C2C Expert Match: Fleet Analysis for Coos County Area Transportation District (Coos Bay, Oregon)
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Islam, Ehsan↗
SEARCH · Engineering Papers
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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C2C Expert Match: Fleet Analysis for Athens-Clarke County, Georgia
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Islam, Ehsan↗
C2C Expert Match: Fleet Analysis for Woodbridge Township, New Jersey
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Talreja, Tarun↗
Hypersonic FLEET Velocimetry on a Three-Dimensional Expansion-Compression Geometry
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Carter, Douglas [Illinois Institute of Technology]↗
Digital Transformation for the Existing Fleet: Where to Start?
To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.
assessment↗
Connected and Learning Based Optimal Freight Management for Efficiency
The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.
33 ADVANCED PROPULSION SYSTEMS↗
Optimal charging management and infrastructure planning for free-floating shared electric vehicles
Recently, major car-sharing service providers have begun to include electric vehicles (EVs) in free-floating car-sharing fleets. For these EVs, downtime due to charging, including time spent traveling to and waiting in queues at charging stations in a sparse charging infrastructure network, is a major barrier to sustainable operation. An intuitive solution to overcome this barrier is to increase the number of fast-charging stations in the fleet service area. This paper studies the relationship between fleet vehicle downtime and the number of charging stations by modeling the fleet operations of a major car-sharing service provider. An integer programming model is developed that jointly optimizes charging station allocation, in terms of the number and location of charging stations, and the assignment of EVs to charging stations. Case study results showed that fleet vehicle charging time comprises 72-75% of the total downtime spent on charging trips. This indicates that charging time, as opposed to travel time or waiting time, is the dominant component of total fleet downtime for charging. The study also shows that by adding 5 to 20 new charging stations reduces total fleet downtime and travel time during charging trips by 2-4% and 26-49%, respectively. Although adding new charging stations to the fleet service area reduces total charging trip travel time significantly, it does not reduce total downtime significantly. Results also show that if the EV battery state of the charge (SOC) threshold—below which a charging trip is initiated—is less than 18%, not all EVs in the car-sharing fleet can be charged using the existing direct current fast chargers (DCFCs) in the fleet’s service area. Furthermore, this implies that adequate charging infrastructure coverage is required to ensure that EVs of a given range can operate in the car-sharing fleet.
25 ENERGY STORAGE↗
Los Angeles Air Force Base Vehicle-to-Grid Demonstration (Final Project Report)
Electrification of non-tactical vehicle fleets represents a key efficiency and energy security objective for the United States Department of Defense. To achieve electrification, the department targeted vehicle-to-grid services as a way to decrease the overall cost of operating the vehicle fleet and achieve rough parity with traditional internal combustion engine vehicle fleets. This report describes efforts to aggregate a fleet of bi-directional electric vehicles and charging stations to provide regulation up and regulation down in the California Independent System Operator ancillary services market. A 29-vehicle electric vehicle demonstration fleet, consisting of mixed purpose and duty vehicles such as sedans, pickups, vans, and medium-duty trucks, was deployed at the Los Angeles Air Force base. The fleet provided frequency regulation to the California Independent System Operator’s wholesale electricity market to determine the capability of recouping some of the additional costs of procuring electric vehicles and their supporting infrastructure. Lawrence Berkeley National Laboratory, with its partner Kisensum, LLC, developed the fleet scheduling, optimization, and control software to allow the vehicle fleet at the air force base to participate in the ancillary services markets. This report focuses on the control software and market interactions, the significant challenges faced and solutions devised to address them, and examines the potential of using the electric vehicle fleet as an energy storage resource for the base buildings, an application known as vehicle-tobuilding, in providing demand response and emergency backup power. The report discusses key findings related to providing frequency regulation to the California Independent System Operator market, electric vehicle fleet performance, compatibility of varying resource parameters of vehicle fleet aggregation, the need for automated methods for communicating hour-ahead energy bidding, challenges related to battery capacity and charge/discharge rates, and monthly settlement revenue.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool
As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.
