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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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Trajectory analysis, reliability of spacecraft equipment, performance prediction, and functional requirements of Voyager Mars spacecraft
Two tasks related to payload activity planning and scheduling were performed. The first task involved making a comparison of space mission activity scheduling problems with production scheduling problems. The second task consisted of a statistical analysis of the output of runs of the Experiment Scheduling Program (ESP). Details of the work which was performed on these two tasks are presented.
The NASA Composite Technology for Exploration (CTE) project is tasked with evaluating methods to analyze and manufacture composite joints for potential use in block upgrades to the Space Launch System (SLS) launch-vehicle structures such as the Payload Attach Fitting (PAF). To perform this task, the CTE project has initiated test and analysis correlation studies for composite joints under various loading conditions. Herein, NASA-developed numerical models are correlated with the experimental results from a series of tension tests. Pretest strain results matched the far-field test data well, but did not capture the nonlinear response in the vicinity of the joint. A refined pretest analytical model was modified to represent progressive failure of the specimens at failure locations observed during the experimental tests. The nonlinear strain response from this progressive failure model predicted the delamination failure load within 15% of the test data, but underpredicted the nonlinearity of the strain response. Further study of composite material models that account for the nonlinear shear response of fabric composites is recommended for the composite joint structures considered in this paper.
Results of a study in which subjects were presented concurrently with the primary task of controlling a second-order plant and the secondary task of controlling a first-order plant. The plant errors for the two tasks were shown on separate visual displays. An auditory display, whose output varied in frequency and volume with the error, was used to supplement the secondary task in half of the runs. To study the effects of the auditory display, two performance measures were obtained: (1) the integral of the squared error (ISE) and (2) the describing functions of the human operator. Statistical analysis of the ISE measures indicated that when the secondary task was supplemented with an auditory display, there was a significant improvement in performance on the secondary task. The performance on the primary task improved on the average, but not significantly. The variances of the ISE values decreased for both the tasks, indicating a more consistent behavior with the auditory display. The describing function analysis showed that supplementing the secondary task with the auditory display increased the low frequency gain of the human operator for this task. The describing functions for the primary task did not show any apparent changes.
NASA Human Research Project (HRP) and Exploration Medical Capabilities (ExMC) team identified a need to implement a human-centered design approach for a computational tool that performs detailed trade space analysis and research prioritization, known as Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT). IMPACT processes numerous parameters such as space vehicle design, mission objectives, evacuation capability, medical events, and mission constraint, including but not limited to; duration, mass, volume, equipment, and medical capability, each with complex and interconnected relationships. The ability for users to navigate through these complexities and provide an intuitive report is critical to aiding stakeholders in the decision-making process of future missions. In this presentation we will discuss how the IMPACT team has applied human-centered design strategies to improve system usability by modelling human-system integration (i.e., task analysis) with the MagicDraw SysML modelling application and performing A/B testing of user interface prototypes.
The Near Term Hybrid Passenger Vehicle Development Program tasks included defining missions, developing distributions of daily travel and composite driving cycles for these missions, providing information necessary to estimate the potential replacement of the existing fleet by hybrids, and estimating acceleration/gradeability performance requirements for safe operation. The data was then utilized to develop mission specifications, define reference vehicles, develop hybrid vehicle performance specifications, and make fuel consumption estimates for the vehicles. The major assumptions which underlie the approach taken to the mission analysis and development of performance specifications are the following: the daily operating range of a hybrid vehicle should not be limited by the stored energy capacity and the performance of such a vehicle should not be strongly dependent on the battery state of charge.
A gradient-based design optimization strategy for practical aerodynamic design applications is presented, which uses the 2D thin-layer Navier-Stokes equations. The strategy is based on the classic idea of constructing different modules for performing the major tasks such as function evaluation, function approximation and sensitivity analysis, mesh regeneration, and grid sensitivity analysis, all driven and controlled by a general-purpose design optimization program. The accuracy of aerodynamic shape sensitivity derivatives is validated on two viscous test problems: internal flow through a double-throat nozzle and external flow over a NACA 4-digit airfoil. A significant improvement in aerodynamic performance has been achieved in both cases. Particular attention is given to a consistent treatment of the boundary conditions in the calculation of the aerodynamic sensitivity derivatives for the classic problems of external flow over an isolated lifting airfoil on 'C' or 'O' meshes.
Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.
Eye movements made by various subjects in the performance of a precognitive tracking task are studied. The tracking task persented by an antiaircraft artillery (AAA) simulator has an input forcing function represented by a deterministic aircraft fly-by. The performance of subjects is ranked by two metrics. Good, mediocre, and poor trackers are selected for analysis based on performance during the difficult segment of the tracking task and over replications. Using phase planes to characterize both the eye movement patterns and the displayed error signal, a simple metric is developed to study these patterns. Two characterizations of eye movement strategies are defined and quantified. Using these two types of eye strategies, two conclusions are obtained about good, mediocre, and poor trackers. First, the eye tracker who used a fixed strategy will consistently perform better. Secondly, the best fixed strategy is defined as a Crosshair Fixator.
EVA timeline development occurs using task execution data generated through underwater training and simulation. This project collected task time data during final training events for several Space Shuttle and International Space Station missions and compared like task time data collected during on-orbit execution. Analysis was performed to compare types of activities and times required for each looking specifically for how activities can be accurately trained from a timeline planning perspective. The data revealed two significant aspects of flight timeline planning; Zero-g task times will match training times for activities that can be accurately simulated with appropriate fidelity hardware; and not all activities can be simulated sufficiently to produce training task times that will reflect required zero-g times. An approach for timeline planning utilizing this knowledge is also presented.
Performance with practice on two dual-task combinations, dual-axis tracking and two discrete information processing tasks, is examined in an effort to identify the presence and development of specific time sharing skills, such as parallel information processing or rapid intertask switching. The generality of time sharing skills also is investigated by examining transfer of these skills between the two qualitatively different task combinations.
The feasibility of monitoring the position of a tether during orbital deployment is discussed. Attention is given to the techniques for attaching reflectors to the tether at periodic intervals during the deployment process, which could then be tracked visually or with a radar unit that is pointed towards the targets by the control system. Consideration is also given to a method for tether attitude and tension detection, and a launching device to attach small instrumentation platforms onto the tether during deployment. The configuration of a tether deployment monitoring system (TEDEMS) and the equipment developed to perform the above tasks are described, along with an analysis of requirements for the construction of a family of space-borne TEDEMS suitable for use on the Space Shuttle, Expendable Launch Vehicles, or the Space Station. The potential uses of the TEDEMS for launching small tether-borne experimental packages are discussed. Design and block diagrams are included.
Initial planetary explorations with the Apollo program had a veritable ground support army monitoring the safety and health of the 12 astronauts who performed lunar surface extravehicular activities (EVAs). Given the distances involved, this will not be possible on Mars. A spacesuit for Mars must be smart enough to replace that army. The next generation suits can do so using 2 software systems serving as virtual companions, LEGACI (Life support, Exploration Guidance Algorithm and Consumable Interrogator) and VIOLET (Voice Initiated Operator for Life support and Exploration Tracking). The system presented in this study integrates data inputs from a suite of sensors into the MIII suit s communications, avionics and informatics hardware for distribution to remote managers and data analysis. If successful, the system has application not only for Mars but for nearer term missions to the Moon, and the next generation suits used on ISS as well. Field tests are conducted to assess capabilities for next generation spacesuits at Johnson Space Center (JSC) as well as the Mars and Lunar analog (Devon Island, Canada). LEGACI integrates data inputs from a suite of noninvasive biosensors in the suit and the astronaut (heart rate, suit inlet/outlet lcg temperature and flowrate, suit outlet gas and dewpoint temperature, pCO2, suit O2 pressure, state vector (accelerometry) and others). In the Integrated Walkback Suit Tests held at NASA-JSC and the HMP tests at Devon Island, communication and informatics capabilities were tested (including routing by satellite from the suit at Devon Island to JSC in Houston via secure servers at VCU in Richmond, VA). Results. The input from all the sensors enable LEGACI to compute multiple independent assessments of metabolic rate, from which a "best" met rate is chosen based on statistical methods. This rate can compute detailed information about the suit, crew and EVA performance using test-derived algorithms. VIOLET gives LEGACI voice activation capability, allowing the crew to query the suit, and receive feedback and alerts that will lead to corrective action. LEGACI and VIOLET can also automatically control the astronaut's cooling and consumable use rate without crew input if desired. These findings suggest that non-invasive physiological and environmental sensors supported with data analysis can allow for more effective management of mission task performance during EVA. Integrated remote and local view of data metrics allow crewmember to receive real time feedback in synch with mission control in preventing performance shortcomings for EVA in exploration missions.
