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At least 487 records · Page 27

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Velocity Measurements in the Wake of the Swept Wing Flow Test (SWIFT) Model at the National Transonic Facility

Femtosecond laser electronic excitation tagging (FLEET) was applied to obtain flowfield velocity data for the Swept Wing Flow Test (SWiFT) at the NASA Langley Research Center National Transonic Facility (NTF). Despite numerous challenges associated with performing flow velocimetry measurements within a large-scale cryogenic wind tunnel facility, the experimental campaign was conducted under various conditions, including dry air at 320 K, cool nitrogen at 240 K, and Mach numbers of 0.2 and 0.8. FLEET velocimetry measurements were performed in the downstream wake of the SWiFT model, providing a quantitative dataset. This dataset includes one-dimensional velocity profiles and two-dimensional velocity maps acquired at different angles of attack and Reynolds numbers. The two-dimensional single component velocity maps indicate relatively uniform flow across the 120-mm wide wake flow survey suggesting that the main flow features can be represented by single-position linear velocity profiles. The measured instantaneous velocity profiles at variable angles of attack are compared to model lift coefficient information obtained at Mach 0.2. At high Reynolds numbers, a sudden velocity decrease was observed in the FLEET measurements at the same time as stall in lift coefficient was observed. At a low Reynolds number, both the velocity profiles and the lift coefficient show a smoother transition, without a sudden stall. Furthermore, the two-dimensional, one component velocity map reveals a velocity deficit region at Mach 0.8 at various angles of attack. Both single shot and mean velocity measurements were acquired allowing assessment of flowfield fluctuations and measurement precisions. The uncertainties are within 4 m/s in mean measurements based on repeatability data and about 5 m/s in instantaneous single-shot measurements. Measurements are reported with ~4.8 mm spatial resolution with 32-pixel averaging used to reduce measurement errors.

Transonic↗

DOE OSTI2020

Online Energy-optimal Routing for Electric Vehicles with Combinatorial Multi-arm Semi-Bandit

We have seen a rapid growth in the adoption of electric vehicle in today’s commercial mobility service market, from carrying passengers to the delivery of goods. One cardinal issue concerning the operation of EVs is the optimal routing of EV fleets with limited battery capacity. In this study, we investigate the energy-optimal online routing problem for the fleet of EVs, which focuses on identifying real-time minimum electricity consumption paths (MECP) for multiple OD pairs with limited information. We develop a multi-OD combinatorial multi-arm semi-bandit model (MCMAB) that uses the fleet of EVs as sensors in the transportation network and promotes the utilization of common information shared by different OD pairs. We further enrich the model with the path elimination policy to obtain MECP of high confidence while significantly reducing the number of learning iterations and the number of explorations needed. We demonstrate the effectiveness of the MCMAB and the efficiency of the path elimination policy with comprehensive numerical experiments in Manhattan, NYC. The results show that the proposed online routing algorithms can achieve near-optimal MECPs efficiently, and the quality of the solutions is significantly better than using the shortest travel time paths as approximate MECPs.

Chen, Xiaowei↗

DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗

DOE OSTI2022

Achieving American Leadership in the Hydropower Supply Chain

In 2020, hydropower accounted for 36.7% of U.S. renewable electricity generation and 7.3% of total electricity generation. While the existing U.S. supply chain effectively supports the nation’s hydropower fleet—the fourth-largest in the world, alongside the third-largest pumped storage hydropower (PSH) fleet—refurbishments, upgrades, and new development are required to modernize and expand the fleet and facilitate a clean, emissions-free U.S. electricity grid by 2035. To achieve these goals, researchers compiled a report examining the U.S. hydropower energy supply chain, including raw materials, processed materials, components, subcomponents, and recycling.

Source record↗

DOE OSTI2020

LWRS 2019 Accomplishments Report

Nuclear energy is an important part of supplying our nation’s energy—safely, dependably, and economically—with reduced carbon dioxide emissions. The United States (U.S.) Department of Energy-Office of Nuclear Energy (DOE-NE) supports a strong and viable domestic nuclear industry. In collaboration with industry programs, the Light Water Reactor Sustainability (LWRS) Program supports the continued operation of the commercial fleet of nuclear power plants. DOE’s role in this program focuses on enhancing the safe, efficient, and economical performance of the nation’s nuclear fleet. This report describes the accomplishments of the LWRS Program during Fiscal Year 2019. DOE-NE’s0F primary mission is to advance nuclear power as a resource capable of making major contributions in meeting the nation’s energy supply, environmental, and energy security needs. Under the guidance of three research objectives, NE resolves barriers to technical, cost, safety, security, and proliferation resistance through early stage research, development, and demonstration (RD&D) to: • Enhance the long-term viability and competitiveness of the existing U.S. reactor fleet • Develop an advanced reactor pipeline • Implement and maintain national strategic fuel-cycle and supply-chain infrastructures.

