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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 955 records · Page 53

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design of the unmanned Multiple Exploratory Probe System (MEPS) for Mars observations

The unmanned Multiple Exploratory Probe System (MEPS) is designed for Mars observations in preparation for manned missions to the planet early in the 21st century. MEPS will test vehicle systems, provide important data about the Martian surface and atmosphere, and assist the planning of manned missions. This mission will be a precursor to the manned missions. MEPS will consist of six primary systems. A Command Information Center (CIC) will be employed as an onboard mission control, communications link, and observation post. The Space Transportation Main Engine (STME) will be used to provide the thrust for Earth-Mars transit following vehicle construction near the Space Station. A polar lander/Orbital Transfer Vehicle (OTV) will be deployed during transit to achieve a polar orbit about Mars. A secondary propulsion will be used to place MEPS into orbit about Mars; this system and the aerobrake will circularize the orbit. Following orbit circulation, a satellite will be deployed to observe the Martian surface and atmosphere and to study the space environment. Polar and equatorial lander systems will land on Mars with rovers to collect surface and atmospheric samples while on-board laboratories will provide initial sample study. Two solid rocket booster/payload vehicles will launch samples into a low Mars orbit. The OTV will rendezvous with each payload capsule and then transfer the samples to Earth for hands-on observation.

Source record↗

An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

Shen, Xuehao↗

Data Compression Techniques for Advanced Space Transportation Systems

Advanced space transportation systems, including vehicle state of health systems, will produce large amounts of data which must be stored on board the vehicle and or transmitted to the ground and stored. The cost of storage or transmission of the data could be reduced if the number of bits required to represent the data is reduced by the use of data compression techniques. Most of the work done in this study was rather generic and could apply to many data compression systems, but the first application area to be considered was launch vehicle state of health telemetry systems. Both lossless and lossy compression techniques were considered in this study.

Bradley, William G.↗

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

Wu, G. Gordon↗

Automated Vehicle Multi-Object Tracking at Scale with CAN

Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen- sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve track- ing from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2020 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

A flight investigation of basic performance characteristics of a teetering-rotor attack helicopter

Flight data were obtained with an instrumented AH-16 helicopter having uninstrumented, standard main-rotor blades. The data are presented to facilitate the analysis of data taken when the same vehicle was flown with instrumented main-rotor blades built with new airfoils. Test results include data on performance, flight-state parameters, pitch-link loads and blade angles for level flight, descending turns and pull-ups. Flight test procedures and the effects of both trim variations and transient phenomena on the data are discussed.

Morris, C. E. K., Jr.↗

Digital Twin Technology for Aviation

As technology progresses, so have the tools for data visualization. This project presents a digital twin model of the San Francisco airport displaying a 10-minute window of historical flight data, visualizing the trajectory data of airplanes and vehicles in three dimensions. Multiple different cameras where implemented to fully utilize the 3D visualization. This is a 100:1 feet scale model created in Autodesk Maya, using the airport center as the origin and recalculating all coordinates accordingly featuring the airport, some surrounding buildings, and the bay. For this project, six different models of airplanes were modeled at a 50:1 feet scale with texturing to mimic real-world aircraft models along with certain airlines. The animation is driven through archived data captured from NASA’s Sherlock Open-Data Portal, cleaned of noisy data points, processed into useable data formats, and implemented into a Maya ASCII file of animation paths with the corresponding previously-stated airplane models attached all using Java based conversion program.

Aleksander Schade↗

Truck Platooning Performance with ADAS and Onboard Camera Data Describing Traffic Interactions

This project was part of the Characterizing Behaviors and Capabilities for Emerging Connected and Automated Vehicle Technologies, Sensors, and Connectivity project. The National Laboratory of the Rockies partnered with Cummins Inc. to collect data from Class 8 tractor trailer combinations in platoon (cooperative adaptive cruise control) operations on public roads in southern Indiana. Data collected include J1939 CAN bus, radar, intervehicle position, and video data. The video data could not be shared in the raw form, so they were processed to extract information on the other vehicles on the road, their relative positions, and intrusion events. This information was then columnized for modeling use and further enhanced by appending road information including road type, speed limit, altitude, and grade. The test route included free-flowing traffic, highway interchanges, and construction zones, as well as low-, medium-, and high-grade sections. Individual test conditions varied by day, with advanced driver-assistance system (ADAS) features engaged or disengaged and different combined vehicle masses tested in addition to uncontrolled variables such as weather and traffic interactions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Aerothermodynamic Testing of the Crew Exploration Vehicle in the LaRC 20-Inch Mach 6 and 31-Inch Mach 10 Tunnels