ADVANCED PROPULSION SYSTEMS↗
Designing a Methodology for Future Air Travel Scenarios
The growing demand on air travel throughout the world has prompted several proposals for the development of commercial aircraft capable of transporting a large number of passengers at supersonic speeds. Emissions from a projected fleet of such aircraft, referred to as high-speed civil transports (HSCT's), are being studied because of their possible effects on the chemistry and physics of the global atmosphere, in particular, on stratospheric ozone. At the same time, there is growing concern about the effects on ozone from the emissions of current (primarily subsonic) aircraft emissions. Evaluating the potential atmospheric impact of aircraft emissions from HSCT's requires a scientifically sound understanding of where the aircraft fly and under what conditions the aircraft effluents are injected into the atmosphere. A preliminary set of emissions scenarios are presented. These scenarios will be used to understand the sensitivity of environment effects to a range of fleet operations, flight conditions, and aircraft specifications. The baseline specifications for the scenarios are provided: the criteria to be used for developing the scenarios are defined, the required data base for initiating the development of the scenarios is established, and the state of the art for those scenarios that have already been developed is discussed. An important aspect of the assessment will be the evaluation of realistic projections of emissions as a function of both geographical distribution and altitude from an economically viable commercial HSCT fleet. With an assumed introduction date of around the year 2005, it is anticipated that there will be no HSCT aircraft in the global fleet at that time. However, projections show that, by 2015, the HSCT fleet could reach significant size. We assume these projections of HSCT and subsonic fleets for about 2015 can the be used as input to global atmospheric chemistry models to evaluate the impact of the HSCT fleets, relative to an all-subsonic future fleet. The methodology, procedures, and recommendations for the development of future HSCT and the subsonic fleet scenarios used for this evaluation are discussed.
Wuebbles, Donald J.↗
Considerations for Femtosecond Laser Electronic Excitation Tagging in High-Speed Flows
Femtosecond laser electronic excitation tagging (FLEET) is an unseeded method for molecular tagging which offers valuable opportunities for measurement of high-speed (transonic, supersonic or hypersonic) flows. The unique nature of high-speed testing demands certain performance from FLEET such as satisfactory signal-to-noise ratio (SNR) at depressed static conditions (i.e., low temperatures, pressures and densities), wide dynamic range for velocity determination (especially single-shot), and measurements with acceptable accuracy and precision. This dissertation strives to evaluate FLEET in those regards and provide strategies to maximize the method's capabilities. A zero-dimensional kinetics model in nitrogen explains FLEET signal changes with pressure/density and/or temperature in terms of plasma-chemical reactions. Poorly known rate coefficients are tuned by comparing model output to measurements, with temporal agreement up to several hundred nanoseconds. Modeling reveals that initial signal peaks at reduced density because of slowed temporal evolution (and decay) of excited populations. Low temperatures enhance signal by enlarging cluster ion populations which contribute to excited species via electron-ion dissociative recombination. A purpose-built free jet facility provides experimental validation of the kinetics model and assesses FLEET velocimetry in low temperature and pressure/density conditions. Signal, lifetime, accuracy and precision results are obtained from unheated subsonic through Mach 4.0 operation of the facility, with best results noted. FLEET measurements of a sweeping jet (SWJ) actuator in compressible operation showcase its advantages in a highly unsteady jet containing subsonic through supersonic velocities. FLEET velocimetry is performed in the device's internal and external flow fields, with the latter compared to hot-wire anemometry. Internal measurements reveal the absence of shockwaves theorized to occur at high pressure ratios. Simultaneous qualitative measurements of compressible jet mixing are shown as a proof-of-concept. Overall, the work demonstrates that previous understanding of SWJ incompressible operation readily extends into the compressible realm. Practical aspects of performing FLEET velocimetry are detailed, along with strategies for improving measurement quality. Determination of a fundamental precision in nitrogen and air is attempted. Experiments show that increasing time delay and/or SNR improves velocimetry precision. A comparison of five camera systems indicates sensors with larger pixels capture higher SNR data and produce more precise results.
