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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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Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
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Thermal emission spectra for a variety of cometary nucleus models were evaluated by a radiative transfer technique adapted from modeling of terrestrial ice and snow fields. It appears that millimeter wave sensing from an interplanetary spacecraft is the most effective available means for distinguishing between alternate models of the nucleus and for evaluating the thermal state of the layer which is below the instantaneous surface where modern theories of the nucleus indicate that sublimation of the cometary volatiles actually occurs.
Methods arising from the area of decentralized control are emerging for analysis and control synthesis for large flexible structures. In this paper the control strategy involves a decentralized model reference adaptive approach using a variable structure control. Local models are formulated based on desired damping and response time in a model-following scheme for various modal configurations. Variable structure controllers are then designed employing co-located angular rate and position feedback. In this scheme local control forces the system to move on a local sliding mode in some local error space. An important feature of this approach is that the local subsystem is made insensitive to dynamical interactions with other subsystems once the sliding surface is reached. Experiments based on the above have been performed for NASA's flexible grid experimental apparatus. The grid is designed to admit appreciable low-frequency structural dynamics, and allows for implementation of distributed computing components, inertial sensors, and actuation devices. A finite-element analysis of the grid provides the model for control system design and simulation; results of several simulations are reported on here, and a discussion of application experiments on the apparatus is presented.
The development is presented for a joint-space adaptive scheme that controls the joint position of a six-degree-of-freedom (DOF) robot end-effector performing fine and precise motion within a very limited workspace. The end-effector was built to study autonomous assembly of NASA hardware in space. The design of the adaptive controller is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method. In the development, it is assumed that the end-effector performs slowly varying motion. Computer simulation is performed to investigate the performance of the developed control scheme on position control of the end-effector. Simulation results manifest that the adaptive control scheme provides excellent tracking of several test paths.
A Cartesian-space control scheme is developed to control the motion of kinematically redundant manipulators with 7 degrees of freedom (DOF). The control scheme consists mainly of proportional derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories. The adaptation law is derived using the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that the manipulator performs non-compliant and slowly-varying motions. The developed control scheme is computationally efficient because its implementation does not require the computation of the manipulator dynamics. Computer simulation performed to evaluate the control scheme performance is presented and discussed.
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
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A Cartesian-space control scheme is developed to control the motion of kinematically redundant manipulators with 7 degrees of freedom (DOF). The control scheme consists mainly of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories. The adaptation law is derived using the concept of model reference adaptive control (MRAC) and Liapunov direct method under the assumption that the manipulator performs noncompliant and slowly-varying motions. The developed control scheme is computationally efficient because its implementation does not require the computation of the manipulator dynamics. Computer simulation performed to evaluate the control scheme performance is presented and discussed.
A multiple-scale model for compressible turbulent flows is proposed. It is assumed that turbulent eddy shocklets are formed primarily by the 'collisions' of large energetic eddies. The extra straining of the large eddy, due to their interactions with shocklets, enhances the energy cascade to smaller eddies. Model transport equations are developed for the turbulent kinetic energies and the energy transfer rates of the different scale. The turbulent eddy viscosity is determined by the total turbulent kinetic energy and the rate of energy transfer from the large scale to the small scale, which is different from the energy dissipation rate. The model coefficients in the modeled turbulent transport equations depend on the ratio of the turbulent kinetic energy of the large scale to that of the small scale, which renders the model more adaptive to the characteristics of individual flow. The model is tested against compressible free shear layers. The results agree satisfactorily with measurements.
Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.
A critical issue with oxidation protected carbon/carbon composites used for spacecraft thermal protection is the formation of coating pinholes. In laboratory experiments, artificial pinholes were drilled through SiC-coatings on a carbon/carbon material and the material was oxidized at 600, 1000, and 1400 C at reduced pressures of air. The attack of the carbon/carbon was quantified by both weight loss and a novel cross-sectioning technique. A two-zone, one dimensional diffusion control model was adapted to analyze this problem. Agreement of the model with experiment was reasonable at 1000 and 1400 C; however results at lower temperatures show clear deviations from the theory suggesting that surface reaction control plays a role.
