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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 289 records · Page 16

All sources NASA NTRS DOE OSTI

NASA NTRS2013

Design Study of Propulsion and Drive Systems for the Large Civil TiltRotor (LCTR2) Rotorcraft

Boeing, Rolls Royce, and NASA have worked together to complete a parametric sizing study for NASA's Large Civil Tilt Rotor (LCTR2) concept 2nd iteration. Vehicle gross weight and fuel usage were evaluated as propulsion and drive system characteristics were varied to maximize the benefit of reduced rotor tip speed during cruise conditions. The study examined different combinations of engine and gearbox variability to achieve rotor cruise tip speed reductions down to 54% of the hover tip speed. Previous NASA studies identified that a 54% rotor speed reduction in cruise minimizes vehicle gross weight and fuel burn. The LCTR2 was the study baseline for initial sizing. This study included rotor tip speed ratios (cruise to hover) of 100%, 77% and 54% at different combinations of engine RPM and gearbox speed reductions, which were analyzed to achieve the lightest overall vehicle gross weight (GW) at the chosen rotor tip speed ratio. Different engine and gearbox technology levels are applied ranging from commercial off-the-shelf (COTS) engines and gearbox technology to entry-in-service (EIS) dates of 2025 and 2035 to assess the benefits of advanced technology on vehicle gross weight and fuel burn. Interim results were previously reported1. This technical paper extends that work and summarizes the final study results including additional engine and drive system study accomplishments. New vehicle sizing data is presented for engine performance at a single operating speed with a multispeed drive system. Modeling details for LCTR2 vehicle sizing and subject engine and drive sub-systems are presented as well. This study was conducted in support of NASA's Fundamental Aeronautics Program, Subsonic Rotary Wing Project.

Robuck, Mark↗

NASA NTRS1981

Straight and chopped dc performance data for a General Electric 5BT 2366C10 motor and an EV-1 controller

Performance data on the General Electric 5BT 2366C10 series wound dc motor and EV-1 Chopper Controller is supplied for the electric vehicle manufacturer. Data is provided for both straight and chopped dc input to the motor, at 2 motor temperature levels. Testing was done at 6 voltage increments to the motor, and 2 voltage increments to the controller. Data results are presented in both tabular and graphical forms. Tabular information includes motor voltage and current input data, motor speed and torque output data, power data and temperature data. Graphical information includes torque-speed, motor power output-speed, torque-current, and efficiency-speed plots under the various operating conditions. The data resulting from this testing shows the speed-torque plots to have the most variance with operating temperature. The maximum motor efficiency is between 86% and 87%, regardless of temperature or mode of operation. When the chopper is utilized, maximum motor efficiency occurs when the chopper duty cycle approaches 100%.

Edie, P. C.↗

NASA NTRS1988

Lateral and longitudinal stability and control parameters for the space shuttle discovery as determined from flight test data

The Discovery vehicle was found to have longitudinal and lateral aerodynamic characteristics similar to those of the Columbia and Challenger vehicles. The values of the lateral and longitudinal parameters are compared with the preflight data book. The lateral parameters showed the same trends as the data book. With the exception of C sub l sub Beta for Mach numbers greater than 15, C sub n sub delta r for Mach numbers greater than 2 and for Mach numbers less than 1.5, where the variation boundaries were not well defined, ninety percent of the extracted values of the lateral parameters fell within the predicted variations. The longitudinal parameters showed more scatter, but scattered about the preflight predictions. With the exception of the Mach 1.5 to .5 region of the flight envelope, the preflight predictions seem a reasonable representation of the Shuttle aerodynamics. The models determined accounted for ninety percent of the actual flight time histories.

Suit, William T.↗

NASA NTRS1999

Autonomous Science Decisions for Mars Sample Return

In the near future NASA intends to explore Mars in preparation for a sample return mission using robotic devices such as landers rovers, orbiters, airplanes, and/or balloons. Such platforms will likely carry imaging devices to characterize the surface morphology, and a variety of analytical instruments intended to evaluated the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved the following sequence of activities: (1) return of scientific data from the vehicle; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) transmission of commands to the vehicle to achieve this activity; and (5) new activity by the vehicle in response to those commands.

