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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 217 records · Page 12

Reach performance while wearing the Space Shuttle launch and entry suit during exposure to launch accelerations

Crewmen aboard the Space Shuttle are subjected to accelerations during ascent (the powered flight phase of launch) which range up to +3 G(sub x). Despite having 33 missions and nine years experience, not to mention all the time spent in development prior to the first flight, no truly quantitative reach study wearing actual crew equipment, using actual Shuttle seats and restraints has ever been done. What little information exists on reach performance while under acceleration has been derived primarily from subjective comments gathered retrospectively from Shuttle flight crews during their post mission debrief. This lack of reach performance data has resulted in uncertainty regarding emergency procedures that can realistically be performed during and actual Shuttle ascent versus what is practiced in the ground-fixed and motion-based Shuttle Simulators. With the introduction on STS-26 of the current Shuttle escape system, the question of reach performance under launch accelerations was once again raised. The escape system's requirement that each crewman wear a Launch/Entry Suit (LES), parachute harness, and parachute were all anticipated to contribute to a further degradation of reach performance during Shuttle ascent accelerations. In order to answer the reach performance question in a quantitative way, a photogrammetric method was chosen so that the actual reach values and associated envelopes could be captured. This would allow quantitative assessment of potential task performance impact and identify areas where changes to our Shuttle ascent emergency procedures might be required. Also, such a set of reach values would be valid for any similar acceleration profile using the same crew equipment. Potential Space Station applications of this data include predicting reach performance during Assured Crew Return Vehicle (ACRV) operations.

Bagian, James P.↗

The X-33 range Operations Control Center

This paper describes the capabilities and features of the X-33 Range Operations Center at NASA Dryden Flight Research Center. All the unprocessed data will be collected and transmitted over fiber optic lines to the Lockheed Operations Control Center for real-time flight monitoring of the X-33 vehicle. By using the existing capabilities of the Western Aeronautical Test Range, the Range Operations Center will provide the ability to monitor all down-range tracking sites for the Extended Test Range systems. In addition to radar tracking and aircraft telemetry data, the Telemetry and Radar Acquisition and Processing System is being enhanced to acquire vehicle command data, differential Global Positioning System corrections and telemetry receiver signal level status. The Telemetry and Radar Acquisition Processing System provides the flexibility to satisfy all X-33 data processing requirements quickly and efficiently. Additionally, the Telemetry and Radar Acquisition Processing System will run a real-time link margin analysis program. The results of this model will be compared in real-time with actual flight data. The hardware and software concepts presented in this paper describe a method of merging all types of data into a common database for real-time display in the Range Operations Center in support of the X-33 program. All types of data will be processed for real-time analysis and display of the range system status to ensure public safety.

Shy, Karla S.↗

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS↗

Medical Telemetry

Telemetry is the process whereby physiological or other data is acquired by instruments, translated into radio signals and j sent to a receiving station where the signals are decoded and recorded. Extensively used in I space operations, it is finding new Earth applications, among them transmission of medical data between emergency vehicles and hospitals. For example, transmission of an electrocardiogram from an ambulance to a hospital enables a physician to read the telemetered EKG and advise ambulance attendants on emergency procedures. Central Medical Emergency Dispatch (CMED) operates as a regional emergency medical communications center for Cleveland, Ohio and Cuyahoga County. The CMED system includes radio and telephone communications from hospital-to-hospital and from ambulance-to-hospital, but for improved emergency life support CMED sought to add a county-wide telemetry capability. The problem was that there were only eight radio frequencies available for telemetry and there were more than 30 potential users in Cleveland alone. NASA's Lewis Research Center volunteered its expert assistance. The Center's engineers studied the systems of other telemetry using cities, surveyed area hospitals to assure compatibility of telemetry equipment, and advised what types of equipment would be needed in emergency vehicles and at the various hospitals. The Lewis plan suggested that CMED be designated the central coordinating agency for the Cuyahoga County system, monitoring all telemetry frequencies and, when requested, assigning one not in use or one to be used at a sufficient distance that it would create no interference problem.

