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NASA NTRSDate not supplied

NASA and Advanced Air Mobility (AAM) National Campaign (NC) Tech Talk: Integrated Data Product

NASA Advanced Air Mobility (AAM) National Campaign has hosted multiple flight tests in a effort to promote public confidence and accelerate the realization of emerging aviation markets for passenger and cargo transportation in urban, suburban, rural, and regional environments. The goals and objectives for each flight test are intended to assess the performance of the vehicle’s capacity to operate safely, efficiently, and sustainably in urban areas. The Airspace Test and Infrastructure (ATI) team processes the flight data to evaluate the effectiveness of air vehicle and airspace management integration, while its analysis capabilities support the assessment of the efficacy of proposed vehicles and ground systems required to enable the vehicles’ operations. The ATI data services team creates many products from the data, first by transforming and merging the data into a single Integrated Data Product (IDP). This aligns data from many sources by time, so that, for example, the winds that impacted a flight can be aligned with its ground track and speed. A detailed IDP enables many types of statistical computation and visualizations that help researchers understand what transpired during the flight and how it can be explained. This Tech Talk will give an overview of the IDP process, including examples of the resulting products created by the data services team. It will also share an application that will allow participants to perform their own data analysis.

National Campaign, Advanced Air Mobility, Integrat↗

NASA NTRSDate not supplied

Status of Mars Retropropulsion Testing in the Langley Unitary Plan Wind Tunnel

Future Mars human landings will be enabled by a powered descent phase starting at supersonic conditions, something which has never been done before on a Mars mission. Significant aerosciences challenges exist due to jet interactions between the retrorocket engine plumes, freestream flow, and vehicle that will affect the aerodynamic behavior during powered descent. Historically, wind tunnel tests have been used to study the interactions with inert gas exhaust simulants in place of rocket engines. On the computational side, flowfield simulations have been completed at full-scale conditions, but the available ground and flight data are not appropriate for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles, due to insufficient data, dissimilar vehicle geometries, and disparate operating conditions. A wind tunnel test has been designed to begin addressing powered descent aerodynamics risks for large-scale human Mars entry concepts and to identify gaps in computational predictive capabilities. The test will be conducted in the NASA Langley Unitary Plan Wind Tunnel and is designed with improvements in model design and data products over past tests. The test campaign will be run using sub-scale model geometries derived from NASA powered descent reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry that generates higher unpowered lift. Both models have been fabricated and are ready for testing. The blunt model is equipped with the flexibility to examine the effects of nozzle pointing direction, number, location, size, and area ratio. The main measurements are heatshield aerodynamic interference forces and moments with a custom flow-through balance, discrete and distributed heatshield pressure, and high-speed flowfield visualization. This paper covers the test objectives, facility, models and instrumentation, and planned test matrix.

Mars↗

NASA NTRSDate not supplied

Status of Mars Retropropulsion Testing in the Langley Unitary Plan Wind Tunnel

Supersonic Retropropulsion↗

NASA NTRS1995

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

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

Wu, G. Gordon↗

NASA NTRS2016

Source Data Applicability Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system where it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for assigning uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide a case study example by translating Ground Benign (GB) and Ground Mobile (GM) to the Airborne Uninhabited Fighter (AUF) environment for three electronic components often found in space launch vehicle control systems. The classification method will be followed by uncertainty-importance routines to assess the need to for more applicable data to reduce uncertainty.

