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At least 325 records · Page 18

Assessment of Condition Monitoring Methods and Technologies for Inservice Inspection and Testing of Nuclear Power Plant Components

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to explore the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components. The advanced technologies considered in this work are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), physics-based models, and digital twins (DT). The interest in the application of advanced technologies for condition monitoring in nuclear power plants continues to grow, and current and future licensees are expected to implement advanced technologies as part of their inservice inspection (ISI) and inservice testing (IST) programs. This report delineates the outcomes of an exploratory investigation into the implementation of advanced condition monitoring technologies to address ISI and IST requirements. A thorough review was conducted of the existing regulatory requirements for ISI and IST, along with an analysis of associated industry practices. Additionally, a state-of-the-art assessment was performed on advanced condition monitoring technologies frequently employed in non-nuclear sectors. This research incorporated two nuclear-specific case studies to illustrate the application of these technologies within the current nuclear fleet. The report provides an exhaustive discussion on the technical challenges, considerations, and opportunities associated with the deployment of advanced condition monitoring technologies. The following are key considerations in the application of advanced technologies for the ISI and IST of nuclear power plant components: • Developing adequate verification and validation procedures to confirm the functional and non-functional requirements, • Developing technical capabilities to conduct real-time asset condition monitoring, • Establishing guidance and protocol for modeling and simulation tools to continuously meet regulatory requirements, • Addressing trustworthiness, explainability, and interpretability of ML/AI methods, • Evaluating maintenance activities to maintain an adequate safety margin and avoid undesirable conditions, • Establishing cybersecure condition monitoring programs associated with a computer-based software system, and • Establishing standardized evaluation metrics for advanced condition monitoring programs. Interest in the use of advanced technologies for condition monitoring in ISI and IST programs continues to grow, and the technology is expected to experience rapid and wide industry adoption in the near future. Adoption of advanced technologies for condition monitoring could have novel and unique impacts on regulatory activities associated with ISI and IST programs. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of ISI and IST programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Integrated application of active controls (IAAC) technology to an advanced subsonic transport project. Conventional baseline configuration study

Characteristics of the U.S. domestic fleet were evaluated to determine the mission characteristics that would have the most impact on U. S. transport fuel use in the future. This resulted in selection of a 197-passenger (plus cargo), about 3710-km (2000 nmi) mission. The existing data base was reviewed and additional analysis was conducted as necessary to complete the technical descriptions. The resulting baseline configuration utilizes a double-lobe, but nearly circular, body with seven-abreast seating. External characteristics feature an 8.71 aspect ratio, 31.5-degree sweep wing, a T-tail empennage, and a dual CF6-6D2, wing-mounted engine arrangement. It provides for 22 LD-2 or 11 LD-3 containers plus bulk cargo in the lower lobe. Passenger/cargo loading, servicing provisions, taxi/takeoff speeds, and field length characteristics are all compatible with accepted airline operations and regulatory provisions. The baseline configuration construction uses conventional aluminum structure except for advanced aluminum alloys and a limited amount of graphite epoxy secondary structure. Modern systems are used, including advanced guidance, navigation, and controls which emphasize application of digital electronics and advanced displays.

Source record↗

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗

Evaluation of the national launch system as a booster for the HL-20

The capability of a proposed national launch system (NLS) to boost the personnel launch system (PLS) manned vehicle has been examined. A reference NLS configuration, the NLS-2 1.5 stage vehicle, and a reference HL-20 PLS configuration were used for the study. Performance has been analyzed for several PLS insertion orbits to support the Space Station Freedom resupply mission. The reliability of the NLS launch vehicle and its contribution to crew safety requirements have been determined. The launch-processing and launch facility requirements of these combined systems were also analyzed. Previous studies of these two systems have focused on either the PLS manned element or NLS launch vehicle. This paper combines the results of prior studies in an analysis of the integrated NLS/PLS configuration. This analysis has found the proposed NLS 1.5 stage launch vehicle to be an excellent booster for the PLS. Predicted performance margins for this launch-vehicle configuration are more than adequate, and acceptable reliability and safety levels are anticipated. Integration of this NLS/PLS configuration into NASA mixed-fleet launch architectures is feasible.

