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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 1,189 records · Page 66

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NASA NTRS1999

A Robust and Scalable Software Library for Parallel Adaptive Refinement on Unstructured Meshes

The design and implementation of Pyramid, a software library for performing parallel adaptive mesh refinement (PAMR) on unstructured meshes, is described. This software library can be easily used in a variety of unstructured parallel computational applications, including parallel finite element, parallel finite volume, and parallel visualization applications using triangular or tetrahedral meshes. The library contains a suite of well-designed and efficiently implemented modules that perform operations in a typical PAMR process. Among these are mesh quality control during successive parallel adaptive refinement (typically guided by a local-error estimator), parallel load-balancing, and parallel mesh partitioning using the ParMeTiS partitioner. The Pyramid library is implemented in Fortran 90 with an interface to the Message-Passing Interface (MPI) library, supporting code efficiency, modularity, and portability. An EM waveguide filter application, adaptively refined using the Pyramid library, is illustrated.

Lou, John Z.↗

NASA NTRS1999

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Figueiredo, Marco A.↗

NASA NTRS1999

Monitoring and Correcting Autonomic Function Aboard Mir: NASA Technology Used in Space and on Earth to Facilitate Adaptation

The broad objective of the research was to study individual characteristics of human adaptation to long duration spaceflight and possibilities of their correction using autonomic conditioning. The changes in autonomic state during adaptation to microgravity can have profound effects on the operational efficiency of crewmembers and may result in debilitating biomedical symptoms. Ground-based and inflight experiment results showed that certain responses of autonomic nervous system were correlated with, or consistently preceded, reports of performance decrements or the symptoms. Autogenic-Feedback-Training Exercise (AFTE) is a physiological conditioning method that has been used to train people to voluntary control several of their own physiological responses. The specific objectives were: 1) To study human autonomic nervous system (ANS) responses to sustained exposure to microgravity; 2) To study human behavior/performance changes related to physiology; 3) To evaluate the effectiveness of preflight autonomic conditioning (AFTE) for facilitating adaptation to space and readaptation to Earth; and 4) To archive these data for the NASA Life Sciences Data Archive and thereby make this information available to the international scientific community.

Cowings, P.↗

NASA NTRS1999

Mechanisms of Sensorimotor Adaptation to Centrifugation

We postulate that centripetal acceleration induced by centrifugation can be used as an inflight sensorimotor countermeasure to retain and/or promote appropriate crewmember responses to sustained changes in gravito-inertial force conditions. Active voluntary motion is required to promote vestibular system conditioning, and both visual and graviceptor sensory feedback are critical for evaluating internal representations of spatial orientation. The goal of our investigation is to use centrifugation to develop an analog to the conflicting visual/gravito-inertial force environment experienced during space flight, and to use voluntary head movements during centrifugation to study mechanisms of adaptation to altered gravity environments. We address the following two hypotheses: (1) Discordant canal-otolith feedback during head movements in a hypergravity tilted environment will cause a reorganization of the spatial processing required for multisensory integration and motor control, resulting in decreased postural stability upon return to normal gravity environment. (2) Adaptation to this "gravito-inertial tilt distortion" will result in a negative after-effect, and readaptation will be expressed by return of postural stability to baseline conditions. During the third year of our grant we concentrated on examining changes in balance control following 90-180 min of centrifugation at 1.4 9. We also began a control study in which we exposed subjects to 90 min of sustained roll tilt in a static (non-rotating) chair. This allowed us to examine adaptation to roll tilt without the hypergravity induced by centrifugation. To these ends, we addressed the question: Is gravity an internal calibration reference for postural control? The remainder of this report is limited to presenting preliminary findings from this study.

Paloski, W. H.↗

NASA NTRS1998

Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects

This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.

Medina, E.↗

NASA NTRS1997

Adaptive Fuzzy Control of a Direct Drive Motor

Medina, E.↗

NASA NTRS2001

Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65' delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

Pirzadeh, Shahyar Z.↗

NASA NTRS2001

Application of Physiological Self-Regulation and Adaptive Task Allocation Techniques for Controlling Operator Hazardous States of Awareness

Prinzel, Hadley, Freeman, and Mikulka found that adaptive task allocation significantly enhanced performance only when used at the endpoints of the task workload continuum (i.e., very low or high workload), but that the technique degraded performance if invoked during other levels of task demand. These researchers suggested that other techniques should be used in conjunction with adaptive automation to help minimize the onset of hazardous states of awareness (HSA) and keep the operator 'in-the-loop.' The paper reports on such a technique that uses psychophysiological self-regulation to modulate the level of task engagement. Eighteen participants were assigned to three groups (self-regulation, false feedback, and control) and performed a compensatory tracking task that was cycled between three levels of task difficulty on the basis of the electroencephalogram (EEG) record. Those participants who had received self-regulation training performed significantly better and reported lower NASA-TLX scores than participants in the false feedback and control groups. Furthermore, the false feedback and control groups had significantly more task allocations resulting in return-to-manual performance decrements and higher EEG difference scores. Theoretical and practical implications of these results for adaptive automation are discussed.

