Sharif Digital Repository

The present paper developed and validated a numerical procedure for the calculation of turbulent combustive flows in converging and diverging ducts. Through simulation of the heat transfer processes, the amounts of production and spread of NOx pollutants were measured. Also, this paper reported the results of a numerical investigation of the effects of the fuel Molecular Weight on NOx emissions in converging and diverging ducts. The fuels which were examined were methane, naphtha, and kerosene. The differential equations in the Von-Misses coordinate system were transformed to a cross-stream coordinate system in order to concentrate more grid lines near wall boundaries. A marching integration... 

In solution of the Euler equations in the steady state external flows, error or residual waves are blamed for decelerating the convergence. These waves may be damped by adding a bulk viscosity term to the momentum equations. We analyse effects of this term on the linearized differential equations, and study its explicit and implicit implementation in one and two space dimensions. Optimum values of the bulk viscosity damping (BVD) are discussed. After generalization to two space dimensions, its performance both alone and in combination with a soft wall boundary condition and residual smoothing in central differencing codes is reviewed. It is shown that BVD is complementary to them, and acts... 

We present a high-performance and efficiently simplified new neural network which improves the existing neural networks for solving general linear and quadratic programming problems. The network, having no need for parameter setting, results in a simple hardware requiring no analog multipliers, is shown to be stable and converges globally to the exact solution. Moreover, using this network we can solve both linear and quadratic programming problems and their duals simultaneously. High accuracy of the obtained solutions and low cost of implementation are among the features of this network. We prove the global convergence of the network analytically and verify the results numerically. © 2005... 

This paper considers flocking to the virtual leader in network of agents with double-integrator. A locally linear algorithm is employed which guarantees exponential flocking to the virtual leader. A lower bound for flocking rate is calculated which is independent of the initial conditions. Simulations are provided to validate the result and it is shown that the calculated rate is not over bound the actual convergence rate. The effect of coefficients of algorithm is investigated and it is shown that the similar results can be inferred from the calculated formula for the convergence rate. Copyright  

The problem of early convergence in the Particle Swarm Optimization (PSO) algorithm often causes the search process to be trapped in a local optimum. This problem often occurs when the diversity of the swarm decreases and the swarm cannot escape from a local optimal. In this paper, a novel dynamic diversity enhancement particle swarm optimization (DDEPSO) algorithm is introduced. In this variant of PSO, we periodically replace some of the swarm's particles by artificial ones, which are generated based on the history of the search process, in order to enhance the diversity of the swarm and promote the exploration ability of the algorithm. Afterwards, we update the velocity of the artificial... 

Market practitioners and speculators attempt to make benefits from the existence of market price gaps and profit opportunities by arbitrage strategies. Although some investors trade stocks based on the available financial and fundamental information of a particular share, there are others who make profits by risk hedging and swing trading opportunities. One of these strategies is pairs trading, which is a sub-category of statistical arbitrage. Pairs trading can assure reasonably a risk-free profit gaining. This paper aims to make a hypothetical portfolio composed of pairs of stocks by exploring a significant association between their prices in the Toronto Stock Exchange, TSX. We compare the... 

This paper deals with a refined analysis and modification of existing results on the flocking algorithms proposed for the second order dynamic agents. In the present work, the limiting condition of ever connectivity is removed and it is proved that the flocking can be reached if only the union of the network proximity graphs during nonoverlapping time intervals becomes connected frequently enough. Also, it is proved that including a static virtual leader cannot model the group objective of achieving the desired velocity and it will stop eventually at a predefined point in the space. The convergence rate to this fixed point is determined too. The last contribution of this paper is definition... 

