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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Training for Long-Duration Space Missions: A Literature Review into Skill Retention and Generalizability

In long-duration space missions, skill retention and generalizability become ever more important as mission length increases, for it is through these capabilities that astronaut crews achieve autonomy. A framework is proposed for future research based on three types of training commonly found in operational scenarios: initial training, refresher training, and just-in-time training. One of the key points of interest identified from the body of literature is the need for a structured and quantifiable approach to characterize skill decay. Such an approach would allow gaining a deeper understanding of the mechanisms through which skill decay operates. Because simulators are used extensively in all types of training, the effects of simulator fidelity on skill retention and generalizability are paramount to understand. Some common fidelity types are defined and their effects on the human operator are discussed. From a review of the literature on all these topics, several research gaps were identified that led to three key opportunities for future research: (1) developing skill decay functions provides theoretical insights into skill decay and allows for several practical applications, such as planning refresher training, (2) the effects of simulator fidelity on skill decay functions should be investigated empirically, and (3) investigating the generalizability of skills learned in initial training to other tasks could provide space crews with greater autonomy. A cybernetic approach might give new insights.

training↗
NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗
NASA NTRSDate not supplied

On Generalizably Improving RANS Predictions of Flow Separation and Reattachment

This work presents progress in an ongoing data-driven turbulence modeling effort at NASA Langley Research Center to improve predictions for separated flows. Two augmentation strategies are presented – one to improve predictions for the point of reattachment after smooth-body separation, and another to improve predictions for flow separation due to prolonged adverse pressure gradients. The reattachment augmentation was inspired from lessons learned during attempts at using field inversion and machine learning (FIML); however, it is prescribed as a conventional analytic closed-form expression. Results show that, when introduced into the SST k-w model, it shortens the otherwise overpredicted separation bubble length for three cases characterized by different Reynolds numbers and flow geometries. The second augmentation, which addresses flow separation under prolonged adverse pressure gradients, is inferred via FIML and applied as a neural network within the Spalart-Allmaras model. It uses features that are chosen such that the presented results show an improved predictive accuracy for the training case without affecting other cases where the augmentation is not needed. Further testing is required to establish the generalizability of this augmentation. The rationale behind the chosen features that serve as inputs to both these augmentations is also presented for the benefit of the reader.

machine learning↗
NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗
NASA NTRS2019

Generalizability of Manual Control Skills Between Control Tasks of Varying Difficulty

This paper presents the results of an experiment that was performed at NASA Ames Research Center using 18 participants in two different groups who trained a task for ten days, with the goal of identifying how skill generalization would occur between two similar tasks of varying difficulty. A cybernetic approach was used. The first group was trained in a simple one-dimensional tracking task and transferred to a difficult two-dimensional tracking task. For the second group, this was reversed. Training with a simple task before transferring to the difficult task resulted in a slower convergence to final performance. However, it did allow participants to start with a better initial performance in the difficult task. Furthermore, after training with a simple task, participants controlled with a higher gain and generated lower lead time constants. However, possibly due to the number of participants, this experiment did not find any statistical evidence to support the conclusion that training with a simple task version helps in learning a more complex task.

skill generalizability↗
NASA NTRS2019

Generalizable Skills and Knowledge for Exploration Missions

This report describes research conducted under Cooperative Agreement 80NSSC18K0042 for the Human Factors and Behavioral Performance Element, Human Research Program, located at the National Aeronautics and Space Administration’s (NASA) Johnson Space Center. The research addresses the Risk of Inadequate Mission, Process, and Task Design and the Risk of Performance Errors Due to Training Deficiencies during exploration-class space missions by identifying the tasks that will be conducted by human crew during an expedition to Mars and the abilities, skills, and knowledge that will be required of crew members. By focusing on an expedition to Mars, we have considered the extremes of what is possible for human space exploration during the first half of the 21st Century and accommodated the human requirements for missions to asteroids, Cis-Lunar orbit, and a return to the Moon.

