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At least 235 records · Page 13

Tests of the Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

Satellite lightning imagers such as the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) and the future GOES-R Geostationary Lightning Mapper (GLM) are designed to detect total lightning (ground flashes + cloud flashes). However, there is a desire to discriminate ground flashes from cloud flashes from the vantage point of space since this would enhance the overall information content of the satellite lightning data and likely improve its operational and scientific applications (e.g., in severe weather warning, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters (one of which is the ground flash fraction), a scalar function was minimized by a numerical method. In order to improve this optimization, a Grobner basis solution was introduced to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. In this study, we test the efficacy of the Grobner basis initialization using actual lightning imager measurements and ground flash truth derived from the national lightning network.

Koshak, William↗

Validation of Atmosphere/Ionosphere Signals Associated with Major Earthquakes by Multi-Instrument Space-Borne and Ground Observations

The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific regions of the atmosphere and the modifications, by dc electric fields, in the ionosphere-atmosphere electric circuit. We retrospectively analyzed temporal and spatial variations of four different physical parameters (gas/radon counting rate, lineaments change, long-wave radiation transitions and ionospheric electron density/plasma variations) characterizing the state of the lithosphere/atmosphere coupling several days before the onset of the earthquakes. Validation processes consist in two phases: A. Case studies for seven recent major earthquakes: Japan (M9.0, 2011), China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and, Chile (M8.8, 2010) and B. A continuous retrospective analysis was preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009. Satellite, ground surface, and troposphere data were obtained from Terra/ASTER, Aqua/AIRS, POES and ionospheric variations from DEMETER and COSMIC-I data. Radon and GPS/TEC were obtaining from monitoring sites in Taiwan, Japan and Italy and from global ionosphere maps (GIM) respectively. Our analysis of ground and satellite data during the occurrence of 7 global earthquakes has shown the presence of anomalies in the atmosphere. Our results for Tohoku M9.0 earthquake show that on March 7th, 2011 (4 days before the main shock and 1 day before the M7.2 foreshock of March 8, 2011) a rapid increase of emitted infrared radiation was observed by the satellite data and an anomaly was developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. Similar approach for analyzing atmospheric and ionospheric parameters has been applied for China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and Chile (M8.8, 2010) eahquakes. Results have revealed the presence of related variations of these parameters implying their connection with the earthquake process. The second phase (B) of this validation included 102 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 10% and has been calculated for the same month of the earthquake occurrence for the entire period of analysis (2003-2009). The commonalities for detecting atmospheric/ionospheric anomalies are: i.) Regularly appearance over regions of maximum stress (i.e., along plate boundaries); ii.) Anomaly existence over land and sea; and iii) association with M>5.9 earthquakes not deeper than 100km. Due to their long duration over the same region these anomalies are not consistent with a meteorological origin. Our initial results from the ISTF validation of multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area, one to seven (average) days prior to the largest earthquakes, and suggest that it could be explained by a coupling process between the observed physical parameters and the pre-earthquake preparation processes.

Ouzounov, Dimitar↗

Inorganic salt mixtures as electrolyte media in fuel cells

Fuel cell designs and techniques for converting chemical energy into electrical energy uses a fuel cell are disclosed. The designs and techniques include an anode to receive fuel, a cathode to receive oxygen, and an electrolyte chamber in the fuel cell, including an electrolyte medium, where the electrolyte medium includes an inorganic salt mixture in the fuel cell. The salt mixture includes pre-determined quantities of at least two salts chosen from a group consisting of ammonium trifluoromethanesulfonate, ammonium trifluoroacetate, and ammonium nitrate, to conduct charge from the anode to the cathode. The fuel cell includes an electrical circuit operatively coupled to the fuel cell to transport electrons from the cathode.

