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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Seamless Integration of Multibody and Orbital Dynamics to Support Human Spaceflight Simulations

At the NASA Johnson Space Center (JSC), modeling capability requirements are often driven by the need to simulate upcoming mission scenarios for analysis, procedures development, and training. In preparation for free-flyer vehicle capture, maneuvers, and release, it was determined that the multibody dynamics capabilities provided by MBDyn and the orbital dynamics capabilities supplied by JEOD needed to be merged to properly simulate the dynamic behaviors expected on-orbit. After initial attempts to combine the two packages proved cumbersome, it was decided that a more refined solution was required to facilitate the interface between these two packages. The resulting interface software package was named MBJEOD. The primary design goals for this new package were to leave MBDyn and JEOD untouched, to simplify and clarify simulation initialization for users, and to support any topology or on-orbit operational scenario that future missions might require. This paper provides a detailed overview of MBJEOD and the approach taken to seamlessly integrate the multibody dynamics of MBDyn with the orbital dynamics of JEOD. Additional attention is given to the numerical considerations required for MBJEOD and the simplifying assumptions leveraged to provide for real-time simulation needs. Verification and validation are addressed and current MBJEOD applications at the NASA JSC are discussed.

modeling↗
NASA NTRS2025

NASA Open Science Data Repository: Open Science for Life in Space

Space biology and health data are critical for the success of deep space missions and sustainable human presence off-world. At the core of effectively managing biomedical risks is the commitment to open science principles, which ensure that data are findable, accessible, interoperable, reusable, reproducible and maximally open. The 2021 integration of the Ames Life Sciences Data Archive with GeneLab to establish the NASA Open Science Data Repository significantly enhanced access to a wide range of life sciences, biomedical-clinical, and mission telemetry data alongside existing ‘omics data from GeneLab. This paper describes the new database, its architecture, and new data streams supporting diverse data types and enhancing data submission, retrieval, and analysis. Features include the Biological Data Management Environment for improved data submission, a new user interface, controlled data access, an enhanced API, and comprehensive public visualization tools for environmental telemetry, radiation dosimetry data, and ‘omics analyses. By fostering global collaboration through its Analysis Working Groups and training programs, the Open Science Data Repository promotes widespread engagement in space biology, ensuring transparency and inclusivity in research. It supports the global scientific community in advancing our understanding of spaceflight's impact on biological systems, ensuring humans will thrive in future deep space missions.

OSDR↗
NASA NTRS1993

A comparative robustness evaluation of feedforward neurofilters

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.

Troudet, Terry↗
NASA NTRS1973

Engineering analysis and test results of the pre-stage planetary gear trains for wrist rotation and pitch assembly and azimuth and elevation assembly of the extendable stiff arm manipulator kit assembly

In order to improve the performance capability of the Extendable Stiff Arm Manipulator (ESAM) it was necessary to increase the overall gear ratio by a factor of approximately four. This is accomplished with minimum effect to existing hardware by the interposition of a planetary gear transmission between the respective drive motors and the harmonic drive transmissions. The engineering analysis in support of this design approach and the subsequent no-load test results are reported.

Morris, R. N.↗
NASA NTRS1998

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗
NASA NTRS1999

In Vivo Noninvasive Analysis of Human Forearm Muscle Function and Fatigue: Applications to EVA Operations and Training Maneuvers

Forearm muscle fatigue is one of the major limiting factors affecting endurance during performance of deep-space extravehicular activity (EVA) by crew members. Magnetic resonance (MR) provides in vivo noninvasive analysis of tissue level metabolism and fluid exchange dynamics in exercised forearm muscles through the monitoring of proton magnetic resonance imaging (MRI) and phosphorus magnetic resonance spectroscopy (P-31-MRS) parameter variations. Using a space glove box and EVA simulation protocols, we conducted a preliminary MRS/MRI study in a small group of human test subjects during submaximal exercise and recovery and following exhaustive exercise. In assessing simulated EVA-related muscle fatigue and function, this pilot study revealed substantial changes in the MR image longitudinal relaxation times (T2) as an indicator of specific muscle activation and proton flux as well as changes in spectral phosphocreatine-to-phosphate (PCr/Pi) levels as a function of tissue bioenergetic potential.

