Project - Lunar orbiter D
NASA information release of Lunar Orbiter D launching, including configurations, systems, mission, and Atlas Agena launch vehicle data
SATELLITE LAUNCHING↗
SEARCH · Engineering Papers
Results for “vehicle data”
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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Downloadable Dynamometer Database (D3): Public Test Data on Advanced-Technology Vehicles
Access to high-quality, independent vehicle test data is critical to advancing energy-efficient transportation research. The Downloadable Dynamometer Database (D3) is a public repository of dynamometer test data on advanced-technology vehicles, generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory and hosted by the Transportation and Power Systems Division. The database has been made available to support researchers, students, and professionals engaged in energy-efficient vehicle research, development, and education. A wide range of vehicle categories has been tested (i.e., alternative fuel vehicles, conventional gasoline and diesel vehicles, all-electric vehicles, hybrid electric vehicles, and plug-in hybrid electric vehicles), as well as various drive cycles and test conditions documented in the accompanying D3 user presentation. Stakeholders can select a vehicle type, identify a vehicle of interest, and download the associated test data for use in their own analyses. Data downloaded from D3 must be accompanied by the required attribution: "This data is from the Downloadable Dynamometer Database and was generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory." These data are critical to vehicle modeling, validation, technology assessment, and educational use.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Synthesizing a New Launch Vehicle Failure Probability Based on Historical Flight Data
New launch vehicles have historically had significantly higher failure probabilities in early flights than what has been predicted using Probabilistic Risk Assessment. Work on a new methodology originally started with ARES I-X and the Common Standards Working Group (CSWG) for range safety applications. CSWG consists of the Federal Aviation Administration (FAA), Air Force, and NASA. Historical launch vehicle data was viewed as the best predictor of success/failure for launches of new vehicles. A launch vehicle database was developed that includes all launches from 1980-2017 (both US and foreign). Entries to the database include: Vehicle by model type; Launch dates; Failure description; Failure Result (Loss Of Vehicle (LOV)/Loss Of Mission (LOM); Failure cause (when available); Vehicle designs (stages/engines/etc.)
Early flight risk↗
Understanding electric vehicle ownership using data fusion and spatial modeling
The global shift toward electric vehicles (EVs) for climate sustainability lacks comprehensive insights into the impact of the built environment on EV ownership, especially in varying spatial contexts. This study, focusing on New York State, integrates data fusion techniques across diverse datasets to examine the influence of socioeconomic and built environmental factors on EV ownership. The utilization of spatial regression models reveals consistent coefficient values, highlighting the robustness of the results, with the Spatial Lag model better at capturing spatial autocorrelation. Further, results underscore the significance of charging stations within a 10-mile radius, indicative of a preference for convenient charging options influencing EV ownership decisions. Factors like higher education levels, lower rental populations, and concentrations of older population align with increased EV ownership. Utilizing publicly available data offers a more accessible avenue for understanding EV ownership across regions, complementing traditional survey approaches.
33 ADVANCED PROPULSION SYSTEMS↗
Impact of battery cell imbalance on electric vehicle range
Due to manufacturing variation, battery cells often possess heterogeneous characteristics, leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge determines the useful life of battery pack, such variation can negatively impact the battery performance and electric vehicles range. Existing research has been focused on control design to mitigate cell imbalance. However, it is yet unclear how much impacts the cell imbalance can have on electric vehicle range. This paper closes this knowledge gap by using a simulation environment consisting of real-world driving speed data, vehicle longitudinal control, propulsion and vehicle dynamics, and cell level battery modeling. In particular, each battery cell is modeled as an equivalent circuit model, and variations among cell parameters are introduced to assess their impact on electric vehicles range and to identify the most influential parameter variations. Simulation results and analysis can be used to assist balancing control design and to benchmark control performance.