Roush, T. L.↗

NASA NTRS1981

Straight and chopped dc performance data for a Prestolite MTC-4001 motor and a general electric EV-1 controller

Performance data on the Prestolite MTC-4001 series wound dc motor and General Electric EV-1 Chopper Controller is supplied for the electric vehicle manufacturer. Data are provided for both straight and chopped dc input to the motor, at 2 motor temperature levels. Testing was done at 6 voltage increments to the motor, and 2 voltage increments to the controller. Data results are presented in both tabular and graphical forms. Tabular information includes motor voltage and current input data, motor speed and torque output data, power data and temperature data. Graphical information includes torque-speed, motor power output-speed, torque-current, and efficiency-speed plots under the various operating conditions. The data resulting from this testing show the speed-torque plots to have the most variance with operating temperature. The maximum motor efficiency is between 76% and 82%, regardless of temperature or mode of operation.

Edie, P. C.↗

NASA NTRS1998

Comparison of the Aerodynamic Characteristics of Similar Models in Two Size Wind Tunnels at Transonic Speeds

The aerodynamic characteristics of two similar models of a lifting body configuration were run in two transonic wind tunnels, one a 16 foot the other a 14-inch and are compared. The 16 foot test used a 2% model while the 14-inch test used a 0.7% scale model. The wind tunnel model configurations varied only in vertical tail size and an aft sting shroud. The results from these two tests compare the effect of tunnel size, Reynolds number, dynamic pressure and blockage on the longitudinal aerodynamic characteristics of the vehicle. The data accuracy and uncertainty are also presented. It was concluded from these tests that the data resultant from a small wind tunnel compares very well to that of a much larger wind tunnel in relation to total vehicle aerodynamic characteristics.

Springer, Anthony M.↗

NASA NTRSDate not supplied

Simulation and Analysis of NASA Lift Plus Cruise eVTOL Crash Test

The National Aeronautics and Space Administration (NASA) will perform a full-scale crash test of a representative electric vertical take-off and landing (eVTOL) fuselage in November 2022. The test article is a carbon-composite fuselage cabin section of the six-passenger lift plus cruise (LPC) eVTOL design concept which was created by NASA to advance understanding of eVTOL propulsion, noise, and safety. The test will consist of impacting the fuselage cabin section onto a concrete surface with a combined horizontal and vertical velocity approximating a severe but survivable crash landing for this vehicle design. Data generated from this test will be used to inform eVTOL crashworthiness regulation development, evaluate the use of energy absorbing concepts within vehicle design, and validate finite element model (FEM) techniques used in crashworthiness predictions. The cabin section response will be evaluated using structural instrumentation, anthropometric test devices (ATDs), and high-speed photogrammetry. This study will compare pre-test FEM predictions to test results to quantify the capability of these tools to predict crashworthiness of the carbon-composite eVTOL airframe.

Crashworthiness↗

NASA NTRSDate not supplied

Simulation and Analysis of NASA Lift Plus Cruise eVTOL Crash Test

Crashworthiness↗

NASA NTRS1983

Development of aerodynamic prediction methods for irregular planform wings

A set of empirical methods was developed to predict low-speed lift, drag and pitching-moment variations with angle of attack for a class of low aspect ratio irregular planform wings suitable for application to advanced aerospace vehicles. The data base, an extensive series of wind-tunnel tests accomplished by the Langley Research Center of the National Aeronautics and Space Administration, is summarized. The approaches used to analyze the wind tunnel data, the evaluation of previously existing methods, data correlation efforts, and the development of the selected methods are presented and discussed. A summary of the methods is also presented to document the equations, computational charts and design guides which have been programmed for digital computer solution. Comparisons of predictions and test data are presented which show that the new methods provide a significant improvement in capability for evaluating the landing characteristics of advanced aerospace vehicles during the preliminary design phase of the configuration development cycle.

Benepe, D. B., Sr.↗

NASA NTRS1974

Supersonic tests of an 0.015 scale space shuttle mated vehicle model (67-OTS) in the LaRC UPWT to obtain aerodynamic force data (IA42A/B)

Wind tunnel tests were conducted of the NASA/Rockwell 0.015 scale configuration 4 mated space shuttle vehicle. Data were obtained for a range of Mach numbers from 1.60 to 4.63 and angles of attack from minus 10 degrees to plus 10 degrees. A complete model build-up was performed. Longitudinal and lateral directional stability and control data were obtained for the tank alone, tank plus solid rocket boosters, and mated configuration of tank plus orbiter plus solid rocket boosters. Single component rudder hinge moment data were obtained at rudder deflections of zero degrees and minus 20 degrees for each Mach number tested.

