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Results for “Cell structure identification”

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

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Hageman, Jacob↗

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Hageman, Jacob J.↗

Demonstration of prominent actin filaments in the root columella

The distribution of actin filaments within the gravity-sensing columella cells of plant roots remains poorly understood, with studies over numerous years providing inconsistent descriptions of actin organization in these cells. This uncertainty in actin organization, and thus in actin's role in graviperception and gravisignaling, has led us to investigate actin arrangements in the columella cells of Zea mays L., Medicago truncatula Gaertn., Linum usitatissiilium L. and Nicotianla benthamiana Domin. Actin organization was examined using a combination of optimized immunofluorescence techniques, and an improved fluorochrome-conjugated phalloidin labeling method reliant on 3-maleimidobenzoyl-N-hydroxy-succinimide ester (MBS) cross-linking combined with glycerol permeabilization. Confocal microscopy of root sections labeled with anti-actin antibodies revealed patterns suggestive of actin throughout the columella region. These patterns included short and fragmented actin bundles, fluorescent rings around amyloplasts and intense fluorescence originating from the nucleus. Additionally, confocal microscopy of MBS-stabilized and Alexa Fluor-phalloidin-labeled root sections revealed a previously undetected state of actin organization in the columella. Discrete actin structures surrounded the amyloplasts and prominent actin cables radiated from the nuclear surface toward the cell periphery. Furthermore, the cortex of the columella cells contained fine actin bundles (or single filaments) that had a predominant transverse orientation. We also used confocal microscopy of plant roots expressing endoplasmic reticulum (ER)-targeted green fluorescent protein to demonstrate rapid ER movements within the columella cells, suggesting that the imaged actin network is functional. The successful identification of discrete actin structures in the root columella cells forms the perception and signaling.

Non-NASA Center↗

The National Grid Project: A system overview

The National Grid Project (NGP) is a comprehensive numerical grid generation software system that is being developed at the National Science Foundation (NSF) Engineering Research Center (ERC) for Computational Field Simulation (CFS) at Mississippi State University (MSU). NGP is supported by a coalition of U.S. industries and federal laboratories. The objective of the NGP is to significantly decrease the amount of time it takes to generate a numerical grid for complex geometries and to increase the quality of these grids to enable computational field simulations for applications in industry. A geometric configuration can be discretized into grids (or meshes) that have two fundamental forms: structured and unstructured. Structured grids are formed by intersecting curvilinear coordinate lines and are composed of quadrilateral (2D) and hexahedral (3D) logically rectangular cells. The connectivity of a structured grid provides for trivial identification of neighboring points by incrementing coordinate indices. Unstructured grids are composed of cells of any shape (commonly triangles, quadrilaterals, tetrahedra and hexahedra), but do not have trivial identification of neighbors by incrementing an index. For unstructured grids, a set of points and an associated connectivity table is generated to define unstructured cell shapes and neighboring points. Hybrid grids are a combination of structured grids and unstructured grids. Chimera (overset) grids are intersecting or overlapping structured grids. The NGP system currently provides a user interface that integrates both 2D and 3D structured and unstructured grid generation, a solid modeling topology data management system, an internal Computer Aided Design (CAD) system based on Non-Uniform Rational B-Splines (NURBS), a journaling language, and a grid/solution visualization system.

Gaither, Adam↗

Proceedings of the Flat-plate Solar Array Project Research Forum on High-efficiency Crystalline Silicon Solar Cells

The high-efficiency crystalline silicon solar cells research forum addressed high-efficiency concepts, surface-interface effects, bulk effects, modeling and device processing. The topics were arranged into six interactive sessions, which focused on the state-of-the-art of device structures, identification of barriers to achieve high-efficiency cells and potential ways to overcome these barriers.

Kachare, R.↗

Crystallographic Characterization of Extraterrestrial Materials by Energy-Scanning X-ray Diffraction

We have continued our long-term project using X-ray diffraction to characterize a wide range of extraterrestrial samples. The stationary sample method with polychromatic X-rays is advantageous because the irradiated area of the sample is always same and fixed, meaning that all diffraction spots occur from the same area of the sample, however, unit cell parameters cannot be directly obtained by this method though they are very important for identification of mineral and for determination of crystal structures. In order to obtain the cell parameters even in the case of the sample stationary method, we apply energy scanning of a micro-beam of monochromatic SR at SPring-8.

Hagiya, Kenji↗

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.

