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, optimization and control of a tubular reactor for thermal bulk post-polymerization of styrene have been investigated. By using the reactor mathematical model, static and dynamic simulations are carried out. Based on an objective function including polymer conversion and polydispersity, reactor optimal temperature profile has been obtained. In the absence of model mismatch, desired product characteristic can also be obtained by applying the corresponding reactor wall or jacket temperature profile. To achieve this temperature trajectory, reactor jacket is divided into three zones and jacket inlet temperatures are used as manipulated variables. Effectiveness of the proposed... 

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... 

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... 

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... 

This study presents a parallel evolutionary optimization approach to determine optimal management strategies of large-scale coastal groundwater problems. The population loops of evolutionary algorithms (EA) are parallelized using shared memory parallelism to address the high computational demands of such applications. This methodology is applied to solve the management problems in an aquifer system in Kish Island, Iran using a three-dimensional density-dependent groundwater numerical model. EAs of continuous ant colony optimization (CACO), particle swarm optimization, and genetic algorithm are utilized to solve the optimization problems. By implementing the parallelization strategy, a...