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At least 19 records

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

The Ares I-X modal test program consisted of three modal tests conducted at the Vehicle Assembly Building at NASA s Kennedy Space Center. The first test was performed on the 71-foot 53,000-pound top segment of the Ares I-X launch vehicle known as Super Stack 5 and the second test was performed on the 66-foot 146,000- pound middle segment known as Super Stack 1. For these tests, two 250 lb-peak electro-dynamic shakers were used to excite bending and shell modes with the test articles resting on the floor. The third modal test was performed on the 327-foot 1,800,000-pound Ares I-X launch vehicle mounted to the Mobile Launcher Platform. The excitation for this test consisted of four 1000+ lb-peak hydraulic shakers arranged to excite the vehicle s cantilevered bending modes. Because the frequencies of interest for these modal tests ranged from 0.02 to 30 Hz, high sensitivity capacitive accelerometers were used. Excitation techniques included impact, burst random, pure random, and force controlled sine sweep. This paper provides the test details for the companion papers covering the Ares I-X finite element model calibration process. Topics to be discussed include test setups, procedures, measurements, data quality assessments, and consistency of modal parameter estimates.

Templeton, Justin D.↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Building a Quality Controlled Database of Meteorological Data from NASA Kennedy Space Center and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) has provided atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER complex is one of the most heavily instrumented sites in the United States with over 31 towers measuring various atmospheric parameters on a continuous basis. An inherent challenge with large sets of data consists of ensuring erroneous data is removed from databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments, however no standard QC procedures for all databases currently exists resulting in QC databases that have inconsistencies in variables, methodologies, and periods of record. The goal of this activity is to use the previous efforts by EV44 to develop a standardized set of QC procedures from which to build meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC procedures will be described. As the rate of launches increases with additional launch vehicle programs, it is becoming more important that weather databases are continually updated and checked for data quality before use in launch vehicle design and certification analyses.

Brenton, James C.↗

Building a QC Database of Meteorological Data From NASA KSC and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) has provided atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER is one of the most heavily instrumented sites in the United States measuring various atmospheric parameters on a continuous basis. An inherent challenge with the large databases that EV44 receives from the ER consists of ensuring erroneous data are removed from the databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments; however, no standard QC procedures for all databases currently exist resulting in QC databases that have inconsistencies in variables, methodologies, and periods of record. The goal of this activity is to use the previous efforts by EV44 to develop a standardized set of QC procedures from which to build flags within the meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC checks are described. The flagged data points will be plotted in a graphical user interface (GUI) as part of a manual confirmation that the flagged data do indeed need to be removed from the archive. As the rate of launches increases with additional launch vehicle programs, more emphasis is being placed to continually update and check weather databases for data quality before use in launch vehicle design and certification analyses.

Brenton, James C.↗

Building a QC Database of Meteorological Data from NASA KSC and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) provides atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER complex is one of the most heavily instrumented sites in the United States with over 31 towers measuring various atmospheric parameters on a continuous basis. An inherent challenge with large datasets consists of ensuring erroneous data are removed from databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments, however no standard QC procedures for all databases currently exists resulting in QC databases that have inconsistencies in variables, development methodologies, and periods of record. The goal of this activity is to use the previous efforts to develop a standardized set of QC procedures from which to build meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC procedures will be described. As the rate of launches increases with additional launch vehicle programs, It is becoming more important that weather databases are continually updated and checked for data quality before use in launch vehicle design and certification analyses.

Brenton, J. C.↗

Exploratory piloted simulator study of the effects of winglets on handling qualities of a representative agricultural airplane

The effects on handling qualities of adding winglets to a representative agricultural aircraft configuration during swath-run maneuvering were evaluated. Aerodynamic data used in the simulation were based on low-speed wind tunnel tests of a full scale airplane and a subscale model. The Cooper-Harper handling qualities rating scale, supplementary pilot comments, and pilot vehicle performance data were used to describe the handling qualities of the airplane with the different wing-tip configurations. Results showed that the lateral-directional handling qualities of the airplane were greatly affected by the application of winglets and winglet cant angle. The airplane with winglets canted out 20 deg exhibited severely degraded lateral directional handling qualities in comparison to the basic airplane. When the winglets were canted inward 10 deg, the flying qualities of the configuration were markedly improved over those of the winglet-canted-out configuration or the basic configuration without winglets, indicating that proper tailoring of the winglet design may afford a potential benefit in the area of handling qualities.

