Sharif Digital Repository

Biological layers are one of the main problems related to water transfer with pipe lines which are formed through time in the inner surface of the pipes by the water nutrients. Hence, the inner surfaces in the pipe lines and water refineries should be made in order not to let these biological layers to be made. The reason is that when the biofilm is formed on these surfaces, the traversing water is polluted. Dredging of these pipes is not only necessary in most of the countries in the world and needs huge amounts of water but is also very complex and expensive.In this research, nanomaterials, namely ZnO, T〖iO〗_2،S〖iO〗_2 have been used to cover the surface of concrete and steel pipes (The... 

Here, we first ivestigate some available nonsmooth algorithms indentilying their drawbacks, and then provide some guidelines to avert these drawbacks. We divide the algorithms to two main classes, first order and second order. The main drawback of the second order class of algorithm is that there does not exist any suitable method to approximate the generalized second order derivative. To solve this problem, we construct a uniform approximation for the generalized Hessian matrix of an SC1 function. Using the discrete gradient and the extended second order derivative, we define the discrete Hessian matrix. We construct a sequence of sets, where each set is composed of discrete Hessian... 

In 2009, a general equation of state (EOS-III) based on an effective near-neighbor pair interaction of an extended Lennard-Jones (3, 6, 12) type has been introduced as : , where is the compressibility factor, p and ρ stand for pressure and molar density , respectively, T is Temperature , and e, f and g are the temperature dependent coefficient of the equation of state . the Z_th and Z_in are the thermal and internal contributions of pressure in the compressibility factor, respectively. this equation of state gives a good description of all types of nano- and bulk –solid and bulk fluid at entire temperature and pressure ranges for which thee is experimental data. Investigation show that... 

The rise in carbon dioxide levels has led to the manifestation of numerous environmental challenges. Currently, the absorption and conversion of carbon dioxide into valuable fuel resources such as synthetic gas, methane, and ethylene are deemed crucial from both environmental and economic standpoints. Despite the presentation of photocatalysts such as titanium oxide and electrocatalysts such as copper, silver, and zinc, their efficiency in CO2 conversion is found to be insufficient. One potential solution to this problem is the utilization of photoelectrocatalytic CO2 recovery. In this study, the aim was to enhance the photoelectrocatalytic reduction of CO2 by designing and manufacturing... 

Multi-objective optimization is an important branch of optimization. One of the most common methods to solve multi-objective problems is to find the Pareto efficient points. In practical applications, there are many instances in which there are no analytical formula for the function and only approximate values at some points are available. Derivative-free optimization is one approach to solve these problems.Here, we consider one of the multi-objective derivative-free optimization techniques called direct multisearch (DMS), recently proposed in the literature. In this method, a commonly used single objective optimization method is generalized to the multiobjective case. A popular category of... 

In this thesis, arranged by [6], the multiplier method is used to solve the network problems with nonlinear constraints and the Newton-like methods are used for updating the required parameters. This method, recently proposed in the literature, is based on solving a sequence of nonlinear optimization subproblems, dependent on the main problem, such that sequence of solutions of these problems converge to the solution of the main problem. In fact, to obtain an acceptable approximation of the main solution, it is needed to solve just a finite number of nonlinear subproblems. The main idea of the multiplier methods is based on eliminating some constraints and adding a penalty term to the... 

Bezier curves are among important curves which are broadly used in different fields such as computer graphic, vector graphic and animation. Among softwares in which these curves are used nowadays are: Adobe, Inkscape, GIMP, Adobe Photoshop, and Illustrator. An important concept in drawing the Bezier curves is to plot these curveswith fewer numbers of control points (low degree). Many algorithms have been introduced to reduce the degree of bezier curves. Here we first describe Bezier curves and their properties. Our main concern here is implementation of a new algorithm for multi-degree reduction of Bezier curves which are constrainted. The algorithm has recently been proposed byWozny and... 

In the modern world, steganography is an image processing technique, revealing to be a suitable process for information hiding. In most cases, steganography has shown to be more effective than cryptography techniques. Recently, there have been attempts to improve the stego-image quality and hiding capacity by introducing new methods. Here, we inspect the advantages and disadvantages of some new steganography methods for digital images. The implemented methods are color and grayscale image steganography with OPVSP algorithm, BRL and GRL methods, and the simple LSB method with OPAP algorithm. Here, we compare the implementation results of these methods using MATLAB 7.4.0, with other common... 

Design, analysis and practical implementation of the filter trust-region algorithms are investigated. First, we introduce two filter trust-region algorithms for solving the unconstrained optimization problem. These algorithms belong to two different class of optimization algorithms: (1) The monotone class, and (2) The non-monotone class. We prove the global convergence of the sequence of the iterates generated by the new algorithms to the first and second order critical points. Then, we propose a filter trust-region algorithm for solving bound constrained optimization problems and show that the algorithm converges to a first order critical point. Moreover, we address some well known... 

