Sharif Digital Repository

Access to a computational tractable method for representing the system more realistically has always been an important issue in power system reliability assessment. The Post Optimal Analysis (POA), as a well recognized technique to attack a set of similar optimization problems, has been successfully used to assess the reliability of composite systems. This method exploits the similarity of the system states to speed up the contingency evaluation procedure without sacrificing the accuracy of the results. In this paper, the performance and practical feasibility of the POA technique for power system reliability evaluation is tested using the Iran power grid. The POA based approach is applicable... 

In this paper, design, simulation and optimization of a novel electrothermally-activated polymeric microactuator capable of generating combination of bidirectional lateral and rotational motions are presented. The composite structure of this actuator is consisted of a symmetric meandered shape silicon skeleton, a SU8 thermal expandable polymer and a thin film chrome layer heater. This actuator is controlled by applying appropriate voltages on its four terminals. With the purpose of dimension optimization, a numerical parametric study is executed. The modeled actuator which is 1560 ?m long, 156 ?m wide and 30 ?m thick, demonstrates a remarkable lateral displacement of 23 ?m at power... 

This paper presents artificial neural network (ANN) meta-models for expensive continuous simulation optimization (SO) with stochastic constraints. These meta-models are used within a sequential experimental design to approximate the objective function and the stochastic constraints. To capture the non-linear nature of the ANN, the SO problem is iteratively approximated via non-linear programming problems whose (near) optimal solutions obtain estimates of the global optima. Following the optimization step, a cutting plane-relaxation scheme is invoked to drop uninformative estimates of the global optima from the experimental design. This approximation is iterated until a terminating condition... 

Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

In this paper, we consider the problem of optimum rate adaptation and power allocation to maximize the delay-limited throughput (DLT) in a time-correlated 2×1 MISO Rayleigh fading channel with Hybrid ARQ in Chase-Combining mode (HARQ-CC). To this aim, we have first formulated the DLT equation based on the outage probability for 2×1 MISO-HARQ channel. We show that exact analytical calculation of the outage probability is not tractable. Therefore, we approximate the outage probability using a log-normal approximation approach. Based on such approximation, optimal rate and power allocations are derived. Finally, using Monte-Carlo simulation, we show that the approximation method provides... 

It is important to test the attitude control systems on satellites before they are launched in space. Traditionally this has been done by dropping the satellite, and firing the thrusters before the satellite makes a soft landing in a net. This method only allows a few seconds of testing and does not lend itself to the measurement of pointing accuracy. A better method is to mount the satellite on a spherical air bearing. In this paper behavior of a semi spherical air bearing is studied and analyzed in various conditions. These bearings are used in different applications such as simulation of approximately frictionless condition which is the satellite's situation in space. In this analysis... 

This paper is concerned with the study of the constant due-date assignment policy in repetitive projects, where the activity durations are exponentially distributed random variables. It is then extended to the case where activity durations follow generalized Erlang distributions. The main feature of this research over the classical PERT networks is that the projects are generated according to a renewal process and share the same facilities. Our approach is first to obtain the project completion time distribution, for each generated project, by constructing a proper continuous-time Markov chain, and then to compute the optimal constant lead time for each particular project. The repetitive... 

The main attempt of this paper is to present a new methodology to model a generic low-level flight close to terrain, which guarantees terrain collision avoidance. Benefiting the advantages of high-speed computer technology, this method uses satellite elevation maps to generate so-called "quad-tree forms". The latter is then used to find the optimal trajectories for low-level flights. The novelty of this approach, entitled the "cost map," lies in the integration of aircraft dynamics into the segmented map. This procedure results in some near-optimal trajectories with respect to aircraft dynamics that could easily be used for minimization of flight path together with pilot effort. Different... 

We describe an intelligent co-simulator for real time production control of a complex flexible manufacturing system (CFMS) having machine and tool flexibility. The manufacturing processes associated with the CFMS are complicated with each operation being possibly done by several machining centers. The co-simulator design approach is built upon the theory of dynamic meta-model based supervisory control with the cooperation of its own embedded intelligent blocks. The system is implemented by coupling of the centralized simulation controller (CSC) and real-time simulator for enforcing dynamic strategies of shop floor control. The posteriori adaptive co-simulator is equipped with a concurrent... 

This paper investigates the problem of assembly line balancing problem, in which the products in the production line may undergo to be reworked on the current task. Since the real manufacturing systems deal with the stochastic nature of the items in production lines, this paper considers the simple assembly line balancing problem type 2 (SALBP-II) under the conditions of stochastic processing time of tasks and the element of reworking system. Exposing to the stochastic conditions encouraged us to handle the problem via simulation optimization procedure, which uses the well known genetic algorithm as an optimization tool. Results show the adaptation and effectiveness of GA to considered... 

