Sharif Digital Repository

A mathematical model for a fixed bed radial flow catalytic reactor was developed for dehydrogenation of heavy paraffins over Pt-Sn/Al2O3 catalyst. The model included appropriate kinetic rate expressions for the main dehydrogenation reaction as well as side reactions and catalyst deactivation. The reactor model consisted of a set of partial and ordinary as well as algebraic equations that were solved numerically to determine the concentration of various species along the radius of the bed as a function of time. The Nelder-Mead optimization method was used to obtain the optimum kinetic parameters. The validity of the model was demonstrated by comparing the predicted paraffin conversion and... 

Recurrent neural networks based on reservoir computing are increasingly being used in many applications. Optimization of the topological structure of the reservoir and the internal connection weights for a given task is one of the most important problems in reservoir computing. In this paper, considering the fact that one can construct a large matrix using Kronecker products of several small-size matrices, we propose a method to optimize the reservoir. Having a small number of parameters to optimize, a gradient based algorithm is applied to optimize parameters, and consequently the reservoir. In addition to reducing the number of parameters for optimization, potentially, the method is able... 

A hybrid genetic algorithm (HGA) was introduced to allocate optimum amount of gas. This method was applied to a group of wells in gas lift in the case of availability limited amount of gas. For testing the ability of the proposed HGA, the results of this work with those of previous works in a field with six wells were compared. Then for an Iranian southern west oil field with nine wells, gas allocation is performed using different amount of available gas. The results show that the introduced method (HGA) is very efficient tool in gas allocation issue  

In this paper, optimal production and maintenance planning of a flexible manufacturing system under a time variant demand is considered. There is a preventive maintenance plan to reduce the failure rate of the machine. It is assumed that the failure rate of the machine is a function of its age and its maintenance rate. It is, also, assumed that the demand of the manufacturing product is time dependent and its rate depends on the level of the advertisement on that product, The objective is to maximize the expected discounted total profit of the firm over an infinite time horizon. To solve this optimization problem, first, an optimal control is characterized by a set of Hamilton-Jacobi-Bellman... 

Photovoltaic-electrolyzer systems are one of the most promising alternatives for obtaining hydrogen from a renewable energy source. Determining size and the operational conditions are always a key issue while coupling directly renewable electricity sources to PEM electrolyzer. In this research, the multi objective optimization approach based on an imperialist competitive algorithm (ICA), which is employed to optimize the size and the operating conditions of a directly coupled photovoltaic (PV)-PEM electrolyzer. This allows the optimization of the system by considering two different objectives, including, minimization of energy transfer loss and maximization of hydrogen generation. Multi... 

In this paper, we used echo state networks - a class of recurrent neural networks - for prediction of drought based on remote sensing data. To this end, the drought index was obtained for a number of stations in different clime zones of Iran. For each station, we also extracted the corresponding vegetation indices based on satellite imagery. Our model takes the satellite-based features as input and outputs the severity of drought. One of the major challenges of echo state networks is optimization of the reservoir parameters. Here we used a method based on Kronecker product in order to substantially reduce the parameter space to be optimized. We then used various optimization techniques... 

A cooperative supply chain seeks to coordinate its members to produce and distribute products along the chain, for minimum overall costs to satisfy customer demand. An integrated multi-period, multiple product and multiple stage supply chain is formulated using a flow networks framework. A Cooperative Supply Chain Optimizer (CSCO), as a central software entity taking advantage of Grid technology, connects and gathers necessary operational information from members of the corporate supply chain. The CSCO then guides supply chain members on ordering decisions, for a minimum overall cost of the entire supply chain, while continuously re-directing the members as new data becomes available. The... 

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different... 

Production optimization is defined as the process of maximizing oil production over the long term while minimizing total production costs. The overall goal is to achieve the optimum profitability from the well or field. In this process, the reservoir system can be considered as a multiple input–output system. In this complex system injection and production wells are known as inputs and outputs. The output of the system is often affected by various parameters consisting reservoir conditions, petrophysics, and PVT data. The optimization of the injector rates and number and installation of submersible pumps are the main issues which have been studied in this paper. Determining the factor with... 

