945 resultados para Redispatch of active power


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Electrical resistance of both the electrodes of a lead-acid battery increases during discharge due to formation of lead sulfate, an insulator. Work of Metzendorf 1] shows that resistance increases sharply at about 65% conversion of active materials, and battery stops discharging once this critical conversion is reached. However, these aspects are not incorporated into existing mathematical models. Present work uses the results of Metzendorf 1], and develops a model that includes the effect of variable resistance. Further, it uses a reasonable expression to account for the decrease in active area during discharge instead of the empirical equations of previous work. The model's predictions are compared with observations of Cugnet et al. 2]. The model is as successful as the non-mechanistic models existing in literature. Inclusion of variation in resistance of electrodes in the model is important if one of the electrodes is a limiting reactant. If active materials are stoichiometrically balanced, resistance of electrodes can be very large at the end of discharge but has only a minor effect on charging of batteries. The model points to the significance of electrical conductivity of electrodes in the charging of deep discharged batteries. (C) 2014 Elsevier B.V. All rights reserved.

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Storage of water within a river basin is often estimated by analyzing recession flow curves as it cannot be `instantly' estimated with the aid of available technologies. In this study we explicitly deal with the issue of estimation of `drainable' storage, which is equal to the area under the `complete' recession flow curve (i.e. a discharge vs. time curve where discharge continuously decreases till it approaches zero). But a major challenge in this regard is that recession curves are rarely `complete' due to short inter-storm time intervals. Therefore, it is essential to analyze and model recession flows meaningfully. We adopt the wellknown Brutsaert and Nieber analytical method that expresses time derivative of discharge (dQ/dt) as a power law function of Q : -dQ/dt = kQ(alpha). However, the problem with dQ/dt-Q analysis is that it is not suitable for late recession flows. Traditional studies often compute alpha considering early recession flows and assume that its value is constant for the whole recession event. But this approach gives unrealistic results when alpha >= 2, a common case. We address this issue here by using the recently proposed geomorphological recession flow model (GRFM) that exploits the dynamics of active drainage networks. According to the model, alpha is close to 2 for early recession flows and 0 for late recession flows. We then derive a simple expression for drainable storage in terms the power law coefficient k, obtained by considering early recession flows only, and basin area. Using 121 complete recession curves from 27 USGS basins we show that predicted drainable storage matches well with observed drainable storage, indicating that the model can also reliably estimate drainable storage for `incomplete' recession events to address many challenges related to water resources. (C) 2014 Elsevier Ltd. All rights reserved.

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In the present work, Li2-x MnO3-y (LMO) thin films have been deposited by radio frequency (RF) reactive magnetron sputtering using acid-treated Li2MnO3 powder target. Systematic investigations have been carried out to study the effect of RF power on the physicochemical properties of LMO thin films deposited on platinized silicon substrates. X-ray diffraction, electron microscopy, surface chemical analysis and electrochemical studies were carried out for the LMO films after post deposition annealing treatment at 500 A degrees C for 1 h in air ambience. Galvanostatic charge discharge studies carried out using the LMO thin film electrodes, delivered a highest discharge capacity of 139 mu Ah mu m(-1) cm(-2) in the potential window 2.0-3.5 V vs. Li/Li+ at 100 W RF power and lowest discharge capacity of 80 mu Ah mu m(-1) cm(-2) at 75 W RF power. Thereafter, the physicochemical properties of LMO films deposited using optimized RF power 100 W on stainless steel substrates has been studied in the thickness range of 70 to 300 nm as a case study. From the galvanostatic charge discharge experiments, a stable discharge capacity of 68 mu Ah mu m(-1) cm(-2) was achieved in the potential window 2.0-4.2 V vs. Li/Li+ tested up to 30 cycles. As the thickness increased, the specific discharge capacity started reducing with higher magnitude of capacity fading.

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We performed Gaussian network model based normal mode analysis of 3-dimensional structures of multiple active and inactive forms of protein kinases. In 14 different kinases, a more number of residues (1095) show higher structural fluctuations in inactive states than those in active states (525), suggesting that, in general, mobility of inactive states is higher than active states. This statistically significant difference is consistent with higher crystallographic B-factors and conformational energies for inactive than active states, suggesting lower stability of inactive forms. Only a small number of inactive conformations with the DFG motif in the ``in'' state were found to have fluctuation magnitudes comparable to the active conformation. Therefore our study reports for the first time, intrinsic higher structural fluctuation for almost all inactive conformations compared to the active forms. Regions with higher fluctuations in the inactive states are often localized to the aC-helix, aG-helix and activation loop which are involved in the regulation and/or in structural transitions between active and inactive states. Further analysis of 476 kinase structures involved in interactions with another domain/protein showed that many of the regions with higher inactive-state fluctuation correspond to contact interfaces. We also performed extensive GNM analysis of (i) insulin receptor kinase bound to another protein and (ii) holo and apo forms of active and inactive conformations followed by multi-factor analysis of variance. We conclude that binding of small molecules or other domains/proteins reduce the extent of fluctuation irrespective of active or inactive forms. Finally, we show that the perceived fluctuations serve as a useful input to predict the functional state of a kinase.

