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At least 379 records · Page 21

FleetREDI Insight: Beverage Delivery in New York City

Capturing real-world data is critical to improving efficiency and supporting technology advancements in commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores beverage delivery tractors operating in New York City. Last-mile beverage delivery supports local bars and restaurants throughout Manhattan and the broader New York City area. Manhattan Beer Distributors is a beverage delivery company operating in Manhattan and the Bronx. Logging devices were installed in 17 vehicles, and operational data were collected between August and October 2022. Two types of vehicles were included in data collection: 7 tractors and 10 bay trucks. Using NLR’s FleetREDI data platform, this dataset provides a summary of daily operation to help understand duty cycle characteristics. This includes daily distance, fuel use, and estimated engine-produced energy consumption for 17 bay trucks and tractors that operated more than 7,500 miles in slow-speed urban operation. ![FleetREDI beverage delivery](FleetREDI-beverage-delivery-nyc.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multipacting analysis of the SNS drift tube linac (DTL) RF vacuum window using Spark3d

An ongoing study at the Spallation Neutron Source (SNS) seeks to better understand and address potential multipacting issues associated with the Drift Tube Linac (DTL) RF vacuum windows. An analysis of several failed operational windows showed indications of excessive RF heating on the TiN-coated alumina ceramics. Coupled with vacuum bursts and arcing during conditioning and/or operational periods, these problems have been attributed to electron activity likely caused by multipacting. The status of the study, 3-D electromagnetic simulation results, mitigating techniques and a future experimental plan for studying multipacting in the SNS DTL vacuum windows are presented.

Toby, George↗

Data reduction for low energy nuclear physics experiments using data frames

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Codebase release 2.0 for sauce

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

Marshall, Caleb (ORCID:0000000211942920)↗

A comprehensive final summary of the MCNP calculations performed concerning the UW 137 Cs release event

This document combines and supersedes earlier reports (e.g. LA-UR-19-32358 and LA-UR-20- 22216) that discussed MCNP-calculated conversion factors (count rate per unit activity per unit area) for collimated 2”x2” NaI detectors (Ludlum model 44-10 and Thermo model SPA3) in contact with various surfaces of interest to the University of Washington 137 Cs release event. These surfaces include: Exterior surface of round and rectangular ducts, Exterior surface of outdoor brick work, Exterior surface of cast iron pipes, Exterior surface of an O 2 filter assembly For each surface, the calculated conversion factors allowed inferences on 137 Cs activity on interior surfaces based on exterior contact measurements of the 662 keV photopeak count rate. The MCNP calculations included the effect of attached collimators (i.e. either a Pb/Sb-based Ludlum or a W-based “Rees” model) on detector response. As a consequence, the conversion factors only apply to the appropriate collimated 2”x2” NaI detector operated in pulse height analysis (PHA) mode. Other assumptions affecting the calculations and valid application of the conversion factors will be outlined below.

54 ENVIRONMENTAL SCIENCES↗

Nevada National Security Site 2019 Waste Management Monitoring Report Area 3 and Area 5 Radioactive Waste Management Sites

