Sharif Digital Repository

Recently, numerous studies have focused on simulation and optimisation of combined cooling, heat, and power (CCHP) systems. This research, from a different perspective, aims to conduct a comprehensive review of the studies performed in the field of solar, geothermal or combined sources, and subsequently analysing the multi-objective evolutionary algorithms to identify the most efficient situation, which satisfy researchers' needs in order to attain a better performance in their ongoing or future research projects. It is worth noting that multi-objective optimisation in these cycles is based on optimising a thermodynamic term (exergy efficiency, thermal efficiency, etc.) and an economic term... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

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... 

Assessment of mechanical properties of glass/metal joints is a challenging process, especially when the application relevant conditions of the joints have to be considered in the test design. In this study, a finite element method (FEM) is implemented to analyze a torsional shear strength test designed for glass-ceramic/steel joints aiming towards solid oxide fuel/electrolysis cells application. Deviations from axial symmetry of the square flanges (ends) of respective hourglass-shaped specimens and also supporting and loading sockets of the test set-up are included in the model to simulate conditions close to reality. Undesirable tensile stress and also shear stress concentration appear at... 

Increasing efficiency, improving energy consumption, and optimizing energy in industries are more than ever considered by researchers. Some methods such as nanoparticles use and porous medium are used to increase the heat transfer rate. For this reason, in this paper, simulation and optimization of a two-dimensional tube with the presence of water–silver nanofluid and porous media have been performed to improve heat transfer. Different profiles of the rate, pressure, and temperature of the two-dimensional tube at volume fraction, porosity coefficient and Darcy numbers have been obtained and finally, the results are compared. Then, the Nusselt number and the friction coefficient in the range... 

Ejector refrigeration system has many advantages over traditional compressor-based systems, including: simplicity, low installation and operating costs and the ability to operate with low-grade thermal energy sources. However, its main drawbacks are low Coefficient of Performance (COP) and failure at high ambient temperatures. To overcome these problems, a novel methodology for designing a multi-ejector refrigeration system is proposed. This system utilizes a parallel array of ejectors instead of one ejector. Therefore, the system can continuously operate at its optimum efficiency. Each ejector works within a specific range of condensing pressures. The condenser pressure governs the... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

In this article, a new algorithm for rather expensive simulation problems is presented, which consists of two phases. In the first phase, as a model-based algorithm, the simulation output is used directly in the optimization stage. In the second phase, the simulation model is replaced by a valid metamodel. In addition, a new optimization algorithm is presented. To evaluate the performance of the proposed algorithm, it is applied to the (s,S) inventory problem as well as to five test functions. Numerical results show that the proposed algorithm leads to better solutions with less computational time than the corresponding metamodel-based algorithm. © 2017 Taylor & Francis Group, LLC  

This research study presents an investigation on the behavior of a Pulsating Heat Pipe Flat-Plate Solar Collector (PHPFPSC) by artificial neural network method and an optimization of the parameters of the collector by genetic algorithm. In this study, several experiments were performed to study the effects of various evaporator lengths, filling ratios, inclination angles, solar radiation, and input chilled water temperature between 9:00 A.M. to 5:00 P.M., and the output temperature of the water tank, which was the output of the system, was also measured. According to the input and output information, multilayer perceptron neural network was trained and used to predict the behavior of the... 

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... 

This paper surveys the literature associated with the application of evolutionary algorithms (EAs) in coastal groundwater management problems (CGMPs). This review demonstrates that previous studies were mostly relied on the application of limited and particular EAs, mainly genetic algorithm (GA) and its variants, to a number of specific problems. The exclusive investigation of these problems is often not the representation of the variety of feasible processes may be occurred in coastal aquifers. In this study, eight EAs are evaluated for CGMPs. The considered EAs are: GA, continuous ant colony optimization (CACO), particle swarm optimization (PSO), differential evolution (DE), artificial bee... 

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... 

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... 

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...