256 resultados para Numerical Approximation


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Charnockite is considered to be generated either through the dehydration of granitic magma by CO2 purging or by solid-state dehydration through CO2 metasomatism during granulite facies metamorphism. To understand the extent of dehydration, CO2 migration is quantitatively modeled in silicate melt and metasomatic fluid as a function of temperature, H2O wt%, pressure, basal CO2 flux and dynamic viscosity. Numerical simulations show that CO2 advection through porous and permeable high-grade metamorphic rocks can generate dehydrated patches close to the CO2 flow path, as illustrated by the occurrences of ``incipient charnockites.'' CO2 reaction-front velocity constrained by field observations is 0.69 km/m.y., a reasonable value, which matches well with other studies. On the other hand, temperature, rate of cooling, and basal CO2 flux are the critical parameters affecting CO2 diffusion through a silicate melt. CO2 diffusion through silicate melt can only occur at temperature greater than 840 degrees C and during slow cooling (<= 3.7 x 10(-5) degrees C/yr), features that are typical of magma emplacement in the lower crust. Stalling of CO2 fluxing at similar to 840 degrees C explains why some deep-level plutons contain both hydrous and anhydrous (charnockitic) mineral assemblages. CO2 diffusion through silicate melt is virtually insensitive to pressure. Addition of CO2 basal flux facilitates episodic dehydrated melt migration by generating fracture pathways.

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Geotextiles and geogrids have been in use for several decades in variety of geo-structure applications including foundation of embankments, retaining walls, pavements. Geocells is one such variant in geosynthetic reinforcement of recent years, which provides a three dimensional confinement to the infill material. Although extensive research has been carried on geocell reinforced sand, clay and layered soil subgrades, limited research has been reported on the aggregates/ballast reinforced with geocells. This paper presents the behavior of a railway sleeper subjected to monotonic loading on geocell reinforced aggregates, of size ranging from 20 to 75 mm, overlying soft clay subgrades. Series of tests were conducted in a steel test tank of dimensions 700 mm x 300 mm x 700 mm. In addition to the laboratory model tests, numerical simulations were performed using a finite difference code to predict the behavior of geocell reinforced ballast. The results from numerical simulations were compared with the experimental data. The numerical and experimental results manifested the importance that the geocell reinforcement has a significant effect on the ballast behaviour. The results depicted that the stiffness of underlying soft clay subgrade has a significant influence on the behavior of the geocell-aggregate composite material in redistributing the loading system.

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The issue of intermittency in numerical solutions of the 3D Navier-Stokes equations on a periodic box 0, L](3) is addressed through four sets of numerical simulations that calculate a new set of variables defined by D-m(t) = (pi(-1)(0) Omega(m))(alpha m) for 1 <= m <= infinity where alpha(m) = 2m/(4m - 3) and Omega(m)(t)](2m) = L-3 integral(v) vertical bar omega vertical bar(2m) dV with pi(0) = vL(-2). All four simulations unexpectedly show that the D-m are ordered for m = 1,..., 9 such that Dm+1 < D-m. Moreover, the D-m squeeze together such that Dm+1/D-m NE arrow 1 as m increases. The values of D-1 lie far above the values of the rest of the D-m, giving rise to a suggestion that a depletion of nonlinearity is occurring which could be the cause of Navier-Stokes regularity. The first simulation is of very anisotropic decaying turbulence; the second and third are of decaying isotropic turbulence from random initial conditions and forced isotropic turbulence at fixed Grashof number respectively; the fourth is of very-high-Reynolds-number forced, stationary, isotropic turbulence at up to resolutions of 4096(3).

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The boxicity (cubicity) of a graph G, denoted by box(G) (respectively cub(G)), is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (cubes) in ℝ k . The problem of computing boxicity (cubicity) is known to be inapproximable in polynomial time even for graph classes like bipartite, co-bipartite and split graphs, within an O(n 0.5 − ε ) factor for any ε > 0, unless NP = ZPP. We prove that if a graph G on n vertices has a clique on n − k vertices, then box(G) can be computed in time n22O(k2logk) . Using this fact, various FPT approximation algorithms for boxicity are derived. The parameter used is the vertex (or edge) edit distance of the input graph from certain graph families of bounded boxicity - like interval graphs and planar graphs. Using the same fact, we also derive an O(nloglogn√logn√) factor approximation algorithm for computing boxicity, which, to our knowledge, is the first o(n) factor approximation algorithm for the problem. We also present an FPT approximation algorithm for computing the cubicity of graphs, with vertex cover number as the parameter.

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In several chemical and space industries, small bubbles are desired for efficient interaction between the liquid and gas phases. In the present study, we show that non-uniform electric field with appropriate electrode configurations can reduce the volume of the bubbles forming at submerged needles by up to three orders of magnitude. We show that localized high electric stresses at the base of the bubbles result in slipping of the contact line on the inner surface of the needle and subsequent bubble formation occurs with contact line inside the needle. We also show that for bubble formation in the presence of highly non-uniform electric field, due to high detachment frequency, the bubbles go through multiple coalescences and thus increase the apparent volume of the detached bubbles. (C) 2013 AIP Publishing LLC.