Fotedar, L. K.↗
NASA NTRS1986

Design and dynamic simulation of a fixed pitch 56 kW wind turbine drive train with a continuously variable transmission

The dynamic analysis of a horizontal axis fixed pitch wind turbine generator (WTG) rated at 56 kW is discussed. A mechanical Continuously Variable Transmission (CVT) was incorporated in the drive train to provide variable speed operation capability. One goal of the dynamic analysis was to determine if variable speed operation, by means of a mechanical CVT, is capable of capturing the transient power in the WTG/wind environment. Another goal was to determine the extent of power regulation possible with CVT operation.

Gallo, C.↗
NASA NTRS1985

Changes in classification accuracy due to varying Thematic Mapper and multispectral scanner spatial, spectral, and radiometric resolution

The present paper provides the results of a factorial experiment designed to study the classification differences resulting from varying TM and MSS sensor resolution. Eight simulated data sets of various TM and MSS spatial, spectral, and radiometric resolutions were generated on the basis of Daedalus aircraft scanner data. It is pointed out that the current study provides more precise results than previous work, because more exact methods of data simulation with regard to the three factors were emphasized. Two methods of analysis are considered in the paper. To improve on earlier studies, efforts were made to collect an extensive amount of ground reference data. The summaries of classification accuracies for the training sites in the factorial analysis are presented in a table.

Acevedo, W.↗
NASA NTRS1987

Theory underlying CRM training: Psychological issues in flight crew performance and crew coordination

What psychological theory and research can reveal about training in Cockpit Resource Management (CRM) is summarized. A framework is provided for the critical analysis of current approaches to CRM training. Background factors and definitions critical to evaluating CRM are reviewed, followed by a discussion of issues directly related to CRM training effectiveness. Some of the things not known about the optimization of crew performance and the research needed to make these efforts as effective as possible are described.

Helmreich, Robert L.↗
NASA NTRS2022

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

A new extravehicular (EVA) suit is being developed for National Aeronautics and Space Administration’s (NASA’s) upcoming lunar missions that will be designed to operate in both the lunar surface and in microgravity. This suit will allow for increased range of motion compared to the current Extravehicular Mobility Unity (EMU) and Apollo era suits and have additional features (e.g. ability to increase pressure in the field) that will enhance the health and safety of exploration astronaut.

Teresa M Reiber↗
NASA NTRS1987

Analysis of Convair 990 rejected-takeoff accident with emphasis on decision making, training and procedures

This paper analyzes a NASA Convair 990 (CV-990) accident with emphasis on rejected-takeoff (RTO) decision making, training, procedures, and accident statistics. The NASA Aircraft Accident Investigation Board was somewhat perplexed that an aircraft could be destroyed as a result of blown tires during the takeoff roll. To provide a better understanding of tire failure RTO's, The Board obtained accident reports, Federal Aviation Administration (FAA) studies, and other pertinent information related to the elements of this accident. This material enhanced the analysis process and convinced the Accident Board that high-speed RTO's in transport aircraft should be given more emphasis during pilot training. Pilots should be made aware of various RTO situations and statistics with emphasis on failed-tire RTO's. This background information could enhance the split-second decision-making process that is required prior to initiating an RTO.