We consider sequential quadratic programming (SQP) methods applied to optimization problems with nonlinear equality constraints and simple bounds, recently introduced in the literature. In particular, we describe and analyze a truncated SQP algorithm due to Izmailov and Solodov in which subproblems are solved approximately by an infeasible predictor-corrector interior-point method, followed by setting to zero some variables and some multipliers so that complementarity conditions for approximate solutions are satisfied. Verifiable truncation conditions based on the residual of optimality conditions of subproblems are explained to ensure both global and fast local convergence. Global... 

We are concerned with describing an active-set algorithm for large-scale nonlinear programming based on the successive linear programming method proposed by Fletcher and Sainz de la Maza. The step computation is performed in two stages. In the first stage a linear program is solved to estimate the active set at the solution. The linear program is obtained by making a linear approximation to the penalty function inside a trust region. In the second stage, an equality constrained quadratic program (EQP) is solved involving only those constraints that are active at the solution of the linear program. The EQP incorporates a trust-region constraint and is solved (inexactly) by means of a... 

In financial portfolio problem, optimization models with uncertainty has been considered. The multi-stage stochastic programming methodology has been used as a solution method for these problems. In this study, we use multi-stage programming with uncertainity to evaluate the asset allocation problem. Some general models have been introduced for problem solving. Non-anticipativity and parent-child models are implemented and solved by both simplex and interior-point methods and the results are compared. The results show the parent-child model to have a better performance. Also, the interior-point method appears to need less computing time than the simplex method  

Column generation technique has became a very important tool in the solution of linear programming problems. Column generation techniques start with solving a reduced version of the master problem. Recently, variations of the standard column generation approach have been proposed which use interior point of the dual feasible set instead of optimal slutions. So, primal-dual column generation technique uses a primal-dual interior point method to obtain well-centered non-optimal solutions of the restricted master problem. We show that the method converges to an optimal solution of the master problem. Then, an improved primal simplex algorithm (IPS) for degenerate linear problems is proposed.... 

Nonlinear optimization is concerned with finding optimal solutions of optimization problems, where the objective function or some constraints are nonlinear. Since many issues in science and engineering can be expressed and formulated as a nonlinear problem, we investigate BFGS method, a successful iterative quasi-Newton method, for solving non-convex problems in unconstrained optimization. The method is based on the work of Yuan and his colleagues, making use of modified weak Wolfe-Powell line search, introducing a certain condition, introducing the next point if the condition is met, introducing a parabolic function if the condition is not established and obtaining the projection point and... 

Data collected from street networks show that travel time in urban street networks is a stochastic variable, whose range of variation increases with the congestion level. Work and school trips comprise the major part of morning peak volumes, whose common characteristic is that they need to be made on time. For this reason, these travelers are pessimistic in their route choice, and try to choose routes which are more reliable. Travel time standard deviation is one of the common measures for estimating travel time reliability that is related to properties of day-to-day travel time distribution on a particular route. Based on the empirical data collected from Tehran street network, this paper... 

Noise or noise pollution, is defined as an unwanted sound, produced mostly by motor vehicles in urban areas. If the noise exceeds its limit, adverse effects on users and citizens are expected. Thus the assessment of the noise level and its comparison with allowable values is mandatory. Traffic induced noise depends upon different factors such as traffic, weather, and, sound barriers. Noise pollution study has a long history all over the world. Many studies, mostly representing the outdoor noise pollution models, have been done in recent years. This paper presents an assessment of traffic-induced noise in a heavily traveled tunnel, locally referred to as Resalat tunnel, which is located in... 

In this thesis, we introduce a novel Artificial Intelligence (AI) system inspired by the philosophical and psychoanalytical concept of imagination as a ``Re-construction of Experiences". Our AI system is equipped with an imagination-inspired module that bridges the gap between textual inputs and other modalities, enriching the derived information based on previously learned experiences. A unique feature of our system is its ability to formulate independent perceptions of inputs. This leads to unique interpretations of a concept that may differ from human interpretations but are equally valid, a phenomenon we term as ``Interpretable Misunderstanding". We employ large-scale models,... 

Preformed particle gels (PPGs) due to its advatantage over commonly used in situ gels has been successfully applied for controlling excess water production in mature oil reservoirs. Field results of using PPGs in oil fields shows that commonly used PPGs are highly sensitive to hard reservoir conditions such as high temperature and salinity and can not effectively block fractures and high permeability layers.Objects of this study are synthesis and evaluating performance of this novel polymer based hydrogel in oil reservoirs with high temperature and salinity. Central composite design ( which is a experiment design approach) was used for synthesizing thirteen gel samples and optimal sample was... 

Sand production from oil reservoirs leads to various problems, such as well productivity reduction, operating equipment corrosion, and increased production costs. Therefore, controlling sand production in unconsolidated reservoirs is crucial for operating companies. Chemical injection into the formation in order to strengthen and reduce sand production is one of the most important methods of sand control. In this study, a hydrogel nanocomposite was designed and its effectiveness in sand control was investigated. Various tests were carried out to define and assess its efficacy, as follows: Morphological tests demonstrated the creation of a dense, homogeneous, and porous structure. Structural...