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Remote Science at Sea With Remotely Operated Vehicles

Conducting sea-going ocean science no longer needs to be limited to the number of berths on a ship given that telecommunications, computing, and networking technologies onboard ships have become familiar mechanisms for expanding scientists’ reach from onshore. The oceanographic community routinely works with remotely operated vehicles (ROVs) and pilots to access real-time video and data from the deep sea, while onboard a ship. The extension of using an ROV and its host vessel’s live-streaming capabilities has been popularized for almost 3 decades as a telepresence technology. Telepresence-enabled vessels with ROVs have been employed for science, education, and outreach, giving a greater number of communities viewing access to ocean science. However, the slower development of technologies and social processes enabling sustained real-time involvement between scientists on-ship and onshore undermines the potential for broader access, which limits the possibility of increasing inclusivity and discoveries through a diversity of knowledge and capabilities. This article reviews ocean scientists’ use of telepresence for ROV-based deep-sea research and funded studies of telepresence capabilities. The authors summarize these studies findings and conditions that lead to defining the use of telepresence-enabled vessels for “remote science at sea.” Authors define remote science at sea as a type of ocean expedition, an additional capability, not a replacement for all practices by which scientists conduct ocean research. Remote science for ocean research is an expedition at-sea directed by a distributed science team working together from at least two locations (on-ship and onshore) to complete their science objectives for which primary data is acquired by robotic technologies, with connectivity supported by a high-bandwidth satellite and the telepresence-enabled ship’s technologies to support the science team actively engaged before, during, and after dives across worksites. The growth of productive ocean expeditions with remote science is met with social, technical, and logistical challenges that impede the ability of remote scientists to succeed. In this article, authors review telepresence-enabled ocean science, define and situate the adjoined model of remote science at sea, and some infrastructural, technological and social considerations for conducting and further developing remote science at sea.

marine technology↗

Evolution of Space Shuttle Range Safety Ascent Flight Envelope Design

For every space vehicle launch from the Eastern Range in Florida, the range user must provide specific Range Safety (RS) data products to the Air Force's 45th Space Wing in order to obtain flight plan approval. One of these data products is a set of RS ascent flight envelope trajectories that define the normal operating region of the vehicle during powered flight. With the Shuttle Program launching 135 manned missions over a 30-year period, 135 envelope sets were delivered to the range. During this time, the envelope methodology and design process evolved to support mission changes, maintain high data quality, and reduce costs. The purpose of this document is to outline the shuttle envelope design evolution and capture the lessons learned that could apply to future spaceflight endeavors.

Brewer, Joan↗

Comparison of forward fuselage to Space Shuttle Orbiter flight pressure data to wind tunnel and analytical results in the hypersonic Mach number range

The Space Transportation System (STS) test program is unique in that it combines flight testing with operational flights using the first operational orbital vehicle (OV-102). The Space Shuttle Orbiter was instrumented to obtain various types of flight data. The instrumentation, designated Development Flight Instrumentation (DFI) includes pressure transducers, thermocouples, calorimeters, and accelerometers. A comparison is conducted between orbiter DFI forward fuselage flight pressure data obtained from OV-102 during the STS-1 reentry, and ground facility data obtained utilizing a 0.04 scale Orbiter forebody model. The comparisons are used to validate the existing experimental data base, optimize the pressure modeling technique, and make possible the refinement of error analysis relative to both. The obtained results indicate, in general, good agreement between flight and ground-based data.

Bradley, P. F.↗

Flight Performance Handbook for Orbital Operations: Orbital Mechanics and Astrodynamics Formulae, Theorems, Techniques, and Applications

This handbook provides parametric data useful both to the space vehicle designer and mission analyst. It provides numerical and analytical relationships between missions and gross vehicle characteristics as a function of performance parameters. The effects of missile constraints and gross guidance limitations plus operational constraints such as launch site location, tracking net location, orbit visibility and mission on trajectory and orbit design parameters are exhibited. The influence of state-of- the-art applications of solar power as compared to future applications of nuclear power on orbit design parameters, such as eclipse time, are among the parameters included in the study. The principal aim, however, is in providing the analyst with useful parametric design information to cover the general area of earth satellite missions in the region of near-earth to cislunar space and beyond and from injection to atmospheric entry and controlled descent. The chapters are organized around the central idea of orbital operations in the 1961-1969 era with emphasis on parametric flight mechanics studies for ascent phase and parking orbits, transfer maneuvers, rendezvous maneuver, operational orbit considerations, and operational orbit control. The results are based almost entirely on the principles of flight and celestial mechanics. Numerous practical examples have been worked out in detail. This is especially important where it has been difficult or impossible to represent all possible variations of the parameters. The handbook contains analytical formulae and sufficient textual material to permit their proper use. The analytic methods consist of both exact and rapid, approximate methods. Scores of tables, working graphs and illustrations amplify the mathematical models which, together with important facts and data, cover the engineering and scientific applications of orbital mechanics. Each of the five major chapters are arranged to provide a rapid review of an entire astrodynamic subject. By the use of compact graphical and tabular presentation the full scope of the material is made available in an easy-to-use style. Throughout the volume the analyst is shown, by means of suitable introductions, notes, authoritative examples, and cross-references the vital interrelation of the various orbital mechanics topics in the general field of earth satellites and satellite rendezvous. The handbook is designed to give the analyst rapid, reliable access to the mathematics of orbital mechanics needed for virtually any working requirements.

