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Spacecraft subsystem performance deterioration caused by nuclear radiation on space missions
An overview of the current turbine aerodynamic analysis and testing activities at NASA/Marshall Space Flight Center (MSFC) is presented. The presentation is divided into three areas. The first area is the three-dimensional (3D), unsteady Computational Fluid Dynamics (CFD) analysis of the Fastrac turbine. Results from a coupled nozzle, blade, and exit guide vane analysis and from an uncoupled nozzle and coupled blade and exit guide vane will be presented. Unsteady pressure distributions, frequencies, and exit profiles from each analysis will be compared and contrasted. The second area is the testing and analysis of the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP) turbine with instrumented first stage blades. The SSME HPFTP turbine was tested in air at the MSFC Turbine Test Equipment (TTE). Pressure transducers were mounted on the first stage blades. Unsteady, 3D CFD analysis was performed for this geometry and flow conditions. A sampling of the results will be shown. The third area is a status of the Turbine Performance Optimization task. The objective of this task is to improve the efficiency of a turbine for potential use on a next generation launch vehicle. This task includes global optimization for the preliminary design, detailed optimization for blade shapes and spacing, and application of advanced CFD analysis. The final design will be tested in the MSFC TTE.
Maintaining safe separation between aircraft is a key determinant of the airspace capacity to handle air transportation. With the advent of satellite-based surveillance, aircraft equipped with the needed technologies are now capable of maintaining awareness of their location in the airspace and sharing it with their surrounding traffic. As a result, concepts and cockpit automation are emerging to enable delegating the responsibility of maintaining safe separation from traffic to the pilot; thus increasing the airspace capacity by alleviating the limitation of the current non-scalable centralized ground-based system. In this paper, an analysis of allocating separation assurance functions to the human pilot and cockpit automation is presented to support the design of these concepts and technologies. A task analysis was conducted with the help of Petri nets to identify the main separation assurance functions and their interactions. Each function was characterized by three behavior levels that may be needed to perform the task: skill, rule and knowledge based levels. Then recommendations are made for allocating each function to an automation scale based on their behavior level characterization and with the help of Subject matter experts.
The CH-47B variable-stability helicopter was used to evaluate a range of height-response configurations while performing a precision hover bob-up task. The purpose of the study was to assess the validity of results obtained in previous ground-based and in-flight simulations in the context of a precision bob-up task and to provide additional flight data for inclusion in revisions to specifications for helicopter handling qualities. Height response characteristics were implemented using explicit model-following techniques, and the resulting CH-47B dynamics were validated using time-domain and frequency-domain data-analysis methods. The tests complemented the previous investigations by providing detailed pilot comments and ratings, and performance and control-utilization data that relate exclusively to the hover bob-up task. The results are compared with those from previous investigations and with new criteria that have been proposed for handling qualities requirements for helicopters.
Procedures for and results of aeroservothermoelastic studies are described. The objectives of these studies were to develop the necessary procedures for performing an aeroelastic analysis of an aerodynamically heated vehicle and to analyze a configuration in the classical cold state and in a hot state. Major tasks include the development of the structural and aerodynamic models, open loop analyses, design of active control laws for improving dynamic responses and analyses of the closed loop vehicles. The analyses performed focused on flutter speed calculations, short period eigenvalue trends and statistical analyses of the vehicle response to controls and turbulence. Improving the ride quality of the vehicle and raising the flutter boundary of the aerodynamically-heated vehicle up to that of the cold vehicle were the objectives of the control law design investigations.
This paper describes the procedures for an results of aeroservothermoelastic studies. The objectives of these studies were to develop the necessary procedures for performing an aeroelastic analysis of an aerodynamically heated vehicle and to analyze a configuration in the classical 'cold' state and in a 'hot' state. Major tasks include the development of the structural and aerodynamic models, open loop analyses, design of active control laws for improving dynamic responses and analyses of the closed loop vehicles. The analyses performed focused on flutter speed calculations, short period eigenvalue trends and statistical analyses of the vehicle response to controls and turbulence. Improving the ride quality of the vehicle and raising the flutter boundary of the aerodynamically-heated vehicle up to that of the cold vehicle were the objectives of the control law design investigations.