42 ENGINEERING↗

DOE OSTI2022

A view on the current and future impact of research reactors

Full text of publication follows. The current fleet of nuclear research reactors worldwide is nearly 70 years old. These reactors have proven to be extremely valuable tools of nuclear science and engineering with a broad and interdisciplinary impact. To date, research reactors are utilized as tools for understanding the physics, operations, and safety of nuclear fission systems. In addition, they are used as intense sources of radiation in support of irradiation testing and nondestructive examination of materials. As this fleet of reactors ages, an urgent need exists to establish new facilities that can propel the benefit of these reactors into the 21. century. In fact, an opportunity exists to build research reactors based on technology concepts that are being considered for nuclear energy reactors. This may include high temperature gas cooled and/or molten salt based advanced and micro reactor concepts. Such future reactors should be designed to maintain the broad utility of current reactors in research and education. However, modern research reactors can be purposefully designed and instrumented to access neutronic and thermal hydraulic information that would support the development and validation of reactor multi-physics modeling and simulation techniques. In this case, the entire phenomenological paradigm of the reactor may be captured to understand the neutronic multiscale and its impact on operations and safety. Moreover, the generated data can be channeled to drive anticipatory examination of the state of the reactor. In general, a symbiotic relation may be envisioned between the modern research reactor and power reactor fleets, which could facilitate the safe and efficient implementation of clean nuclear energy. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Wind Turbine Maintenance Costs: Assessing the Potential of Gear Oil Improvements

Wind turbine operations & maintenance (O&M) costs constitute a sizable portion of total energy cost for wind power. There are many components in a utility-scale wind turbine that need to be lubricated with either oil or grease. This study uses gearbox oil as an example and assesses how lubricant technology improvements may impact wind turbine power production and levelized cost of energy. Using the modeling tools (i.e., WOMBAT, reV, and SAM) developed at National Renewable Energy Laboratory and lubrication oil technology scenarios defined based on inputs provided by ExxonMobil and industry stakeholders, we quantify the potential for increasing energy production and reducing maintenance costs across the current and future U.S. fleet of wind turbines as a result of improvements in lubrication technologies. The modeled improvements reduce the median levelized cost of energy by 1-2% across the U.S. fleet. Cumulative saving from gear oil technology improvements in 2050 for U.S. fleet is estimated to be approximately $6 billion. Extending the lubricant replacement interval has a larger impact on total cost and energy production than reducing lubricant cost.

costs↗

DOE OSTI2025

An On-Demand Electric Transit Case Study of New Rochelle, New York

This work explores the extent to which an on-demand mobility service utilizing lightweight electric vehicles (EVs) provides community and sustainability benefits in New Rochelle, New York. Travel and survey data from September 2019 through 2023 are used to describe the system and estimate impacts on travelers. The system was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service is utilized primarily for short trips (86% under 2 miles), and the small, right-sized EVs have carbon dioxide emissions associated with charging the fleet that are roughly one-quarter of the fleet emissions of conventional hybrid vans and nearly 50 times less than a fleet of diesel buses. Mapping current socio-spatial dynamics of travel demand can inform equity performance, as well as assist future planning and service area development and possible extensions to similar smaller, lower-density environments that are nearby and connected to major metropolitan areas. The findings in this case study suggest on-demand electric transit may be a significant and growing space for advancing clean and highly valued public mobility services. Sustainable public transport interventions that consider right-sized, electric, on-demand vehicles can help achieve improved accessibility and reduce energy use and greenhouse gas emissions. This work was presented at the Transportation Research Board (TRB) 2025 Annual Meeting on January 7, 2025.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2025

A Study of Financial Impacts of Pooled Rideshare Based on Assignment Strategies

This study explores the potential profitability of a pooled rideshare service in a simulation-based case study of two US metropolitan regions in the context of two fleet assignment strategies. A new method of obtaining more accurate fares is created to address scalability and accuracy assumptions relevant to pooling choice. Cases for private rideshare fleets, public mobility on demand offerings, and autonomous fleets are explored and analyzed. Two regions of differing types are explored to illustrate the impacts of geo-spatial demand density of profitability, with one region capturing a large urban and suburban environment and the second a less dense more compact small city. Results indicate that the cost of human drivers is prohibitively expensive, and regulation of driver pay extends the issue of financial viability. Despite these shortcomings, a more efficient rideshare assignment strategy is shown to increase profitability by as much as 60%. The smaller, more dense region was illustrated to experience a greater increase in profitability than the larger region when pooling was improved.