An experimental wind tunnel program is being conducted in support of a NASA wide effort to develop a Space Shuttle replacement and to support the Agency s long term objective of returning to the Moon and Mars. This report documents experimental measurements made on several scaled ceramic heat transfer models of the proposed Crew Exploration Vehicle Crew Module. The experimental data highlighted in this test report are to be used to assess numerical tools that will be used to generate the flight aerothermodynamic database. Global heat transfer images and heat transfer distributions were obtained over a range of freestream Reynolds numbers and angles of attack with the phosphor thermography technique. Heat transfer data were measured on the forebody and afterbody and were used to infer the heating on the vehicle as well as the boundary layer state on the forebody surface. Several model support configurations were assessed to minimize potential support interference. In addition, the ability of the global phosphor thermography method to provide quantitative heating measurements in the low temperature environment of the capsule base region was assessed. While naturally fully developed turbulent levels were not obtained on the forebody, the use of boundary layer trips generated fully developed turbulent flow. Laminar and turbulent computational results were shown to be in good agreement with the data. Backshell testing demonstrated the ability to obtain data in the low temperature region as well as demonstrating the lack of significant model support hardware influence on heating.

Berger, Karen T.↗

Aerothermodynamic Testing of the Crew Exploration Vehicle in the LaRC 20-Inch Mach 6 and 31-Inch Mach 10 Tunnels

An experimental wind tunnel program is being conducted in support of a NASA wide effort to develop a Space Shuttle replacement and to support the Agency s long term objective of returning to the Moon and Mars. This article documents experimental measurements made on several scaled ceramic heat transfer models of the proposed Crew Exploration Vehicle Crew Module. The experimental data highlighted in this article are to be used to assess numerical tools that will be used to generate the flight aerothermodynamic database. Global heat transfer images and heat transfer distributions were obtained over a range of freestream Reynolds numbers and angles of attack with the phosphor thermography technique. Heat transfer data were measured on the forebody and afterbody and were used to infer the heating on the vehicle as well as the boundary layer state on the forebody surface. Several model support configurations were assessed to minimize potential support interference. In addition, the ability of the global phosphor thermography method to provide quantitative heating measurements in the low temperature environment of the capsule base region was assessed. While naturally fully developed turbulent levels were not obtained on the forebody, the use of boundary layer trips generated fully developed turbulent flow. Laminar and turbulent computational results were shown to be in good agreement with the data. Backshell testing demonstrated the ability to obtain data in the low temperature region as well as demonstrating the lack of significant model support hardware influence on heating.

Berger, Karen T.↗

Hybrid Wing Body Configuration System Studies

The objective of this study was to develop a hybrid wing body (HWB) sizing and analysis capability, apply that capability to estimate the fuel burn potential for an HWB concept, and identify associated technology requirements. An advanced tube with wings concept was also developed for comparison purposes. NASA s Flight Optimization System (FLOPS) conceptual aircraft sizing and synthesis software was modified to enable the sizing and analysis of HWB concepts. The noncircular pressurized centerbody of the HWB concept was modeled, and several options were created for defining the outboard wing sections. Weight and drag estimation routines were modified to accommodate the unique aspects of an HWB configuration. The resulting capability was then utilized to model a proprietary Boeing blended wing body (BWB) concept for comparison purposes. FLOPS predicted approximately a 15 percent greater drag, mainly caused by differences in compressibility drag estimation, and approximately a 5 percent greater takeoff gross weight, mainly caused by the additional fuel required, as compared with the Boeing data. Next, a 777-like reference vehicle was modeled in FLOPS and calibrated to published Boeing performance data; the same mission definition was used to size an HWB in FLOPS. Advanced airframe and propulsion technology assumptions were applied to the HWB to develop an estimate for potential fuel burn savings from such a concept. The same technology assumptions, where applicable, were then applied to an advanced tube-with-wings concept. The HWB concept had a 39 percent lower block fuel burn than the reference vehicle and a 12 percent lower block fuel burn than the advanced tube-with-wings configuration. However, this fuel burn advantage is partially derived from assuming the high-risk technology of embedded engines with boundary-layer-ingesting inlets. The HWB concept does have the potential for significantly reduced noise as a result of the shielding advantages that are inherent with an over-body engine installation.

Nickol, Craig L.↗