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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 721 records · Page 40

Thermal Modeling and Analysis of the Hurricane Imaging Radiometer (HIRad)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗

Modeling and Analysis of the Hurricane Imaging Radiometer (HIRAD)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗

Underwater Multi-Node Radio Communication Solutions for Planetary Exploration

The exploration of the presumably life harboring subsurface ocean of Europa will provide scientists with extensive new knowledge in the search for extraterrestrial life. A highly miniaturized payload is required to penetrate a narrow passage through the thick ice crust covering Europa's surface. Underwater wireless communications may be the most viable means of communication for such exploratory missions, accounting for size and weight restrictions. This presents a challenge to achieve satisfactory data rates and a range that permits autonomous underwater vehicles (AUVs) to communicate within their region of operation, as well as with a surface lander or orbiter. This work presents thorough prototype experimentation on an underwater communication system established between several nodes using RF signals. During an eight-week internship experience at NASA's Ames Research Center in September-October 2014, our team developed a Europa exploration mission concept, built representative hardware, and carried out tests to assess the feasibility of key aspects of the concept. Experiments demonstrating the viability of RF communication underwater comprised inspecting the effect of depth and horizontal distance on signal strength as well as the optimum positioning of antennas. To test the system's performance, two submersibles were designed and built. A commercially available remotely operated vehicle (ROV) was also modified and used as a main communication node. The two submersibles were wirelessly connected and accommodated sensors capable of characterizing water properties and equipped with 2.4 GHz, 1 mW transceivers to communicate the measured data. The communication procedure is that the main communication node requests the collected data from the two submersibles when in range and receives it instantly through RF. This work models what may take place during an actual mission to Europa. The developed mission concept involved a hybrid communication system consisting of acoustic and RF signals to enhance the capability of the nodes to communicate over greater distances. The AUVs will need to avoid obstacles and maneuver around to collect data based on predefined algorithms. Thus, they will be provided with two positioning systems; the inertial navigation system, backed with an acoustic positioning system to mitigate drift. The AUVs divide the ocean into planes and explore along circular paths increasing in diameter with depth. Moreover, they make use of miniaturized sensors to map the surrounding environment. In this paper, the ROV and the submersibles are described, along with sections explaining the mechanism of communication and the testing procedures conducted to yield results.

Europa↗

2.2.5.401 - Ocean Observing Prize

The Powering the Blue Economy: Ocean Observing Prize is a $2.4M contest that challenges innovators to develop solutions that integrate marine renewable energy with ocean observation platforms to revolutionize our ability to monitor, manage, and understand the ocean. Competitors are challenged to design, build, and test novel, wave-powered, self-charging autonomous underwater vehicle (AUV) systems that could be suitable for a 6-month deployment in the Atlantic Ocean to monitor hurricane formation. Through engagement with the end user ocean observing community, the team identified challenges in a lack of data on storm intensity, endangering coastal communities. This challenge could be addressed by collecting data before, during, and after a hurricane develops and strengthens at sea. Amassing this data, however, requires an ocean observing system that can be deployed at sea for long periods, waiting for approaching storms. To help solve this problem, competitors are working to integrate wave energy capture with AUV systems to collect this data, helping to better protect coastal communities from oncoming storms. Solutions developed through this prize aim to enable long-term collection of data before, during, and after a hurricane that will help better forecast storm intensity. The prize mechanism provides an environment to accelerate technology development for innovators and helps to improve awareness of marine energy and its ability to provide power to blue economy applications.

coastal communities↗

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗

A flight investigation of blade-section aerodynamics for a helicopter main rotor having 10-64C airfoil sections

Pressure data at 90 percent blade radius were obtained for a helicopter main rotor with 10-64C blade sections during flight. Concurrent measurements ere made of vehicle flight state, performance and some rotor loads. The test envelope included hover, level flight from about 65 to 162 knots, climb and descent, and collective fixed maneuvers. Good agreement is shown between some sets of airfoil pressure distributions obtained in flight and those from two-dimensional wind-tunnel tests or theoretical calculations.

Morris, C. E. K., Jr.↗

Autonomous support for microorganism research in space

A preliminary design for performing on-orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the COMmercial Experiment Transported (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with inflight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibration, and radiation are provided for environmental regulation and experimental data collection. Additional experiment data acquisition includes optical density measurement, microscopy, video, and file photography. Onboard full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.

Luttges, M. W.↗

Noise Exposure Maps of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection

Urban Air Mobility↗

Noise Exposure Map of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection. (To hear the voice please utilize the video uploaded to the record)

Urban Air Mobility↗

X-Ray Imagery as the Record of All Data of Interest in Hypervelocity Impact Fragment Studies

Laboratory study of hypervelocity spacecraft fragmentation has traditionally involved the collection and analysis of fragments that were caught in deceleration material surrounding the impact. This process has typically involved the disintegration of the catchment material either through chemical dissolution, or through physical excavation to recover the fragments. Due to the scale of the three impact tests—the Satellite Orbital Debris Characterization Impact Test (SOCIT), the DebriSat satellite impact test, and the DebrisLV launch vehicle impact test—the latter two using more than 12 cubic meters of polyurethane foam to capture the fragments, hese projects have used x-ray imagery to precisely locate and thus, to more efficiently extract fragments in the soft-catch material. Three years into the DebriSat fragment extraction process, a side study was initiated to explore what additional information could be discerned from the x-rays, with significant results. This study was instrumental to a rapid replacement and retooling as the project was forced to replace the x-ray system around which the extraction process had been based. The revised process continues to map the debris for extraction. The project has, in parallel, systematically addressed the limits/tolerances of what x-rays can reveal about size, shape, density, mass, velocity, energy, and deformation/damage of the fragment during the deceleration in the catchment material while replicating the original extraction mapping function. All of these features have been optimized or have sufficient understanding to characterize the basic factors that will define a complete data set extracted solely from x-ray imagery. It is an ideal time to develop such a process, with extracted fragments providing “ground truth” against image-only data, and abundant available imagery of the same fragments under both the prior and replacement x-ray technologies, which have several fundamentally different characteristics. This paper addresses the types and quality of hypervelocity fragmentation data that can be and has been extracted from x-rays. It further addresses the question of whether and under what circumstances future hypervelocity experiments can use x-ray methods to largely—or to completely—avoid the extraction process in recording all appropriate results. Lastly, this paper addresses lessons learned and how future efforts can be further optimized.