Paul, Joseph↗

DOE OSTI2026

Validating Simulated Models of Energy Consumption by a Battery Electric Motorcoach: A real-world deployment in a harsh climate.

Many efforts have been made to simulate energy consumption of battery electric buses (BEBs) to optimize their deployment into existing fleets. The models produced, however, are rarely validated against real-world consumption data, limiting their generalizability and widespread application to fleets around the US. Furthermore, a major concern specific to BEBs is the effects of harsh climates on their performance. We build upon the state-of-the-art energy consumption modeling techniques developed for BEBs and apply them to a unique geographic context and a unique electrified vehicle. This geography, climate, and vehicle further the existing understanding of the factors affecting medium- and heavy-duty electric vehicles (MHDEVs) by allowing for new relationships to be tested and by assessing the generalizability of known relationships to new contexts. We find that temperature is less predictive of energy consumption for the battery electric motorcoach (BEM) in the case study environment than it is for BEBs in other studies. A mitigating factor that we presume to be working on the relationship between temperature and energy consumption is the fact that the BEM route does not stop between origin and destination to exchange passengers, and in turn, conditioned cabin air. Our model also incorporates wind speed and direction relative to travel, which is a novel contribution of our methodology. Results from our study are helpful for transit service planners, fleet operators, and logistics firms for improving their ability to predict performance of potential deployments of MHDEVs into existing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

DOE OSTI2026

USABILITY EXTENSION OF THE ŠKODA VPVR/M CASK FOR TRANSPORTING IRRADIATED FUEL ASSEMBLIES

New abstract from the final version being submitted now: This paper discusses the evolution and enhanced usability of the ŠKODA VPVR/M cask for the transport of irradiated fuel assemblies, particularly within the context of the demand for the delivery of newly appearing irradiated HEU fuel types for which the cask did not yet have a license to transport. Over time, the cask’s internal basket construction has demonstrated notable adaptability to accommodate various exotic HEU fuel types from research reactors of differing origins. The paper outlines sever-al custom internal baskets developed for specific fuel types, including those from Belarus and Serbia, as well as from Georgia, Uzbekistan, and MNSR cores, as well as a recently designed basket for MTR and TRIGA assemblies. The findings high-light the high flexibility and adaptability of the cask, supported by successful rede-signs and licensing efforts, underscoring its value for the safe and secure transport of nuclear material. Old abstract from the draft version that was already approved: The Russian Research Reactor Fuel Return (RRRFR) program, since its inception, has continuously used the ŠKODA VPVR/M Cask fleet designed for the repatriation of irradiated highly enriched uranium (HEU) fuel. As the program progressed (from shut-down and a quasi-abandoned reactor, and/or as it began to include fuels of Chinese and US origin), new challenges emerged for the transport Cask. These were fuel types that had not yet been licensed for the Cask. Although these requirements did not arise during the design of the basic ŠKODA VPVR/M Cask, as revealed by the retrospective analyses, the Internal Basket of the ŠKODA VPVR/M Cask gives a high degree of flexibility to accommodate additional fuel types. This paper provides a brief overview of the ŠKODA VPVR/M Cask, which holds a B(U) type license, and introduces the different types of Internal Baskets that have already been licensed to transport so-called exotic irradiated HEU fuel types, in addition to the original license. The paper presents a new Internal Basket design for accommodating MTR-type and TRIGA-type irradiated HEU fuel assemblies. This includes a detailed presentation of the design basis and the new MTR-TRIGA Internal Basket, as well as the licensing matters of the package under the name ŠKODA MTR-TRIGA Cask, and the conformity test (dry- and wet-run) operations made to verify compliance with the new Internal Basket. Then, as a summary, the usage record for the Cask fleet is presented, and finally, the paper concludes with the consolidated experiences gained during the utilization of the ŠKODA VPVR/M Cask fleet, emphasizing the high degree of Cask flexibility ensured by the Internal Basket’s construction.