Environmental monitoring data are collected at and around the Area 3 and Area 5 Radioactive Waste Management Sites (RWMSs) within the Nevada National Security Site (NNSS). This report summarizes the 2019 environmental data to provide an overall evaluation of RWMS performance and to support environmental compliance and performance assessment (PA) activities. Some of these data (e.g., radiation exposure, air, and groundwater) are presented in other reports (Mission Support and Test Services, LLC 2019, 2020a, 2020b). Direct radiation monitoring data indicate exposure levels at the Area 3 and Area 5 RWMSs are within the range of background levels measured at the NNSS. Slightly elevated exposure levels outside the Area 3 RWMS are attributed to nearby historical aboveground nuclear weapons tests. Air monitoring data at the Area 3 and Area 5 RWMSs show that tritium concentrations in water vapor and americium and plutonium concentrations in air particles are below Derived Concentration Standards for these radionuclides. Groundwater monitoring data indicate the groundwater in the uppermost aquifer beneath the Area 5 RWMS is not impacted by RWMS operations. Results of groundwater analysis from wells around the Area 5 RWMS are below established investigation levels. Leachate samples collected from the leachate collection systems at the Area 5 mixed low-level waste disposal unit are below established contaminant regulatory limits. During 2019, precipitation at the Area 3 RWMS was 77 percent above average, and precipitation at the Area 5 RWMS was 69 percent above average. Water balance measurements indicate that evapotranspiration from the vegetated weighing lysimeter at the Area 5 RWMS dries the soil and prevents downward percolation of precipitation more effectively than evaporation as measured from the bare-soil weighing lysimeter. Vadose zone monitoring in the Area 3 and Area 5 RWMS soil covers shows no evidence of precipitation percolating through the covers to the waste. Moisture from precipitation did not percolate below 120 centimeters (3.9 feet [ft]) in the vegetated final cover on the U-3ax/bl disposal unit at the Area 3 RWMS during 2019. There was no drainage through 2.4 meters (8 ft) of soil as indicated from the Area 3 drainage lysimeters that received only natural precipitation. At the Area 3 RWMS, which received three times the natural precipitation, 57 percent of the applied precipitation and irrigation drained from the bare-soil drainage lysimeter. All 2019 monitoring data indicate that the Area 3 and Area 5 RWMSs are performing within expectations of the model and parameter assumptions for the facilities’ PAs.

2019↗

Weapon Systems Risk-Assessment Tool Review

To anticipate, and potentially mitigate, future problems in aging weapon systems, four unique riskassessment techniques were analyzed, including root-cause analysis tools, six-sigma problemsolving approaches, and lean six-sigma tools. Identifying the most efficient process, or tool, is crucial for successful application to current and future weapon systems, subsystems, and components. The following processes were reviewed: Fault Tree Analysis, Failure Modes and Effects Analysis, Bow-Tie Analysis, and Hazard and Operability Study. A systematic assessment was performed to determine the most desirable method, and included investigating qualitative versus quantitative characteristics, scope, process durations, advantages, and limitations. Presented results will outline the study findings and further illustrate a capacity to identify future issues and/or concerns, and ultimately, reduce risk.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Annual Summary Report for the Remote-Handled Low-Level Waste Disposal Facility—FY2021

This Fiscal Year (FY) 2021 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 2021, 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. Sixteen total waste-canister shipments were received at the RHLLW Disposal Facility, and 16 total waste canisters were emplaced.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Annual Summary Report for the Remote-Handled Low-Level Waste Disposal Facility—FY 2022

This Fiscal Year (FY) 2022 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 2022, 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. Fifteen waste canister shipments were received at the RHLLW Disposal Facility, and 15 waste canisters were emplaced in disposal vaults.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DPE Techno-Economic Analyses

This National Energy Technology Laboratory (NETL) report presents the results of an extensive set of techno-economic analyses for several open-cycle coal fuel oxy-fired direct power extraction (DPE) concepts. These power cycles make use of a conducting plasma accelerated through a magnetic field to generate direct current directly without the need for moving parts. Similar to gas turbines, the efficiency of the power cycle increases with increasing working fluid temperature and typically, plasma temperatures are much higher than the inlet temperature of even the most advanced gas turbine available today, affording the opportunity for very high cycle efficiencies. Most of the study uses high-fidelity models to assess a coal-fueled oxy-combustion DPE system with an AUSC steam bottoming cycle. Two baseline configurations were explored, one with relatively conservative operating point parameters and another with relatively aggressive operating point parameters. Additional analysis on the high-fidelity models as well as reduced order models were performed to analyze the cost and performance potential more thoroughly for the baseline systems and to compare their performance to two alternate open-cycle DPE systems.

