Results for “commercial fleet” — Page 4

DOE OSTI2026

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for 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 propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for 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 propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for 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 propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for 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 propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for 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 propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Detailed Simulation Datasets Quantifying U.S. DOE VTO/HFTO R&D Benefits Across Light- to Heavy-Duty Vehicles

For more than 20 years, Argonne National Laboratory’s Vehicle & Mobility Systems Department has assessed how R&D investments by the U.S. Department of Energy’s Transportation Technologies Office and Alternative Fuels and Feedstocks Office affect vehicle energy use and cost. The analyses are performed using Autonomie, Argonne’s full-vehicle simulation tool for energy consumption, performance, and cost. The study covers five time frames ranging from present day through 2050, with more than 30 vehicle classes and applications (10 light duty and >20 medium and heavy duty), as well as six powertrain configurations (conventional, start-stop, hybrid electric vehicle, plug-in hybrid electric vehicle, battery-electric vehicle, and fuel cell electric vehicle) and five fuels (gasoline, diesel, natural gas, hydrogen, and electricity). Low and high technology uncertainty scenarios have been considered to capture a realistic range of outcomes. The resulting datasets include the assumptions used (i.e., efficiency, $/kWh), vehicle-level data (power, energy, weight, and cost), and outputs such as energy consumption, manufacturer’s suggested retail price, and total cost of ownership. These data are critical to stakeholders working in transportation, technology assessment, and long-term R&D planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Autonomie Simulation Datasets in Support of U.S. DOT-NHTSA Advanced Vehicle Technology Research

Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Downloadable Dynamometer Database (D3): Public Test Data on Advanced-Technology Vehicles

Access to high-quality, independent vehicle test data is critical to advancing energy-efficient transportation research. The Downloadable Dynamometer Database (D3) is a public repository of dynamometer test data on advanced-technology vehicles, generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory and hosted by the Transportation and Power Systems Division. The database has been made available to support researchers, students, and professionals engaged in energy-efficient vehicle research, development, and education. A wide range of vehicle categories has been tested (i.e., alternative fuel vehicles, conventional gasoline and diesel vehicles, all-electric vehicles, hybrid electric vehicles, and plug-in hybrid electric vehicles), as well as various drive cycles and test conditions documented in the accompanying D3 user presentation. Stakeholders can select a vehicle type, identify a vehicle of interest, and download the associated test data for use in their own analyses. Data downloaded from D3 must be accompanied by the required attribution: "This data is from the Downloadable Dynamometer Database and was generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory." These data are critical to vehicle modeling, validation, technology assessment, and educational use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data

Standard of practice approaches to time series cluster analysis involve careful feature engineering, often utilizing expert input to tune and select features by hand. In many cases, expert input may not be readily available, or there may not yet exist a community consensus on the ideal features for a given application. This paper compares the results of several cluster analysis methods, using both hand selected features and those extracted automatically, when applied to large geospatial time series telematics data from commercial trucking fleets. The impacts of feature selection, dimensionality reduction, and choice of clustering algorithm on the quality of clustering results are explored. Results from this analysis confirm prior results that domain agnostic features are competitive with the hand engineered features with respect to clustering quality metrics. These results also provide new insight into the most successful strategies for identifying structure in large unstructured vehicle telematics data, and suggest that time series clustering using automatic feature extraction can be an effective approach to extract structure from large scale geospatial time series data in cases when hand selected features are not available.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors (Final Project Report)

Advanced (i.e., non-light-water) reactor technologies offer developers new opportunities to enhance the reliability, efficiency, and safety of nuclear power reactors through changes in fundamental design and operation. A variety of advanced design concepts are being developed that generally trend toward increased reliance on innovative, inherent, and passive safety features. Many of these features are substantially different from components now found in large light water reactors (LWRs) that dominate the commercial operating fleet. Similarly, non-light water reactor (non-LWR) suppliers are also pursuing market niches quite different from the regional baseload power generation sites typically associated with large LWR facilities.

