SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Graphical data is presented for Type 1 ballistic transfers to Jupiter (1974 to 1986), Saturn (1976 to 1986) and Uranus (1985). There are four graphs for each launch opportunity, namely the hyperbolic excess speed at earth departure, the hyperbolic excess speed at planet arrival, the declination of the hyperbolic departure asymptote, and the declination of the hyperbolic approach asymptote.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Trajectory determination from optical and radar data of spacecraft
Data return advantages of earth-Mars-earth flyby trajectories over more conventional Mars trajectories
Determination of spacecraft orbits by trajectory measurement data
Trajectory and photochemical model calculations based on retrospective meteorological data for the operations areas of the NASA Pacific Exploratory Mission (PEM)-West mission are summarized. The trajectory climatology discussed here is intended to provide guidance for flight planning and initial data interpretation during the field phase of the expedition by indicating the most probable path air parcels are likely to take to reach various points in the area. The photochemical model calculations which are discussed indicate the sensitivity of the chemical environment to various initial chemical concentrations and to conditions along the trajectory. In the post-expedition analysis these calculations will be used to provide a climatological context for the meteorological conditions which are encountered in the field.
One approach to qualitative reasoning about dynamical systems is to extract qualitative information by searching or making queries on databases containing very large numbers of trajectories. The efficiency of such queries depends crucially upon finding an appropriate data structure for trajectories of dynamical systems. Suppose that a large number of parameterized trajectories gamma of a dynamical system evolving in R sup N are stored in a database. Let Eta is contained in set R sup N denote a parameterized path in Euclidean Space, and let the Euclidean Norm denote a norm on the space of paths. A data structure is defined to represent trajectories of dynamical systems, and an algorithm is sketched which answers queries.
This research program has dealt with two projects in the field of planetary atmosphere dynamics and radiative energy transfer, one theoretical and one experimental. The first project, in radiative energy transfer, incorporated the capability to isolate and quantify the contribution of individual atmospheric components to the Venus radiative balance and thermal structure to greatly improve the current understanding of the radiative processes occurring within the Venus atmosphere. This is possible by varying the mixing ratios of each gas species, and the location, number density and aerosol size distributions of the clouds. This project was a continuation of the work initiated under a 1992 University Consortium Agreement. Under the just completed grant, work has continued on the use of a convolution-based algorithm that provided the capability to calculate the k coefficients of a gas mixture at different temperatures, pressures and spectral intervals from the separate k-distributions of the individual gas species. The second primary goal of this research dealt with the Doppler wind retrieval for the Successful Galileo Jupiter probe mission in December, 1995. In anticipation of the arrival of Galileo at Jupiter, software development continued to read the radioscience and probe/orbiter trajectory data provided by the Galileo project and required for Jupiter zonal wind measurements. Sample experiment radioscience data records and probe/orbiter trajectory data files provided by the Galileo Radioscience and Navigation teams at the Jet Propulsion Laboratory, respectively, were used for the first phase of the software development. The software to read the necessary data records was completed in 1995. The procedure by which the wind retrieval takes place begins with initial consistency checks of the raw data, preliminary data reductions, wind recoveries, iterative reconstruction of the probe descent profile, and refined wind recoveries. At each stage of the wind recovery consistency is checked and maintained between the orbiter navigational data, the radioscience data, and the probe descent profile derived by the Atmospheric Instrument Team. Preliminary results show that the zonal winds at Jupiter increase with depth to approximately 150 m/s.
The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012.
Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.
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.
The trajectories of the wing tip vortices of a typical agricultural aircraft were experimentally determined by flight test. A flow visualization method, similar to the vapor screen method used in wind tunnels, was used to obtain trajectory data for a range of flight speeds, airplane configurations, and wing loadings. Detailed measurements of the spanwise surface pressure distribution were made for all test points. Further, a powered 1/8 scale model of the aircraft was designed, built, and used to obtain tip vortex trajectory data under conditions similar to that of the full scale test. The effects of light wind on the vortices were demonstrated, and the interaction of the flap vortex and the tip vortex was clearly shown in photographs and plotted trajectory data.
The trajectories of the wing tip vortices of a typical agricultural aircraft were experimentally determined by flight test. A flow visualization method, similar to the vapor screen method used in wind tunnels, was used to obtain trajectory data for a range of flight speeds, airplane configurations, and wing loadings. Detailed measurements of the spanwise surface pressure distribution were made for all test points. Further, a powered 1/8 scale model of the aircraft was designed, built, and used to obtain tip vortex trajectory data under conditions similar to that of the full-scale test. The effects of light wind on the vortices were demonstrated, and the interaction of the flap vortex and the tip vortex was clearly shown in photographs and plotted trajectory data.
NASA s ARES I-X vehicle launched on a suborbital test flight from the Eastern Range in Florida on October 28, 2009. NASA generated a Range Safety (RS) flight data package to meet the RS trajectory data requirements defined in the Air Force Space Command Manual 91-710. Some products included in the flight data package were a nominal ascent trajectory, ascent flight envelope trajectories, and malfunction turn trajectories. These data are used by the Air Force s 45th Space Wing (45SW) to ensure Eastern Range public safety and to make flight termination decisions on launch day. Due to the criticality of the RS data in regards to public safety and mission success, an independent validation and verification (IV&V) effort was undertaken to accompany the data generation analyses to ensure utmost data quality and correct adherence to requirements. Multiple NASA centers and contractor organizations were assigned specific products to IV&V. The data generation and IV&V work was coordinated through the Launch Constellation Range Safety Panel s Trajectory Working Group, which included members from the prime and IV&V organizations as well as the 45SW. As a result of the IV&V efforts, the RS product package was delivered with confidence that two independent organizations using separate simulation software generated data to meet the range requirements and yielded similar results. This document captures ARES I-X RS product IV&V analysis, including the methodology used to verify inputs, simulation, and output data for an RS product. Additionally a discussion of lessons learned is presented to capture advantages and disadvantages to the IV&V processes used.
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.
This is the first of three supplements to the Handbook of Mars Stopover Missions Using Venus Swingbys, Part 6 of NASA SP-35, Planetary Flight Handbook. NASA SP-35, Part 6, contains a general discussion, contour charts and related graphical information. Supplement B contains the tabular trajectory data for 30-day stopover time missions, and Supplement C contains the tabular trajectory data for 60-day stopover time missions.