Based on an analysis of aviation decision-makers' time-related weather information needs, an abstraction of the aviation weather decision task was developed, that involves 4-D intersection testing between aircraft trajectory hypertubes and hazardous weather hypervolumes. The framework builds on the hypothesis that hazardous meteorological fields can be simplified using discrete boundaries of surrogate threat attributes. The abstractions developed in the framework may be useful in studying how to improve the performance of weather forecasts from the trajectory-centric perspective, as well as for developing useful visualization techniques of weather information.
This document includes the critical analysis review of the American Society of Mechanical Engineers (ASME) Section III Division 5 Subsection HH Subpart B (HHB), including Mandatory Appendices, that was published in 2023. In the context of this document, reference to “the code” is specific to this subsection unless otherwise specified. A specific composites task group within the ASME Nonmetallic Design and Materials Working Group, with the support of external experts, was established to perform a gap analysis review. The significant findings are summarized here. The committee response with suggested action items are detailed in the body of the report.
Trust and attention allocation are pivotal determinants in human-automation interaction. However, there are scarce empirical findings regarding the relationship between trust and attention allocation. Observations from our previous work suggested there may be a negative correlation between trust in automation and eye movement towards automation, though no formal analysis of these data had been conducted to quantify this relationship. The present meta-analysis examined the relationship between three dimensions of trust in automation (performance, process, and purpose) and visual attention allocation to the automation. Specifically, we applied Cumming’s (2014) meta-analysis technique to combine evidence across three experiments. Results indicated a negative correlation between trust in automation and visual sampling of the automated system monitoring task for performance-based trust, but not for process- or purpose-based trust. These findings suggest that operators scanned the automation’s behavior less frequently when indicating higher performance-based trust towards the automation.
Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study was to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts were recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests included assessments of sensory dependency and adaptability. Visual dependency involved treadmill walking while viewing a moving virtual visual scene. Vestibular perceptual thresholds were measured while seated during lateral translations. Proprioception dependency was measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability was performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms (adaptive Functional Mobility Test, aFMT). The neuroimaging tests characterized individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests utilized saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Thirty ISS crewmembers were recruited, including 12 first-time fliers, 6F, and mission durations lasting 185.5 ± 45.5 days, mean ± std. We utilized a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There was considerable variability among all post-flight performance outcomes. Based on an ordinal scale survey, 72% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. Understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.
A multi-task simulation of a semi-automatic supervisory control system was developed to provide an environment in which training, operator strategy development, failure detection and resolution, levels of automation, and operator workload can be investigated. The goal was to develop a well-defined, but realistically complex, task that would lend itself to model-based analysis. The name of the task (POPCORN) reflects the visual display that depicts different task elements milling around waiting to be released and pop out to be performed. The operator's task was to complete each of 100 task elements that ere represented by different symbols, by selecting a target task and entering the desired a command. The simulated automatic system then completed the selected function automatically. Highly significant differences in performance, strategy, and rated workload were found as a function of all experimental manipulations (except reward/penalty).
The commercial nuclear power industry is facing a potential shortage of certified nondestructive evaluation (NDE) analysts to meet future in-service inspection demands. Automated data analysis (ADA) currently supports human inspectors in tasks such as eddy current evaluations for steam generator examinations. Machine learning (ML) systems are nearing the capability to pass performance demonstration tests for ultrasonic testing (UT) inspections of reactor pressure vessel upper head penetrations in nuclear power plants (NPPs). Current research and development is focused on assisted analysis (AA) of ADA versus fully automated examinations. This presentation will cover assessment of ML flaw detection on dissimilar metal weld (DMW) piping joints.
Thermal and flow sensor instrumentation was developed for use as an integral part of the space shuttle orbiter reusable thermal protection system. The effort was performed in three tasks: a study to determine the optimum instruments and instrument installations for the space shuttle orbiter RSI and RCC TPS; tests and/or analysis to determine the instrument installations to minimize measurement errors; and analysis using data from the test program for comparison to analytical methods. A detailed review of existing state of the art instrumentation in industry was performed to determine the baseline for the departure of the research effort. From this information, detailed criteria for thermal protection system instrumentation were developed.