John B. Bacon↗

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Gorinevsky, Dimitry↗

How to Interactively Operate the Global Hawk UAS NOAA/NASA ENSO Payload, from Your Armchair, Five Thousand Kilometers Away

This paper will describe the information technologies developed by NASA and NOAA for the February 2016 Sensing Hazards with Operational Unmanned Technology (SHOUT) El Niño Southern Oscillation (ENSO) Campaign. The air vehicle is a NASA Global Hawk UAS, with a primary payload of four instruments, two developed by NASA, two developed by NOAA. The aircraft is based at the NASA Armstrong Flight Research Center, Edwards Air Force Base, California. The payload components are remotely operated by scientists at various facilities, and the data collected downloaded over satellite links in real time for analysis and collaboration. NOAA: Advanced Vertical Atmospheric Profiling System (AVAPS), developed by NCAR, which deploys dozens of dropsondes at altitudes up to 65,000 ft to collect high vertical resolution measurements of the temperature, pressure, relative humidity, and wind speed and direction. NASA: High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), a radar designed to examine the factors of storm intensity: formation, structure and intensification. NOAA: O3 Photometer (UAS-O3), designed specifically for autonomous, precise, and accurate O3 measurements in the upper troposphere and lower stratosphere (UT/LS). NASA JPL: High Altitude MMIC Sounding Radiometer (HAMSR), an atmospheric microwave temperature and humidity sounder instrument that looks at the microwave spectrum.

Southern Oscilliation↗

Wind Tunnel-Based Aerodynamic Model Identification for a Tilt-Wing, Distributed Electric Propulsion Aircraft

This paper describes the methodology used to develop a high-fidelity aerodynamic model for the Langley Aerodrome No. 8 (LA-8) tandem tilt-wing, distributed electric propulsion, vertical takeoff and landing aircraft. Electric vertical takeoff and landing (eVTOL) vehicle configurations exhibit aerodynamic characteristics of both fixed-wing and rotary-wing aircraft as well as complex vehicle-specific phenomena, such as propeller-wing interactions and high incidence angle propeller aerodynamics. Consequently, conventional aircraft aerodynamic modeling strategies require modification when applied to eVTOL aircraft. Two novel system identification-based approaches are used to develop an aerodynamic model for the LA-8 aircraft configuration using wind tunnel data collected with design of experiments techniques. The modeling strategies are compared by assessing their predictive performance for validation data acquired separately from the data used to identify the model and are shown to have sufficient predictive capability. Research findings are presented with a discussion of unique eVTOL aerodynamic modeling characteristics and practical strategies to inform future aerodynamic modeling efforts for eVTOL aircraft.

Urban Air Mobility↗

Sustainable Campus with PEV and Microgrid

Market penetration of electric vehicles (EVs) is gaining momentum, as is the move towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a significant portion of transportation energy use onto building electricity meters. Hence, integration strategies for energy-efficiency in buildings and transport sectors are of increasing importance. This paper focuses on a portion of that integration: the analysis of an optimal interaction of EVs with a building-serving transformer, and coupling it to a microgrid that includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang Technological University (NTU), Singapore campus. The system under study is the Laboratory of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy Management System (MG-EMS) project. The paper analyses three different case scenarios to estimate the number of EVs that can be supported by the building transformer serving LaCER. An approximation of the actual load data collected for the building into different time intervals is performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be supported by the transformer with and without the microgrid are analyzed. The numbers of possible EVs that can be charged at any given time under the three scenarios are also determined. The possibility of using EV fleet at NTU campus to achieve demand response capability and intermittent PV output leveling through vehicle to grid (V2G) technology and building energy management systems is also explored.

Singh, Reshma↗

1977 Baltimore Travel Survey

The Baltimore Travel Dataset—conducted by the U.S. Federal Highway Administration and the University of California, Berkeley—is a detailed survey of demographic characteristics and travel patterns for 967 households in Baltimore, Maryland. The survey was conducted in May and June of 1977. The original goal of the survey was to collect an “ideal” dataset for disaggregate travel demand analysis.

1Hz data↗

1993 Baltimore Household Travel Survey

The 1993 Baltimore Household Travel Survey is a detailed survey of demographic characteristics and travel patterns for 2,692 households in Baltimore, Maryland. The original goal of the survey was to collect an “ideal” dataset for disaggregate travel demand analysis.

1Hz data↗

Autonomous support for microorganism research in space

A preliminary design for performing on orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the Commercial Experiment Transporter (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with in-flight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibrations, and radiation are provided for environmental regulation and experimental data collection. Additional experimental data acquisition includes optical density measurement, microscopy, video, and film photography. On-board full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.

Fleet, Mary L.↗