50 resultados para energy simulation

em Indian Institute of Science - Bangalore - Índia


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The dissipation rate of turbulent kinetic energy (epsilon) is a key parameter for mixing in surface aerators. In particular, determination epsilon across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix (R) calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system, oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.

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The dissipation rate of turbulent kinetic energy(e)is a key parameter for mixing in surface aerators. In particular, determination e across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system,oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.

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The protein folding funnel paradigm suggests that folding and unfolding proceed as directed diffusion in a multidimensional free energy surface where a multitude of pathways can be traversed during the protein's sojourn from initial to final state. However, finding even a single pathway, with the detail chronicling of intermediates, is an arduous task. In this work we explore the free energy surface of unfolding pathway through umbrella sampling, for a small globular a-helical protein chicken-villin headpiece (HP-36) when the melting of secondary structures is induced by adding DMSO in aqueous solution. We find that the unfolding proceeds through the initial separation or melting of aggregated hydrophobic core that comprises of three phenylalanine residues (Phe7, Phe11, and Phe18). This separation is accompanied by simultaneous melting of the second helix. Unfolding is found to be a multistage process involving crossing of three consecutive minima and two barriers at the initial stage. At a molecular level, Phe18 is observed to reorient itself towards other hydrophobic grooves to stabilize the intermediate states. We identify the configuration of the intermediates and correlate the intermediates with those obtained in our previous works. We also give an estimate of the barriers for different transition states and observe the softening of the barriers with increasing DMSO concentration. We show that higher concentration of DMSO tunes the unfolding pathway by destabilizing the third minimum and stabilizing the second one, indicating the development of a solvent modified, less rugged pathway. The prime outcome of this work is the demonstration that mixed solvents can profoundly transform the nature of the energy landscape and induce unfolding via a modified route. A successful application of Kramer's rate equation correlating the free energy simulation results shows faster rate of unfolding with increasing DMSO concentration. This work perhaps presents the first systematic theoretical study of the effect of a chemical denaturant on the microscopic free energy surface and rates of unfolding of HP-36. (C) 2014 AIP Publishing LLC.

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The results are presented of applying multi-time scale analysis using the singular perturbation technique for long time simulation of power system problems. A linear system represented in state-space form can be decoupled into slow and fast subsystems. These subsystems can be simulated with different time steps and then recombined to obtain the system response. Simulation results with a two-time scale analysis of a power system show a large saving in computational costs.

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There exist many investigations of ionic transport in a variety of glasses. These studies exhibit strong correlation between ionic conductivity and activation energy: Typically, it is found that higher conductivity is associated with lower activation energies and vice versa. Although there are explanations for this at a phenomenological level, there is no consistent physical picture to explain the correlation between conductivity and activation energy. We have carried out molecular dynamics simulation as a function of the size of the impurity atom or diffusant (both neutral and charged) in a host amorphous matrix. We find that there is a maximum in self-diffusivity as a function of the size of the impurity atom suggesting that there is an appropriate size for which the diffusivity is maximum. The activation energy is found to be the lowest for this size of the impurity. A similar maximum has been previously found in other condensed phases, such as confined fluids and dense liquids, and has its origin in the levitation effect. The implications of this result for understanding ionic conductivity in glasses are discussed. Our results suggest that there is a relation between microscopic structure of the amorphous solid, diffusivity or conductivity, and activation energy. The nature of this relationship is discussed in terms of the levitation parameter showing that diffusivity is maximum when the size of the neck or doorway radius is comparable with the size of the diffusant. Our computational results here are in excellent agreement with independent experimental results of Nascimento et al. [Braz. J. Phys. 35, 626 (2005)] that structural features of the glass are important in determining the ionic conductivity.

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We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

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We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor. The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio, LEDs, and external flash memory. Using the manufacturerpsilas data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

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The CCEM method (Contact Criteria and Energy Minimisation) has been developed and applied to study protein-carbohydrate interactions. The method uses available X-ray data even on the native protein at low resolution (above 2.4 Å) to generate realistic models of a variety of proteins with various ligands.The two examples discussed in this paper are arabinose-binding protein (ABP) and pea lectin. The X-ray crystal structure data reported on ABP-β-l-arabinose complex at 2.8, 2.4 and 1.7 Å resolution differ drastically in predicting the nature of the interactions between the protein and ligand. It is shown that, using the data at 2.4 Å resolution, the CCEM method generates complexes which are as good as the higher (1.7 Å) resolution data. The CCEM method predicts some of the important hydrogen bonds between the ligand and the protein which are missing in the interpretation of the X-ray data at 2.4 Å resolution. The theoretically predicted hydrogen bonds are in good agreement with those reported at 1.7 Å resolution. Pea lectin has been solved only in the native form at 3 Å resolution. Application of the CCEM method also enables us to generate complexes of pea lectin with methyl-α-d-glucopyranoside and methyl-2,3-dimethyl-α-d-glucopyranoside which explain well the available experimental data in solution.