42 ENGINEERING↗

DOE OSTI2020

Workshop to Plan R&D Support of Fuel/Basket Modification for Direct Disposal of Future DPCs

By 2030 about half of all spent nuclear fuel (SNF) arising from the current fleet of commercial power plants will be in dual-purpose canisters (DPCs), which are designed for storage and transportation but not for disposal. As an alternative to complete repackaging of the fuel for disposal, considerable cost savings and lower worker dose could be realized by directly disposing of this SNF in DPCs. The principal technical consideration is criticality control in a geologic repository, because the DPCs are large and depend on neutron absorbing basket components for criticality control. Neutron absorbing materials are generally aluminum-based, and under disposal conditions can degrade after a few hundred years contact with ground water. Simple modifications to the SNF assemblies or the DPC baskets could help to achieve direct disposal, and this is one of the approaches being studied to address the possibility of disposal criticality (SNL 2020a). Five fuel/basket modification concepts have been proposed (SNL 2020b) and a virtual workshop was conducted to solicit review and feedback on these concepts. The proposed solutions are: 1) zone loading of DPCs to limit reactivity, 2) replacing absorber plates with advanced neutron absorbing (ANA) material, 3) adding disposal control rods to pressurized water reactor (PWR) assemblies, 4) rechanneling boiling water reactor (BWR) assemblies with ANA material, and 5) basket insert plates (chevron inserts) made from ANA material. The presentations from the workshop are provided in this report, and the workshop discussions are summarized. This information includes prioritization of the proposed fuel/basket modification solutions, and prioritization of the associated model development, validation testing, and quality assurance activities. Information documented in this report will help to steer research and development efforts at Sandia National Laboratories, Oak Ridge National Laboratory, and Idaho National Laboratory that support the U.S. Department of Energy, Office of Nuclear Energy, Spent Fuel and Waste Science and Technology program

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Advance Reactor Operational Technology Architecture Categorization

Seven generation III+ and generation IV nuclear reactor types, based on twelve reactor concepts surveyed, are examined using functional decomposition to extract relevant operational technology (OT) architecture information. This information is compared to existing nuclear power plants (NPPs) OT architectures to highlight novel and emergent cyber risks associated with next generation NPPs. These insights can help inform operational technology architecture requirements that will be unique to a given reactor type. Next generation NPPs have streamlined OT architectures relative to the current generation II commercial NPP fleet. Overall, without compensatory measures that provide sufficient and efficient cybersecurity controls, next generation NPPs will have increased cyber risk. Verification and validation of cyber-physical testbeds and cyber risk assessment methodologies may be an important next step to reduce cyber risk in the OT architecture design and testing phase. Coordination with safety requirements can result in OT architecture design being an iterative process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Nuclear Waste Attributes of SMRs Scheduled for Near-Term Deployment

The purpose of this study is to evaluate the nuclear waste attributes of Small Modular Reactors (SMRs) scheduled for deployment within this decade using available data and established nuclear waste metrics, with the results compared to a reference large Pressurized Water Reactor (PWR). The current fleet of commercial nuclear reactors in the U.S. is composed of 92 large Light Water Reactors (LWR) with an average electricity generating capacity of over 1,000 MWe each. These large LWRs built on-site in massive construction projects have been the mainstay of the industry for the last 50 years. However, new construction soon is expected to include several designs of smaller reactors primarily fabricated in factories and installed in the field in modules. Some of these SMRs will also be LWRs, while some will use other coolants such as liquid metals, molten salts or gases, and different types of fuels. The technologies and economics of SMRs have been the focus of many studies, but there has been only minimal information published on the amount of nuclear waste different types of SMRs are expected to generate and no reports focused on near-term-deployable designs. In this study, the nuclear waste attributes of three small reactors scheduled for near-term-deployment, VOYGR TM (from NuScale Power), Natrium TM ab (from TerraPower), and Xe-100 (from X-energy), were assessed by comparing nuclear waste metrics with those of a reference large Pressurized Water Reactor (PWR).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Multi-Fidelity Scheme for Accelerating 4D Finite Element Analysis for Mircoreactors

Next-generation microreactors are currently being designed to be operated terrestrial and extraterrestrial for remote surface power production. These systems will provide an alternative source of carbon-free energy that is versatile and can be utilized for various applications. These applications of microreactors have prompted the usage of high-fidelity unstructured finite element (FE) based approaches to provide time-dependent solutions for multiple physics fields. Computing these high-fidelity (4-D) solutions for multiple design iterations, physics fields, and transient events requires an immense computational cost. These high-fidelity solutions are computational expensive and the cost can be reduced through the implementation of less accurate low-fidelity solutions. Unlike the current fleet of commercial nuclear reactors, these next-gen systems present challenges due to the material and physical limitations required. Due to these constraints, the brute force technique of parameterizing important system characteristics determines whether a design meets the project objective. A system such as a nuclear reactor could have thousands of design parameters that affect system performance. In order to analyze the entire parameter space of such a complex system would require millions of CPU hours and countless design iterations. This costly approach is not practical due to regulatory and budget limitations. In this proposal, an approach that utilizes hybrid high-fidelity and low-fidelity FE models to reduce the computational cost of evaluating these applications in 4-D will be presented. The accuracy of the high-fidelity model and the computational efficiency of the low-fidelity model are taken advantage of to produce a solution that closely resembles the full order high-fidelity solution. By utilizing an unconverged coarse FE mesh, operation limits such as temperature, structural loading, etc., can be evaluated in an accelerated fashion and then can be spatially interpolated onto a finer mesh. The resulting error arising from the coarse mesh can be mitigated with a discrepancy function that actively quantifies and corrects the error in the coarse solution. This discrepancy function can be periodically updated with high-fidelity calculations across the temporal domain thus requiring less iterations on the fine mesh. As a result, the computational cost can be reduced for the evaluation and design iteration of microreactors. The proposal for this research contains three sections: Section 2 provides a literature review, Section 3 outlines the methodology for the proposed multi-fidelity scheme, and Section 4 displays preliminary results of the proposed research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Analysis of Water-Energy Issues for Nuclear Power with Industry Perspective