FLEET↗
The Development of Vocational Vehicle Drive Cycles and Segmentation
Under a collaborative interagency agreement between the U.S. Environmental Protection Agency and the U.S Department of Energy (DOE), the National Renewable Energy Laboratory (NREL) performed a series of in-depth analyses to characterize the on-road driving behavior including distributions of vehicle speed, idle time, accelerations and decelerations, and other driving metrics of medium- and heavy-duty vocational vehicles operating within the United States. As part of this effort, NREL researchers segmented U.S. medium- and heavy-duty vocational vehicle driving characteristics into three distinct operating groups or clusters using real world drive cycle data collected at 1 Hz and stored in NREL's Fleet DNA database. The Fleet DNA database contains millions of miles of historical real-world drive cycle data captured from medium- and heavy vehicles operating across the United States. The data encompass data from existing DOE activities as well as contributions from valued industry stakeholder participants. For this project, data captured from 913 unique vehicles comprising 16,250 days of operation were drawn from the Fleet DNA database and examined. The Fleet DNA data used as a source for this analysis has been collected from a total of 30 unique fleets/data providers operating across 22 unique geographic locations spread across the United States. This includes locations with topology ranging from the foothills of Denver, Colorado, to the flats of Miami, Florida. The range of fleets, geographic locations, and total number of vehicles analyzed ensures results that include the influence of these factors. While no analysis will be perfect without unlimited resources and data, it is the researchers understanding that the Fleet DNA database is the largest and most thorough publicly accessible vocational vehicle usage database currently in operation. This report includes an introduction to the Fleet DNA database and the data contained within, a presentation of the results of the statistical analysis performed by NREL, review of the logistic model developed to predict cluster membership, and a discussion and detailed summary of the development of the vocational drive cycle weights and representative transient drive cycles for testing and simulation. Additional discussion of known limitations and potential future work are also included in the report content.
54 ENVIRONMENTAL SCIENCES↗
Next Generation Environmentally-Friendly Driving Feedback Systems Research and Development
The objective of this project is to design, develop, and demonstrate a next-generation, federal safety- and emission-complaint driving feedback system that can be deployed across the existing vehicle fleet and improve fleet average fuel efficiency by at least 2%. The project objective was achieved with the driving feedback system that encourages fuel-efficient vehicle travel and operation through: 1) Eco-Routing Navigation module that suggests the most fuel-efficient route from one stop to the next, 2) Eco-Driving Feedback module that provides sensible information, recommendation, and warning regarding fuel-efficient vehicle operation, and 3) Eco-Score and Eco-Rank module that provides a means for driving performance tracking, self-evaluation, and peer comparison. The system also collects and stores vehicle travel and operation data, which are used by Algorithm Updating module to customize the other modules for specific vehicles and adapts them to specific drivers over time. The driving feedback system was designed and developed as an aftermarket technology that can be retrofitted to vehicles in the existing fleet. It consists of a mobile application for smart devices running Android operating system, a vehicle on-board diagnostics connector, and a data server. While the system receives and utilizes real-time vehicle and engine data from the vehicle’s controller area network bus through the vehicle’s on-board diagnostic connector, it does not modify or interfere with the vehicle’s controller area network bus, and thus, is in compliance with federal safety and emission regulations. The driving feedback system was demonstrated and then installed on 45 vehicles from three different fleets for field operational test. These include 15 private vehicles of the general public, 15 pickup trucks of the California Department of Transportation that are assigned to individual employees for business use, and 15 shuttle buses of the Riverside Transit Agency that are used for paratransit service. Detailed vehicle travel and operation data including route taken, driving speed, acceleration, braking, and the corresponding fuel consumption, were collected both before and during the test period. The data analysis results show that the fleet average fuel efficiency improvements for the three fleets with the use of the driving feedback system are in the range of 2% to 9%. The economic viability of the driving feedback system is high. A fully deployed system would require capital investment in smart device ($150-$350) and on-board diagnostics connector ($50-$100) as well as paying operating costs for wireless data plan and subscription fees ($20-$30 per month) for connecting to the data server and receiving various system services. For individual consumers who already own a smart device (such as smartphone) and commercial fleets that already use some kind of telematics services, the costs for deploying this driving feedback system would be much lower.
