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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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NASA NTRS1982

OSTA-1 lessons learned and recommendations for future payloads

Five remote sensing experiments, together with one air pollution and one bioengineering experiment, were incorporated into the first Space Shuttle scientific payload of the NASA Office of Space and Terrestrial Applications (OSTA-1). The instrument package, experimental procedures, and specialized personnel teams all performed satisfactorily. Attention is presently given to the lessons learned during the OSTA-1-incorporating mission, STS-2 of November 12, 1981. Payload test and integration teams should never take unfamiliar facilities for granted. Training, especially if it employs hands-on experience with full-scale mockups and mission simulations, is found to be highly effective. Ephemeris data is too important to trust to table-top calculators, since errors propagate in repeated calculations. Terminal access to an off-line computer is required.

Baldwin, R. R.↗

NASA NTRS1988

Application of pattern recognition techniques to the identification of aerospace acoustic sources

A pattern recognition system was developed that successfully recognizes simulated spectra of five different types of transportation noise sources. The system generates hyperplanes during a training stage to separate the classes and correctly classify unknown patterns in classification mode. A feature selector in the system reduces a large number of features to a smaller optimal set, maximizing performance and minimizing computation.

Fuller, Chris R.↗

NASA NTRS1989

Space station Simulation Computer System (SCS) study for NASA/MSFC. Volume 4: Conceptual design report

The Simulation Computer System (SCS) is the computer hardware, software, and workstations that will support the Payload Training Complex (PTC) at Marshall Space Flight Center (MSFC). The PTC will train the space station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. In the first step of this task, a methodology was developed to ensure that all relevant design dimensions were addressed, and that all feasible designs could be considered. The development effort yielded the following method for generating and comparing designs in task 4: (1) Extract SCS system requirements (functions) from the system specification; (2) Develop design evaluation criteria; (3) Identify system architectural dimensions relevant to SCS system designs; (4) Develop conceptual designs based on the system requirements and architectural dimensions identified in step 1 and step 3 above; (5) Evaluate the designs with respect to the design evaluation criteria developed in step 2 above. The results of the method detailed in the above 5 steps are discussed. The results of the task 4 work provide the set of designs which two or three candidate designs are to be selected by MSFC as input to task 5-refine SCS conceptual designs. The designs selected for refinement will be developed to a lower level of detail, and further analyses will be done to begin to determine the size and speed of the components required to implement these designs.

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NASA NTRS1989

Space station Simulation Computer System (SCS) study for NASA/MSFC. Volume 5: Study analysis report

The Simulation Computer System (SCS) is the computer hardware, software, and workstations that will support the Payload Training Complex (PTC) at the Marshall Space Flight Center (MSFC). The PTC will train the space station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be on-board the Freedom Space Station. The further analysis performed on the SCS study as part of task 2-Perform Studies and Parametric Analysis-of the SCS study contract is summarized. These analyses were performed to resolve open issues remaining after the completion of task 1, and the publishing of the SCS study issues report. The results of these studies provide inputs into SCS task 3-Develop and present SCS requirements, and SCS task 4-develop SCS conceptual designs. The purpose of these studies is to resolve the issues into usable requirements given the best available information at the time of the study. A list of all the SCS study issues is given.

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NASA NTRS1993

Space time neural networks for tether operations in space

A space shuttle flight scheduled for 1992 will attempt to prove the feasibility of operating tethered payloads in earth orbit. due to the interaction between the Earth's magnetic field and current pulsing through the tether, the tethered system may exhibit a circular transverse oscillation referred to as the 'skiprope' phenomenon. Effective damping of skiprope motion depends on rapid and accurate detection of skiprope magnitude and phase. Because of non-linear dynamic coupling, the satellite attitude behavior has characteristic oscillations during the skiprope motion. Since the satellite attitude motion has many other perturbations, the relationship between the skiprope parameters and attitude time history is very involved and non-linear. We propose a Space-Time Neural Network implementation for filtering satellite rate gyro data to rapidly detect and predict skiprope magnitude and phase. Training and testing of the skiprope detection system will be performed using a validated Orbital Operations Simulator and Space-Time Neural Network software developed in the Software Technology Branch at NASA's Lyndon B. Johnson Space Center.