Ogburn, M. E.↗

Stall/spin flight results for the remotely piloted spin research vehicle

The unmanned, remotely piloted, unpowered, spin research vehicle was used to evaluate the effects of the nose boom and of a wind tunnel-designed nose strake on the vehicle's stall/spin characteristics. The flight-determined directional stability derivatives and the attempted spin entries indicated that the vehicle with a nose strake had increased resistance to departure and spin. The acquisition of high quality steady spin data for this vehicle was made possible by the remotely piloted technique. The zero control smooth spin modes were found to be highly repeatable for a given configuration and to vary with forebody configuration. Several spin recovery techniques, including a nose parachute, are also evaluated.

Iliff, K. W.↗

Orion Handling Qualities During ISS Rendezvous and Docking

The Orion spacecraft was designed to rendezvous with multiple vehicles in low earth orbit (LEO) and beyond. To perform the required rendezvous and docking task, Orion must provide enough control authority to perform coarse translational maneuvers while maintaining precision to perform the delicate docking corrections. While Orion has autonomous docking capabilities, it is expected that final approach and docking operations with the International Space Station (ISS) will initially be performed in a manual mode. A series of evaluations was conducted by NASA and Lockheed Martin at the Johnson Space Center to determine the handling qualities (HQ) of the Orion spacecraft during different docking and rendezvous conditions using the Cooper-Harper scale. This paper will address the specifics of the handling qualities methodology, vehicle configuration, scenarios flown, data collection tools, and subject ratings and comments. The initial Orion HQ assessment examined Orion docking to the ISS. This scenario demonstrates the Translational Hand Controller (THC) handling qualities of Orion. During this initial assessment, two different scenarios were evaluated. The first was a nominal docking approach to a stable ISS, with Orion initializing with relative position dispersions and a closing rate of approximately 0.1 ft/sec. The second docking scenario was identical to the first, except the attitude motion of the ISS was modeled to simulate a stress case ( 1 degree deadband per axis and 0.01 deg/sec rate deadband per axis). For both scenarios, subjects started each run on final approach at a docking port-to-port range of 20 ft. Subjects used the THC in pulse mode with cues from the docking camera image, window views, and range and range rate data displayed on the Orion display units. As in the actual design, the attitude of the Orion vehicle was held by the automated flight control system at 0.5 degree deadband per axis. Several error sources were modeled including Reaction Control System (RCS) jet angular and position misalignment, RCS thrust magnitude uncertainty, RCS jet force direction uncertainty due to self plume impingement, and Orion center of mass uncertainty.

Hart, Jeremy J.↗

Evaluation of Heave Disturbance Rejection and Control Response Criteria on the Handling Qualities Evaluation of Urban Air Mobility (UAM) eVTOL Quadrotors Using the Vertical Motion Simulator

The first piloted handling qualities study of an urban air mobility (UAM) vehicle leveraging the Vertical Motion Simulator (VMS) at NASA Ames Research Center was conducted in Spring 2021. The VMS provides a unique capability to reduce risk by assessing and iterating control designs. Minimal sources currently exist to provide performance and handling qualities data for large, rotor speed-controlled vehicles outside of the software environment. The study compares multiple handling qualities performance configurations for rotor speed and blade pitch-controlled variants of a six-passenger quadrotor conceptual design model developed by the NASA Revolutionary Vertical Lift Technology (RVLT) Project. Additionally, both ADS-33 and a tailored set of performance standards (notionally representing the agility required of a UAM mission) are examined under conditions with and without light turbulence. Preliminary results did show significant variation in ratings based on the set of standards utilized, controller tuning to either Level 1 or boundary Level 1/ Level 2 conditions, and presence or lack of turbulence. A custom approach and landing maneuver was also designed to bring these evaluation tasks together in a more comprehensive application.

Handling Qualities↗

NASA ride quality program at the Flight Research Center

A flight test program to determine the effects of low frequency vibrations on passengers in short haul aircraft is discussed. The objective of the program is to accumulate flight test data on aircraft ride quality in terms of vehicle motion and acceleration and human responses. The subjects discussed are: (1) test procedures, (2) data processing, and (3) the program schedule.

