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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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At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS2017

Manned Versus Unmanned Risk and Complexity Considerations for Future Midsized X-Planes

The objective of this work was to identify and estimate complexity and risks associated with the development and testing of new low-cost medium-scale X-plane aircraft primarily focused on air transport operations. Piloting modes that were evaluated for this task were manned, remotely piloted, and unmanned flight research programs. This analysis was conducted early in the data collection period for X-plane concept vehicles before preliminary designs were complete. Over 50 different aircraft and system topics were used to evaluate the three piloting control modes. Expert group evaluations from a diverse set of pilots, engineers, and other experts at Aeronautics Research Mission Directorate centers within the National Aeronautics and Space Administration provided qualitative reasoning on the many issues surrounding the decisions regarding piloting modes. The group evaluations were numerically rated to evaluate each topic quantitatively and were used to provide independent criteria for vehicle complexity and risk. An Edwards Air Force Base instruction document was identified that emerged as a source of the effects found in our qualitative and quantitative data. The study showed that a manned aircraft was the best choice to align with test activities for transport aircraft flight research from a low-complexity and low-risk perspective. The study concluded that a manned aircraft option would minimize the risk and complexity to improve flight-test efficiency and bound the cost of the flight-test portion of the program. Several key findings and discriminators between the three modes are discussed in detail.

x-planes↗

NASA NTRS2017

Manned Versus Unmanned Risk and Complexity Considerations for Future Midsized X-Planes

quanitive analysis↗

DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2003

An Indispensable Ingredient: Flight Research and Aircraft Design

Flight research-the art of flying actual vehicles in the atmosphere in order to collect data about their behavior-has played a historic and decisive role in the design of aircraft. Naturally, wind tunnel experiments, computational fluid dynamics, and mathematical analyses all informed the judgments of the individuals who conceived of new aircraft. But flight research has offered moments of realization found in no other method. Engineer Dale Reed and research pilot Milt Thompson experienced one such epiphany on March 1, 1963, at the National Aeronautics and Space Administration s Dryden Flight Research Center in Edwards, California. On that date, Thompson sat in the cockpit of a small, simple, gumdrop-shaped aircraft known as the M2-F1, lashed by a long towline to a late-model Pontiac Catalina. As the Pontiac raced across Rogers Dry Lake, it eventually gained enough speed to make the M2-F1 airborne. Thompson braced himself for the world s first flight in a vehicle of its kind, called a lifting body because of its high lift-to-drag ratio. Reed later recounted what he saw:

Gorn, Michael H.↗

NASA NTRSDate not supplied

Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and Workload

Technological advances have increased the automation of Uncrewed Aerial Vehicles, allowing human operators to manage multiple vehicles at a high-level without the need to understand low-level system behaviors. Previous laboratory studies have explored the relationship between reliability, trust, use of automation and the effects of number of vehicles under supervision on subjective workload. Due to the limitations resulting from the COVID-19 pandemic, in-person laboratory studies are not always possible. Therefore, this work aimed to investigate if remote data collection alternatives, such as Amazon’s Mechanical Turk, can provide comparative results as those obtained in laboratory settings. A study was conducted in the context of small drone operations. As expected, higher reliability led to higher trust ratings and the inclusion of more vehicles led to higher workload. In contrast, reliability unexpectedly had no effect on intention to use the automation. Though these results were encouraging, several limitations were identified.

trust↗

NASA NTRS2012

Explanation Capabilities for Behavior-Based Robot Control

A recent study that evaluated issues associated with remote interaction with an autonomous vehicle within the framework of grounding found that missing contextual information led to uncertainty in the interpretation of collected data, and so introduced errors into the command logic of the vehicle. As the vehicles became more autonomous through the activation of additional capabilities, more errors were made. This is an inefficient use of the platform, since the behavior of remotely located autonomous vehicles didn't coincide with the "mental models" of human operators. One of the conclusions of the study was that there should be a way for the autonomous vehicles to describe what action they choose and why. Robotic agents with enough self-awareness to dynamically adjust the information conveyed back to the Operations Center based on a detail level component analysis of requests could provide this description capability. One way to accomplish this is to map the behavior base of the robot into a formal mathematical framework called a cost-calculus. A cost-calculus uses composition operators to build up sequences of behaviors that can then be compared to what is observed using well-known inference mechanisms.

Huntsberger, Terrance L.↗

DOE OSTI2025

Commercial Fleet Level Emissions and Energy Tracker (COFLEET) v1.0

This tool generates the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and assess the fleetwide energy and emission outcomes. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to generate fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The tool also provides fleet turnover and emission forecasts under various forecasted fleet electrification scenarios. This tool helps policymakers and practitioners advance the commercial fleet generation for emission models. This study also provides some sample datasets for state and local transportation/air quality agencies to test, which can reduce the estimation bias associated with using MOVES default fleets.