Ambrosio, Alphonso↗

A Field-Deployable Wireless Data Acquisition System for Ground-Test Arrays

This paper describes the development, characterization, and deployment of a field-deployable wireless data acquisition system for ground-test arrays, applicable in noise-source localization or beamforming measurements such as those encountered during airframe noise flyover measurement tests. The system design is enabled by commercially available, low-power Internet of Things (IoT) processors and Wi-Fi communication components. Time is synchronized across the array wirelessly by leveraging the Coordinated Universal Time (UTC) time provided by the Global Positioning System (GPS). Initial laboratory characterization of the system demonstrated its ability to meet acoustic bandwidth, dynamic range, time synchronization, environmental, and battery life requirements for typical ground-test array deployments. A successful system deployment at NASA Langley was performed that included measurement of a suspended elevated static noise source, and Uncrewed Aerial System (UAS) vehicle measurements using a quadcopter operated both in hover mode and forward flight. Beamform analysis of the acquired data showed an excellent ability of the array to extract accurate sound pressure levels from the suspended source. Synchronization of the array and vehicle GPS timecodes allowed the ability to extract acoustic signatures from the UAS vehicle during hover and forward flight maneuvers over the array. These results validate that the use of a high channel count wireless array is advantageous in airframe and propulsion noise flyover test campaigns.

wireless↗

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗

The Weather Analysis Display (WAND) Tool: Developing a Meteorological Data Display Tool for Situational Awareness During Day-Of-Launch of Space Launch Vehicles Using Python

Atmospheric conditions are an important driver in the design and operation of space launch vehicles. The Profile Envision and Splicing Tool (PRESTO) was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) to generate vertically complete atmospheric profiles from various data sources at NASA’s Kennedy Space Center (KSC), co-located on the United States Air Force (USAF) Eastern Range (ER), for NASA’s Space Launch System (SLS) day-of-launch (DOL) loads and trajectory analysis. PRESTO was designed solely to generate a vertically complete atmospheric profile (Orcutt et al., 2017). However, NE has also been tasked to provide a quality assessment of meteorological data examined on DOL, which goes beyond PRESTO’s utility. Thus, NE developed the Weather Analysis Display (WAND) to visualize data from all available observation systems in conjunction with climatological databases. WAND can display data from various sources in multiple ways, including Skew-T Log-P plots, time-height cross sections, and time series. WAND was developed in Python 3 taking advantage of common packages, such as NumPy for data handling, SciPy for mathematical functions, Matplotlib for data visualization, and Tkinter for the execution of the Graphical User Interface (GUI).

Orcutt, John M.↗

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Gundy-Burlet, Karen↗

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

Mariner Mars 1971 project. Volume 3: Mission operations system implementation and standard mission flight operations

The Mariner Mars 1971 mission which was another step in the continuing program of planetary exploration in search of evidence of exobiological activity, information on the origin and evolution of the solar system, and basic science data related to the study of planetary physics, geology, planetology, and cosmology is reported. The mission plan was designed for two spacecraft, each performing a separate but complementary mission. However, a single mission plan was actually used for Mariner 9 because of failure of the launch vehicle for the first spacecraft. The implementation is described, of the Mission Operations System, including organization, training, and data processing development and operations, and Mariner 9 spacecraft cruise and orbital operations through completion of the standard mission from launch to solar occultation in April 1972 are discussed.

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Raw_data_Batch_I: Downers Grove to Darien

Date of collection: May 11, 2023 Location: Downers Grove to Darien, IL This dataset contains lidar and vision data collected in Downers Grove and Darien, IL. The vehicle started in Downers Grove at the intersection of Main and Ogden, headed east. At the intersection of Odgen and IL 83, it then headed south until IL 33 and then west along IL 33 until the intersection of IL 33 and Lemont Road. It then headed north along Lemont Road/Main Street until the intersection of Main and Ogden. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![downers grove image](downers-grove-darien.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Space shuttle phase B. Volume 2: Technical summary, addendum A

A study was conducted to analyze the characteristics and performance data for the booster vehicles to be used with the space shuttle operations. It was determined that the single pressure-fed booster offered the lowest program cost per flight of the pressure-fed booster arrangements studied. The fly back booster required the highest peak annual funding and highest program cost. It was recommended that the pressure-fed booster, series burn with liquid oxygen phase, be continued for further study. The flyback booster study was discontinued. Both solid and liquid propelled booster vehicles with 14 by 45 foot and 15 by 60 foot payload orbiters were considered.

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