Small Unmanned Aircraft Systems (UAS) have show to be useful for numerous observations that can be helpful in Earth science research and related applications. The potential benefits of small instrumented platforms operated within line-of-sight include high spatial resolution, quick response, minimum environmental impact, and affordability, Results to date suggest there is a strong future for small UASs operated for research and environmental monitoring purposes. For example, there is clearly significant potential for observations suitable for agricultural research and production activities. Local scale atmospheric measurements can be helpful in our understanding of water and carbon cycle processes, as well as provide monitoring of key environmental factors such as carbon dioxide and ozone. Recent work has included an emphasis on remote sensing coastal observations, w3h an eye towards related measurements in the polar regions. Specific elements associated with successfully utilizing these small airborne systems include mission definition, sensors and data systems, platform subsystems, airspace access and training.
Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation.
Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM(Trop,Nat)) and drained (PEATCLSM(Trop,Drain)) tropical peatlands. Simulations with PEATCLSM(Trop,Nat) were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM(North,Nat)) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM(Trop,Drain) was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM(Trop,Drain) outperformed CLSM, PEATCLSM(North,Nat) and PEATCLSM(Trop,Nat) over drained sites. Despite the overall improvements of PEATCLSM(Trop,Nat) over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.
This paper describes the design, development, and initial use of a generalized and configurable lunar lander simulation to support NASA’s Artemis Program. This simulation is being developed for the Crew Compartment Office (CrewCo) in the Human Landing Systems (HLS) program and is called the HLS CrewCo Lander Simulation (HCLS). The HCLS provides insight into the challenges associated with returning humans to the Moon and the particular difficulties of operating at the Lunar South Pole. A generalized lunar landing spacecraft based on a government reference design has been modeled but the simulation can be modified and adapted to model vendor designs as well. The simulation architecture and toolsets provide a flexible framework that allows for quickly prototyping and evaluating various aspects of a piloted lunar landing system. This includes the modeling of all principal human controlled flight phases: rendezvous and docking with crew transfer systems; docked orbital outpost operations; undocking and lunar transfer; lunar orbital operations; lunar deorbit, descent, and landing (DDL); lunar surface operations; lunar ascent; and return to the orbital outpost. The flexibility of the simulation allows for the integrated evaluation of potential vehicle subsystems, crew displays, guidance and control modes, and trajectory designs. The purpose of the HCLS is not to design the ideal lunar lander, but rather to understand the strengths and weaknesses of vehicle design choices.
Foregrounding climate education in formal science learning environments provides students with opportunities to develop critical climate-related knowledge and skills. However, research has shown many challenges to teaching and learning about Earth’s climate and global climate change (GCC). This longitudinal study aims to establish how secondary science teachers, over time, implement model-based climate curricula in support of students’ climate and GCC education by utilizing EzGCM. The model (EzGCM) is a data-driven, computer-based climate modeling tool use to explore global climate data. Multiple sources of data collection, including teacher interviews, classroom observations, and daily reflections, were employed to address the research question: “How did two teachers’ implementation strategies evolve over the three-year study while utilizing a model-based, climate-focused curriculum?” This study provides insight into how and why these resources [model-based climate education curricula] are utilized in science learning environments, thereby informing ongoing efforts to enhance climate education and, in doing so, preparing the next generation of climate-literate adults prepared to confront this most critical global challenge of our age. The findings showed while both teachers engaged in increasingly model-centric instructional practices, these changes were modest. Furthermore, both teacher’s observed classroom practices were less model-centric than the designed curriculum. Ultimately emphasizing the transition from existing practices to improved ones, rather than seeking the perfect approach, the study offers practical insights that can honestly assist secondary educators in real-world settings by highlighting state of climate education in secondary science classrooms.