Xu, Xiaodan [Lawrence Berkeley National Laboratory↗

DOE OSTI2022

FY 2021 Federal Vehicle Fleet Data Overview [Slides]

This presentation provides an overview of the fiscal year (FY) 2021 federal motor vehicle fleet dataset collected through the Federal Automotive Statistical Tool (FAST). FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles. The presentation discusses the size of the dataset; provides a high-level look at what the collected information shows about the makeup and operation of the federal motor vehicle fleet during FY 2021 and how that compares with recent years; discusses the process used to review the agency submissions comprising the dataset; and discusses how overall quality of the dataset has been assessed.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Database to Enable Facial Analysis for Driving Studies (DEFADS)

Naturalistic Driving Studies (NDS) collect and utilize data on drivers in real-world environments in instrumented vehicles. A common problem with such studies is driver privacy. In this work we collected a dataset of 77 human subjects performing scripted driving-related activities. We used three camera systems for the collection, including two high-resolution webcam devices as well as a third system from an actual NDS (the Second Strategic Highway Research Project, or SHRP2). This report covers the data collection process and summarizes the dataset, which will be made publicly available to researchers under a data usage license.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Transit Bus Electrification Evaluation from GPS Speed Traces

Through the USAID-NREL partnership, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) has evaluated the potential for transit bus electrification in Mexico City and two locations in León, Mexico to inform future vehicle and infrastructure purchases. NREL collected IHz GPS data between September to October of 2017 from the existing transit buses as inputs to the Future Automotive Systems Technology Simulator (FASTSim) tool. NREL used the data and FASTSim models to provide detailed operational performance requirements of electric buses operated within the context of the three locations and highlighted bus operations that are candidates for electrification.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

2011-2012 Maryland Route 200 Travel Survey

The 2011-2012 Maryland Route 200 Travel Survey collected in-vehicle global positioning system (GPS) data to investigate the use of Maryland Route 200, also known as the Intercounty Connector. The University of Maryland conducted the survey between October 2011 and February 2012 in Washington, D.C., and Baltimore, Maryland. Its goal was to increase understanding of the potential use of Maryland Route 200, a tolled freeway connecting Maryland's Montgomery County and Prince George's County. Dedicated in-vehicle GPS devices were installed in 260 vehicles to record location information every 60 seconds if movement was detected. Survey subjects partook in an initial participation form as well as a recall survey, providing social demographic information and a one-day travel diary.

1Hz data↗

NASA NTRS1989

The MANTA: An RPV design to investigate forces and moments on a lifting surface

The overall goal was to investigate and exploit the advantages of using remotely powered vehicles (RPV's) for in-flight data collection at low Reynold's numbers. The data to be collected is on actual flight loads for any type of rectangular or tapered airfoil section, including vertical and horizontal stabilizers. The data will be on a test specimen using a force-balance system which is located forward of the aircraft to insure an undisturbed air flow over the test section. The collected data of the lift, drag and moment of the test specimen is to be radioed to a grand receiver, thus providing real-time data acquisition. The design of the mission profile and the selection of the instrumentation to satisfy aerodynamic requirements are studied and tested. A half-size demonstrator was constructed and flown to test the flight worthiness of the system.

Bryan, Kevin↗

NASA NTRS1998

The Recovery of TOMS-EP

On December 13th 1998, the Total Ozone Mapping Spectrometer - Earth Probe (TOMS-EP) spacecraft experienced a Single Event Upset which caused the system to reconfigure and enter a Safe Mode. This incident occurred two and a half years after the launch of the spacecraft which was designed for a two year life. A combination of factors, including changes in component behavior due to age and extended use, very unfortunate initial conditions and the safe mode processing logic prevented the spacecraft from entering its nominal long term storage mode. The spacecraft remained in a high fuel consumption mode designed for temporary use. By the time the onboard fuel was exhausted, the spacecraft was Sun pointing in a high rate flat spin. Although the uncontrolled spacecraft was initially in a power and thermal safe orientation, it would not stay in this state indefinitely due to a slow precession of its momentum vector. A recovery team was immediately assembled to determine if there was time to develop a method of despinning the vehicle and return it to normal science data collection. A three stage plan was developed that used the onboard magnetic torque rods as actuators. The first stage was designed to reduce the high spin rate to within the linear range of the gyros. The second stage transitioned the spacecraft from sun pointing to orbit reference pointing. The final stage returned the spacecraft to normal science operation. The entire recovery scenario was simulated with a wide range of initial conditions to establish the expected behavior. The recovery sequence was started on December 28th 1998 and completed by December 31st. TOMS-EP was successfully returned to science operations by the beginning of 1999. This paper describes the TOMS-EP Safe Mode design and the factors which led to the spacecraft anomaly and loss of fuel. The recovery and simulation efforts are described. Flight data are presented which show the performance of the spacecraft during its return to science. Finally, lessons learned are presented.