30 DIRECT ENERGY CONVERSION↗

Operation of the Fast Neutron Coincidence Collar (FNCL) with a DD-Neutron Generator

For more than 30 years, the quantitative assay of the 235 U content of light water reactor fresh fuel assemblies relied on measuring coincidence neutrons from fissions induced by an Am(Li) neutron source using 3 He based detectors. The Fast Neutron Collar (FNCL) developed by the International Atomic Energy Agency (IAEA), replaces traditional 3 He proportional counters with an array of liquid scintillator detectors arranged about the fuel assembly to provide improved measurement precision and reduced sensitivity to gadolinium poison rods. The FNCL relies on Am(Li) neutron sources that are no longer commercially available. This work examines the replacement of Am(Li) sources with a commercial off the-shelf deuterium–deuterium (DD) neutron generator. In addition to mitigating supply concerns, the neutron generator offers advantages in measurement precision and potential automation of sequential passive/active neutron measurements. This report presents the initial performance results for both the integrated DD/FNCL and Am(Li)/FNCL assays of compact depleted uranium, low-enriched uranium, and highly enriched uranium standards along with an estimate of the expected performance for fresh fuel assemblies. A discussion of the design and operation of the “FNCL Analysis and Simulation Software” is also provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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↗

Advanced Data Science Model for Detecting Intelligent Malware

This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.

42 ENGINEERING↗

Causal CCF Parameter Estimations 2020

This report documents the quantitative results of the causal common-cause failure (CCF) parameter estimations for the failure cause groups “component,” “design,” “environment,” “human,” and “other,” based on CCF data through 2020 in the U.S. Nuclear Regulatory Commission (NRC) CCF database: https://rads.inl.gov/Pages/CCF.aspx. This report utilizes the same data period (2006–2020) and CCF templates as INL/EXT-21-62940, Revision 1, CCF Parameter Estimations, 2020 Update. The 2015 causal CCF prior distributions for the specific failure cause groups (instead of the 2015 generic CCF prior distributions) were used in this report to estimate the associated causal CCF parameters. All the 2015 causal CCF prior distributions and generic CCF prior distributions were developed in INL/EXT-21-43723, Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors, using CCF data from 1997 to 2015. These quantitative results were developed to support the causal alpha factor model and should be used as appropriate in probabilistic risk assessment (PRA) studies such as the NRC Significance Determination Process for commercial nuclear power plants in the United States.

99 GENERAL AND MISCELLANEOUS↗

Driving Economics and Reducing Risks: The Business Case for Security-by-Design in Nuclear Power

This report provides an analysis of the financial, operational, and strategic advantages of incorporating Security-by-Design (SeBD) early in the lifecycle of nuclear power plant projects. By framing security as a foundational design element rather than a late-stage add-on, owners, vendors, and operators can reduce budget overruns, strengthen regulatory compliance, and increase revenue opportunities. The report details key lifecycle phases, highlighting the strategic imperative for organizations (including project developers, investors, vendors, and regulators) to adopt SeBD. Drawing on industry estimates, real-world case studies, and comparative cost analyses, the findings underscore that even a modest upfront investment in SeBD can yield substantial long-term returns by preventing costly retrofit activities, minimizing regulatory delays, and positioning nuclear vendors for the ability to adapt in the evolving security market. By avoiding excessive retrofit expenses and positioning security as a built-in feature rather than an afterthought, nuclear projects can protect their financial performance, enhance public trust, and secure a competitive edge in an increasingly complex global energy market. The authors advocate for SeBD’s strategic implementation, supported by established quality management methodologies, thereby promoting continuous improvement and defect avoidance. Ultimately, early SeBD integration represents a strategic investment, yielding significant returns by preventing costly retrofits and positioning nuclear projects for enhanced competitiveness and public trust.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Annual Summary Report for the Remote-Handled Low-Level Waste Disposal Facility—FY 2024

This Fiscal Year (FY) 2024 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 (INL). Annual review of the adequacy of the PA and CA for the Remote-Handled Low-Level Waste (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 2024, 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. Nineteen waste canister shipments were received at the RHLLW Disposal Facility, and all nineteen waste canisters were emplaced in disposal vaults.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