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At least 1,045 records · Page 58

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NASA NTRS1982

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstance, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviours. The model admits several possibilities for adaptive mechanisms which do not involve internal model updating. Further systematic efforts to experimentally refine and validate the model are indicated.

Oman, C. M.↗

NASA NTRS1985

Adaptive Inverse Control for Rotorcraft Vibration Reduction

This thesis extends the Least Mean Square (LMS) algorithm to solve the mult!ple-input, multiple-output problem of alleviating N/Rev (revolutions per minute by number of blades) helicopter fuselage vibration by means of adaptive inverse control. A frequency domain locally linear model is used to represent the transfer matrix relating the higher harmonic pitch control inputs to the harmonic vibration outputs to be controlled. By using the inverse matrix as the controller gain matrix, an adaptive inverse regulator is formed to alleviate the N/Rev vibration. The stability and rate of convergence properties of the extended LMS algorithm are discussed. It is shown that the stability ranges for the elements of the stability gain matrix are directly related to the eigenvalues of the vibration signal information matrix for the learning phase, but not for the control phase. The overall conclusion is that the LMS adaptive inverse control method can form a robust vibration control system, but will require some tuning of the input sensor gains, the stability gain matrix, and the amount of control relaxation to be used. The learning curve of the controller during the learning phase is shown to be quantitatively close to that predicted by averaging the learning curves of the normal modes. For higher order transfer matrices, a rough estimate of the inverse is needed to start the algorithm efficiently. The simulation results indicate that the factor which most influences LMS adaptive inverse control is the product of the control relaxation and the the stability gain matrix. A small stability gain matrix makes the controller less sensitive to relaxation selection, and permits faster and more stable vibration reduction, than by choosing the stability gain matrix large and the control relaxation term small. It is shown that the best selections of the stability gain matrix elements and the amount of control relaxation is basically a compromise between slow, stable convergence and fast convergence with increased possibility of unstable identification. In the simulation studies, the LMS adaptive inverse control algorithm is shown to be capable of adapting the inverse (controller) matrix to track changes in the flight conditions. The algorithm converges quickly for moderate disturbances, while taking longer for larger disturbances. Perfect knowledge of the inverse matrix is not required for good control of the N/Rev vibration. However it is shown that measurement noise will prevent the LMS adaptive inverse control technique from controlling the vibration, unless the signal averaging method presented is incorporated into the algorithm.

Jacklin, Stephen A.↗

NASA NTRS2022

Coupling Carbon Oxidation and Surface Recession in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that are often made out of carbon-based reinforcement and a polymeric matrix. They endure high-temperature oxidation and surface recession when re-entering Earth’s atmosphere. Ablation is the result of many coupled and competing thermal, mechanical, and chemical phenomena, and it is difficult to isolate the role of each on the overall degradation of the TPS. Here we develop an ablation model for material recession coupled explicitly to finite rate carbon oxidation in complex microstructures. In this work, Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al, was adapted to tally surface reactions and other surface data on a per-grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also develop robust algorithms which handle the evolution of the flow cells and solid material regions, including split cells (flow cell divided in two by a solid surface). Finally, we demonstrate our implicit chemistry model for 2D and 3D geometries by producing reaction statistics and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗

NASA NTRS1994

Operations for Learning with Graphical Models

This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian net- works, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, and the manipulation of probability models from the exponential family. These operations adapt existing techniques from statistics and automatic differentiation to graphs. Two standard algorithm schemes for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximization algorithm. Some algorithms are developed in this graphical framework including a generalized version of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing some popular algorithms that fall within the framework presented. The main original contributions here are the decomposition techniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.

Buntine, Wray L.↗

NASA NTRS1993

Techniques and resources for storm-scale numerical weather prediction

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

Droegemeier, Kelvin↗

NASA NTRS2018

Adaptive Control Allocation for Powered Descent Vehicles

The following work details a study into real-time failure adaptive control allocation method for powered descent vehicle systems. The motivation for this work is to enable future human and robotic missions utilizing a powered descent system to tolerate engine failures in flight without the loss of crew or assets. This study is conducted using a six degree-of-freedom trajectory simulation of a PDV (Powered Descent Vehicle) experiencing either a loss of thrust or an engine stuck full on failure scenario. Sequential least squares in the frequency domain is used on-board to process inertial measurement unit (IMU) data and generate an estimate of the PDV plant model, which is then fed to the guidance and control system. Data used by the sequential least squares method is generated from an in-flight maneuver. The work herein focuses on determining a maneuver that is least impactful to the PDV trajectory and enables a suitable plant model estimate. A 1.5-second-long maneuver with an amplitude of 5 percent throttle is determined to provide suitable data for the sequential least squares method to estimate a plant model. A PDV implementing this method can adapt to a single engine failure and continue to reach its touchdown conditions.