Williams, Peggy S.↗

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Williams-Hayes, Peggy S.↗

High resolution radiometric measurements of convective storms during the GATE experiment

Using passive microwave data from the NASA CV-990 aircraft and radar data collected during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), an empirical model was developed relating brightness temperatures sensed at 19.35 GHz to surface rainfall rates. This model agreed well with theoretical computations of the relationship between microwave radiation and precipitation in the tropics. The GATE aircraft microwave data was then used to determine the detailed structure of convective systems. The high spatial resolution of the data permitted identification of individual cells which retained unique identities throughout their lifetimes in larger cloud masses and allowed analysis of the effects of cloud merger.

Fowler, G.↗

High-Temperature Desulfurization of Heavy Fuel-Derived Reformate Gas Streams for SOFC Applications

Desulfurization of the hot reformate gas produced by catalytic partial oxidation or autothermal reforming of heavy fuels, such as JP-8 and jet fuels, is required prior to using the gas in a solid oxide fuel cell (SOFC). Development of suitable sorbent materials involves the identification of sorbents with favorable sulfidation equilibria, good kinetics, and high structural stability and regenerability at the SOFC operating temperatures (650 to 800 C). Over the last two decades, a major barrier to the development of regenerable desulfurization sorbents has been the gradual loss of sorbent performance in cyclic sulfidation and regeneration at such high temperatures. Mixed oxide compositions based on ceria were examined in this work as regenerable sorbents in simulated reformate gas mixtures and temperatures greater than 650 C. Regeneration was carried out with dilute oxygen streams. We have shown that under oxidative regeneration conditions, high regeneration space velocities (greater than 80,000 h(sup -1)) can be used to suppress sulfate formation and shorten the total time required for sorbent regeneration. A major finding of this work is that the surface of ceria and lanthanan sorbents can be sulfided and regenerated completely, independent of the underlying bulk sorbent. This is due to reversible adsorption of H2S on the surface of these sorbents even at temperatures as high as 800 C. La-rich cerium oxide formulations are excellent for application to regenerative H2S removal from reformate gas streams at 650 to 800 C. These results create new opportunities for compact sorber/regenerator reactor designs to meet the requirements of solid oxide fuel cell systems at any scale.

Flytzani-Stephanopoulos, Maria↗

Estimation of dynamic rotor loads for the rotor systems research aircraft: Methodology development and validation

The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.

Duval, R. W.↗

Temperature dependence of Fe/++/ crystal field spectra - Implications to mineralogical mapping of planetary surfaces

Results are reported of Fe(++) crystal field spectral measurements for olivines and pyroxenes up to 400 C. The results are correlated with crystal structure data at elevated temperatures, and the validity of remote-sensed identifications of minerals on hot surfaces of the moon and Mercury is assessed. Two techniques were used to obtain spectra of minerals at elevated temperatures using a spectrophotometer. One employed a diamond cell assembly or a specially designed sample holder to measure polarized absorption spectra of heated single crystals. For the other technique, a sample holder was designed to attach to a diffuse reflectance accessory to produce reflectance spectra of heated powdered samples. Polarized absorption spectra of forsterite at 20-400 C are shown in a graph. Other graphs show the temperature dependence of Fe(++) crystal field bands in olivines, the diffuse reflectance spectra of olivine at 40-400 C, the polarization absorption spectra of orthopyroxene at 30-400 C, the diffuse reflectance spectra of pigeonite at 40-400 C, and unpolarized absorption spectra of lunar pyroxene from Apollo 15 rock 15058.

Sung, C.-M.↗

Molecular motors and their functions in plants

Molecular motors that hydrolyze ATP and use the derived energy to generate force are involved in a variety of diverse cellular functions. Genetic, biochemical, and cellular localization data have implicated motors in a variety of functions such as vesicle and organelle transport, cytoskeleton dynamics, morphogenesis, polarized growth, cell movements, spindle formation, chromosome movement, nuclear fusion, and signal transduction. In non-plant systems three families of molecular motors (kinesins, dyneins, and myosins) have been well characterized. These motors use microtubules (in the case of kinesines and dyneins) or actin filaments (in the case of myosins) as tracks to transport cargo materials intracellularly. During the last decade tremendous progress has been made in understanding the structure and function of various motors in animals. These studies are yielding interesting insights into the functions of molecular motors and the origin of different families of motors. Furthermore, the paradigm that motors bind cargo and move along cytoskeletal tracks does not explain the functions of some of the motors. Relatively little is known about the molecular motors and their roles in plants. In recent years, by using biochemical, cell biological, molecular, and genetic approaches a few molecular motors have been isolated and characterized from plants. These studies indicate that some of the motors in plants have novel features and regulatory mechanisms. The role of molecular motors in plant cell division, cell expansion, cytoplasmic streaming, cell-to-cell communication, membrane trafficking, and morphogenesis is beginning to be understood. Analyses of the Arabidopsis genome sequence database (51% of genome) with conserved motor domains of kinesin and myosin families indicates the presence of a large number (about 40) of molecular motors and the functions of many of these motors remain to be discovered. It is likely that many more motors with novel regulatory mechanisms that perform plant-specific functions are yet to be discovered. Although the identification of motors in plants, especially in Arabidopsis, is progressing at a rapid pace because of the ongoing plant genome sequencing projects, only a few plant motors have been characterized in any detail. Elucidation of function and regulation of this multitude of motors in a given species is going to be a challenging and exciting area of research in plant cell biology. Structural features of some plant motors suggest calcium, through calmodulin, is likely to play a key role in regulating the function of both microtubule- and actin-based motors in plants.

