 2016). Under the MP 1 Characterization Plan, fuel foils at different points in the foil fabrication process (e.g., hot rolled annealed, cold rolled annealed) were studied to understand the effect of various thermomechanical processes on the fuel microstructure. Samples were sent to each of the three organizations so that testing and analysis could be performed independently using similar equipment and a standardized set of measurement and analysis procedures. The MP 1 experiment will provide an opportunity to understand the effects of processing conditions on the final fuel microstructure, to compare independently obtained results, and achieve a three-way validation. PNNL characterized 28 uranium–10 wt% molybdenum (U 10Mo) samples. Six pieces/specimens from each sample/foil were sectioned, in accordance with the MP 1 Characterization Plan. Similarly, INL and LANL also examined 24 and 17 U 10Mo specimens, respectively. These total 69 samples consist of six types of MP 1 characterization foils fabricated by Babcock and Wilcox Technologies (BWXT) from ingots produced by the Y-12 National Security Complex: (a.) 0.047 in.-thick hot-rolled and annealed samples with and without Zr layers; (b.) 0.02 in.-thick cold-rolled and annealed samples with and without Zr layers; and (c.) 0.01 in.-thick cold-rolled and annealed samples with and without Zr layers. Microstructure, chemical composition, carbide morphology, U 10Mo foil thickness, Zr thickness, mechanical properties (microhardness), and density were evaluated in both longitudinal and transverse directions for foils of the three different thicknesses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

PNNL's Characterization Summary for MP-2 Experiment

Characterization of as-fabricated fuel was performed at Pacific Northwest National Laboratory (PNNL) in accordance with the characterization plan for the fabrication of U 10Mo plate fuel for the U.S. High Performance Research Reactor conversion program’s Fuel Fabrication Pillar (INL 2021). Similar characterization work is also being performed at Idaho National Laboratory to provide a detailed understanding of the as-fabricated foils that would be irradiated in the Mini-Plate 2 (MP 2) experiment. Under the MP 2 characterization plan, foils are studied that have different fabrication parameters (such as rolling condition, rolling thickness reduction, co-rolling with Zr layers). Similar samples from master foils were sent to both the organizations, so that the testing and analysis can be done independently using similar equipment and standardized measurement and analysis procedures. A final, consolidated report will be prepared based on this work and will summarize all the information obtained from the two laboratories. The MP 2 experiment will provide an opportunity to understand the effects of processing conditions on the final fuel microstructure, to compare results obtained independently, and achieve a two-way validation. In Fiscal Year 2022, PNNL received five MP 2 cast (PD STD2) samples to examine the foils’ chemistry and microstructure. For each cast sample, PNNL received samples from three different locations. PNNL also received and characterized 24 U 10Mo foil samples, by sectioning four pieces/specimens from each foil, in accordance with the MP 2 Characterization Plan (INL 2021). These 24 samples consist of four types of foils from BWX Technologies: 0.047 in. thick hot-rolled and annealed samples with Zr layers; 0.025 in. thick cold-rolled and annealed samples with Zr layers; 0.0105 in. thick cold-rolled and annealed samples with Zr layers. Along with these, PNNL also received four plates with Zr layers that were 0.025 in. and 0.0105 in. thick. This report describes the results of PNNL’s MP 2 foil characterization. Microstructure, Mo homogeneity, carbide fraction and morphology, U 10Mo foil thickness, and Zr thickness were evaluated in both the longitudinal and transverse directions for all the foils of the three different thicknesses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Motivation and Design of the OCPP Security Service

Pacific Northwest National Laboratory is conducting in-depth research aimed at exploring how zero trust security principles can be effectively applied to electric vehicle charging infrastructure. This investigation seeks to enhance the resilience and reliability of these systems against cyber threats, ensuring secure and uninterrupted access to charging services for electric vehicle users and electric supply. Zero trust is a security concept centered on the belief that system operators should not automatically trust users or systems based on their location, whether inside or outside the organization, but instead must verify everything trying to connect to their systems before granting access. A key aspect of the project is to demonstrate and validate zero trust approaches targeted to electric vehicle (EV) charging infrastructure. It has been observed that both open-source and commercial solutions often overlook the specific protocols employed in managing EV charging stations and proceeded with a general, protocol-agnostic approach. While these strategies effectively block non-authorized routes to the charging infrastructure, they do not tackle the situations where attackers may exploit legitimate access channels, such as the inattentive operator model posited by the Idaho National Laboratory. To address this gap, this paper proposes and discusses a new security service targeted to the Open Charge Point Protocol (OCPP), which is the de facto protocol for the management of charging stations and serves a critical role in the broader adoption of electric vehicles. The design and architecture of the proposed OCPP security service are discussed in detail, outlining how it aims to safeguard charging station management system (CSMS) functions. The service is particularly important in scenarios where the charging station operator (CSO), responsible for the maintenance and operation of charging stations, and the charging network provider (CNP), which manages the charging network's accessibility and billing, are separate entities. This distinction is crucial because CSOs and CNPs often have different priorities, objectives, and operational responsibilities, which may not always align perfectly. For instance, a CSO might prioritize uptime and customer satisfaction, while a CNP might focus on maximizing revenue and network utilization. Such misalignment can create security vulnerabilities, as each entity might implement different policies and standards, potentially leaving gaps in the overall security posture.

33 ADVANCED PROPULSION SYSTEMS↗

FY2024 Mid-Year Report: Verification of Spent Fuel Inside Dry Storage Casks by Cask Top Fast Neutron Mapping

This project is developing a prototype scanner array verification system for detection of missing fuel assemblies in spent-fuel storage casks. The prototype consists of six fast-neutron scintillator detectors mounted to a linear actuator frame that is placed on the top of a spent fuel cask to scan across all fuel assembly positions. The scanner array was assembled and tested at LLNL in prior years. A field test schedule has been requested at the Idaho National Laboratory (INL) Cask Farm site for FY2024. Following the Field Test, we will present results and discuss the technology with the IAEA. The IAEA may have special requirements for portability, shipping, lifting, and installation. We will incorporate additional improvements to the system based on lessons learned from the Field Test and feedback from the IAEA. If successful, the technology can be transferred to the IAEA or other stakeholders for assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