Al Hassan, Mohammad↗

NASA NTRSDate not supplied

LA-8 Computational Analysis and Validation Studies Using FlightStream

With the emerging market of Urban Air Mobility and the associated unique new flight vehicles with the capability of vertical takeoff and landing, design tools need to be calibrated to assist in the development of these new flight vehicle concepts. Distributed electric propulsion (DEP) covers these vehicles with high-energy flow from the array of motors, which leads to extensive propulsion/airframe interaction effects. With limited experimental data of vehicles using DEP and vehicle operation across a large range of angles of attack, including post-stall conditions, there is a lack of validated design tools to advance new vehicle concepts that have blown wings and operate in multiple flight modes. Although some CFD tools can handle the integration of multiple propulsors and unique geometries, the computational time with a full vehicle is extraordinary. FlightStream, a surface vorticity flow solver that can run in a fraction of the time of other CFD methods, has been evaluated using the Langley Aerodrome No. 8 (LA-8) vehicle as a test case. The LA-8 vehicle is a DEP tandem tilt-wing research vehicle that was designed, built, and tested at NASA Langley Research Center. The LA-8 design features both high-performance and high-technical risks aspects. The vehicle has gone through extensive design of experiments wind tunnel testing in the NASA Langley 12-Foot Low-Speed Wind Tunnel in order to capture all modes of operation. In addition, the LA-8 vehicle has undergone wind tunnel testing with and without propellers, which contributes to the validation of FlightStream for aerodynamic performance in blown and unblown wing cases. This study shows that FlightStream can produce trends and magnitudes of the lift and drag coefficients similar to the data collected from the wind tunnel testing of LA-8. The test cases were both blown and unblown wing cases and with and without high lift control surface deflections.

Steven Curtis Geuther↗

NASA NTRS1979

Electric and hybrid vehicles

Report characterizes state-of-the-art electric and hybrid (combined electric and heat engine) vehicles. Performance data for representative number of these vehicles were obtained from track and dynamometer tests. User experience information was obtained from fleet operators and individual owners of electric vehicles. Data on performance and physical characteristics of large number of vehicles were obtained from manufacturers and available literature.

Source record↗

NASA NTRS2003

Development and Flight Testing of an Autonomous Landing Gear Health-Monitoring System

Development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation; and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

NASA NTRS2002

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

NASA NTRS1975

ASTP (SA-210) Launch vehicle operational flight trajectory. Part 3: Final documentation

Trajectory data are presented for a nominal and two launch window trajectory simulations. These trajectories are designed to insert a manned Apollo spacecraft into a 150/167 km. (81/90 n. mi.) earth orbit inclined at 51.78 degrees for rendezvous with a Soyuz spacecraft, which will be orbiting at approximately 225 km. (121.5 n. mi.). The launch window allocation defined for this launch is 500 pounds of S-IVB stage propellant. The launch window opening trajectory simulation depicts the earliest launch time deviation from a planar flight launch which conforms to this constraint. The launch window closing trajectory simulation was developed for the more stringent Air Force Eastern Test Range (AFETR) flight azimuth restriction of 37.4 degrees east-of-north. These trajectories enclose a 12.09 minute launch window, pertinent features of which are provided in a tabulation. Planar flight data are included for mid-window reference.

Carter, A. B.↗

NASA NTRS2012

Onboard Sensor Data Qualification in Human-Rated Launch Vehicles

The avionics system software for human-rated launch vehicles requires an implementation approach that is robust to failures, especially the failure of sensors used to monitor vehicle conditions that might result in an abort determination. Sensor measurements provide the basis for operational decisions on human-rated launch vehicles. This data is often used to assess the health of system or subsystem components, to identify failures, and to take corrective action. An incorrect conclusion and/or response may result if the sensor itself provides faulty data, or if the data provided by the sensor has been corrupted. Operational decisions based on faulty sensor data have the potential to be catastrophic, resulting in loss of mission or loss of crew. To prevent these later situations from occurring, a Modular Architecture and Generalized Methodology for Sensor Data Qualification in Human-rated Launch Vehicles has been developed. Sensor Data Qualification (SDQ) is a set of algorithms that can be implemented in onboard flight software, and can be used to qualify data obtained from flight-critical sensors prior to the data being used by other flight software algorithms. Qualified data has been analyzed by SDQ and is determined to be a true representation of the sensed system state; that is, the sensor data is determined not to be corrupted by sensor faults or signal transmission faults. Sensor data can become corrupted by faults at any point in the signal path between the sensor and the flight computer. Qualifying the sensor data has the benefit of ensuring that erroneous data is identified and flagged before otherwise being used for operational decisions, thus increasing confidence in the response of the other flight software processes using the qualified data, and decreasing the probability of false alarms or missed detections.