Green, Justin S.↗

NASA NTRS1974

Adaptive sequential estimation with applications

A sequential estimator is presented and demonstrated which successfully tracks the system state and model errors in the presence of significant and unpredictable system or environmental variations. This adaptive estimation concept is shown to lead to a new and attractive approach to parameter identification problems. Simulation results are presented in an orbit determination problem, where the estimator tracks the orbit and unmodeled accelerations due to errors in the geopotential model. Some results in a re-entry trajectory estimation problem are also summarized.

Jazwinski, A. H.↗

NASA NTRS2024

Asheville Urban Development II: Mapping Urban Heat to Support Cooling Initiatives and Climate Resilience Planning in the Greater Asheville Area

Asheville, North Carolina experiences the urban heat island effect, where temperatures in the city are higher than in surrounding rural areas. This effect intensifies with increased urbanization and less vegetative cover. Asheville’s urban heat island was exacerbated by population increases and tree cover decline, escalating the need for heat mitigation. We partnered with the City of Asheville’s Sustainability Department and Asheville GreenWorks whose actions prioritize sustainable city planning and equitable climate resilience. Using NASA Earth observations and ancillary datasets we spatially mapped urban heat, heat vulnerability, and cooling and adaptive capacity from 2019-2023. To map urban heat, we used Landsat 8 and 9 Operational Land Imager and Thermal Infrared Sensor for land surface temperature and albedo data and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station for evapotranspiration data. We assessed heat vulnerability using the urban heat data andthe Centers for Disease Control and Prevention’s Social Vulnerability Index. To evaluate cooling and adaptive capacity we used the InVEST Urban Cooling Model, integrating our heat vulnerability analysis with land use and cover data from Sentinel-1 Synthetic Aperture Rada rand Sentinel-2 Multispectral Instrument. Our results revealed distinct spatial patterns of urban heat, heat vulnerability, and cooling and adaptive capacity in Asheville with downtown as the focal hotspot and an outward decreasing radial pattern. These findings highlight targeted need for interventions to reduce heat impacts, address environmental injustices, and enhance climate resilience. Our project provided research to local organizations that can be used for heat mitigation in the greater Asheville area.

Authors not in NED but are confirmed contractors. ↗

NASA NTRS1986

Adaptive finite element methods for compressible flow problems

Some recent work on adaptive FEMs for solving transient Euler equations in two-dimensional domains is summarized. The formulation of an FEM model of the Euler equations is shown, and the application of the adaptive strategies to data management schemes is addressed. Sample numerical results from the application of the model and strategies to the flow over a step and to transient cases are given.

Oden, J. T.↗

NASA NTRS2002

Skeletal Adaptation to Daily Activity: A Biochemical Perspective

Musculoskeletal forces generated by normal daily activity on Earth maintain the functional and structural properties of muscle and bone throughout most of one's adult life. A reduction in the level of cumulative daily loading caused by space flight, bed rest or spinal cord injury induces rapid muscle atrophy, functional changes in muscle, and bone resorption in regions subjected to the reduced loading. Bone cells in culture and bone tissue reportedly respond to a wide variety of non-mechanical and mechanical stimuli ranging, from electromagnetic fields, and hormones to small amplitude, high frequency vibrations, fluid flow, strain rate, and stress/strain magnitude. However, neither the transduction mechanism that transforms the mechanical input into a muscle or bone metabolic response nor the characteristics, of the loading history that directly or indirectly stimulates the cell is known. Identifying the factors contributing to the input stimulus will have a major impact on the design of effective countermeasures for long duration space flight. This talk will present a brief overview of current theories of bone remodeling and functional adaptation to mechanical loading. Work from our lab will be presented from the perspective of daily cumulative loading on Earth and its relationship to bone density and structure. Our objective is to use the tibia and calcaneus as model bone sites of cortical and cancellous bone adaptation, loaded daily by musculoskeletal forces in equilibrium with the ground reaction force. All materials that will be discussed are in the open scientific literature.

Whalen, Robert T.↗

NASA NTRS1979

Analysis and design of an adaptive multi-loop controlled two winding buck/boost regulator

Small signal low frequency linear average model is derived for a multi-loop controlled two-winding buck/boost converter employing average techniques and the describing function method. The model reveals that a well-designed multi-loop control can provide a second-order zero adaptive to output filter parameter changes due to component tolerances, temperature changes, aging, and the effect of duty cycle modulation. It also can provide stabilization effect by shifting the positive zero to the left-half S-plane. Design guidelines are formulated to optimize regulator-loop dependent characteristics.