Robertson, Brent↗

NASA NTRS1998

Ceramic Fairings for A Hypersonic Flight Experiment

Fairings composed of Rigid Fibrous Insulations (RSI) were fabricated, instrumented, and coated using techniques that were recently developed at NASA Ames Research Center. These RSI components are part of a specific assembly of materials which were built onto a wing of a Pegasus flight vehicle. The assembly was designed to collect aerothermal data during a designated mission to deliver a satellite to earth orbit. The objective of the flight experiment is to validate the theory of boundary layer transition at flight speeds in excess of Mach 3. The actual flight experiment is scheduled to occur during the summer of 1998. Fabrication and installation methodologies will be discussed with a brief description of the wing glove assembly.

Churchward, Rex↗

NASA NTRS2012

CloudSat Anomaly Recovery and Operational Lessons Learned

In April 2011, NASA's pioneering cloud profiling radar satellite, CloudSat, experienced a battery anomaly that placed it into emergency mode and rendered it operations incapable. All initial attempts to recover the spacecraft failed as the resultant power limitations could not support even the lowest power mode. Originally part of a six-satellite constellation known as the "A-Train", CloudSat was unable to stay within its assigned control box, posing a threat to other A-Train satellites. CloudSat needed to exit the constellation, but with the tenuous power profile, conducting maneuvers was very risky. The team was able to execute a complex sequence of operations which recovered control, conducted an orbit lower maneuver, and returned the satellite to safe mode, within one 65 minute sunlit period. During the course of the anomaly recovery, the team developed several bold, innovative operational strategies. Details of the investigation into the root-cause and the multiple approaches to revive CloudSat are examined. Satellite communication and commanding during the anomaly are presented. A radical new system of "Daylight Only Operations" (DO-OP) was developed, which cycles the payload and subsystem components off in tune with earth eclipse entry and exit in order to maintain positive power and thermal profiles. The scientific methodology and operational results behind the graduated testing and ramp-up to DO-OP are analyzed. In November 2011, the CloudSat team successfully restored the vehicle to consistent operational collection of cloud radar data during sunlit portions of the orbit. Lessons learned throughout the six-month return-to-operations recovery effort are discussed and offered for application to other R&D satellites, in the context of on-orbit anomaly resolution efforts.

cloud profiling radar satellite↗

DOE OSTI2020

Electric Vehicle Adoption in Illinois

Over 1.3 million plug-in electric vehicles (PEVs) have been sold in the United States since 2010 when the first Chevy Volt and Nissan Leaf vehicles came on the market. Currently, electric vehicles account for about 2% of monthly light-duty vehicle (LDV) sales. More than 40 different electric vehicle models are actively being marketed, and most of these are LDVs. Over the last few years, automakers have brought more models, with varying mileage ranges, to the market, including medium-duty and heavy-duty trucks and buses. Government agencies at the federal, regional, and state levels, as well as utilities across the United States, have provided financial and non-financial incentives to promote electric vehicle adoption and charging infrastructure deployment. Argonne National Laboratory, sponsored by the U.S. Department of Energy, has developed tools and collected data to quantify the energy, economic, and environmental benefits of electric vehicles. This project has three objectives. First, we summarize the policies and other actions of the federal government, various states/regions, and utilities to promote PEV adoption, and evaluate their relative effectiveness based on a review of the literature. Second, we identify possible PEV adoption paths or scenarios that would result in PEVs making up 15% of all on-road vehicles in Illinois, and we quantify the resulting impacts on petroleum consumption and electricity demand. We also summarize the possible reduction in greenhouse gas (GHG) and criteria pollutant emissions due to PEV adoption. The PEV scenarios include private and public adoption of electric cars, light trucks (e.g., sports utility vehicles [SUVs], vans, pickups), medium-duty vehicles (MDVs), and heavy-duty vehicles (HDVs). Third, we estimate hourly charging loads of light-duty PEVs in 2030 associated with these scenarios, incorporating assumptions about vehicle electric range, efficiency, and travel behavior.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗

NASA NTRS1981

A data collection scheme for identification of parameters in a driver model

A high gain steering controller to compensate for limitations in a handicapped driver's range of motion is employed when adapting vehicle to his use. A driver/vehicle system can become unstable as vehicle speed is increased, therefore it is desirable to use a computer simulation of the driver/vehicle combination as a design tool to investigate the system response prior to construction of a controller and road testing. Unknown driver parameters must be identified prior to use of the model for system analysis. A means to collect the data necessary for identification of these driver model parameters without extensive instrumentation of a vehicle to measure and record vehicle states is addressed. Initial tests of the procedure identified all of the driver parameters with errors of 6% or less.

Mooring, B. W.↗