Angell, Charles Austen↗

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗

Superconducting Effects in Optimization of Magnetic Penetration Thermometers for X-ray Microcalorimeters

We have made high resolution x-ray microcalorimeters using superconducting MoAu bilayers and Nb meander coils. The temperature sensor is a Magnetic Penetration Thermometer (MPT). Operation is similar to metallic magnetic calorimeters, but instead of the magnetic susceptibility of a paramagnetic alloy, we use the diamagnetic response of the superconducting MoAu to sense temperature changes in an x-ray absorber. Flux-temperature responsivtty can be large for small sensor heat capacity, with enough dynamic range for applications. We find models of observed flux-temperature curves require several effects to explain flux penetration or expulsion in the microscopic devices. The superconductor is non-local, with large coherence length and weak pinning of flux. At lowest temperatures, behavior is dominated by screening currents that vary as a result of the temperature dependence of the magnetic penetration depth, modified by the effect of the nonuniformity of the applied field occurring on a scale comparable to the coherence length. In the temperature regime where responslvity is greatest, spadal variations in the order parameter become important: both local variations as flux enters/leaves the film and an intermediate state is formed, and globally as changing stability of the electrical circuit creates a Meissner transition and flux is expelled/penetrates to minimize free energy.

Stevenson, Thomas R.↗

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

Structural Decomposition↗

On the Variability of Wilson Currents by Storm Type and Phase

Storm total conduction currents from electrified clouds are thought to play a major role in maintaining the potential difference between the earth's surface and the upper atmosphere within the Global Electric Circuit (GEC). However, it is not entirely known how the contributions of these currents vary by cloud type and phase of the clouds life cycle. Estimates of storm total conduction currents were obtained from data collected over two decades during multiple field campaigns involving the NASA ER-2 aircraft. In this study the variability of these currents by cloud type and lifecycle is investigated. We also compared radar derived microphysical storm properties with total storm currents to investigate whether these storm properties can be used to describe the current variability of different electrified clouds. The ultimate goal is to help improve modeling of the GEC via quantification and improved parameterization of the conduction current contribution of different cloud types.

Deierling, Wiebke↗

Evaluation of Dielectric-Barrier-Discharge Actuator Substrate Materials

A key, enabling element of a dielectric barrier discharge (DBD) actuator is the dielectric substrate material. While various investigators have studied the performance of different homogeneous materials, most often in the context of related DBD experiments, fundamental studies focused solely on the dielectric materials have received less attention. The purpose of this study was to conduct an experimental assessment of the body-force-generating performance of a wide range of dielectric materials in search of opportunities to improve DBD actuator performance. Materials studied included commonly available plastics and glasses as well as a custom-fabricated polyimide aerogel. Diagnostics included static induced thrust, electrical circuit parameters for 2D surface discharges and 1D volume discharges, and dielectric material properties. Lumped-parameter circuit simulations for the 1D case were conducted showing good correspondence to experimental data provided that stray capacitances are included. The effect of atmospheric humidity on DBD performance was studied showing a large influence on thrust. The main conclusion is that for homogeneous, dielectric materials at forcing voltages less than that required for streamer formation, the material chemical composition appears to have no effect on body force generation when actuator impedance is properly accounted for.

Wilkinson, Stephen P.↗

Experimental Investigation of a Direct-drive Hall Thruster and Solar Array System at Power Levels up to 10 kW

As NASA considers future exploration missions, high-power solar-electric propulsion (SEP) plays a prominent role in achieving many mission goals. Studies of high-power SEP systems (i.e. tens to hundreds of kilowatts) suggest that significant mass savings may be realized by implementing a direct-drive power system, so NASA recently established the National Direct-Drive Testbed to examine technical issues identified by previous investigations. The testbed includes a 12-kW solar array and power control station designed to power single and multiple Hall thrusters over a wide range of voltages and currents. In this paper, single Hall thruster operation directly from solar array output at discharge voltages of 200 to 450 V and discharge powers of 1 to 10 kW is reported. Hall thruster control and operation is shown to be simple and no different than for operation on conventional power supplies. Thruster and power system electrical oscillations were investigated over a large range of operating conditions and with different filter capacitances. Thruster oscillations were the same as for conventional power supplies, did not adversely affect solar array operation, and were independent of filter capacitance from 8 to 80 ?F. Solar array current and voltage oscillations were very small compared to their mean values and showed a modest dependence on capacitor size. No instabilities or anomalous behavior were observed in the thruster or power system at any operating condition investigated, including near and at the array peak power point. Thruster startup using the anode propellant flow as the power 'switch' was shown to be simple and reliable with system transients mitigated by the proper selection of filter capacitance size. Shutdown via cutoff of propellant flow was also demonstrated. A simple electrical circuit model was developed and is shown to have good agreement with the experimental data.