Stuster, Jack↗
NASA NTRS2019

Generalizability of Manual Control Skills between Control Tasks of Varying Difficulty

This paper presents the results of an experiment that was performed at NASA Ames Research Center using 18 participants in two different groups who trained a task for ten days, with the goal of identifying how skill generalization would occur between two similar tasks of varying difficulty. A cybernetic approach was used. The first group was trained in a simple one-dimensional tracking task and transferred to a difficult two-dimensional tracking task. For the second group, this was reversed. Training with a simple task before transferring to the difficult task resulted in a slower convergence to final performance. However, it did allow participants to start with a better initial performance in the difficult task. Furthermore, after training with a simple task, participants controlled with a higher gain and generated lower lead time constants. However, possibly due to the number of participants, this experiment did not find any statistical evidence to support the conclusion that training with a simple task version helps in learning a more complex task.

Pieters, Marc A.↗
NASA NTRSDate not supplied

A generalizable machine learning approach to predict land surface temperature

Monitoring of land surface and atmospheric states is highly reliant on satellite data. Traditionally, data products are generated using carefully tuned and validated algorithms for low-earth orbit (LEO) sensors. However, the emerging constellation of geostationary (GEO) sensors contributes global, high temporal resolution observations which can better capture the diurnal variability of key observables like land surface temperature (LST). Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from LEO and GEO satellites to develop a deep learning-based method for sensor-to-sensor algorithm emulation. Our model is trained on GOES-16 thermal bands to predict MODIS Terra LST and achieves a validation error <2K. Further, application of the model to unseen times of day and a second GEO sensor observing an unseen spatial domain demonstrate the generalization of the deep learning model across space, time and spectra. We anticipate that the synergies between a variety of active orbit configurations can be used to accelerate application of existing algorithms to new datasets.

Kate Marie Duffy↗
NASA NTRS2019

Training for Long-Duration Space Missions: A Literature Review into Skill Retention and Generalizatility

In long-duration space missions, skill retention and generalizability become ever more important as mission length increases, for it is through these capabilities that astronaut crews achieve autonomy. A framework is proposed for future research based on three types of training commonly found in operational scenarios: initial training, refresher training, and just-in-time training. One of the key points of interest identified from the body of literature is the need for a structured and quantifiable approach to characterize skill decay. Such an approach would allow gaining a deeper understanding of the mechanisms through which skill decay operates. Because simulators are used extensively in all types of training, the effects of simulator fidelity on skill retention and generalizability are paramount to understand. Some common fidelity types are defined and their effects on the human operator are discussed. From a review of the literature on all these topics, several research gaps were identified that led to three key opportunities for future research: (1) developing skill decay functions provides theoretical insights into skill decay and allows for several practical applications, such as planning refresher training, (2) the effects of simulator fidelity on skill decay functions should be investigated empirically, and (3) investigating the generalizability of skills learned in initial training to other tasks could provide space crews with greater autonomy. A cybernetic approach might give new insights.

Pieters, Marc A.↗
NASA NTRS1976

A statistical method for treating molecular line opacities

A method for treating atomic and molecular line opacities in cool stellar atmospheres by a statistical opacity sampling is investigated. Under the usual assumptions of plane-parallel geometry, radiative equilibrium, hydrostatic equilibrium, and LTE, each radiative quantity is computed monochromatically at each chosen frequency and depth without any averaging of the opacity. The number of frequencies needed to allow an accurate integration of the energy flux over a given spectral interval is investigated as a function of depth, including opacity for both CN and C2. This method is extended to the calculation of a model atmosphere of a star, and the effect of the number and placement of frequency points is studied. The method is applied to treating molecular lines of CO, C2, and CN in a cool carbon star. Significant advantages of the opacity sampling method are its flexibility, which permits computation of models having arbitrary variations of chemical composition and of opacity with wavelength and depth, and generalizability to include departures from LTE.