Duffy, James B.↗

Condition Assessment of Kevlar Composite Materials Using Raman Spectroscopy

This viewgraph presentation includes the following main concepts. Goal: To evaluate Raman spectroscopy as a potential NDE tool for the detection of stress rupture in Kevlar. Objective: Test a series of strand samples that have been aged under various conditions and evaluate differences and trends in the Raman response. Hypothesis: Reduction in strength associated with stress rupture may manifest from changes in the polymer at a molecular level. If so, than these changes may effect the vibrational characteristics of the material, and consequently the Raman spectra produced from the material. Problem Statement: Kevlar composite over-wrapped pressure vessels (COPVs) on the space shuttles are greater than 25 years old. Stress rupture phenomena is not well understood for COPVs. Other COPVs are planned for hydrogen-fueled vehicles using Carbon composite material. Raman spectroscopy is being explored as an non-destructive evaluation (NDE) technique to predict the onset of stress rupture in Kevlar composite materials. Test aged Kevlar strands to discover trends in the Raman response. Strength reduction in Kevlar polymer will manifest itself on the Raman spectra. Conclusions: Raman spectroscopy has shown relative changes in the intensity and FWHM of the ~1613 cm(exp -1) peak. Reduction in relative intensity for creep, fleet leader, and SIM specimens compared to the virgin strands. Increase in FWHM has been observed for the creep and fleet leader specimens compared to the virgin strands. Changes in the Raman spectra may result from redistributing loads within the material due to the disruption of hydrogen bonding between crystallites or defects in the crystallites from aging the Kevlar strands. Peak shifting has not been observed to date. Analysis is ongoing. Stress measurements may provide a tool in the short term.

Washer, Glenn↗

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

Fleet manager↗

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗

MOSAIC: An Effective FFT-based Numerical Method to Assess Aging Properties of Concrete

As the nuclear fleet in the United States ages and subsequent license renewal applications grow, the prediction of concrete durability at extended operation becomes more important. To address this issue, a Fast-Fourier Transform (FFT) method is utilized to simulate aging-related degradation of concrete within the Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) software. MOSAIC utilizes compositional phase maps to simulate damage from radiation-induced volumetric expansion (RIVE), applied force, creep, and thermal expansion. This compositional detail allows each mineral in the microstructure to be assigned specific material properties, allowing the simulation to be as accurate and representative as possible. The principal goal of MOSAIC is to simulate the effects of nonlinear aging mechanisms occurring in nuclear concrete on the macroscopic mechanical properties, using only the aggregate microstructure compositional information as a starting point. Here, several realistic example simulations are shown to demonstrate the utility and uniqueness of the MOSAIC software.

36 MATERIALS SCIENCE↗

High-Fidelity Simulations of a Tiltwing Vehicle for Urban Air Mobility

NASA is playing an important role in the development of the urban air mobility ecosystem by identifying key research areas and establishing a fleet of conceptual reference vehicles for urban air mobility applications. This paper delves deeper into the study of NASA’s six-passenger tiltwing air taxi aerodynamics using high-fidelity computational fluid dynamics simulations. NASA’s OVERFLOW flow solver has been loosely-coupled with the rotorcraft comprehensive analysis code CAMRAD II. Dual-time stepping, high-order accurate schemes, and the delayed detached-eddy simulation are employed. The tiltwing configuration is analyzed in airplane and helicopter mode, with flight conditions representative of an air taxi mission. Airloads, wake geometry, and performance are studied to identify the unique flow features of this configuration. NASA’s tiltwing vehicle is one of the conceptual designs intended to focus and guide NASA’s research activities in support of aircraft development for vertical take-off and landing air taxi operations.

RVLT↗

Phase 1: Duke Energy Zero Emission Resource Integration Study (ZERIS); Phase 2: Carbon-Free Resource Integration Study for Duke Energy (Final Report)

Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.

14 SOLAR ENERGY↗

Carbon/graphite fiber risk analysis and assessment study: An assessment of the risk to Douglas commercial transport aircraft

The potential hazard to electrical and electronic devices should there be a release of free carbon fibers due to an aircraft crash and fire was assessed. Exposure and equipment sensitivity data were compiled for a risk analysis. Results are presented in the following areas: DC-9/DC-10 electrical/electronic component characterization; DC-9 and DC-10 fiber transfer functions; potential for transport aircraft equipment exposure to carbon fibers; and equipment vulnerability assessment. Results reflect only a negligible increase in risk for the DC-9 and DC-10 fleets either now or projected to 1993.

Schjelderup, H. C.↗

Hydropower capacity factors trending down in the United States

Abstract The United States hydropower fleet has faced increasing environmental and regulatory pressures over the last half century, potentially constraining total generation. Here we show that annual capacity factor has declined at four fifths of United States hydropower plants since 1980, with two thirds of decreasing trends significant at p < 0.05. Results are based on an analysis of annual energy generation totals and nameplate capacities for 610 plants (>5 megawatt), representing 87% of total conventional hydropower capacity in the United States. On aggregate, changes in capacity factor imply a fleetwide, cumulative generation decrease of 23% since 1980 before factoring in capacity upgrades—akin to retiring a Hoover Dam once every two to three years. Changes in water availability explain energy decline in only 21% of plants, highlighting the importance of non-climatic drivers of generation, including deterioration of plant equipment as well as changes to dam operations in support of nonpower objectives.