Prinzel, Lawrence J., III↗

NASA NTRS2001

Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

Prinzel, Lawrence J., III↗

NASA NTRS2001

Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

Pirzadeh, Shahyar Z.↗

NASA NTRS2000

Effects of Adrenergic Blockade on Postpartum Adaptive Responses Induced by Labor Contractions

Prenatal exposure to labor contractions augments the expression of postnatal adaptive responses in newborn rats. Near-term rat fetuses exposed prenatally to simulated labor contractions and delivered by cesarean section breath and attach to nipples at greater frequencies than non-stimulated fetuses. Plasma NE (norepinephrine) and EPI (epinephrine) was significantly elevated in newborn rats exposed to vaginal birth or simulated labor contractions (compressions) with cesarean delivery as compared to non-compressed fetuses. In the present study, we investigated adrenergic mechanisms underlying labor-induced postnatal adaptive responses. Following spinal transection of late pregnant rat dams, fetuses were administered neurogenic or non-neurogenic adrenergic blockade: 1) bretylium (10 mg/kg sc) to prevent sympathetic neuronal release, 2) hexamethonium (30 mg/kg) to produce ganglionic blockade, 3) phenoxybenzanune (10mg/kg sc), an a- adrenergic receptor antagonist, 4) ICI-118551, 10 mg/kg sc), a b receptor antagonist, or 5) vehicle alone. Fetuses were either compressed (C) or non-compressed (NC) prior to cesarean delivery. a- and b- adrenergic antagonists reduced respiration and nipple attachment rates while sympathetic and vehicle alone did not. These results provide additional support for the hypothesis that adaptive neonatal effects of labor contractions are mediated by adrenal and extra-adrenal catecholamines.

Ronca, April E.↗

NASA NTRS2001

Psychophysiological Control of Acognitive Task Using Adaptive Automation

The major focus of the present proposal was to examine psychophysiological variables related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding worker performance. Byrne and Parasuraman have argued for the use of psychophysiological measures in the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a cognitive vigilance task. Previous research in our laboratory, supported by NASA, has demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative than a positive, feedback condition. In addition, this condition produces less subjective workload and larger P300 event related potentials to auditory stimuli presented in a concurrent oddball task. We have also recently shown that the closed-loop system used to control the level of automation in a tracking task can also be used to control the event rate of stimuli in a vigilance monitoring task. By changing the event rate based on the subject's index of arousal, we have been able to produce improved monitoring, relative to various control groups. We have demonstrated in our initial closed-loop experiments with the the vigilance paradigm that using a negative feedback contingency (i.e. increasing event rates when the EEG index is low and decreasing event rates when the EEG index is high) results in a marked decrease of the vigilance decrement over a 40 minute session. This effect is in direct contrast to performance of a positive feedback group, as well as a number of other control groups which demonstrated the typical vigilance decrement. Interestingly, however, the negative feedback group performed at virtually the same level as a yoked control group. The yoked control group received the same order of changes in event rate that were generated by the negative feedback subjects using the closed-loop system. Thus it would appear to be possible to optimize vigilance performance by controlling the stimuli which subjects are asked to process.

Freeman, Frederick↗

NASA NTRS1994

Is Linear Displacement Information Or Angular Displacement Information Used During The Adaptation of Pointing Responses To An Optically Shifted Image?

Twenty-four observers looked through a pair of 20 diopter wedge prisms and pointed to an image of a target which was displaced vertically from eye level by 6 cm at a distance of 30 cm. Observers pointed 40 times, using only their right hand, and received error-corrective feedback upon termination of each pointing response (terminal visual feedback). At three testing distances, 20, 30, and 40 cm, ten pre-exposure and ten post-exposure pointing responses were recorded for each hand as observers reached to a mirror-viewed target located at eye level. The difference between pre- and post-exposure pointing response (adaptive shift) was compared for both Exposed and Unexposed hands across all three testing distances. The data were assessed according to the results predicted by two alternative models for processing spatial-information: one using angular displacement information and another using linear displacement information. The angular model of spatial mapping best predicted the observer's pointing response for the Exposed hand. Although the angular adaptive shift did not change significantly as a function of distance (F(2,44) = 1.12, n.s.), the linear adaptive shift increased significantly over the three testing distances 02 44) = 4.90 p less than 0.01).