Sneden, C.↗
NASA NTRS1977

Digital high density (80 Mb/s) tape

Work with a state-of-the-art high density PCM tape recorder reproducer system is described. The tape recorder is designed for 80 Mb/s operation at an overall bit error rate of .00001and for 40 Mb/s operation at .000001. The article describes the process of measuring the error rate. Also detailed is a data rate buffer designed for use in recent radar experiments and generalizable to most potential uses of the recorder system.

Donner, M. D.↗
NASA NTRS1986

A methodology for the design and evaluation of user interfaces for interactive information systems

The definition of proposed research addressing the development and validation of a methodology for the design and evaluation of user interfaces for interactive information systems is given. The major objectives of this research are: the development of a comprehensive, objective, and generalizable methodology for the design and evaluation of user interfaces for information systems; the development of equations and/or analytical models to characterize user behavior and the performance of a designed interface; the design of a prototype system for the development and administration of user interfaces; and the design and use of controlled experiments to support the research and test/validate the proposed methodology. The proposed design methodology views the user interface as a virtual machine composed of three layers: an interactive layer, a dialogue manager layer, and an application interface layer. A command language model of user system interactions is presented because of its inherent simplicity and structured approach based on interaction events. All interaction events have a common structure based on common generic elements necessary for a successful dialogue. It is shown that, using this model, various types of interfaces could be designed and implemented to accommodate various categories of users. The implementation methodology is discussed in terms of how to store and organize the information.

Dominick, Wayne D.↗
NASA NTRS1992

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 22: Establishing a research agenda for Scientific and Technical Information (STI): Focus on the user

The goal is the creation of a generally accepted, systematically developed and implemented, but user focused, research agenda for the Advisory Group for Aerospace Research and Development (AGARD) and the Technical Information Panel (TIP) member countries. Information use seldom exists as an isolated incident. Information use usually takes place within organizational and interpersonal contexts. Therefore, it should not be studied in isolation, but rather in an holistic environment. Once implemented, this research agenda could be completed within 3 to 5 years. The results would be generalizable to AGARD member nations, would form the basis for the development of theory based practice, and would form a significant body of knowledge that can be used by AGARD information professionals for policy, practice, product, and systems development.

Pinelli, Thomas E.↗
NASA NTRS1992

Plasma wave profiles of earth's bow shock at low Mach numbers - ISEE 3 observations on the far flank

A survey of selected crossings far downstream from the subsolar shock is presented in which the overall plasma wave (PW) behavior of a selected set of nearly perpendicular crossings and another set of limited Mach number but broad geometry are delinated. The result is a generalizable PW signature, or signatures, of low Mach number shocks and some likely implications of those signatures for the weak shock's plasma physical processes on the flank. The data are found to be consistent with the presence of ion beam interactions producing noise ahead of the shock in the ion acoustic frequency range. The presence or absence, and the amplitudes, of PW activity are explainable by the presence or absence of a population of upstream ions controlled by the component of the interplanetary magnetic field normal to the solar wind flow.

Greenstadt, E. W.↗
NASA NTRS1994

Further studies of gravitationally unstable protostellar disks

Models of the solar nebula reveal that it might have been gravitationally unstable, both early and later in its evolution. Such instabilities produce density waves and associated gravitational torques, which are potent agents of angular momentum transport. In previous work, we conducted a series of numerical simulations designed to quantify the effects of gravitational instabilities in a generalizable way (Tomley, Cassen, & Steiman-Cameron 1991). Here we present a second series of simulations in which we examine disks of greater size, increased star/disk mass ratio, and flatter surface density distribution than those in our initial study. The purpose is to represent disks at a later stage of evolution than those already studied, to test the quantitative relations derived in our earlier work and to explore the effects of mass ratio on the results. The new results indicate that the tendencies for unstable, uncooled disks to heat to stability and for dynamical evolution rates to be proportional to cooling rates are general characteristics of the behavior of gravitationally unstable disks. Nevertheless, there are quantitative, and (for strong cooling) even qualitative differences that are revealed in the new simulations, particularly with regard to the cooling rates at which clumping tends to occur.

Tomley, Leslie↗