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This paper describes coupled-effect simulations of smart micro gas-sensors based on standard BiCMOS technology. The smart sensor features very low power consumption, high sensitivity and potential low fabrication cost achieved through full CMOS integration. For the first time the micro heaters are made of active CMOS elements (i.e. MOSFET transistors) and embedded in a thin SOI membrane consisting of Si and SiO2 thin layers. Micro gas-sensors such as chemoresistive, microcalorimeteric and Pd/polymer gate FET sensors can be made using this technology. Full numerical analyses including 3D electro-thermo-mechanical simulations, in particular stress and deflection studies on the SOI membranes are presented. The transducer circuit design and the post-CMOS fabrication process, which includes single sided back-etching, are also reported.

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For surface modification of stamping dies, an inseparable two-dimensional binary-phase gratings is introduced to implement the wavefront transformation of high-power laser beams. The design and fabrication of the gratings are described in detail. Two-dimensional even sampling encoding scheme is adopted to overcome the limitations of conventional Dammann grating in the design of two-dimensional output patterns. High diffractive efficiency (>70%) can be achieved through the transformation of the Gaussian laser beam into several kinds of two-dimensional arrays in focal plan. The application of the binary-phase gratings in the laser surface modification of ductile iron is investigated, and the results show that the hardness and the wear resistance of the sample surface were improved significantly by using the binary-phase gratings. (C) 2008 Elsevier Ltd. All rights reserved.

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Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context ofactive self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

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The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept ofpower over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

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The experimental portion of this thesis tries to estimate the density of the power spectrum of very low frequency semiconductor noise, from 10-6.3 cps to 1. cps with a greater accuracy than that achieved in previous similar attempts: it is concluded that the spectrum is 1/fα with α approximately 1.3 over most of the frequency range, but appearing to have a value of about 1 in the lowest decade. The noise sources are, among others, the first stage circuits of a grounded input silicon epitaxial operational amplifier. This thesis also investigates a peculiar form of stationarity which seems to distinguish flicker noise from other semiconductor noise.

In order to decrease by an order of magnitude the pernicious effects of temperature drifts, semiconductor "aging", and possible mechanical failures associated with prolonged periods of data taking, 10 independent noise sources were time-multiplexed and their spectral estimates were subsequently averaged. If the sources have similar spectra, it is demonstrated that this reduces the necessary data-taking time by a factor of 10 for a given accuracy.

In view of the measured high temperature sensitivity of the noise sources, it was necessary to combine the passive attenuation of a special-material container with active control. The noise sources were placed in a copper-epoxy container of high heat capacity and medium heat conductivity, and that container was immersed in a temperature controlled circulating ethylene-glycol bath.

Other spectra of interest, estimated from data taken concurrently with the semiconductor noise data were the spectra of the bath's controlled temperature, the semiconductor surface temperature, and the power supply voltage amplitude fluctuations. A brief description of the equipment constructed to obtain the aforementioned data is included.

The analytical portion of this work is concerned with the following questions: what is the best final spectral density estimate given 10 statistically independent ones of varying quality and magnitude? How can the Blackman and Tukey algorithm which is used for spectral estimation in this work be improved upon? How can non-equidistant sampling reduce data processing cost? Should one try to remove common trands shared by supposedly statistically independent noise sources and, if so, what are the mathematical difficulties involved? What is a physically plausible mathematical model that can account for flicker noise and what are the mathematical implications on its statistical properties? Finally, the variance of the spectral estimate obtained through the Blackman/Tukey algorithm is analyzed in greater detail; the variance is shown to diverge for α ≥ 1 in an assumed power spectrum of k/|f|α, unless the assumed spectrum is "truncated".