Snyder, John S.↗

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

structural model decomposition↗

Infrared Dielectric Properties of Low-Stress Silicon Oxide

Silicon oxide thin films play an important role in the realization of optical coatings and high-performance electrical circuits. Estimates of the dielectric function in the far- and mid-infrared regime are derived from the observed transmittance spectrum for a commonly employed low-stress silicon oxide formulation. The experimental, modeling, and numerical methods used to extract the dielectric function are presented.

Silicon oxide↗

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Hybrid Systems Diagnosis↗

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics↗

Vibration Ring

A vibration ring is provided to remove vibratory energy from a machine driveline. The vibration ring includes a compression cage configured to generate vibratory excitation within a material. The material is configured to generate an electric charge dissipated through or harvested by an electric circuit.

Asnani, Vivake M.↗

Coilgun Acceleration Model Containing Multiple Interacting Coils

A coilgun operates by pulsing current through an axially-arranged series of independently-controlled coils inductively interacting with a small, electrically-conductive, azimuthally-symmetric projectile to accelerate it to high velocities. The electrical circuits are programmed to pulse current through the coils in such a way so as to impart further electromagnetic acceleration in each stage. A method is developed to calculate the mutual inductance between the coils and between each coil and the projectile. These terms are used to write a system of first-order ordinary differential equations governing the projectile velocity and the current flow in each coil. While the inclusion of the electromagnetic interactions between coils significantly complicates the equation set as more coil sets are included in the problem, casting the problem symbolically in mass matrix form permits solution using standard numerical Runge-Kutta techniques. Comparing a projectile with a single-turn to that comprised of nine-turns, the inductance of the former is much smaller, but this leads to a greater induced projectile current. The lower inductance and greater current appear to offset each other with little difference in the acceleration profile for the two cases. For the limited cases studied, coils with a discharge half-cycle equal to the time for a projectile to transit from one coil to the next yield increased efficiency.

Polzin, Kurt A.↗

PMSM Parameter Estimation using a Linear Unknown Input Interval Observer

In this paper, the problem of permanent magnet synchronous motor (PMSM) speed and unknown load torque estimation is addressed. For this purpose, a interval unknown input observer (UIO) for linear time-invariant (LTI) systems is used. First, the PMSM model is linearized in order to make it in a suitable form for the linear interval UIO. Then, the interval UIO is applied to allow the joint estimation of the motor speed and the unknown load torque disturbance. The main advantages of this approach is that it not only allows the joint state and unknown input estimation, but also to take the different uncertainty sources into account. Indeed, taking model and measurement uncertainty into account is crucial. Assuming that the measurement noise and disturbances are bounded, lower and upper bounds are first computed for the unmeasured state (motor speed) and then for the unknown input (load torque). The proposed approach and its limitations are demonstrated with the nonlinear PMSM model derived from its equivalent electrical circuit.

Elinirina I Robinson↗

Estimation of Permanent Magnet Synchronous Motor Parameters using a Linear Unknown Input Interval Observer

This paper develops and evaluate a technique to estimate the speed and unknown load torque of a permanent magnet synchronous motor (PMSM). An interval unknown input observer (UIO) for linear time-invariant (LTI) systems is designed and utilized to estimate the PMSM parameters. Interval UIOs are advantageous as they allow for the estimation of both states and unknown inputs, while accounting for varying uncertainty sources, such as model and measurement uncertainties inherent in dynamic systems and processes. First, the nonlinear PMSM model is linearized to transform it to a suitable form for application of the linear interval UIO. Then, the interval UIO is applied to jointly estimate the motor speed and the unknown load torque disturbance. Assuming that the measurement noise and disturbances are bounded, lower and upper bounds are first computed for the unmeasured state (motor speed) and then for the unknown input (load torque). The proposed approach and its limitations are demonstrated for the nonlinear PMSM model derived from its equivalent electrical circuit.

Elinirina I Robinson↗

Control of oscillations in a discharge circuit

Development of electric discharge circuit damping element which increases in resistance with current and time is described. Damping element is resistor made of tungsten wire which has large resistance-temperature coefficient. Specifications of tungsten resistor and incorporation into circuit are explained.

Cheng, D. Y.↗