13 HYDRO ENERGY↗

FleetREDI Insight: Intrastate Coach Bus Dataset

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 coach buses operating in Colorado. Coach buses are a primary mover for intrastate transit and are primarily used for longer trips with more comfortable seats and a restroom. All Aboard America! Holdings Inc. offers various fixed-service and charter routes across Colorado on its Bustang fleet out of its depot in Golden, Colorado. NLR installed logging devices and collected operational data on nine 40-foot Bustang motorcoaches operating on fixed routes from May through August 2022. 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 nine motorcoaches that operated more than 33,000 miles. These vehicles primarily operated on Interstate 25 and Interstate 70. ![FleetREDI interstate bus](FleetREDI-interstate-bus.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of all-electric secondary power for transport aircraft

This report covers a study by Douglas Aircraft Company (DAC) of electrical power systems for advanced transport aircraft based upon an all-electric design concept. The concept would eliminate distributed hydraulic and pneumatic secondary power systems, and feature an expanded secondary electrical power system redesigned to supply power to the loads customarily supplied by hydraulic or pneumatic power. The initial study was based on an advanced 20-kHz electrical power transmission and distribution system, using a system architecture supplied by NASA-Lewis Research Center for twin-engine aircraft with many advanced power conversion concepts. NASA-LeRC later requested DAC to refocus the study on 400-Hz secondary power distribution. Subsequent work was based on a three-engine MD-11 aircraft, selected by DAC as a baseline system design that would provide data for the comparative cost/benefit analysis. The study concluded that the 20-kHz concept produced many expected benefits, and that the all-electric trijet weight savings on hardware redesign would be 2,304 pounds plus a 2.1-percent fuel reduction and resized for a total weight reduction of 11,000 pounds. Cost reductions for a fleet of 800 aircraft in a 15-year production program were estimated at $76.71 million for RDT&E; $2.74 million per aircrat for production; $9.84 million for nonrecurring expenses; $120,000 per aircraft for product support; and $300,000 per aircraft per year for operating and maintenance costs, giving a present value of $1.914 billion saved or a future value of $10.496 billion saved.

Murray, W. E.↗

Human-Autonomy Teaming Research in Support of m:N Operations

Since 2019, the NASA and industry partners have been involved in research focused on a novel paradigm for operations of remotely piloted aircraft. This paradigm involves multiple people sharing a fleet of multiple vehicles between them. Referred to as m:N (pronounced “em-to-en”), this configuration describes a ratio where m is the number of operators and N is the number of vehicles. Through force and asset multiplication, the m:N concept seeks to enable a scalable and resilient operation of remotely crewed vehicles. The primary means of obtaining such a robust operation is through allowing a flexible crew of variable size to dynamically attend to the needs of assets in while performing real-time operator workload management. It is in that sense that assets are shared between operators: as needed (such as in events of elevated workload) an operator in an m:N context can “handoff” the responsibility for some amount of assets, nh < N, to be absorbed by the m – 1 crew members on staff. At some time later, these nh assets could be returned to their original owner or they may be further distributed to other crew if called for by the mission. During this panel, I will elaborate on the research activity undertaken by the Human-Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center over the previous three years. The studies conducted by the HAT Lab range from interviews with subject matter experts, a cognitive walkthrough, a task analysis, and two simulation experiments to-date. During experimentation, pilots made use of an advanced Ground Control Station developed by the HAT Lab and industry partners to simulate m:N operations in two large, metropolitan areas of Southern California: Los Angeles and San Diego. Further experimentation planned over the next few years. Results from our research to-date indicates that pilots of a moderately sized fleet of about a dozen remotely crewed aircraft adequately maintained safety performance and situation awareness of their aircraft, even when presented with unexpected situations of heightened workload.

multi-vehicle control↗

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗

A Hydropower facility as an Energy Water Signal Processor

In recent times, various efforts have been made to address the challenge of adequately representing hydropower systems in modeling frameworks, accounting for the lack of data to represent the multiple constraints in hydropower operation. This research is a pilot data-driven methodology for characterizing, classifying, and comparing the water-to-energy and energy-to-water signal transformations that hydropower facilities as signal processors accomplish. In this study, a Box Jenkins transfer function/noise model is used to identify the relationship between reservoir inflows and outflows. For examining the feasibility of this methodology, 5-minute fleet data for five storage and five run-of-river facilities was provided by the Tennessee Valley Authority (TVA) and transfer function models are developed. The influence of past inflow and outflow values on the current outflow decisions was investigated and summarized by examining the results of Box Jenkins methodology. Finally, dominance analysis was introduced to add value to the Box Jenkins model results and provide different stakeholders with a set of concepts to convey the functionality of hydropower.

13 HYDRO ENERGY↗

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