Bautista, Abigail B.↗

NASA NTRS1997

Evaluation of a Neural Adaptive Flight Controller

The objective of this paper is to present results from the evaluation of a direct adaptive tracking controller. The control architecture employs both pre-trained and an on-line neural networks to represent the non-linear aircraft dynamics in the model inversion portion of the controller. The aircraft model used for this evaluation is representative of the F-15 Advanced Control Technology for Integrated Vehicles (ACTIVE) aircraft. The controller was evaluated for three cases: (1) nominal conditions; (2) loss of control power; and (3) loss of control power in the presence of atmospheric turbulence. The results were compared with the existing F-15 ACTIVE conventional mode controller in all cases. The results indicate extremely desirable airframe stabilization characteristics for case (1) that do not degrade significantly for case (2) or (3) as does the conventional mode controller. It was concluded that this controller exhibits both stable and robust adaptive characteristics when subjected to mild and extreme loss of control power conditions. Integration of this neural adaptive flight controller into the full non-linear six degree-of-freedom F-15 ACTIVE simulation is recommended for evaluation in a real-time high fidelity piloted simulation environment.

Totah, Joseph J.↗

NASA NTRS2001

Designing Adaptive Low-Dissipative High Order Schemes for Long-Time Integrations

A general framework for the design of adaptive low-dissipative high order schemes is presented. It encompasses a rather complete treatment of the numerical approach based on four integrated design criteria: (1) For stability considerations, condition the governing equations before the application of the appropriate numerical scheme whenever it is possible; (2) For consistency, compatible schemes that possess stability properties, including physical and numerical boundary condition treatments, similar to those of the discrete analogue of the continuum are preferred; (3) For the minimization of numerical dissipation contamination, efficient and adaptive numerical dissipation control to further improve nonlinear stability and accuracy should be used; and (4) For practical considerations, the numerical approach should be efficient and applicable to general geometries, and an efficient and reliable dynamic grid adaptation should be used if necessary. These design criteria are, in general, very useful to a wide spectrum of flow simulations. However, the demand on the overall numerical approach for nonlinear stability and accuracy is much more stringent for long-time integration of complex multiscale viscous shock/shear/turbulence/acoustics interactions and numerical combustion. Robust classical numerical methods for less complex flow physics are not suitable or practical for such applications. The present approach is designed expressly to address such flow problems, especially unsteady flows. The minimization of employing very fine grids to overcome the production of spurious numerical solutions and/or instability due to under-resolved grids is also sought. The incremental studies to illustrate the performance of the approach are summarized. Extensive testing and full implementation of the approach is forthcoming. The results shown so far are very encouraging.

Yee, Helen C.↗

NASA NTRS1998

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

Oliker, Leonid↗

NASA NTRS1998

Dynamic Load Balancing for Adaptive Unstructured Grids

Dynamic mesh adaptation on unstructured grids is a powerful tool for computing unsteady three-dimensional problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture phenomena of interest, such procedures make standard computational methods more cost effective. Highly refined meshes are required to accurately capture shock waves, contact discontinuities, vortices, and shear layers in fluid flow problems. Adaptive meshes have also proved to be useful in several other areas of computational science and engineering like computer vision and graphics, semiconductor device modeling, and structural mechanics. Local mesh adaptation provides the opportunity to obtain solutions that are comparable to those obtained on globally-refined grids but at a much lower cost. Additional information is contained in the original extended abstract.

Biswas, Rupak↗

NASA NTRS1999

Self-Avoiding Walks Over Adaptive Triangular Grids

Space-filling curves is a popular approach based on a geometric embedding for linearizing computational meshes. We present a new O(n log n) combinatorial algorithm for constructing a self avoiding walk through a two dimensional mesh containing n triangles. We show that for hierarchical adaptive meshes, the algorithm can be locally adapted and easily parallelized by taking advantage of the regularity of the refinement rules. The proposed approach should be very useful in the runtime partitioning and load balancing of adaptive unstructured grids.

Heber, Gerd↗