Transfer of training as a function of stimulus and response integration of paired associates.
Transfer of training as function of stimulus and response integration of paired associates
LEARNING↗
SEARCH · Engineering Papers
Results for “Transfer learning”
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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A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations
Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.
Radiation↗
Brain-cell protein synthesis specifically related to learning
Hippocampus nerve cells protein fractions synthesis in rats, noting relation to learning process during transfer of handedness
Hyden, H.↗
Transfer mechanisms in verbal discrimination.
Transfer mechanisms in verbal discrimination learning
VERBAL COMMUNICATION↗
General and specific factors in the intersensory transfer of form.
This study assessed the relative contributions of specific and nonspecific components to intersensory transfer between vision and touch. A paired-associate paradigm was used in which visual metric figures and their tactual analogs served as stimuli, and familiar adjectives were the responses. Positive intersensory transfer, characterized by symmetry across modalities was obtained. The contribution of nonspecific learning to this effect was negligible. Intersensory transfer was found to be less efficient than the empirically determined maximum level of intrasensory transfer possible in this task.
Clark, J. L.↗
Vehicle Steering control: A model of learning
A hierarchy of strategies were postulated to describe the process of learning steering control. Vehicle motion and steering control data were recorded for twelve novices who drove an instrumented car twice a week during and after a driver training course. Car-driver describing functions were calculated, the probable control structure determined, and the driver-alone transfer function modelled. The data suggested that the largest changes in steering control with learning were in the way the driver used the lateral position cue.
Smiley, A.↗
Offsetting Gravity
The Coastal Center and the NASA Biomedical Team are working together to adapt a suspension device that simulates weightlessness. Attempts to approximate weightlessness have led astronauts underwater and into harnesses that suspend all or part of their weight. One such device, built at Langley Research Center, is being transferred to rehabilitation work. It can help a person walk and re-learn muscular coordination following a stroke. Hospitals could use it to lift handicapped persons.
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Investigation of the neurological correlates of information reception
Animals trained to respond to a given pattern of electrical stimuli applied to pathways or centers of the auditory nervous system respond also to certain patterns of acoustic stimuli without additional training. Likewise, only certain electrical stimuli elicit responses after training to a given acoustic signal. In most instances, if a response has been learned to a given electrical stimulus applied to one center of the auditory nervous system, the same stimulus applied to another auditory center at either a higher or lower level will also elicit the response. This kind of transfer of response does not take place when a stimulus is applied through electrodes implanted in neural tissue outside of the auditory system.
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Experimenters' reference based upon Skylab experiment management
The methods and techniques for experiment development and integration that evolved during the Skylab Program are described to facilitate transferring this experience to experimenters in future manned space programs. Management responsibilities and the sequential process of experiment evolution from initial concept through definition, development, integration, operation and postflight analysis are outlined and amplified, as appropriate. Emphasis is placed on specific lessons learned on Skylab that are worthy of consideration by future programs.
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The NASA Turbulent Heat Flux Experiments: Summary and Lessons Learned
The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds- averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.
RANS↗
The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned
The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.
RANS↗
MSFC Skylab experimenter's reference
The methods and techniques for experiment development and integration that evolved during the Skylab Program are described to facilitate transferring this experience to experimenters in future manned space programs. Management responsibilities and the sequential process of experiment evolution from initial concept through definition, development, integration, operation and postflight analysis are outlined in the main text and amplified, as appropriate, in appendixes. Emphasis is placed on specific lessons learned on Skylab that are worthy of consideration by future programs.
Source record↗
Why surface-truth field study is needed in remote-sensing instruction
Especially designed field studies are needed in remote sensing technology transfer courses regardless of the field work provided by the students'/trainees' major disciplines because the remote sensing discipline has unique emphases and needs. Modification of existng schedules to include field work provides the equivalent of extending the duration of the program with the added benefit of enhancing learning achievements per actual program day. The process of surface truth field instruction, levels of student capabilities and stages in the development of surface truth field studies are discussed.
Wake, W. H.↗
NASA philosophy concerning space stations as operations centers for construction and maintenance of large orbiting energy systems
Future United States plans for manned space-flight activities are summarized, emphasizing the long-term goals of achieving permanent occupancy and limited self-sufficiency in space. NASA-sponsored studies of earth-orbiting Space Station concepts are reviewed along with lessons learned from the Skylab missions. Descriptions are presented of the Space Transportation System, the Space Construction Base, and the concept of space industrialization (the processing and manufacturing of goods in space). Future plans for communications satellites, solar-power satellites, terrestrial observations from space stations, and manned orbital-transfer vehicles are discussed.
Freitag, R. F.↗
Work function determination of promising electrode materials for thermionic energy converters
The work function determinations of candidate materials for low temperature (1400 K) thermionics through vacuum emission tests are discussed. Two systems, a vacuum emission test vehicle and a thermionic emission microscope are used for emission measurements. Some nickel and cobalt based super alloys were preliminarily examined. High temperature physical properties and corrosion behavior of some super alloy candidates are presented. The corrosion behavior of sodium is of particular interest since topping cycles might use sodium heat transfer loops. A Marchuk tube was designed for plasma discharge studies with the carbide and possibly some super alloy samples. A series of metal carbides and other alloys were fabricated and tested in a special high temperature mass spectrometer. This information coupled with work function determinations was evaluated in an attempt to learn how electron bonding occurs in transition alloys.
Jacobson, D.↗
ATC contingency operations in the en-route flight regime
Air traffic control (ATC) operations were examined to learn what factors of controller performance should be given consideration in the design and development of future automation systems enhancing ATC. Contingencies were of two types: those constraining airspace usage or traffic flow (i.e., weather); and those related to system and equipment usage (i.e., radar/radio status). Examination of controller response to contingencies and workload pressures showed differing effects on controller allocations of effort among the three primary function of planning, monitoring, and informaton transfer. Automation advancements oriented towards aiding the controller in performing monitoring tasks may offer the most substantial safety benefit.
Lyman, E. G.↗
Orbit transfer vehicle engine study. Volume 3: Program costs
Budgetary and planning cost estimates are presented that were prepared for the development, production and operation and flight support phases for each of the engines proposed for OTV propulsion. The major features of each category engine are described. The development program estimates were structured to the preliminary program Work Breakdown Structures (WBS). Program costs are provided within the applicable WBS elements to Level 4 for each category engine. The production program cost estimates assume a first production lot of 50 units produced at a rate of two units per month. Cumulative average unit costs assume a 90% learning capability. The operations and flight support cost estimates are based on 15, 30 and 45 missions per year for the period 1988 through 1999. Estimated funding requirements were developed for each category and program phase. All cost estimates and funding data are presented in 1979 dollars. The assumptions and ground rules for these estimates are summarized.
Source record↗
Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder
Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.
Mahyar Garshasbi↗