Nowadays pull system is widely used in many industries. In the recent decade, many researchers adopt pull system to supply chain and present preference of this system. In this paper, a general Pull system for a stochastic supply chain process will be adapted along with optimizing a Pull Stochastic Supply chain. This Supply Chain, SC, is used with combining CONWIP and KANBAN, the two famous pull systems, for controlling the SC. Under assumptions of stochastic demand rate, stochastic production and transportation times, and stochastic distributions for backlog cost, a simulation modeling is used. In optimization process, concerning supply chain complexity, a simulation optimization procedure... 

In this paper, an optimal design is performed for powder die-pressing process based on the genetic algorithm approach. It includes the shape optimization of powder component, the optimal design of punch movements, and the friction optimization of powdertool interface. The genetic algorithm is employed to perform an optimal design based on a fixed-length vector of design variables. The technique is used to obtain the desired optimal compacted component by verifying the prescribed constraints. The numerical modeling of powder compaction simulation is applied based on a large deformation formulation, powder plasticity behavior, and frictional contact algorithm. A Lagrangian finite element... 

This paper presents an evolutionary based approach to achieve optimal management of a coastal aquifer to control saltwater intrusion. An improved Elitist Continuous Ant Colony Optimization (ECACO) algorithm is employed for optimal control variables setting of coastal aquifer management problem. The objectives of the optimal management are; maximizing the total water-pumping rate, while controlling the drawdown limits and protecting the wells from saltwater intrusion. Since present work is one of the first efforts towards the application of an ECACO algorithm, sharp interface solution for steady state problem is first exploited. The performance of the developed optimization model is evaluated... 

Purpose - The purpose of this paper is to present a shape optimization technique for powder forming processes based on the genetic algorithm approach. The genetic algorithm is employed to optimize the geometry of component based on a fixed-length vector of design variables representing the changes in nodal coordinates. The technique is used to obtain the desired optimal compacted component by changing the boundaries of component and verifying the prescribed constraints. Design/methodology/approach - The numerical modeling of powder compaction simulation is applied based on a large deformation formulation, powder plasticity behavior, and frictional contact algorithm. A Lagrangian finite... 

We study the problem of optimizing the symbol error probability (SEP) performance of cluster-based cooperative wireless sensor networks (WSNs). We propose that to achieve the minimum SEP at the destination, a joint optimization of power allocation and relay selection should be accomplished. To this aim, we reformulate the SEP performance of a simple cluster-based cooperative WSN in the general form and solve the joint optimization problem efficiently. Simulation results demonstrate that the proposed joint optimization can efficiently improve the SEP performance of the network in comparison with the previous disjoint optimal relay selection schemes  

In this paper, dynamic programming alignment is replaced by a particle swarm optimization (PSO) procedure in time warping problem. The basic PSO is a very slow process to be applied to speech recognition application. In order to achieve a higher performance, by inspiring of PSO optimization methodology, we introduced a PSO Inspired Time warping Algorithm (PTW) that significantly increase the computational performance of time warping in alignments of long length massive data sets. As a main enhancement, a pruning strategy with an add-in controlling threshold is defined in PTW that causes a considerable reduction in recognition time, while maintaining the system accuracy comparing to DTW. ©... 

Estimation of efficiency of axial flow gas turbines under variety of conditions i.e. different speed and pressure ratio has been hampered by lack of reliable experimental data and experiments cost. Because the flow in an axial turbine is complex and many mechanisms of the flow losses in turbine have not been known well, loss models are necessary not only in the preliminary process of mean line prediction, but also in the further process of through flow calculation in the simulation and optimization of turbines. Present study has been carried out using 1-D modeling. Simulation computer code is prepared for one-stage axial turbine based on Ainley&Mathieson method with some modifications in the... 

This paper presents a comprehensive comparison between job-level dynamic scheduling algorithms on real-time multiprocessor environments using simulation. Earliest Deadline First (EDF) and Least Laxity First (LLF) are two well-known and extensively applied dynamic scheduling algorithms which have been proved to be optimal on uniprocessor systems. However, neither is shown to be optimal on multiprocessors. Many researches have already been done on aforementioned algorithms, but to the best of our knowledge, none of which has compared the efficiency of the two algorithms under similar conditions. Perhaps the main reason is that LLF algorithm is fully dynamic and impractical to implement. In... 

In this paper, a flux search controller is proposed to increase the efficiency of a direct torque controlled induction motor with light load. The reference flux value is determined through a two stage minimization algorithm with the amplitude of the stator current as the objective function. In the transient state, a great flux step is used to speed up the convergence. In the steady state, a noise cancellation algorithm is used to let using small flux step and improves the steady state behavior of flux controller. Simulation and experimental confirm the fast dynamics of the proposed method and its superiority compared to the other optimal flux search controllers. © 2005 IEEE  

Inorganic scale deposition has been found to affect many industrial processes, including water injection into the oil reservoirs. The incompatibility of high sulfate ion content of seawater with formation water containing calcium ions results in formation damage and production decline. In this study, several simultaneous techniques are utilized for qualitative and quantitative analyses of calcium sulfate scale to get more insight into the formation damage during smart water flooding at micro and nanoscales. In the experimental section, calcium sulfate deposition due to the mixing of the formation water and seawater samples was investigated using the dynamic quartz crystal microbalance...