Mahmoud, M. F.↗

NASA NTRSDate not supplied

Initial Evaluation of CropManage Decision-Support Model for Vineyard ET Estimation

The CropManage(CM) decision-support web application was originally developed by U.C. Cooperative Extension to support evapotranspiration (ET) based irrigation scheduling and nutrient management of cool-season vegetables. The model uses prescribed crop phenology curves to develop daily estimates of fractional green canopy cover (Fc) within the field. Periodic Fc observations acquired by ground-based methods or imported from NASA’s Satellite Irrigation Management Support (SIMS) can be used to adjust the prescribed timeseries for such factors as weather anomalies or non-standard agronomic practice, as needed. Fc is then converted to daily crop coefficient (fraction of reference ET) values. The crop coefficient is combined with reference evapotranspiration, collected by the California Irrigation Management Information System, to derive daily ET estimates for the given field. Irrigation runtime recommendations are issued for a given date based on total ET since the last irrigation event (less any rainfall), and corrected for distribution uniformity of the water delivery system. In this project, CM was adapted to vineyards by adding sub-models to account for early-season depletion of stored soil moisture, cover crop presence, and intentional water stress. An initial trial was performed on a Central Coast winegrape vineyard, where an eddy covariance tower measured daily ET during from May-Dec 2020. Total ET for the period showed strong agreement between the tower-based measurements (443 mm) and the CM model (431 mm). The model tended to overestimate cumulative ET during mid-June by up to 30 mm (about 15%) and later underestimated cumulative ET by as much as 65 mm (about 23%) in late September, suggesting that additional model calibration is needed to improve simulation of within-season variability. Results will be reported for trials on additional vineyard sites conducted during the 2021 season.

Evaluation↗

NASA NTRS1989

Residual interference and wind tunnel wall adaption

Measured flow variables near the test section boundaries, used to guide adjustments of the walls in adaptive wind tunnels, can also be used to quantify the residual interference. Because of a finite number of wall control devices (jacks, plenum compartments), the finite test section length, and the approximation character of adaptation algorithms, the unconfined flow conditions are not expected to be precisely attained even in the fully adapted stage. The procedures for the evaluation of residual wall interference are essentially the same as those used for assessing the correction in conventional, non-adaptive wind tunnels. Depending upon the number of flow variables utilized, one can speak of one- or two-variable methods; in two dimensions also of Schwarz- or Cauchy-type methods. The one-variable methods use the measured static pressure and normal velocity at the test section boundary, but do not require any model representation. This is clearly of an advantage for adaptive wall test section, which are often relatively small with respect to the test model, and for the variety of complex flows commonly encountered in wind tunnel testing. For test sections with flexible walls the normal component of velocity is given by the shape of the wall, adjusted for the displacement effect of its boundary layer. For ventilated test section walls it has to be measured by the Calspan pipes, laser Doppler velocimetry, or other appropriate techniques. The interface discontinuity method, also described, is a genuine residual interference assessment technique. It is specific to adaptive wall wind tunnels, where the computation results for the fictitious flow in the exterior of the test section are provided.

Mokry, Miroslav↗

NASA NTRS1988

Dynamic models for simulation of the 70-M antenna axis servos

Dynamic models for the various functional elements of the 70 m antenna axis servos are described. The model representing the digital position controller, the linear and nonlinear properties of the physical hardware, and the dynamics of the flexible antenna structure are encoded in six major function blocks. The general modular structure of the function blocks facilitates their adaptation to a variety of dynamic simulation studies. Model parameter values were calculated from component specifications and design data. A simulation using the models to predict limit cycle behavior produced results in excellent agreement with field test data from the DSS 14 70-m antenna.

Hill, R. E.↗

NASA NTRS2001

Unic Unstructured CFD Methodology Development

Base heating characteristics is crucial to the success and the overall performance of the X-33 engine. Base heating is important throughout the entire flight trajectory due to the aerospike engine design of X-33. The base region is surrounded by the hot-gas plume, which expands, circulates and impinges on the base. An advanced computation fluid dynamics method is employed in an effort to develop a robust, accurate and efficient tool for the X-33 base heating performance predictions. This computational tool is developed based on a Navier-Stokes flow solver, which is suitable for general complex geometry and includes turbulence, finite-rate chemistry, and radiation models. To fulfill the fast turnaround requirement as a design analysis tool, adaptive mesh refinement method and parallel-computing algorithm are also incorporated in the present model. Case study for the X-33 base-region fluid dynamics and heat transfer characteristics are presented.

Chen, Y. S.↗

NASA NTRS1994

Dynamic Simulation of a Periodic 10 K Sorption Cryocooler

A transient thermal simulation model has been developed to simulate the dynamic performance of a multiple-stage 10 K sorption cryocooler for spacecraft sensor cooling applications that require periodic quick-cooldown (under 2 minutes) , negligible vibration, low power consumption, and long life (5 to 10 years). The model was specifically designed to represent the Brilliant Eyes Ten-Kelvin Sorption Cryocooler Experiment (BETSCE), but it can be adapted to represent other sorption cryocooler systems as well. The model simulates the heat transfer, mass transfer, and thermodynamic processes in the cryostat and the sorbent beds for the entire refrigeration cycle, and includes the transient effects of variable hydrogen supply pressures due to expansion and overflow of hydrogen during the cooldown operation. The paper describes model limitations and simplifying assumptions, with estimates of errors induced by them, and presents comparisons of performance predictions with ground experiments. An important benefit of the model is its ability to predict performance sensitivities to variations of key design and operational parameters. The insights thus obtained are expected to lead to higher efficiencies and lower weights for future designs.

cryocooler design performance sorption simulation ↗

NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗

NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Bosworth, John T.↗