25 ENERGY STORAGE↗
Lunar Orbiter Flight Set for August
Lunar orbiter A - configuration, tasks, Atlas Agena launch vehicle, data acquisition and evaluation, and mission events
SPACECRAFT CONFIGURATION↗
Mass and Reliability System (MaRS)
The Safety and Mission Assurance (S&MA) Directorate is responsible for mitigating risk, providing system safety, and lowering risk for space programs from ground to space. The S&MA is divided into 4 divisions: The Space Exploration Division (NC), the International Space Station Division (NE), the Safety & Test Operations Division (NS), and the Quality and Flight Equipment Division (NT). The interns, myself and Arun Aruljothi, will be working with the Risk & Reliability Analysis Branch under the NC Division's. The mission of this division is to identify, characterize, diminish, and communicate risk by implementing an efficient and effective assurance model. The team utilizes Reliability and Maintainability (R&M) and Probabilistic Risk Assessment (PRA) to ensure decisions concerning risks are informed, vehicles are safe and reliable, and program/project requirements are realistic and realized. This project pertains to the Orion mission, so it is geared toward a long duration Human Space Flight Program(s). For space missions, payload is a critical concept; balancing what hardware can be replaced by components verse by Orbital Replacement Units (ORU) or subassemblies is key. For this effort a database was created that combines mass and reliability data, called Mass and Reliability System or MaRS. The U.S. International Space Station (ISS) components are used as reference parts in the MaRS database. Using ISS components as a platform is beneficial because of the historical context and the environment similarities to a space flight mission. MaRS uses a combination of systems: International Space Station PART for failure data, Vehicle Master Database (VMDB) for ORU & components, Maintenance & Analysis Data Set (MADS) for operation hours and other pertinent data, & Hardware History Retrieval System (HHRS) for unit weights. MaRS is populated using a Visual Basic Application. Once populated, the excel spreadsheet is comprised of information on ISS components including: operation hours, random/nonrandom failures, software/hardware failures, quantity, orbital replaceable units (ORU), date of placement, unit weight, frequency of part, etc. The motivation for creating such a database will be the development of a mass/reliability parametric model to estimate mass required for replacement parts. Once complete, engineers working on future space flight missions will have access a mean time to failures and on parts along with their mass, this will be used to make proper decisions for long duration space flight missions
Barnes, Sarah↗
Operations of the Optical Communications Demonstration for the Orion EM-2 Mission
The GSFC implementation of an Optical Communication System to demonstrate an operational optical communication link for Orion EM-2. It will serve as a base for providing an operational optical communications capability for future Orion missions. GSFC plans to maintain a development path for the optical communication flight terminal to allow commercialization and implementation on future Orion missions. The Orion optical module part of the optical communications flight terminal and its control electronics have a common architecture with the ILLUMA-T optical terminal provided by GSFC for use on the ISS. The plan is to flow data from Orion through the Optical Communication Fight Terminal to the Optical Communication Ground Terminal and reverse. NASA's Orion spacecraft is an exploratory vehicle designed for longer-duration flights beyond the Moon. Following Orion's Exploration Mission-1 (EM-1), during which the spacecraft will travel beyond the Moon, enter a distant retrograde orbit around the Moon and return to Earth unmanned, Exploration Mission-2 (EM-2) will see a crewed spacecraft complete a slightly different flight path. First crewed test flight of the Orion spacecraft, currently targeting a June 30, 2022 launch. The mission involves: One revolution in Low Earth Orbit (LEO) parking orbit to verify basic Orion systems functionality and deploy solar arrays. A single 42-hour Highly Elliptical Orbit (HEO) intermediate checkout orbit allows characterization of the Orion vehicle system performance prior to committing to a cis-lunar flight. Trans Lunar Injection (TLI) burn using Orion Service Module (SM) main engine, which sends Orion on a lunar flyby and free return. Skip reentry at lunar return velocities to splashdown off the coast of San Diego. Total mission duration is approximately 10 days. EM-2 is the first crewed mission of the Orion Spacecraft that crew brings more video up/downloads, file transfers, and real-time chats with family back home and high-rate communications enables live HD streaming for Crew conferences, Public Affairs Office (PAO) events, and significant mission events. Also still collecting vehicle data on numerous Orion subsystems via Development Flight Instrumentation (DFI) allows large data volume returns sooner for DFI and future science payloads, as opposed to waiting for end-of-mission. O2O is a demonstration of operational utility system tested as a Developmental Test Objective (DTO) and not required to meet mission requirements/success/ Flight Test Objectives (FTO). EM-2 architecture is as close to future mission operational architecture as possible.Orion subsystems (video, DFI, etc.) expected to generate ~250 GB of data in the first 24 hours of flight. Total data generated over the mission estimated to be more than 400 GBUsing S-Band alone, Orion limited to ~ 6GB of data downlink per day. Because of this limitation, Orion is planning to limit live video downlinks on EM-1 in order to downlink high priority fileswith 1 hour/day of Optical Communication, Orion could downlink ~6x more data per day (~ 36GB/day).The optical communication system is capable of multiple data rates up to at least 80 Mbps downlink for the transfer of Orion data to Earth while Orion is operating in the lunar vicinity.