The bacterial strain MJ01 was isolated from stock tank water of one of the Iranian south oil field production facilities. The 16S rRNA gene of isolate, MJ01, showed 99% similarity to Bacillus subtilis. The results revealed that biosurfactant produced by this strain was lipopeptide-like surfactin based on FTIR analysis. Critical micelle concentration of produced surfactin in distilled water was 0.06 g/l. Wettability study showed that at zero salinity surfactin can change original oil-wet state to water-wet state, but in seawater salinity it cannot modify the wettability significantly. To utilize this biosurfactant in ex situ MEOR process, economical and reservoir engineering technical... 

In this paper we consider a two-level supply chain system consisting of one warehouse and one retailer. The retailer faces Poisson demand. We introduce a new approach to inventory control in the supply chain management which is different from the classical policies used in the literature of inventory and production control systems. In this system, the retailer constantly orders a fixed amount of product to the warehouse in a predetermined time interval; i.e., the ordering size and the time interval between any two consecutive orders from the retailer to the warehouse are fixed numbers. The advantage of this policy is that the warehouse is facing a uniform and deterministic demand which... 

Optimization of any production operation is a tool for increasing production rates and reducing production costs. Water flooding is one of the techniques that frequently be used to increase oil recovery after primary depletion. A methodology for optimizing the production by using the net present value of a heterogeneous reservoir under water flooding has been presented, which is based on controlling the bottomhole pressures of the production wells, using smart well technology. For this purpose, a numerical flow simulator is coupled with an optimization program. The technique was implemented on a synthetic two dimensional oil reservoir with heterogeneous permeability. This optimization... 

When the reservoir energy is too low for the well to flow, or the production rate desired is greater than the reservoir energy can deliver, using some kind of artificial lift method to provide the energy to bring the fluid to the surface, seems to be necessary. Continuous flow gas lift is one of the most common artificial lift methods widely used in the oil industry during which, at appropriate pressure, gas is injected in a suitable depth into the tubing to gasify the oil column, and thus assist the production. Each well has an optimal point at which it will produce the most oil. In ideal conditions, at which there is no limitation in the total amount of available gas, a sufficient amount... 

Hydrogen is considered to be the fuel of the future. It is a cleaner alternative to the fossil fuels we consume every day. Of all the different hydrogen production pathways that exist, producing the gas by utilizing the power generated by renewable energy sources has been a topic of interest for many researchers across the world. The following work focuses on minimizing the energy loss by optimizing the size and the operating conditions of an electrolyzer directly connected to a photovoltaic (PV) module at different irradiance. The hydrogen, in the proposed system, is produced using a proton exchange membrane (PEM) electrolyzer. A nonlinear method is considered, because of the complexity of... 

Recently production optimization has gained increasing interest in the petroleum industry. The most computationally expensive part of the production optimization process is the evaluation of the objective function performed by a numerical reservoir simulator. Employing surrogate models (a.k.a. proxy models) as a substitute for the reservoir simulator is proposed for alleviating this high computational cost.In this study, a novel approach for constructing adaptive surrogate models with application in production optimization problem is proposed. A dynamic Artificial Neural Networks (ANNs) is employed as the approximation function while the training is performed using an adaptive sampling... 

The aim of this research was to present an experimental method for large-scale production of silver chloride nanoparticles using spinning disk reactor. Silver nitrate and sodium chloride were used as the reactants, and the protecting agent was gelatin. The experiments were carried out in a continuous mode by injecting the reactants onto the surface of the spinning disk, where a chemical precipitation reaction took place to form AgCl particles. The effects of various operating variables, including supersaturation, disk rotational speed, reactants flow rate, disk diameter, and excess ions, on the particle size of products were investigated. In addition, the AgCl nanoparticles were...