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In the present work, the thermal efficiency of a conventional domestic burner is studied both experimentally and numerically for liquefied petroleum gas (LPG) and piped natural gas (PNG) fuels. Three-dimensional computational fluid dynamic (CFD) modeling of the steady-state flow, combustion and heat transfer to the vessel is reported for the first time in such burners. Based on the insights from the CFD model concerning the flow and heat transfer, design modifications in the form of a circular insert and a radiant sheet are proposed which are observed to increase thermal efficiency for LPG. For PNG, predictions showed that loading height was a much more important factor affecting efficiency than these design modifications and an optimal loading height could be identified. Experiments confirm these trends by showing an improvement in burner thermal efficiency of 2.5% for LPG with the modified design, and 10% for PNG with the optimal loading height, demonstrating that the CFD modeling approach developed in the present work is a useful tool to study domestic burners. (C) 2013 Elsevier Ltd. All rights reserved.

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In this study the cooling performance due to air flow and aerodynamics of the Formula Student open wheeled race car has been investigated and optimized with the help of CFD simulations and experimental validation. The race car in context previously suffered from overheating problems. Flow analysis was carried out based on the detailed race car 3D model (NITK Racing 2012 formula student race car). Wind tunnel experiments were carried out on the same. The results obtained from the computer simulations are compared with experimental results obtained from wind tunnel testing of the full car. Through this study it was possible to locate the problem areas and hence choose the best configuration for the cooling duct. The CFD analysis helped in calculating the mass flow rate, pressure and velocity distribution for different velocities of the car which is then used to determine the heat dissipated by the radiator. Area of flow separation could be visualized and made sure smooth airflow into the radiator core area. This significantly increased the cooling performance of the car with reduction in drag.

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Heat and mass transfer studies in a calandria based reactor is quite complex both due to geometry and due to the complex mixing flow. It is challenging to devise optimum operating conditions with efficient but safe working range for such a complex configuration. Numerical study known to be very effective is taken up for investigation. In the present study a 3D RANS code with turbulence model has been used to compute the flow fields and to get the heat transfer characteristics to understand certain design parameters of engineering importance. The angle of injection and of the coolant liquid has a large effect on the heat transfer within the reactor.

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The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.

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We study the tradeoff between delivery delay and energy consumption in a delay-tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the message and the number of destinations that have received the message. We formulate the problem as a controlled continuous-time Markov chain and derive the optimal closed-loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ordinary differential equation (ODE) (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open-loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed-loop policy.

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We investigate the impact of the nucleation law for nucleation on Al-Ti-B inoculant particles, of the motion of inoculant particles and of the motion of grains on the predicted macrosegregation and microstructure in a grain-refined Al-22 wt.% Cu alloy casting. We conduct the study by numerical simulations of a casting experiment in a side-cooled 76×76×254 mm sand mould. Macrosegregation and microstructure formation are studied with a volume-averaged two-phase model accounting for macroscopic heat and solute transport, melt convection, and transport of inoculant particles and equiaxed grains. On the microscopic scale it accounts for nucleation on inoculant particles with a given size distribution (and corresponding activation undercooling distribution)and for the growth of globular solid grains. The growth kinetics is described by accounting for limited solute diffusion in both liquid and solid phases and for convective effects. We show that the consideration of a size distribution of the inoculants has a strong impact on the microstructure(final grain size) prediction. The transport of inoculants significantly increases the microstructure heterogeneities and the grain motion refines the microstructure and reduces the microstructure heterogeneities.

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A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.

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An aeroelastic analysis is used to investigate the rate dependent hysteresis in piezoceramic actuators and its effect on helicopter vibration control with trailing edge flaps. Hysteresis in piezoceramic materials can cause considerable complications in the use of smart actuators as prime movers in applications such as helicopter active vibration control. Dynamic hysteresis of the piezoelectric stack actuator is investigated for a range of frequencies (5 Hz (1/rev) to 30 Hz (6/rev)) which are of practical importance for helicopter vibration analysis. Bench top tests are conducted on a commercially available piezoelectric stack actuator. Frequency dependent hysteretic behavior is studied experimentally for helicopter operational frequencies. Material hysteresis in the smart actuator is mathematically modeled using the theory of conic sections. Numerical simulations are also performed at an advance ratio of 0.3 for vibration control analysis using a trailing edge flap with an idealized linear and a hysteretic actuator. The results indicate that dynamic hysteresis has a notable effect on the hub vibration levels. It is found that the theory of conic sections offers a straight forward approach for including hysteresis into aeroelastic analysis.

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We present a nonequilibrium strong-coupling approach to inhomogeneous systems of ultracold atoms in optical lattices. We demonstrate its application to the Mott-insulating phase of a two-dimensional Fermi-Hubbard model in the presence of a trap potential. Since the theory is formulated self-consistently, the numerical implementation relies on a massively parallel evaluation of the self-energy and the Green's function at each lattice site, employing thousands of CPUs. While the computation of the self-energy is straightforward to parallelize, the evaluation of the Green's function requires the inversion of a large sparse 10(d) x 10(d) matrix, with d > 6. As a crucial ingredient, our solution heavily relies on the smallness of the hopping as compared to the interaction strength and yields a widely scalable realization of a rapidly converging iterative algorithm which evaluates all elements of the Green's function. Results are validated by comparing with the homogeneous case via the local-density approximation. These calculations also show that the local-density approximation is valid in nonequilibrium setups without mass transport.