Non-NASA Center↗

Bifunctional alkaline oxygen electrodes

The authors describe the identification and testing of electrocatalysts and supports for the positive electrode of moderate-temperature, single-unit, rechargeable alkaline fuel cells. Recent work on Na(x)Pt3O4, a potential bifunctional catalyst, is described, as well as the application of novel approaches to the development of more efficient bifunctional electrode structures. The three dual-character electrodes considered here showed similar superior performance; the Pt/RhO2 and Rh/RhO2 electrodes showed slightly better performance than the Pt/IrO2 electrode. It is concluded that Na(x)Pt3O4 continues to be a promising bifunctional oxygen electrode catalyst but requires further investigation and development.

Swette, L.↗

Chemical vapor deposition growth

The chemical vapor deposition (CVD) method for the growth of Si sheet on inexpensive substrate materials is investigated. The objective is to develop CVD techniques for producing large areas of Si sheet on inexpensive substrate materials, with sheet properties suitable for fabricating solar cells meeting the technical goals of the Low Cost Silicon Solar Array Project. Specific areas covered include: (1) modification and test of existing CVD reactor system; (2) identification and/or development of suitable inexpensive substrate materials; (3) experimental investigation of CVD process parameters using various candidate substrate materials; (4) preparation of Si sheet samples for various special studies, including solar cell fabrication; (5) evaluation of the properties of the Si sheet material produced by the CVD process; and (6) fabrication and evaluation of experimental solar cell structures, using standard and near-standard processing techniques.

Ruth, R. P.↗

Chemical vapor deposition growth

The objective was to investigate and develop chemical vapor deposition (CVD) techniques for the growth of large areas of Si sheet on inexpensive substrate materials, with resulting sheet properties suitable for fabricating solar cells that would meet the technical goals of the Low Cost Silicon Solar Array Project. The program involved six main technical tasks: (1) modification and test of an existing vertical-chamber CVD reactor system; (2) identification and/or development of suitable inexpensive substrate materials; (3) experimental investigation of CVD process parameters using various candidate substrate materials; (4) preparation of Si sheet samples for various special studies, including solar cell fabrication; (5) evaluation of the properties of the Si sheet material produced by the CVD process; and (6) fabrication and evaluation of experimental solar cell structures, using impurity diffusion and other standard and near-standard processing techniques supplemented late in the program by the in situ CVD growth of n(+)/p/p(+) sheet structures subsequently processed into experimental cells.

Ruth, R. P.↗

Familial orthostatic tachycardia due to norepinephrine transporter deficiency

Orthostatic intolerance (OI) or postural tachycardia syndrome (POTS) is a syndrome primarily affecting young females, and is characterized by lightheadedness, palpitations, fatigue, altered mentation, and syncope primarily occurring with upright posture and being relieved by lying down. There is typically tachycardia and raised plasma norepinephrine levels on upright posture, but little or no orthostatic hypotension. The pathophysiology of OI is believed to be very heterogeneous. Most studies of the syndrome have focused on abnormalities in norepinephrine release. Here the hypothesis that abnormal norepinephrine transporter (NET) function might contribute to the pathophysiology in some patients with OI was tested. In a proband with significant orthostatic symptoms and tachycardia, disproportionately elevated plasma norepinephrine with standing, impaired systemic, and local clearance of infused tritiated norepinephrine, impaired tyramine responsiveness, and a dissociation between stimulated plasma norepinephrine and DHPG elevation were found. Studies of NET gene structure in the proband revealed a coding mutation that converts a highly conserved transmembrane domain Ala residue to Pro. Analysis of the protein produced by the mutant cDNA in transfected cells demonstrated greater than 98% reduction in activity relative to normal. NE, DHPG/NE, and heart rate correlated with the mutant allele in this family. CONCLUSION: These results represent the first identification of a specific genetic defect in OI and the first disease linked to a coding alteration in a Na+/Cl(-)-dependent neurotransmitter transporter. Identification of this mechanism may facilitate our understanding of genetic causes of OI and lead to the development of more effective therapeutic modalities.

Review, Tutorial↗