33 ADVANCED PROPULSION SYSTEMS↗
Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions
Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.
Biomass Co-firing↗
Multiparameter Flowfield Measurements in High-Pressure, Cryogenic Environments Using Femtosecond Lasers
Femtosecond laser electronic excitation tagging (FLEET) and Rayleigh scattering (RS) from a femtosecond laser are demonstrated in the NASA Langley 0.3-m Transonic Cryogenic Tunnel (TCT). The measured signals from these techniques are examined for their thermodynamic dependencies in pure nitrogen. The FLEET signal intensity and signal lifetimes are found to scale primarily with the gas density, as does the RS signal. Several models are developed, which capture these physical behaviors. Notably, the FLEET and Rayleigh scattering intensities scale linearly with the flow density, while the FLEET signal decay rates are a more complex function of the thermodynamic state of the gas. The measurement of various flow properties are demonstrated using these techniques. While density was directly measured from the signal intensities and FLEET signal lifetime, temperature and pressure were measured using the simultaneous FLEET velocity measurements while assuming the flow had a constant total enthalpy. Measurements of density, temperature, and pressure from the FLEET signal are made with accuracies as high as 5.3 percent, 0.62 percent, and 6.2 percent, respectively, while precisions were approximately 10 percent, 0.26 percent, and 11 percent for these same quantities. Similar measurements of density from Rayleigh scattering showed an overall accuracy of 3.5 percent and a precision of 10.2 percent over a limited temperature range (T greater than 195 K). These measurements suggest a high degree of utility at using the femtosecond-laser based diagnostics for making multiparameter measurements in high-pressure, cryogenic environments such as large-scale TCT facilities.
Burns, Ross A.↗
Market Analysis of the Subsonic Single Aft Engine (SUSAN) Transport Aircraft Concept
This paper presents a detailed market analysis of the U.S. domestic aviation market in support of the NASA subsonic single aft engine (SUSAN) regional aircraft concept. The current scoping of the SUSAN concept is intended to compete in the medium to large (160-180 seats) narrow body market, with range capabilities of up to 2,500 nautical miles, and expected fuel burn reduction up to 40% relative to conventional 2 engine aircraft. Recent historical trends suggest growth in aviation passenger demand will continue to be met by the narrow body fleet of aircraft; however, a comprehensive review is required to understand how these current fleet trends could evolve in the future. Moreover, estimating and forecasting the potential market size is the critical first step when developing a new aircraft concept to determine commercial viability. To assist in the trade space exploration of the SUSAN concept, a generalized traffic and fleet forecast of the U.S. aviation market is conducted. Using publicly available aviation data from the U.S. Bureau of Transportation Statistics and passenger demand forecasts from FAA, a multinomial logit model is estimated to predict the composition of the future fleet by aircraft size. These fleet forecasts are then used as inputs for a fleet evolution model to provide required operational forecasts at the aircraft specific level. Forecast scenarios with and without the SUSAN concept are compared, and a breakeven analysis is performed to evaluate the commercial viability of the SUSAN aircraft from an operating cost perspective. Results from the multinomial logit fleet forecast indicate the narrow body size category of 150+ seats dominating the market, comprising 87% of the future revenue passenger miles market share in 2050 (up from 60% in 2019). Forecast scenarios with the SUSAN concept see a maximum cumulative decline in fuel cost of 20% by 2050, while a breakeven analysis shows competitive advantage of the SUSAN aircraft, due to expected fuel burn reduction, at moderate levels of increased maintenance and capital costs.