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A novel high-average-power pulsed CO2 laser with a unique electrode structure is presented. The operation of a 5-kW transverse-flow CO2 laser with the preionized pulse-train switched technique results in pulsation of the laser power, and the average laser power is about 5 kW. The characteristic of this technique is switching the preionized pulses into pulse trains so as to use the small preionized power (hundreds of watts) to control the large main-discharge power (tens of kilowatts). By this means, the cost and the complexity of the power supply are greatly reduced. The welding of LF2, LF21, LD2, and LY12 aluminum alloy plates has been successfully achieved using this laser. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

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A novel high-average-power pulsed CO2 laser with a unique electrode structure is presented. The operation of a 5-kW transverse-flow CO2 laser with the preionized pulse-train switched technique results in pulsation of the laser power, and the average laser power is about 5 kW. The characteristic of this technique is switching the preionized pulses into pulse trains so as to use the small preionized power (hundreds of watts) to control the large main-discharge power (tens of kilowatts). By this means, the cost and the complexity of the power supply are greatly reduced. The welding of LF2, LF21, LD2, and LY12 aluminum alloy plates has been successfully achieved using this laser. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

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This work presents active control of high-frequency vibration using skyhook dampers. The choice of the damper gain and its optimal location is crucial for the effective implementation of active vibration control. In vibration control, certain sensor/actuator locations are preferable for reducing structural vibration while using minimum control effort. In order to perform optimisation on a general built-up structure to control vibration, it is necessary to have a good modelling technique to predict the performance of the controller. The present work exploits the hybrid modelling approach, which combines the finite element method (FEM) and statistical energy analysis (SEA) to provide efficient response predictions at medium to high frequencies. The hybrid method is implemented here for a general network of plates, coupled via springs, to allow study of a variety of generic control design problems. By combining the hybrid method with numerical optimisation using a genetic algorithm, optimal skyhook damper gains and locations are obtained. The optimal controller gain and location found from the hybrid method are compared with results from a deterministic modelling method. Good agreement between the results is observed, whereas results from the hybrid method are found in a significantly reduced amount of time. © 2012 Elsevier Ltd. All rights reserved.

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Directional coupler can be constructed by putting multiple photonic crystal waveguides together. The propagation of the optical field entering this system symmetrically was analysed numerically according to self-imaging principle. On the basis of this structure, ultracompact multiway beam splitter was designed and the ones with three and four output channels were discussed in details as examples. By simply tuning the effective refractive index of two dielectric rods in the coupler symmetrically to induce the redistribution of the power of the optical field, uniform or free splitting can be achieved. Compared with the reported results, this way is simpler, more feasible and more efficient and has extensive practical value in future photonic integrated circuits.

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A modeling study is conducted to investigate the plasma flow and heat transfer characteristics of low-power (kW class) arc-heated thrusters (arcjets) with 2:1 hydrogen/nitrogen to simulate decomposed hydrazine as the propellant. The all-speed SIMPLE algorithm is employed to solve the governing equations, which take into account the effects of compressibility, the Lorentz force and Joule heating, as well as the temperature- and pressure-dependence of the gas properties. Typical computed results about the temperature, velocity and Mach number distributions within arcjet thruster are presented for the case with arc current of 9 A and inlet stagnant pressure of 3.3×105 Pa to show the flow and heat transfer characteristics. It is found that the propellant is heated mainly in the near-cathode and constrictor region, with the highest plasma temperature appearing near the cathode tip, and the flow transition from the subsonic to supersonic regime occurs within the constrictor region. The effect of gas viscosity on the plasma flow within arcjet thruster is examined by an additional numerical test using artificially reduced values of gas viscosity. The test results show that the gas viscosity appreciably affects the plasma flow and the performance of the arcjet thruster for the cases with the hydrazine or hydrogen as the propellant. The integrated axial Lorentz force in the thruster nozzle is also calculated and compared with the thrust force of the arcjet thruster. It is found that the integrated axial Lorentz force is much smaller than the thrust force for the low-power arcjet thruster. Modeling results for the NASA 1-kW class arcjet thruster with simulated hydrazine as the propellant are found to be reasonably consistent with available experimental data.

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Liquid phase hydrodechlorination of chlorinated benzenes was studied over Ni/active carbon (Ni/AC), Ni/gamma-Al2O3, Ni/SiO2 and Raney Ni. The complete dechlorination of chlorobenzene (ClBz) was realized at 333-343 K on Ni/AC under hydrogen atmosphere of 1.0 MPa in the presence of alkaline hydroxide. Dichloro- and trichlorobenzenes were also hydrodechlorinated with 50-95% yields of benzene under the similar conditions, as above. The reaction follows zero-order to ClBz concentration and 1.9 order to hydrogen pressure. The reaction does not proceed in the absence of alkaline hydroxide, suggesting the complete coverage of active nickel surface with produced chlorine and the removal of the chlorine ion with hydroxide ion as a rate-limiting step. The active catalysts were characterized by H-2 chemisorption and transmission electron microscopy techniques. The apparent activity strongly depends on the active area of nickel on catalyst surface. (C) 2004 Published by Elsevier B.V.