A two-year task sponsored by NASA's Mars Technology Program's Advanced Entry, Descent and Landing (EDL) work area includes investigation of improvements to EDL navigation by processing spacecraft-to-spacecraft radiometric data. Spacecraft-to-spacecraft navigation will take advantage of the UHF link between two spacecraft (i.e. to an orbiter from an approaching lander for EDL telemetry relay) to build radiometric data, specifically the velocity between the two spacecraft along the radio beam, that are processed to determine position and velocity in real time. The improved onboard state knowledge provided by spacecraft-to-spacecraft navigation will improve the performance of entry guidance by providing a more accurate state estimate and ultimately reduce the landed position error. A previous paper documented the progress of the first year of this task, including the spacecraft definitions, selection and documentation of the required algorithms and analysis results used to define the algorithm set. The final year of this task is reported here. Topics include modifications to the previously selected algorithm set for implementation, and performance of the implemented algorithms in a stand-alone filter, on an emulator of the target processor and finally on a breadboard processing unit.
A multiprocessing architecture for performing real time monitoring and analysis using knowledge-based problem solving techniques is discussed. To handle asynchronous inputs and perform in real time, the system consists of three or more separate processes which run concurrently on one or more processors and communicate via a message passing scheme. The Data Management Process gathers, compresses, scales and sends the incoming telemetry data to other tasks. The Inference Process consists of a proprietary high performance inference engine that runs at 1000 rules per second using telemetry data to perform real time analysis on the state and health of the Space Telescope. The multiprocessing architecture has been interfaced to a simulator and is able to process the incoming telemetry in real time.
Laboratory testing of advanced aerospace components very often requires highly accurate temperature measurement and control devices, as well as methods to precisely analyze and predict the performance of such components. Analysis of test articles depends on accurate measurements of temperature across the specimen. Where possible, this task is accomplished using many thermocouples welded directly to the test specimen, which can produce results with great precision. However, it is known that thermocouple spot welds can initiate deleterious cracks in some materials, prohibiting the use of welded thermocouples. Such is the case for the nickel-based superalloy MarM-247, which is used in the high temperature, high pressure heater heads for the Advanced Stirling Converter component of the Advanced Stirling Radioisotope Generator space power system. To overcome this limitation, a method was developed that uses small diameter contact thermocouples to measure the temperature of heater head test articles with the same level of accuracy as welded thermocouples. This paper includes a brief introduction and a background describing the circumstances that compelled the development of the contact thermocouple measurement method. Next, the paper describes studies performed on contact thermocouple readings to determine the accuracy of results. It continues on to describe in detail the developed measurement method and the evaluation of results produced. A further study that evaluates the performance of different measurement output devices is also described. Finally, a brief conclusion and summary of results is provided.
Substantial evidence supports the claim that inadequate training leads to performance errors. Barshi and Loukopoulos (2012) demonstrate that even a task as carefully developed and refined over many years as operating an aircraft can be significantly improved by a systematic analysis, followed by improved procedures and improved training (see also Loukopoulos, Dismukes, & Barshi, 2009a). Unfortunately, such a systematic analysis of training needs rarely occurs during the preliminary design phase, when modifications are most feasible. Training is often seen as a way to compensate for deficiencies in task and system design, which in turn increases the training load. As a result, task performance often suffers, and with it, the operators suffer and so does the mission. On the other hand, effective training can indeed compensate for such design deficiencies, and can even go beyond to compensate for failures of our imagination to anticipate all that might be needed when we send our crew members to go where no one else has gone before. Much of the research literature on training is motivated by current training practices aimed at current training needs. Although there is some experience with operations in extreme environments on Earth, there is no experience with long-duration space missions where crews must practice semi-autonomous operations, where ground support must accommodate significant communication delays, and where so little is known about the environment. Thus, we must develop robust methodologies and tools to prepare our crews for the unknown. The research necessary to support such an endeavor does not currently exist, but existing research does reveal general challenges that are relevant to long-duration, high-autonomy missions. The evidence presented here describes issues related to the risk of performance errors due to training deficiencies. Contributing factors regarding training deficiencies may pertain to organizational process and training programs for spaceflight, such as when training programs are inadequate or unavailable. Furthermore, failure to match between tasks on the one hand, and learning and memory abilities on the other hand is a contributing factor, especially when individuals' relative efficiency with which new information is acquired, and adjustments made in behavior or thinking, are inconsistent with mission demands. Thus, if training deficiencies are present, the likelihood of errors or of the inability to successfully complete a task increases. What's more, the overall risk to the crew, the vehicle, and the mission increases.
In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.