Lea, Robert N.↗

NASA NTRS1992

Propellant production and useful materials: Hardware data from components and the systems

Research activities at the University of Arizona/NASA Space Engineering Research Center are described; the primary emphasis is on hardware development and operation. The research activities are all aimed toward introducing significant cost reductions through the utilization of resources locally available at extraterrestrial sites. The four logical aspects include lunar, Martian, support, and common technologies. These are described in turn. The hardware realizations are based upon sound scientific principles which are used to screen a host of interesting and novel concepts. Small scale feasibility studies are used as the screen to allow only the most promising concepts to proceed. Specific examples include: kg/day-class oxygen plant that uses CO2 as the feed stock, spent stream utilization to produce methane and 'higher' compounds (using hydrogen from a water electrolysis plant), separation of CO from the CO2, reduction of any iron bearing silicate (lunar soils), production of structural components, smart sensors and autonomous controls, and quantitative computer simulation of extraterrestrial plants. The most important feature of all this research continues to be the training of high-quality students for our future in space.

Ramohalli, Kumar↗

NASA NTRS1994

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

Spirkovska, Lilly↗

NASA NTRS1998

Using Neural Networks for Sensor Validation

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

Mattern, Duane L.↗

NASA NTRS2019

Airframe and Engine Icing

This is both a presented version of NASA's in-flight icing training aids, and a brief discussion of NASA Glenn's two icing-capable facilities that simulate the airframe and engine icing environments. This presentation has been adapted for a Kent State University Aviation Safety Day. The original version was developed in 2006 time frame, and has been presented to both pilots and engineers.

pilot↗

NASA NTRSDate not supplied

Aeroacoustic Characterization of Optimum Hovering Rotors using Artificial Neural Networks

This work illustrates the use of artificial neural network modeling in the aerodynamic and aeroacoustic characterization of optimum hovering rotors over a broad range of design and operating conditions. Design of Experiments was used to create input feature spaces over eight input factors: the number of rotor blades, rotor radius, rotor rotation rate, design thrust condition, collective pitch, airfoil camber, the location of maximum camber, and the airfoil thickness. A low-fidelity tool chain was then used at the discrete data points defined by the designed input feature spaces to analytically design optimum hovering rotors and simulate aerodynamic and aeroacoustic quantities. This allowed for the generation of data sets over which to train and test the artificial neural network prediction models. Prediction models were trained over the data sets for the actual thrust generated by the rotor, power loading, tonal thickness and loading noise at the fundamental blade passage frequency, and broadband self-noise at seventeen one-third octave bands between 1 kHz and 40 kHz. These prediction models were validated by testing over data previously unseen by the models to quantify their capability for generalization to new data within the design feature space. The models were then used to study the effect each input feature had on the aeroacoustics and aerodynamics of optimum hovering rotors and physical insights were concluded to further explain the effect of each input. This characterization study showed that tonal noise and power loading were most sensitive to the number of rotor blades and the rotor rotation rate and that broadband noise was most sensitive to collective pitch and the design thrust condition.

Christopher S Thurman↗

NASA NTRSDate not supplied

Earth Entry System Atmosphere Model Study

The Mars Sample Return Campaign has the ambitious goal of returning Mars samples back to Earth [1]. The Earth Entry System (EES), containing the samples, conducts entry, descent, and landing (EDL) on a direct Earth trajectory. During EDL, the EES traverses through many regions of Earth’s atmosphere before impacting the ground at Utah Test and Training Range (UTTR). This poster highlights preliminary results from a study that assessed the flight mechanics simulation sensitivity to atmosphere model settings and investigated the validity of current atmosphere models as compared to available atmospheric data measurements.

Rohan Deshmukh↗

NASA NTRSDate not supplied

Examining the Relationship between Self-Reported Workload and Resilient Performance in Airline Flight Crews

Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.

Michael Stewart↗

NASA NTRSDate not supplied

Examining the Relationship Between Workload and Resilient Performance in Airline Flight Crews