42 - ENGINEERING↗

DOE OSTI2024

Electrification Analysis: Manhattan Beer

This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline, the Manhattan Beer Electrification Project. This project determined that Class-8 beverage distribution trucks operating in Manhattan show substantial electrification potential due to daily driving distances below 50 miles and low average speeds of 22mph or less. Their duty cycle needs can often be met by even modestly sized batteries and charging infrastructure. Vulnerable communities near their routes would benefit from fleet electrification.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Electrification Analysis: Container Ports' Cargo Handling Equipment

This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline, the Electrification Analysis of Container Ports' Cargo Handling Equipment project. This project created a scalable solution to model energy demand per shipping container moved (kWh/TEU) for an all-electric cargo handling equipment fleet located at a maritime port. The model allows stakeholders to understand energy demand at each electric vehicle (EV) equipment level and is easily scalable to container demand and EV adoption rate projections.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

ReachNow EV Driving Data From Seattle, WA, Portland, OR, and New York, NY

ReachNow provided Idaho National Laboratory (INL) with a dataset describing approximately 49,000 trips taken by customers and employees in approximately 100 BMW i3 EVs operating in ReachNow's free-floating car-sharing fleets in Seattle, WA, Portland, OR, and New York, NY between May 2016 and February 2017. Data fields include vehicle rental period start and end timestamps, the location where vehicles were parked at the start and end of rental periods, and distance driven during rental periods. A field categorizing the user during each rental period is also included. This field makes it possible to identify when vehicles were rented by customers and when vehicles were driven by fleet management team employees to reposition, charge, or service the vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

ReachNow EV Driving Data From Seattle, WA, Portland, OR, and New York, NY

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

DOE EV Data Collection - Charging Data

Charging data are collected from one of three sources, each with varying levels of additional information. These sources, in approximate order from most to least additional information, are: • The electric vehicle supply equipment (charger) • Onboard the vehicle itself • From a utility submeter. Many chargers provide software that allows for the collection and reporting of charging session data. If unavailable, data may be recorded by the charging vehicle’s onboard systems. If neither of these options is available, data can be acquired from utility submeters that simply track the energy flowing to one or more chargers. Data collected directly from the electric vehicle supply equipment (EVSE) are typically the most accurate and highest frequency. However, it is not always possible to discern which exact vehicle is being charged during any one session. EVSE-side data can be identified where a single charger ID but a range of vehicle IDs are present (e.g., CH001, EV001-EV005). Data collected from the vehicle’s onboard systems usually does not provide information on which exact charger is being used. Vehicle-side data can be identified where a single Vehicle ID but a range of Charger IDs are present (e.g., EV001, CH001-CH005). Data collected from utility submeters provide no information on which specific vehicle is charging or which specific charger is in use. Submeter data can be identified where multiple Vehicle IDs and multiple Charger IDs are present, but only a single Fleet ID is present (e.g., EV001-EV005, CH001-CH005, Fleet01). The **Charge Data Daily/Session Dictionaries** contains definitions for each available parameter collected as part of an individual charging session, aggregated at either a daily or session level. The parameters available will vary between vehicles and chargers. The **Charger Attributes** table contains specific charger characteristics, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. The **Charger Attributes Data Dictionary** contains definitions for each available parameter collected on the physical and operational characteristics of the charging hardware itself. The **Vehicle Attributes Data Dictionary** contains definitions for each available parameter associated with a vehicle’s physical and functional attributes and fleet context. The **Vehicle Attributes** table contains specific vehicle characteristics, coded to an anonymous Vehicle ID. This Vehicle ID can be used as a key between vehicle data and vehicle attribute tables, and in cases where charging data are supplied, links a vehicle with the charger(s) that supplied it power. The **Charging Data** tables contain the data from each charger’s operations, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. Data is being uploaded quarterly through 2023 and subject to change until the conclusion of the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Federal Automotive Statistical Tool: FY 2022 Data Call Status & Review Tools [Slides]

This presentation presents an overview of current federal vehicle fleet current data collection efforts covering required information submissions about the motor vehicles, fueling centers, and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation also provides an overview of the capabilities within FAST to assist federal agency users with reviewing and improving the quality of their fleet data submissions. This presentation is intended for delivery via WebEx at the November 9, 2022 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed by INL and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

PV System Availability from Commercial and Utility-Scale Systems [Slides]

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data, and publish aggregated, anonymized results. An assessment of system availability is conducted on 1128 systems which passed our data quality checks, and include cumulative energy meter data. Overall inverter availability is low in the first 6 months of system performance before reaching steady-state by the end of the first year. System-level aggregated data shows a median (P50) system availability of 0.99, and a lower P90 value of 0.95. A dependence on system size is also identified, with worse inverter availability results for larger PV systems. Potential causes of this effect are under investigation.

14 SOLAR ENERGY↗