We describe an approach and existing software tool support for effective interactions between human factors engineers and systems engineers in early analysis activities during system acquisition. We examine the tasks performed during this stage, emphasizing those tasks where system engineers and human engineers interact. The Concept of Operations (ConOps) document is an important product during this phase, and particular attention is paid to its influences on subsequent acquisition activities. Understanding this influence helps ConOps authors describe a complete system concept that guides subsequent acquisition activities. We identify commonly used system engineering and human engineering tools and examine how they can support the specific tasks associated with system definition. We identify possible gaps in the support of these tasks, the largest of which appears to be creating the ConOps document itself. Finally, we outline the goals of our future empirical investigations of tools to support system concept definition.
We describe an approach and existing software tool support for effective interactions between human factors engineers and systems engineers in early analysis activities during system acquisition. We examine the tasks performed during this stage, emphasizing those tasks where system engineers and human engineers interact. The Concept of Operations (ConOps) document is an important product during this phase, and particular attention is paid to its influences on subsequent acquisition activities. Understanding this influence helps ConOps authors describe a complete system concept that guides subsequent acquisition activities. We identify commonly used system engineering and human engineering tools and examine how they can support the specific tasks associated with system definition. We identify possible gaps in the support of these tasks, the largest of which appears to be creating the ConOps document itself. Finally, we outline the goals of our future empirical investigations of tools to support system concept definition.
The microstructure of a 2D woven ceramic matrix composite displays significant variability and irregularity. For example, a chemical vapor infiltrated (CVI) SiC/SiC composite exhibits significant amount of porosity arranged in irregular patterns. Furthermore, the fiber tows within a ply frequently have irregular shape and spacing, and the stacked plies are often misaligned and irregularly nested within each other. The goal of an ongoing project at NASA Glenn is to investigate the effects of the complex microstructure and its variability on the properties and the durability of the material. One key requirement for this effort is the development of methods to characterize the distribution in as-fabricated ceramic matrix composite (CMC) microstructures with the objective of correlating microstructural distribution parameters with mechanical performance. An initial task in this effort was to perform quantitative image analysis of polished cross sections of CVI SiC/SiC composite specimens. This analysis provided sample distributions of various microstructural composite features, including: inter-tow pore sizes and shapes, transverse sectioned tow sizes and shapes, and within ply tow spacing. This information can then be used to quantify the effect of extreme values of these features on the local stress state with the goal of determining the likelihood of matrix cracking at a given external load.
In order to mitigate the risk of rocket propulsion development, efficient, accurate, detailed fluid dynamics analysis and testing of the turbomachinery is necessary. To support this requirement, a task was developed at NASA Marshall Space Flight Center (MSFC) to improve turbine aerodynamic performance through the application of advanced design and analysis tools. These tools were applied to optimize a supersonic turbine design suitable for a reusable launch vehicle (RLV). The hot gas path and blading were redesigned-to obtain an increased efficiency. The goal of the demonstration was to increase the total-to- static efficiency of the turbine by eight points over the baseline design. A sub-scale, cold flow test article modeling the final optimized turbine was designed, manufactured, and tested in air at MSFC s Turbine Airflow Facility. Extensive on- and off- design point performance data, steady-state data, and unsteady blade loading data were collected during testing.
Lunar surface craters smaller than the spatial resolution of surface meshes used in typical Lunar surface thermal models (10 to 60 meters per pixel) may impact the accuracy of thermal model extrema predictions. The goal of this study is to investigate the thermal sensitivity of representative lander systems with realistic thermal surface orientations in bare and cratered terrain environments at relevant Artemis mission locations. This thermal analysis task investigates the impact of lunar surface craters on lander radiator performance by comparing heat rejection capability results between bare and cratered terrain environments. This study examines external body-mounted lander radiator thermal performance across varying lander heights (5.5m, 20m, 50m) and radiator orientations (horizontal, 45º tilted, and vertical) at two representative Artemis mission latitudes (-89.5ºS and -82.5ºS), spanning from the Shackleton Connecting Ridge to Mons Mouton Plateau.