Hardin, R.↗

DOE OSTI2021

Improving the performance of first- and last-mile mobility services through transit coordination, real-time demand prediction, advanced reservations, and trip prioritization

Socio-demographic trends and recent economic development patterns have resulted in travel behavior changes that call for more flexible and accessible public transit options. Because flexible transit services vary in scope, size, and service type, new data-informed methods are useful to optimize services based on the specific needs of local communities and riders. In this study, real-world demand and vehicle trajectory data were used to evaluate and optimize system performance for an existing first-mile–last-mile (FMLM) service in Robinson Township, PA. A general FMLM model for arbitrary demand and service supply was then developed to quantify system performance—both travel time costs and day-to-day reliability—for various operational polices considering spatio-temporal demand variation and transportation network dynamics. Heuristics were used for optimal real-time vehicle routing in sizable real-world networks accommodating various service types and scopes. In this case study, total user costs were reduced by 18.6% when rides were coordinated with mainline fixed-route transit. Predictive routing strategies were shown to marginally improve system performance under sparse and variable spatio-temporal demand. The case study also highlights potentially large travel time and user reliability improvements—reductions of 51% and 53.8%, respectively—when trip requests were made in advance of their desired pickup time. Finally, we show that travel time reliability can be improved for time-inflexible trips with trip prioritization without increasing total user costs. These results were stable to changes in demand density.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1976

Results of an investigation of Reynolds effects on integrated vehicle elevon hinge moments and wing panel loads obtained with 0.010 scale model 72 OTS in the Rockwell trisonic wind tunnel (IA141)

Wind tunnel investigations were conducted on an 0.010-scale representation of the VL70-000140C Integrated Space Shuttle Launch Vehicle. The primary test objective was to obtain Reynolds number effects on orbiter elevon hinge moments and wing bending/torsional moments. Launch vehicle aerodynamic force data were also recorded. The elevon hinge moments, wing bending/torsional moments, and vehicle force data were recorded over an angle of attack range of -6 deg to +6 deg, an angle of sideslip range of -6 deg to +6 deg, at Mach numbers of 0.6, 0.975, 1.05 and 1.25. The Reynolds number was varied from a minimum of 4.5 million/foot to a maximum of 11.5 million/foot. The complete integrated configuration was tested with the orbiter elevons set at 0 deg and deflected to 9 deg on the outboard elevon and 10 deg on the inboard elevon. Testing was conducted in the TWT 19.7% porous transonic test section with the model sting mounted through the orbiter base. All aerodynamic force data were obtained from internal strain gage balance located in the orbiter.

Mennell, R. C.↗

DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2012

Determination of Barometric Altimeter Errors for the Orion Exploration Flight Test-1 Entry

The Exploration Flight Test 1 (EFT-1) mission is the unmanned flight test for the upcoming Multi-Purpose Crew Vehicle (MPCV). During entry, the EFT-1 vehicle will trigger several Landing and Recovery System (LRS) events, such as parachute deployment, based on on-board altitude information. The primary altitude source is the filtered navigation solution updated with GPS measurement data. The vehicle also has three barometric altimeters that will be used to measure atmospheric pressure during entry. In the event that GPS data is not available during entry, the altitude derived from the barometric altimeter pressure will be used to trigger chute deployment for the drogues and main parachutes. Therefore it is important to understand the impact of error sources on the pressure measured by the barometric altimeters and on the altitude derived from that pressure. The error sources for the barometric altimeters are not independent, and many error sources result in bias in a specific direction. Therefore conventional error budget methods could not be applied. Instead, high fidelity Monte-Carlo simulation was performed and error bounds were determined based on the results of this analysis. Aerodynamic errors were the largest single contributor to the error budget for the barometric altimeters. The large errors drove a change to the altitude trigger setpoint for FBC jettison deploy.

Brown, Denise L.↗

DOE OSTI2025

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

2020 Annual Technology Baseline (ATB) Cost and Performance Data for Transportation Technologies

The 2020 Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. The Transportation ATB includes current and projected estimates through 2050 for light-duty vehicle technologies as well as conventional and alternative fuels. This excel files include vehicle, fuel, and joined vehicle and fuel data with calculated levelized cost and emission values associated with the 2020 Transportation ATB. NREL has also provided a Tableau workbook to further explore the data. A website documents this data at https://atb.nlr.gov .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

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↗

NASA NTRS1988

Aircraft and ground vehicle friction correlation test results obtained under winter runway conditions during joint FAA/NASA Runway Friction Program

Aircraft and ground vehicle friction data collected during the Joint FAA/NASA Runway Friction Program under winter runway conditions are discussed and test results are summarized. The relationship between the different ground vehicle friction measurements obtained on compacted snow- and ice-covered conditions is defined together with the correlation to aircraft tire friction performance under similar runway conditions.

Yager, Thomas J.↗