The water-energy nexus is a dynamic, ever evolving challenge involving technological changes, regulatory updates, economic constraints, environmental issues, and political attributes. This report expands on a previous report that gave an initial assessment of the water-energy nexus challenges facing the U.S. commercial industry. This follow-up report provides analysis and insights from stakeholder interviews focusing on the issues faced by the U.S. commercial nuclear energy industry within the water-energy nexus space. This report updates and expand the “Cooling Water Issues and Opportunities at U.S. Nuclear Power Plants” This report includes analysis on water withdrawal and consumption by operating nuclear reactors, evolving policy risks that could impact the operation of the existing commercial nuclear fleet, implications of water markets, trading and water rights, the changing energy grid, progressing environmental risks (including analysis on the possible impact of climate change on water availability and nuclear power plant performance), and opportunities to reduce water related risk. The feedback from the stakeholders’ interviews helps incorporate viewpoints from within the nuclear and related industry that can lack representation in other research areas, without constituting a comprehensive opinion survey. Stakeholders interviewed include nuclear power plants operators, water treatment providers, developers, and vendors of reactor technologies.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Development of a CRAB-MELCOR Framework for Utilization in Support of Estimating a Realistic Mechanistic Source Term for Microreactors

Research and development activities are being performed to link important advanced non-light-water microreactor technology research and development activities sponsored by the U.S. Department of Energy’s Office of Nuclear Energy with regulatory requirements and critical licensing needs likely to impact the deployment of a domestic commercial microreactor fleet. This report presents the progress of ongoing work to perform a gap analysis of the coupling of the Nuclear Regulatory Commission’s Comprehensive Reactor Analysis Bundle code suite and MELCOR code. This key Fiscal Year 2023 research reflects microreactor regulatory needs and challenges noted by industry, Department of Energy, and Nuclear Regulatory Commission stakeholders.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Investigate the Security of Electric Vehicle (EV) Ecosystem Applications

Apps that run on mobile devices are one of critical components of the electric vehicle (EV) ecosystem and pose possible threat actor points of entry that may impact the trust and security of EV charging systems in the future. Mobile apps often rely on communication between cloud servers and users, thereby creating potential points of entry for cyberattacks. Although app stores such as Apple App Store or Google Play Store generally test the security of apps, the cyber aspects may not be sufficient for many entities including DOD, federal fleets, and commercial entities. A more thorough inspection and the ability to influence developers is imminently needed. This research studies security attributes and vulnerabilities of a sample of mobile applications that support key user functions in the EV ecosystem. The study shows that all analyzed apps have security risks, categorized as either high or medium or both and a comprehensive cybersecurity guideline for developing mobile apps is necessary.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Regulatory Research Planning for Micro-Reactor Development

A limited-scope Regulatory Research Development Plan (RRDP) is being developed to link important advanced non light water nuclear microreactor technology research and development (R&D) activities sponsored by the U.S. Department of Energy’s Office of Nuclear Energy (DOE NE), Science, and Technology to regulatory requirements and critical licensing needs likely to impact the deployment of a domestic commercial microreactor fleet. This document is a precursor to that forthcoming limited scope microreactor RRDP. This report is being published to aid in the identification of key fiscal year (FY) 2022 topical research opportunities (as conveyed to the RRDP development team) by respondent microreactor developers and suppliers in consideration of micro-reactor regulatory needs and challenges noted by industry, DOE, and Nuclear Regulatory Commission (NRC) stakeholders. Although this document does not contain the regulatory effects analysis and R&D recommendations that is expected in the final RRDP, this document is being released now to assist DOE researchers and investigators in FY22 research planning activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