Batthauer, Byron E.↗
NASA NTRSDate not supplied

Examining Artifacts from GLOBE Program Research Symposia & Using Network Analysis Techniques to Characterize Students’ Authentic STEM Investigations

For the past several years, the GLOBE Program's International Virtual Science Symposia (IVSS) and Student Research Symposia (SRS) have provided opportunities for U.S. and international students to present their Earth science research investigations to the GLOBE community through online or in-person events. This presentation will share the techniques and findings of an evaluation study that used student posters and written reports to characterize their research investigations through multiple lenses and frameworks. The study began with a list of characteristics drawn from a literature review, an analysis of sample projects, and several reviews by expert stakeholders and scientists, which comprehensively covered diverse relevant frameworks including citizen science, student STEM learning through authentic experiences, and The GLOBE Program model. Once applied to 207 student projects, this list of codes revealed the frequency and prevalence of various qualities and experiences represented by GLOBE student research investigations. An innovative application of social network analysis techniques to the coded dataset revealed frequently cooccurring characteristics. This networking approach identified and conceptually mapped several "clusters" of characteristics that typified student projects, empirically based on the submitted projects themselves. The basic quantitative investigation of frequencies indicates the extent to which various characteristics are present in - or absent from - GLOBE SRS and IVSS projects, while the network analysis provides a descriptive framework for typifying projects. Ultimately, the descriptive framework fostered a suite of assessment tools to help The GLOBE Program's staff, scientists, and research project judges understand the diversity of student research projects. GLOBE can use these tools to identify and respond to areas of need; for instance, the descriptive framework illustrates the potential for further education and training resources related to data analysis, interpretation of data, and credibility of scientific claims. This presentation will share the novel utilization of network analysis techniques to holistically assess and react to student research contributions.

Ann Martin↗
NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗
NASA NTRS1990

In-flight crew training

The Helmet Mounted Display system and Part Task Trainer are two projects currently underway that are closely related to the in-flight crew training concept. The first project is a training simulator and an engineering analysis tool. The simulator's unique helmet mounted display actually projects the wearer into the simulated environment of 3-D space. Miniature monitors are mounted in front of the wearers eyes. Partial Task Trainer is a kinematic simulator for the Shuttle Remote Manipulator System. The simulator consists of a high end graphics workstation with a high resolution color screen and a number of input peripherals that create a functional equivalent of the RMS control panel in the back of the Orbiter. It is being used in the training cycle for Shuttle crew members. Activities are underway to expand the capability of the Helmet Display System and the Partial Task Trainer.

Gott, Charles↗
NASA NTRSDate not supplied

NEUROSPF: A Tool For the Symbolic Analysis of Neural Networks

This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and translates them into a Java representation that is amenable for analysis using the Symbolic PathFinder symbolic execution tool. Notably, NEUROSPF encodes specialized peer classes for parsing the model’s parameters, thereby enabling efficient analysis. With NEUROSPF the user has the flexibility to specify either the inputs or the network internal parameters as symbolic, promoting the application of program analysis and testing approaches from software engineering to the field of machine learning. For instance, NEUROSPF can be used for coverage-based testing and test generation, finding adversarial examples and also constraint-based repair of neural networks, thus improving the reliability of neural networks and of the applications that use them.