Wong, Edmond↗

NASA NTRSDate not supplied

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗

NASA NTRS1975

Atmosphere Explorer set for launch

The Atmosphere Explorer-D (Explorer-54) is described which will explore in detail an area of the earth's outer atmosphere where important energy transfer, atomic and molecular processes, and chemical reactions occur that are critical to the heat balance of the atmosphere. Data are presented on the mission facts, launch vehicle operations, AE-D/Delta flight events, spacecraft description, scientific instruments, tracking, and data acquisition.

Source record↗

NASA NTRS1972

Atlas/Centaur-29 Intelsat 4 (F5), operations summary

Mission, launch operations, communications, and test operation are discussed for the Intelsat 4 satellite. These include mission objective and plan, launch vehicle and spacecraft descriptions, postlaunch operations, data acquisition, meteorological plan, and F-1 and F-0 day operations.

Source record↗

NASA NTRS2014

Stability and Control CFD Investigations of a Generic 53 Degree Swept UCAV Configuration

NATO STO Task Group AVT-201 on "Extended Assessment of Reliable Stability & Control Prediction Methods for NATO Air Vehicles" is studying various computational approaches to predict stability and control parameters for aircraft undergoing non-linear flight conditions. This paper contributes an assessment through correlations with wind tunnel data for the state of aerodynamic predictive capability of time-accurate RANS methodology on the group's focus configuration, a 53deg swept and twisted lambda wing UCAV, undergoing a variety of roll, pitch, and yaw motions. The vehicle aerodynamics is dominated by the complex non-linear physics of round leading-edge vortex flow separation. Correlations with experimental data are made for static longitudinal/lateral sweeps, and at varying frequencies of prescribed roll/pitch/yaw sinusoidal motion for the vehicle operating with and without control surfaces. The data and the derived understanding should prove useful to the AVT-201 team and other researchers who are developing techniques for augmenting flight simulation models from low-speed CFD predictions of aircraft traversing non-linear regions of a flight envelope.

Frink, Neal T.↗

NASA NTRS1998

Reusable Rocket Engine Operability Modeling and Analysis

This paper describes the methodology, model, input data, and analysis results of a reusable launch vehicle engine operability study conducted with the goal of supporting design from an operations perspective. Paralleling performance analyses in schedule and method, this requires the use of metrics in a validated operations model useful for design, sensitivity, and trade studies. Operations analysis in this view is one of several design functions. An operations concept was developed given an engine concept and the predicted operations and maintenance processes incorporated into simulation models. Historical operations data at a level of detail suitable to model objectives were collected, analyzed, and formatted for use with the models, the simulations were run, and results collected and presented. The input data used included scheduled and unscheduled timeline and resource information collected into a Space Transportation System (STS) Space Shuttle Main Engine (SSME) historical launch operations database. Results reflect upon the importance not only of reliable hardware but upon operations and corrective maintenance process improvements.

Christenson, R. L.↗

NASA NTRS2004

Exchange of Standardized Flight Dynamics Data

Spacecraft operations require the knowledge of the vehicle trajectory and attitude and also that of other spacecraft or natural bodies. This knowledge is normally provided by the Flight Dynamics teams of the different space organizations and, as very often spacecraft operations involve more than one organization, this information needs to be exchanged between Agencies. This is why the Navigation Working Group within the CCSDS (Consultative Committee for Space Data Systems), has been instituted with the task of establishing standards for the exchange of Flight Dynamics data. This exchange encompasses trajectory data, attitude data, and tracking data. The Navigation Working Group includes regular members and observers representing the participating Space Agencies. Currently the group includes representatives from CNES, DLR, ESA, NASA and JAXA. This Working Group meets twice per year in order to devise standardized language, methods, and formats for the description and exchange of Navigation data. Early versions of some of these standards have been used to support mutual tracking of ESA and NASA interplanetary spacecraft, especially during the arrival of the 2003 missions to Mars. This paper provides a summary of the activities carried out by the group, briefly outlines the current and envisioned standards, describes the tests and operational activities that have been performed using the standards, and lists and discusses the lessons learned from these activities.

standards↗

NASA NTRS2003

Development and Flight Testing of an Adaptable Vehicle Health-Monitoring Architecture

Development and testing of an adaptable wireless health-monitoring architecture for a vehicle fleet is presented. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained adaptable expert system. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate, and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear.

Woodard, Stanley E.↗