We propose an observer for attitude and position estimation of a rigid body using translational and angular velocity measurements together with a single landmark. Under an observability condition depending on landmark position, global and asymptotic convergence of attitude and position estimation errors to zero is achieved. We extend the observer for the case of nonideal velocity measurements. Simulation examples demonstrate convergence properties of the observer in the face of noise and bias in velocity measurements  

This paper introduces adaptive consensus, a spatio-temporal adaptive method to improve convergence behavior of the current consensus fusion schemes. This is achieved by introducing a time adaptive weighting method for updating each sensor data in each iteration. Adaptive consensus method will improve node convergence rate, average convergence rate and the variance of error over the network. A mathematical formulation of the method according to the adaptive filter theory as well as derivation of the time adaptive weights and convergence conditions are presented. The analytical results are verified by simulation as well. ©2006 IEEE  

We propose an inexact nonmonotone successive quadratic programming (SQP) algorithm for solving nonlinear programming problems with equality constraints and bounded variables. Regarding the value of the current feasibility violation and the minimum value of its linear approximation over a trust region, several scenarios are envisaged. In one scenario, a possible infeasible stationary point is detected. In other scenarios, the search direction is computed using an inexact (truncated) solution of a feasible strictly convex quadratic program (QP). The search direction is shown to be a descent direction for the objective function or the feasibility violation in the feasible or infeasible... 

We propose an inexact nonmonotone successive quadratic programming (SQP) algorithm for solving nonlinear programming problems with equality constraints and bounded variables. Regarding the value of the current feasibility violation and the minimum value of its linear approximation over a trust region, several scenarios are envisaged. In one scenario, a possible infeasible stationary point is detected. In other scenarios, the search direction is computed using an inexact (truncated) solution of a feasible strictly convex quadratic program (QP). The search direction is shown to be a descent direction for the objective function or the feasibility violation in the feasible or infeasible... 

We propose an inexact nonmonotone successive quadratic programming (SQP) algorithm for solving nonlinear programming problems with equality constraints and bounded variables. Regarding the value of the current feasibility violation and the minimum value of its linear approximation over a trust region, several scenarios are envisaged. In one scenario, a possible infeasible stationary point is detected. In other scenarios, the search direction is computed using an inexact (truncated) solution of a feasible strictly convex quadratic program (QP). The search direction is shown to be a descent direction for the objective function or the feasibility violation in the feasible or infeasible... 

In this work, we study the lossy source coding of a Gaussian source with polar codes. We show through two distributions on discrete alphabet, quantized approach as well as Central Limit Theorem (CLT) approach, when the alphabet size grows to infinity, polar codes can achieve the rate distortion bound for a Gaussian source. By comparing the rate of convergence on two distributions, we show that the quantized approach have a better convergence rate than the CLT approach  

An improved progressive preconditioning method for analyzing steady inviscid and laminar flows around fully wetted and sheet-cavitating hydrofoils is presented. The preconditioning matrix is adapted automatically from the pressure and/or velocity flow-field by a power-law relation. The cavitating calculations are based on a single fluid approach. In this approach, the liquid/vapour mixture is treated as a homogeneous fluid whose density is controlled by a barotropic state law. This physical model is integrated with a numerical resolution derived from the cell-centered Jameson's finite volume algorithm. The stabilization is achieved via the second-and fourth-order artificial dissipation... 

In this paper we highlight a remarkable difference between the step responses of a classical second-order transfer function and its fractional-order counterpart. It can be easily shown that the step response of a stable classical second-order transfer function crosses its final value infinitely over time. In contrast, it is illustrated here that the step responses of a fractional-order counterpart of the classical second-order model possess only a finite number of such crossovers. In other words, for such a system one can find a specific time instant after which the step response is over or under-convergent to its final value. This property interprets some phenomena observed in the... 

The purpose of dictionary learning problem is to learn a dictionary D from a training data matrix Y such that Y ≈ DX and the coefficient matrix X is sparse. Many algorithms have been introduced to this aim, which minimize the representation error subject to a sparseness constraint on X. However, the dictionary learning problem is non-convex with respect to the pair (D,X). In a previous work [Sadeghi et al., 2013], a convex approximation to the non-convex term DX has been introduced which makes the whole DL problem convex. This approach can be almost applied to any existing DL algorithm and obtain better algorithms. In the current paper, it is shown that a simple modification on that approach...