Michael Stewart↗

NASA NTRSDate not supplied

Modeling and Simulation Efforts to Support Improved Comfort in ARGOS

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch, and here we present preliminary modeling of that device using the open-source biomechanical tool OpenSim [1,2] with an in-house developed plugin. We analyze a series of motions performed by a single shirt-sleeved subject with goals of characterizing the device, validating the model, and predicting whether reduced gravity conditions (i.e., lunar gravity (Lg) or Martian gravity (Mg)) can be accurately simulated with the device, as well as providing comfort to the ARGOS user. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are either obtained from (1) inverse kinematics (IK) using motion capture markers on the various components of the device or (2) calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. Given the joint angles of the device, the resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) in order to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data and the forces from manual measurements of the spring both independently and integrated within the device. We found that calculated joint angles generally represent the angles measured and computed with IK, supporting a possible analysis workflow inputting human motion data and observing system behavior under varied design parameters. In two different device configurations in which the maximum applied force was 131 N, our current model accurately captured force with a difference of 2-3 N from measured loads. Though our initial test was performed with a shirt-sleeve subject, arm weights were added to emulate the weight of the suit sleeve and the subject was positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup. Arm range of motion tasks were performed outside of the HUT, inside the HUT, and inside the HUT while using the device. A variety of other upper body tasks were completed as well. In summary, we have developed a model to investigate and verify an upper limb offload device currently in development. We believe this model will be a valuable tool not only for device characterization but also to predict proper configurations to simulate Lg or Mg conditions, investigate range of motion concerns, predict limitations such as internal collisions and contacts, and inform future design improvements.

L B Nilsson↗

NASA NTRS1991

Use of simulated neural networks of aerial image classification

The utility of one layer neural network in aerial image classification is examined. The network was trained with the delta rule. This method was shown to be useful as a classifier in aerial images with good resolution. It is fast, it is easy to implement, because it is distribution-free, nothing about statistical distribution of the data is needed, and it is very efficient as a boundary detector.

Medina, Frances I.↗

NASA NTRS1992

An evaluation of training effectiveness of an intelligent tutoring system

The study evaluated the training effectiveness of an intelligent tutoring system (ITS) for the Remote Manipulator System (RMS). The study examined how well individuals learn the training content and skills from the RMS ITS and to what extent the content and skills learned using the ITS transfer to RMS task performance in the SES, a high fidelity simulator. Three astronauts completed 8 2-hour ITS sessions addressing movement in three coordinate systems, grapple, ungrapple, berth, and unberth procedures, and singularities and reach limits. Their performance was also observed in an SES training session. Performance data were collected using multiple measures: ITS task performance, transfer performance on the SES, a conceptual knowledge test, an opinion survey completed by astronauts, and comments and observations from astronauts and trainers. Results indicated the RMS ITS to be moderately effective and provided evidence of the efficacy of ITS's, in general. Comments and suggestions are provided relating to how the ITS could be improved and to enable decision makers to judge the effectiveness of the RMS ITS.

Johnson, Debra Steele↗

NASA NTRS1987

Cockpit resource management training at People Express

In January 1986 in a continuing effort to maintain and improve flight safety and solve some Cockpit Resource Management (CRM) problems, People Express implemented a new CRM training program. It is a continuously running program, scheduled over the next three years and includes state-of-the-art full-mission simulation (LOFT), semi-annual seminar workshops and a comprehensive academic program authored by Robert W. Mudge of Cockpit Management Resources Inc. That program is outlined and to maximize its contribution to the workshop's goals, is organized into four topic areas: (1) Program content: the essential elements of resource management training; (2) Training methods: the strengths and weaknesses of current approaches; (3) Implementation: the implementation of CRM training; and (4) Effectiveness: the effectiveness of training. It is confined as much as possible to concise descriptions of the program's basic components. Brief discussions of rationale are included, however no attempt is made to discuss or review popular CRM tenets or the supporting research.

Bruce, Keith D.↗

NASA NTRS1986

Simulation studies of alternate longitudinal control systems for the space shuttle orbiter in the landing regime

Simulations of the space shuttle orbiter in the landing task were conducted by the NASA Ames-Dryden Flight Research Facility using the Ames Research Center vertical motion simulator (VMS) and the total in-flight simulator (TIFS) variable-stability aircraft. Several new control systems designed to improve the orbiter longitudinal response characteristics were investigated. These systems improved the flightpath response by increasing the amount of pitch-rate overshoot. Reduction in the overall time delay was also investigated. During these evaluations, different preferences were noted for the baseline or the new systems depending on the pilot background. The trained astronauts were quite proficient with the baseline system and found the new systems to be less desirable than the baseline. On the other hand, the pilots without extensive flight training with the orbiter had a strong preference for the new systems. This paper presents the results of the VMS and TIFS simulations. A hypothesis is presented regarding the control strategies of the two pilot groups and how this influenced their control systems preferences. Interpretations of these control strategies are made in terms of open-loop aircraft response characteristics as well as pilot-vehicle closed-loop characteristics.

Powers, B. G.↗