Jacob M. Wishart↗
EVALUATION OF THE EFFECTIVENESS OF TRUCK EFFICIENCY TECHNOLOGIES IN CLASS 8 TRACTOR-TRAILERS BASED ON A TRACTIVE ENERGY ANALYSIS USING MEASURED DRIVE CYCLE DATA
Quantifying the fuel savings that can be achieved from different truck fuel efficiency technologies for a fleet s specific usage allows the fleet to select the combination of technologies that will yield the greatest operational efficiency and profitability. This paper presents an analysis of vehicle usage in a commercial vehicle fleet and an assessment of advanced efficiency technologies using an analysis of measured drive cycle data for a class 8 regional commercial shipping fleet. Drive cycle measurements during a period of a full year from six tractor-trailers in normal operations in a less-than-truckload (LTL) carrier were analyzed to develop a characteristic drive cycle that is highly representative of the fleet s usage. The vehicle mass was also estimated to account for the variation of loads that the fleet experienced. The drive cycle and mass data were analyzed using a tractive energy analysis to quantify the fuel efficiency and CO2 emissions benefits that can be achieved on class 8 tractor-trailers when using advanced efficiency technologies, either individually or in combination. Although differences exist among class 8 tractor-trailer fleets, this study provides valuable insight into the energy and emissions reduction potential that various technologies can bring in this important trucking application.
LaClair, Tim J↗
Utilization of Used Nuclear Fuel in a Potential Future US Fuel Cycle Scenario - 13499
To date, the US reactor fleet has generated approximately 68,000 MTHM of used nuclear fuel (UNF) and even with no new nuclear build in the US, this stockpile will continue to grow at approximately 2,000 MTHM per year for several more decades. In the absence of reprocessing and recycle, this UNF is a liability and needs to be dealt with accordingly. However, with the development of future fuel cycle and reactor technologies in the decades ahead, there is potential for UNF to be used effectively and efficiently within a future US nuclear reactor fleet. Based on the detailed expected operating lifetimes, the future UNF discharges from the existing reactor fleet have been calculated on a yearly basis. Assuming a given electricity demand growth in the US and a corresponding growth demand for nuclear energy via new nuclear build, the future discharges of UNF have also been calculated on a yearly basis. Using realistic assumptions about reprocessing technologies and timescales and which future fuels are likely to be reprocessed, the amount of plutonium that could be separated and stored for future reactor technologies has been determined. With fast reactors (FRs) unlikely to be commercially available until 2050, any new nuclear build prior to then is assumed to be a light water reactor (LWR). If the decision is made for the US to proceed with reprocessing by 2030, the analysis shows that the UNF from future fuels discharged from 2025 onwards from the new and existing fleet of LWRs is sufficient to fuel a realistic future demand from FRs. The UNF arising from the existing LWR fleet prior to 2025 can be disposed of directly with no adverse effect on the potential to deploy a FR fleet from 2050 onwards. Furthermore, only a proportion of the UNF is required to be reprocessed from the existing fleet after 2025. All of the analyses and conclusions are based on realistic deployment timescales for reprocessing and reactor deployment. The impact of the delay in recycling the UNF from the FRs due to time in the core, cooling time, reprocessing, and re-fabrication time is built into the analysis, along with impacts in delays and other key assumptions and sensitivities have been investigated. The results of this assessment highlight how the UNF from future reactors (LWRs and FRs) and the resulting fissile materials (U and Pu) from reprocessing can be effectively utilized, and show that the timings of future nuclear programs are key considerations (both for reactors and fuel cycle facilities). The analysis also highlights how the timings are relevant to managing the UNF and how such an analysis can therefore assist in informing the potential future R and D strategy and needs of the US fuel cycle programs and reactor technology. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