neural networks↗
NASA NTRSDate not supplied

Isolator Shock Train Response to Dual-Mode Scramjet Throttling-Like Forcing

Typical dual-mode scramjet designs employ an isolator component situated between the inlet and combustor. The isolator fluidically buffers the inlet from the combustor via the formation of a shock train, an interconnected series of shock-boundary layer interactions. The isolator is required during ramjet-engine operation and at the lower edges of the scramjet operational envelope. In an operational engine, transient behavior imposes fluidic dynamics due to attitude adjustments, combustor throttling, aberrant resonances within the combustor, etc. To accommodate these transients, the shock train adjusts on both temporal and spatial scales. Sufficiently large downstream pressure increases in the combustor play a critical role during unstart, whereby strong compression waves propagate upstream in the isolator to ultimately force the shock train out the inlet, if it cannot stabilize to the pressure increase. This critically reduces the engine mass flow rate, potentially causing a catastrophic reduction in thrust and loss of the vehicle. A nearly instantaneous unstart can, in principle, be predicted by a ratio of the normal shock pressure jump in an inviscid isolator. However, lower-magnitude perturbations, below this bound, also induce unstarts. Understanding the transient behavior inherent in unsteady isolator operation is critical to reducing safety margin in isolator length and refining engine control algorithms to improve engine performance. The Isolator Dynamics Research Lab (IDRL) is a cold-flow, direct-connect isolator facility ideal for assessing the fundamental fluid dynamics of shock trains. The internal flow of a scramjet isolator is modeled using a 2D, symmetric Mach 2.5 nozzle followed by a 695 mm long, 25.4x50.8 mm rectangular isolator test section. A blockage cone on a high-speed ball screw actuator downstream of the isolator is pulsed to simulate the throttling behavior in an operational combustor. Wall flush high-speed static pressure transducers detect the streamwise shock train within the isolator. Time delays between the onset of the throttling and the response motion of the shock train are analyzed to assess the controlling scales and parameters. From this analysis, the response time of the isolator shock train system is found to depend primarily on the isolator back pressure time-rate-of-change but quickly saturates to a maximum propagation speed along the isolator. These results inform dual-mode scramjet engine designers of the critical parameters and limits of an unstart resistant engine.

scramjet↗
NASA NTRS1989

Test and validation for robot arm control dynamics simulation

The Flight Telerobotic Servicer (FTS) program will require an ability to develop, in a cost effective manner, many simulation models for design, analysis, performance evaluation, and crew training. Computational speed and the degree of modeling fidelity associated with each simulation must be commensurate with problem objectives. To demonstrate evolving state-of-the-art general purpose multibody modeling capabilities, to validate these by laboratory testing, and to expose their modeling shortcomings, two focus problems at the opposite ends of the simulation spectrum are defined: (1) Coarse Acquisition Control Dynamics. Create a real time man-in-the-control-loop simulator. Provide animated graphical display of robot arm dynamics and tactile feedback sufficient for cueing the operator. Interface simulator software with human operated tactile feedback controller; i.e., the Kraft mini-master. (2) Fine, Precision Mode Control Dynamics. Create a high speed, high fidelity simulation model for the design, analysis, and performance evaluation of autonomous 7 degree-of-freedom (DOF) trajectory control algorithms. This model must contain detail dynamic models for all significant dynamics elements within the robot arm, such as joint drive mechanisms.

Yae, K. Harold↗
NASA NTRS1997

Measurement and Analysis of Atmospheric Spectral Optical Depths with NASA Ames Airborne Sunphotometers During TARFOX and ACE-2

In accordance with the scope of work of this contract, the following tasks were undertaken and completed during the course of the contract: (1) Participation in the design and development of the 14-channel Ames Airborne Tracking Sunphotometer (AATS-14), including the development and implementation of Visual Basic software for real-time data processing and display and post-acquisition data reduction and analysis. (2) Operation of the six-channel Ames Airborne Tracking Sunphotometer (AATS-6) aboard the University of Washington C-131A during TARFOX and in-field analysis and presentation of data acquired with the AATS-6. (3) Post-mission analysis of data acquired during TARFOX with the AATS-6 and the AATS-14. (4) Pre-TARFOX calibration of the AATS-6 at Mauna Loa Observatory in May 1996, and post-TARFOX calibration of the AATS-6 and AATS- 14 at Zugspitze, Germany in October 1996, including analyses of all data sets. (5) Analysis of AATS-14 airborne calibration data acquired on 17 November 1996 during a late afternoon Pelican flight over the central California coast. (6) Operational training, instrument preparation, field coordination, and analysis of shipboard measurements of aerosol optical depth with the AATS-6 during ACE-2. (7) Coordination of data acquisition with the AATS-14 aboard the Pelican during ACE-2 and in-field preliminary data analysis and presentation. (8) Calibration of the AATS-6 and AATS-14 in April/May 1997 at Mauna Loa prior to ACE-2, and post-mission calibration of the AATS-6 at Mauna Loa in August 1997.

Livingston, John M.↗