Optical Communication↗
Spatial Transferability of Machine Learning Based Volume Estimation Models
High-quality traffic volume data is essential for efficient transportation planning and operations. However, such high-quality data is expensive to collect, owing primarily to the high capital cost of installing and maintaining continuous counting stations (CCSs). Recent availability of probe-based vehicle data offers a cost-effective solution for increasing the observability of traffic volumes. However, having ample ground truth traffic data is a prerequisite for developing robust volume estimation models. Though this might not be a big issue in many states, states with scarce CCS data might be able to benefit from robust volume estimation models developed in (adjacent) data-rich states. While there is a reasonable amount of spatial transferability research in the transportation domain, there is a dearth of knowledge on the spatial transferability of probe-based volume estimation models. To address this gap, this paper explores spatial transferability of volume estimation models developed from data in three states (Colorado, North Carolina, and Pennsylvania). Results indicate that it is extremely important to maintain temporal consistency when attempting spatial transferability of volume estimation models. It was also found that models trained on regions with lower peak traffic volumes will limit the performance of models transferred to states with higher peak hourly traffic volumes. Corroborating findings from existing spatial transferability research on other topics, it was found that a meta-model (developed using data from multiple states) performs better than volume estimation models developed within any one of the states.
ADVANCED PROPULSION SYSTEMS↗
Liquid and Solid Propulsion Systems Attributes - Unique, Common and Complementary
In this study, attributes are described for solid and liquid propulsion systems based on historical data. This study is not intended to compare liquid and solid propulsion system attributes, rather to present options for their use in various mission scenarios. US launch vehicle data from 1970 to 2008 was analyzed to assess solid and liquid propulsion development cost and schedule characteristics, performance features, and safety and mission success attributes. The study assessed historical trends for liquid and solid systems, and investigated implications of those trends. It was found that the two propulsion technologies have unique, common and complementary attributes that can be leveraged to meet mission requirements.
Cannon, James L.↗
Liftoff and Transition Aerodynamics of the Ares I (A106) Launch Vehicle
An investigation has been conducted in the NASA Langley Research Center 14- by 22- Foot Subsonic Wind Tunnel to obtain the liftoff and transition aerodynamics of the Ares I (A106) Crew Launch Vehicle. Data were obtained in free-air at angles of attack from 10 to 90 at various roll angles and at roll angles of 0 to 360 at various angles of attack. In addition, tower effects were assessed by testing with and without a mobile launcher/tower at all wind azimuth angles and at various model heights to simulate the rise of the vehicle as it clears the tower on launch. The free-air data will be used for low speed high angle of attack flight simulation and as a bridge to the low angle of attack ascent database (0.5 < Mach < 5.0) being developed with data from the Langley Unitary Plan Wind Tunnel and Boeing Polysonic Wind Tunnel. The Ares I Database Development Team will add incremental tower effects data to the free-air data to develop the database for tower clearance.
Capone, Francis J.↗
A linear stochastic model of the human operator
A linear stochastic model of the human operator is developed and applied to the problem of piloted control of an aircraft. The pilot and aircraft are modeled as linear time-invariant systems containing both process and measurement noise. The loop closure by the pilot is determined by formulating the problem as an optimal stochastic control problem. The solution to the optimal control problem yields not only the pilot's optimal control output which he uses to control the vehicle, but also the optimal combination of his observations of the vehicle states upon which the pilot bases his control. A method is presented so that, using experimental pilot vehicle data, the cost functional which is minimized in the optimal control problem will be numerically equal to the pilot rating that the pilot would associate with the given vehicle and task.
