Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.

A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

Algorithmic approach to simulate Hamiltonian dynamics and an NMR simulation of quantum state transfer

We propose an iterative algorithm to simulate the dynamics generated by any n-qubit Hamiltonian. The simulation entails decomposing the unitary time evolution operator U (unitary) into a product of different time-step unitaries. The algorithm product-decomposes U in a chosen operator basis by identifying a certain symmetry of U that is intimately related to the number of gates in the decomposition. We illustrate the algorithm by first obtaining a polynomial decomposition in the Pauli basis of the n-qubit quantum state transfer unitary by Di Franco et al. [Phys. Rev. Lett. 101, 230502 (2008)] that transports quantum information from one end of a spin chain to the other, and then implement it in nuclear magnetic resonance to demonstrate that the decomposition is experimentally viable. We further experimentally test the resilience of the state transfer to static errors in the coupling parameters of the simulated Hamiltonian. This is done by decomposing and simulating the corresponding imperfect unitaries.

Simulation of Potential and Electric Field Profiles for transmission line Insulators

Since the end of second world war, extra high voltage ac transmission has seen its development. The distances between generating and load centres as well as the amount of power to be handled increased tremendously for last 50 years. The highest commercial voltage has increased to 765 kV in India and 1,200 kV in many other countries. The bulk power transmission has been mostly performed by overhead transmission lines. The dual task of mechanically supporting and electrically isolating the live phase conductors from the support tower is performed by string insulators. Whether in clean condition or under polluted conditions, the electrical stress distribution along the insulators governs the possible flashover, which is quite detrimental to the system. Hence the present investigation aims to study accurately, the field distribution for various types of porcelain/ceramic insulators (Normal and Antifog discs) used for high-voltage transmission. The surface charge simulation method is employed for the field computation. A comparison on normalised surface resistance, which is an indicator for the stress concentration under polluted condition, is also attempted.

Simulation of surface and volume stress for high voltage transmission insulators

The bulk of power transmission from the generating stations to the load centres is carried through overhead lines. The distances involved could span several hundreds of kilometres. To minimize line losses, power transmission over such long distances is carried out at high voltages (several hundreds of kV). A network of outdoor lines operating at different voltages has been found to be the most economical method of power delivery. The disc insulators perform dual task of mechanically supporting and electrically isolating the live phase conductors from the support tower. These insulators have to perform under various environmental conditions; hence the electrical stress distribution along the insulators governs the possible flashover, which is quite detrimental to the system. In view of this the present investigation aims to simulate the surface electric field stress on different types of porcelain/ceramic insulators; both normal and anti-fog type discs which are used for high voltage transmission/distribution systems are considered. The surface charge simulation method is employed for the field computation to simulate potential, electric field, surface and bulk/volume stress.

Conformational dynamics of HIV-1 protease: a comparative molecular dynamics simulation study with multiple amber force fields

Flap dynamics of HIV-1 protease (HIV-pr) controls the entry of inhibitors and substrates to the active site. Dynamical models from previous simulations are not all consistent with each other and not all are supported by the NMR results. In the present work, the er effect of force field on the dynamics of HIV-pr is investigated by MD simulations using three AMBER force fields ff99, ff99SB, and ff03. The generalized order parameters for amide backbone are calculated from the three force fields and compared with the NMR S2 values. We found that the ff99SB and ff03 force field calculated order parameters agree reasonably well with the NMR S2 values, whereas ff99 calculated values deviate most from the NMR order parameters. Stereochemical geometry of protein models from each force field also agrees well with the remarks from NMR S2 values. However, between ff99SB and ff03, there are several differences, most notably in the loop regions. It is found that these loops are, in general, more flexible in the ff03 force field. This results in a larger active site cavity in the simulation with the ff03 force field. The effect of this difference in computer-aided drug design against flexible receptors is discussed.

Electrochemical capacitors: Technical challenges and prognosis for future markets

Electrochemical capacitors are potential devices that could help bringing about major advances in future energy storage. They are lightweight and their manufacture and disposal has no detrimental effects on the environment. A comprehensive description of fundamental science of electrochemical capacitors is presented. Similarities and differences between electrochemical capacitors and secondary batteries for electrical energy storage are highlighted and various types of electrochemical capacitors are discussed with special reference to lead-carbon hybrid ultracapacitors. Some envisaged applications of electrochemical capacitors are described along with the technical challenges and prognosis for future markets. (C) 2012 Published by Elsevier Ltd.

Simulation of Influence of Bilayer Melting on Dynamics and Thermodynamics of Interfacial Water

We investigate the effect of bilayer melting transition on thermodynamics and dynamics of interfacial water using molecular dynamics simulation with the two-phase thermodynamic model. We show that the diffusivity of interface water depicts a dynamic crossover at the chain melting transition following an Arrhenius behavior until the transition temperature. The corresponding change in the diffusion coefficient from the bulk to the interface water is comparable with experimental observations found recently for water near 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) vesicles Phys. Chem. Chem. Phys. 13, 7732 (2011)]. The entropy and potential energy of interfacial water show distinct changes at the bilayer melting transition, indicating a strong correlation in the thermodynamic state of water and the accompanying first-order phase transition of the bilayer membrane. DOI: 10.1103/PhysRevLett.110.018303

Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation

Given the increasing cost of designing and building new highway pavements, reliability analysis has become vital to ensure that a given pavement performs as expected in the field. Recognizing the importance of failure analysis to safety, reliability, performance, and economy, back analysis has been employed in various engineering applications to evaluate the inherent uncertainties of the design and analysis. The probabilistic back analysis method formulated on Bayes' theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis-Hastings algorithm has proved to be highly efficient to address this issue. It is also quite flexible and is applicable to any type of prior information. In this paper, this method has been used to back-analyze the parameters that influence the pavement life and to consider the uncertainty of the mechanistic-empirical pavement design model. The load-induced pavement structural responses (e.g., stresses, strains, and deflections) used to predict the pavement life are estimated using the response surface methodology model developed based on the results of linear elastic analysis. The failure criteria adopted for the analysis were based on the factor of safety (FOS), and the study was carried out for different sample sizes and jumping distributions to estimate the most robust posterior statistics. From the posterior statistics of the case considered, it was observed that after approximately 150 million standard axle load repetitions, the mean values of the pavement properties decrease as expected, with a significant decrease in the values of the elastic moduli of the expected layers. An analysis of the posterior statistics indicated that the parameters that contribute significantly to the pavement failure were the moduli of the base and surface layer, which is consistent with the findings from other studies. After the back analysis, the base modulus parameters show a significant decrease of 15.8% and the surface layer modulus a decrease of 3.12% in the mean value. The usefulness of the back analysis methodology is further highlighted by estimating the design parameters for specified values of the factor of safety. The analysis revealed that for the pavement section considered, a reliability of 89% and 94% can be achieved by adopting FOS values of 1.5 and 2, respectively. The methodology proposed can therefore be effectively used to identify the parameters that are critical to pavement failure in the design of pavements for specified levels of reliability. DOI: 10.1061/(ASCE)TE.1943-5436.0000455. (C) 2013 American Society of Civil Engineers.

Eulerian two-phase flow simulation and experimental validation of semisolid slurry generation process using cooling slope

Experimental and numerical studies of slurry generation using a cooling slope are presented in the paper. The slope having stainless steel body has been designed and constructed to produce semisolid A356 Al alloy slurry. The pouring temperature of molten metal, slope angle of the cooling slope and slope wall temperature were varied during the experiment. A multiphase numerical model, considering liquid metal and air, has been developed to simulate the liquid metal flow along the cooling channel using an Eulerian two-phase flow approach. Solid fraction evolution of the solidifying melt is tracked at different locations of the cooling channel following Schiel's equation. The continuity, momentum and energy equations are solved considering thin wall boundary condition approach. During solidification of the melt, based on the liquid fraction and latent heat of the alloy, temperature of the alloy is modified continuously by introducing a modified temperature recovery method. Numerical simulations has been carried out for semisolid slurry formation by varying the process parameters such as angle of the cooling slope, cooling slope wall temperature and melt superheat temperature, to understand the effect of process variables on cooling slope semisolid slurry generation process such as temperature distribution, velocity distribution and solid fraction of the solidifying melt. Experimental validation performed for some chosen cases reveals good agreement with the numerical simulations.

Force Biased Molecular Dynamics Simulation Study of Effect of Dendrimer Generation on Interaction with DNA

We have studied the effect of dendrimer generation on the interaction between dsDNA and the PAMAM dendrimer using force biased simulation of dsDNA with three generations of dendrimer: G3, G4, and G5. Our results for the potential of mean force (PMF) and the dendrimer asphericity along the binding pathway, combined with visualization of the simulations, demonstrate that dendrimer generation has a pronounced impact on the interaction. The PMF increases linearly with increasing generation of the dendrimer. While, in agreement with previous results, we see an increase in the extent to which the dendrimer bends the dsDNA with increasing dendrimer generation, we also see that the deformation of the dendrimer is greater with smaller generation of the dendrimer. The larger dendrimer forces the dsDNA to conform to its structure, while the smaller dendrimer is forced to conform to the structure of the dsDNA. Monitoring the number of bound cations at different values of force bias distance shows the expected effect of ions being expelled when the dendrimer binds dsDNA.

Dynamic mechanism design for markets with strategic resources

The assignment of tasks to multiple resources becomes an interesting game theoretic problem, when both the task owner and the resources are strategic. In the classical, nonstrategic setting, where the states of the tasks and resources are observable by the controller, this problem is that of finding an optimal policy for a Markov decision process (MDP). When the states are held by strategic agents, the problem of an efficient task allocation extends beyond that of solving an MDP and becomes that of designing a mechanism. Motivated by this fact, we propose a general mechanism which decides on an allocation rule for the tasks and resources and a payment rule to incentivize agents' participation and truthful reports. In contrast to related dynamic strategic control problems studied in recent literature, the problem studied here has interdependent values: the benefit of an allocation to the task owner is not simply a function of the characteristics of the task itself and the allocation, but also of the state of the resources. We introduce a dynamic extension of Mezzetti's two phase mechanism for interdependent valuations. In this changed setting, the proposed dynamic mechanism is efficient, within period ex-post incentive compatible, and within period ex-post individually rational.

Full Chemical Kinetic Simulation of Biogas Early Phase Combustion in SI Engines

This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.