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Background: One of the major challenges in understanding enzyme catalysis is to identify the different conformations and their populations at detailed molecular level in response to ligand binding/environment. A detail description of the ligand induced conformational changes provides meaningful insights into the mechanism of action of enzymes and thus its function. Results: In this study, we have explored the ligand induced conformational changes in H. pylori LuxS and the associated mechanistic features. LuxS, a dimeric protein, produces the precursor (4,5-dihydroxy-2,3-pentanedione) for autoinducer-2 production which is a signalling molecule for bacterial quorum sensing. We have performed molecular dynamics simulations on H. pylori LuxS in its various ligand bound forms and analyzed the simulation trajectories using various techniques including the structure network analysis, free energy evaluation and water dynamics at the active site. The results bring out the mechanistic details such as co operativity and asymmetry between the two subunits, subtle changes in the conformation as a response to the binding of active and inactive forms of ligands and the population distribution of different conformations in equilibrium. These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters. In addition, we have also elucidated the variations in the dynamics of water co-ordination to the Zn2+ ion in LuxS and its relation to the rigidity at the active sites. Conclusions: In this article, we provide details of a novel method for the identification of conformational changes in the different ligand bound states of the protein, evaluation of ligand-induced free energy changes and the biological relevance of our results in the context of LuxS structure-function. The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.

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Preparation of semisolid slurry using a cooling slope is increasingly becoming popular, primarily because of the simplicity in design and ease control of the process. In this process, liquid alloy is poured down an inclined surface which is cooled from underneath. The cooling enables partial solidification and the incline provides the necessary shear for producing semisolid slurry. However, the final microstructure of the ingot depends on several process parameters such as cooling rate, incline angle of the cooling slope, length of the slope and initial melt superheat. In this work, a CFD model using volume of fluid (VOF) method for simulating flow along the cooling slope was presented. Equations for conservation of mass, momentum, energy and species were solved to predict hydrodynamic and thermal behavior, in addition to predicting solid fraction distribution and macrosegregation. Solidification was modeled using an enthalpy approach and a volume averaged technique for the different phases. The mushy region was modeled as a multi-layered porous medium consisting of fixed columnar dendrites and mobile equiaxed/fragmented grains. The alloy chosen for the study was aluminum alloy A356, for which adequate experimental data were available in the literature. The effects of two key process parameters, namely the slope angle and the pouring temperature, on temperature distribution, velocity distribution and macrosegregation were also studied.

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For the first time, the impact of energy quantisation in single electron transistor (SET) island on the performance of hybrid complementary metal oxide semiconductor (CMOS)-SET transistor circuits has been studied. It has been shown through simple analytical models that energy quantisation primarily increases the Coulomb Blockade area and Coulomb Blockade oscillation periodicity of the SET device and thus influences the performance of hybrid CMOS-SET circuits. A novel computer aided design (CAD) framework has been developed for hybrid CMOS-SET co-simulation, which uses Monte Carlo (MC) simulator for SET devices along with conventional SPICE for metal oxide semiconductor devices. Using this co-simulation framework, the effects of energy quantisation have been studied for some hybrid circuits, namely, SETMOS, multiband voltage filter and multiple valued logic circuits. Although energy quantisation immensely deteriorates the performance of the hybrid circuits, it has been shown that the performance degradation because of energy quantisation can be compensated by properly tuning the bias current of the current-biased SET devices within the hybrid CMOS-SET circuits. Although this study is primarily done by exhaustive MC simulation, effort has also been put to develop first-order compact model for SET that includes energy quantisation effects. Finally, it has been demonstrated that one can predict the SET behaviour under energy quantisation with reasonable accuracy by slightly modifying the existing SET compact models that are valid for metallic devices having continuous energy states.

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This paper proposes a hybrid solar cooking system where the solar energy is transported to the kitchen. The thermal energy source is used to supplement the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. Solar energy is transferred to the kitchen by means of a circulating fluid. Energy collected from sun is maximized by changing the flow rate dynamically. This paper proposes a concept of maximum power point tracking (MPPT) for the solar thermal collector. The diameter of the pipe is selected to optimize the overall energy transfer. Design and sizing of different components of the system are explained. Concept of MPPT is validated with simulation and experimental results. (C) 2010 Elsevier Ltd. All rights reserved.

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Characteristics of pre-monsoon and monsoon boundary layer structure and turbulence were studied in New Delhi and Bangalore, India during the summer of 1987. Micrometeorological towers were installed and instrumented at these locations to provide mean and turbulent surface layer measurements, while information on the vertical structure of the atmosphere was obtained using miniradiosondes. Thermal structures of the pre-monsoon and monsoon boundary layers were quite distinct. The daytime, pre-monsoon boundary layer observed over New Delhi was much deeper than that of the monsoon boundary layer observed over Bangalore and at times was characterized by multiple inversions. Surface, turbulent sensible heat fluxes at both sites were approximately the same (235 and 200 Wm−2 for New Delhi and Bangalore, respectively). Diurnal variations in the monsoon boundary layer at Bangalore were more regular compared to those under pre-monsoon conditions at New Delhi. One-dimensional numerical simulations of the pre-monsoon boundary layer using a turbulent energy closure scheme show good agreement with observations.