Durrett, J. C.↗
Measurement, analysis, and prediction of aircraft interior noise
Considerations of comfort of passengers and crew in light aircraft and helicopters indicate substantial benefits may be obtained by the reduction of interior noise levels. This paper discusses an ongoing research effort to reduce interior noise in such vehicles. Data from both field and laboratory studies for a light aircraft are presented. The laboratory data indicate that structural vibration is an efficient source of interior noise and should be considered in the reduction of interior noise. Flight data taken on a helicopter before and after installation of acoustic treatment demonstrate that over 30 dB of noise reduction can be obtained in certain portions of the spectra. However, subjective evaluations of the treated vehicle indicate that further reductions in interior noise are desirable. An existing interior noise prediction method which was developed for large jet transports was applied to study low-frequency noise in a light aircraft fuselage. The results indicate that improvements in the analytical model may be necessary for the prediction of interior noise of light aircraft.
Howlett, J. T.↗
Harnessing the Power of AI: Status and Expansion of Current Domestic Transport Security Through Flexible Embedded Hardware
As applications of Artificial Intelligence (AI) continue to expand, there are increasing opportunities to leverage applied AI methodologies with mobile transportation focused embedded systems. Current applications of AI in transportation focus on a variety of areas, including fuel efficiency, safety, security, and other broad fields of optimization or detection. To leverage these AI workflows and methodologies in the field, teams must utilize complex embedded systems capable of implementing these AI-enabled algorithms in real-time. In this paper, we will investigate how these algorithms can be integrated into existing technologies leveraging vehicle data - such as the Controller Area Network Transport Security Tracking and Reporting Unit (C-STAR). The C-STAR technology is an embedded platform with onboard computation capable of running next generation algorithms in vehicle systems AI, such as preventative maintenance, driver authentication, and transport security. As deployed in the field, the C-STAR has a limited AI functionality –this paper will directly discuss how a device like C-STAR can be utilized and the advantages of integrating these new technologies. We will open with relevant background information and transportation projects that leverage AI, focusing specifically on those around transport security such as vehicle identification, anomaly detection, and deterrence. We will then extend this into potential opportunities and scaling for AI methodologies using platforms like the C-STAR. Finally, we will speak directly to the challenges of deploying AI-powered workflows, such as computing power needs, bandwidth, hallucinations, and other regulatory considerations.
Cook, Adian [ORNL] (ORCID:0000000160825395)↗
Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint
Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.
ADVANCED PROPULSION SYSTEMS↗
GEOS-2 refraction program summary document
Data from an extensive array of collocated instrumentation at the Wallops Island test facility were intercompared in order to (1) determine the practical achievable accuracy limitations of various tropospheric and ionospheric correction techniques; (2) examine the theoretical bases and derivation of improved refraction correction techniques; and (3) estimate internal systematic and random error levels of the various tracking stations. The GEOS 2 satellite was used as the target vehicle. Data were obtained regarding the ionospheric and tropospheric propagation errors, the theoretical and data analysis of which was documented in some 30 separate reports over the last 6 years. An overview of project results is presented.
Mallinckrodt, A. J.↗
Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System
Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.
ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
Development and Validation of Generic Maneuvering Flight Noise Abatement Guidance for Helicopters
An extensive flight test campaign has been conducted to look into developing actionable advice for pilots of today’s vehicles to reduce their acoustic footprints. Ten distinct vehicles were tested at three different test ranges, with nine of the vehicles’ data being documented here. Twelve pairs of turning conditions were tested to determine their effect on blade-vortex interaction noise. Each turning flight condition was evaluated using the peak A-weighted, band-limited (50 Hz - 2500 Hz), sound pressure level measured throughout the maneuver. This metric was a surrogate for blade-vortex interaction noise, and the difference between the peak values of each turning pair was investigated. That peak value difference was subsequently corrected by the offset from the intended vehicle altitude at turn initiation from the actual altitude at initiation. The corrected amplitudes were investigated and grouped into six validated actionable guidance principles that can be given to pilots to immediately reduce their acoustic footprint during operations.
Flight Test↗