Gee, S. W.↗

Archive data base and handling system for the Orbiter flying qualities experiment program

The OFQ archives data base and handling system assembled as part of the Orbiter Flying Qualities (OFQ) research of the Orbiter Experiments Program (EOX) are described. The purpose of the OFQ archives is to preserve and document shuttle flight data relevant to vehicle dynamics, flight control, and flying qualities in a form that permits maximum use for qualified users. In their complete form, the OFQ archives contain descriptive text (general information about the flight, signal descriptions and units) as well as numerical time history data. Since the shuttle program is so complex, the official data base contains thousands of signals and very complex entries are required to obtain data. The OFQ archives are intended to provide flight phase oriented data subsets with relevant signals which are easily identified for flying qualities research.

Myers, T. T.↗

HiMAT flight program: Test results and program assessment overview

The Highly Manueverable Aircraft Technology (HiMAT) program consisted of design, fabrication of two subscale remotely piloted research vehicles (RPRVs), and flight test. This technical memorandum describes the vehicles and test approach. An overview of the flight test results and comparisons with the design predictions are presented. These comparisons are made on a single-discipline basis, so that aerodynamics, structures, flight controls, and propulsion controls are examined one by one. The interactions between the disciplines are then examined, with the conclusions that the integration of the various technologies contributed to total vehicle performance gains. An assessment is made of the subscale RPRV approach from the standpoint of research data quality and quantity, unmanned effects as compared with manned vehicles, complexity, and cost. It is concluded that the RPRV technique, as adopted in this program, resulted in a more complex and costly vehicle than expected but is reasonable when compared with alternate ways of obtaining comparable results.

Deets, Dwain A.↗

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

The Mars Science Laboratory (MSL) Entry, Descent And Landing Instrumentation (MEDLI): Hardware Performance and Data Reconstruction

The Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation (MEDLI) hardware was a first-of-its-kind sensor system that gathered temperature and pressure readings on the MSL heatshield during Mars entry on August 6, 2012. MEDLI began as challenging instrumentation problem, and has been a model of collaboration across multiple NASA organizations. After the culmination of almost 6 years of effort, the sensors performed extremely well, collecting data from before atmospheric interface through parachute deploy. This paper will summarize the history of the MEDLI project and hardware development, including key lessons learned that can apply to future instrumentation efforts. MEDLI returned an unprecedented amount of high-quality engineering data from a Mars entry vehicle. We will present the performance of the 3 sensor types: pressure, temperature, and isotherm tracking, as well as the performance of the custom-built sensor support electronics. A key component throughout the MEDLI project has been the ground testing and analysis effort required to understand the returned flight data. Although data analysis is ongoing through 2013, this paper will reveal some of the early findings on the aerothermodynamic environment that MSL encountered at Mars, the response of the heatshield material to that heating environment, and the aerodynamic performance of the entry vehicle. The MEDLI data results promise to challenge our engineering assumptions and revolutionize the way we account for margins in entry vehicle design.

Little, Alan↗

Space shuttle flying qualities and criteria assessment

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

Myers, T. T.↗

Computer analysis of railcar vibrations

Computer models and techniques for calculating railcar vibrations are discussed along with criteria for vehicle ride optimization. The effect on vibration of car body structural dynamics, suspension system parameters, vehicle geometry, and wheel and rail excitation are presented. Ride quality vibration data collected on the state-of-the-art car and standard light rail vehicle is compared to computer predictions. The results show that computer analysis of the vehicle can be performed for relatively low cost in short periods of time. The analysis permits optimization of the design as it progresses and minimizes the possibility of excessive vibration on production vehicles.

Vlaminck, R. R.↗

Augmenting the Space Environment Complex's Thermal Vacuum Capabilities for Artemis 1 Orion Spacecraft Testing

The Space Environments Complex at Glenn Research Center’s Neil A Armstrong Test Facility (formerly Plum Brook Station) recently successfully completed Artemis 1 thermal vacuum testing. The Space Environments Complex boasts the world’s largest thermal vacuum chamber with a 122-foot tall, 100-foot diameter aluminum assembly vacuum chamber. The fifty-year old chamber has been adapted over its history to conduct several unique test campaigns in a variety of test environments. Artemis 1 Orion spacecraft testing is the most complex test campaign the Space Environments Complex has undergone to date, with temperature limits between -250 F to +300F in a high vacuum with significant requirements for quality data and contamination control of a flight vehicle. This presentation covers the improvements and innovations in the cryoshroud and thermal systems, data acquisition, as well as contamination and cleanliness to accommodate the rigors of a flight vehicle during a six-week thermal vacuum test. Additionally, the presentation covers successes and lessons learned from the testing.

Erin Reed↗