Sharif Digital Repository

Particle capture at porous media in cross-flow microfiltration is studied to investigate permeability reduction as a function of membrane pore size and particle size distribution. A new model in pore scale and its pertinent mathematical expressions, which consider pore and particle size distribution, are provided. Permeability reduction of the membrane because of size exclusion during particulate suspension flow was predicted using the developed model. It is assumed that the size exclusion is the dominant mechanism of particle retention causes pore blocking and permeability reduction in the porous media.The exact analytical solution of the stochastic model for size exclusion is used to... 

Increasing the social welfare and achieving real competitive markets are the main purposes of consumers participation in electricity markets. Hence, Demand Response Programs (DRPs) have been designed to consider the consumers participation. One of these programs named Emergency Demand Response Program (EDRP) is based on consumers' responses to high electricity prices and to the incentives that are paid by Independent System Operators (ISOs) in the critical hours. In this paper, a model has been proposed for EDRP participation in the Stochastic Security Constrained Unit Commitment (SCUC) program. Both the spinning reserve and the demand side reserve, which is modeled as EDRP, are taken into... 

In this paper, particle deposition in the upper airways and five lobes of a human lung is simulated. The simulation is based on a stochastic lung model, derived from detailed morphometric measurements. Pathways are simulated using Monte Carlo methods consequently the whole structure changes both stochastically and statistically in each simulation. In this investigation the termination phenomena is a function of each daughter's diameter which best satisfies the lung's morphometry. Complementary to the previous available assumptions, i.e. flow divisions according to the ratio of daughter's cross sections or distal volumes, in this investigation flow rates are computed in an upward manner... 

In this paper, a multiproduct multi-chance constraint stochastic inventory control problem is considered, in which the time-periods between two replenishments are assumed independent and identically distributed random variables. For the problem at hand, the decision variables are of integer-type, the service-level is a chance constraint for each product, and the space limitation is another constraint of the problem. Furthermore, shortages are allowed in the forms of fuzzy random quantities of lost sale that are backordered. The developed mathematical formulation of the problem is shown to be a fuzzy random integer-nonlinear programming model. The aim is to determine the maximum level of... 

A new mathematical model for the capacitated multi-facility location-allocation problem with probabilistic customers' locations and demands is developed in this article. The model is formulated into the frameworks of the expected value model (EVM) and the chance-constrained programming (CCP) based on two different distance measures. In order to solve the model, two hybrid intelligent algorithms are proposed, where the simplex algorithm and stochastic simulation are the bases for both algorithms. However, in the first algorithm, named SSGA, a special type of genetic algorithm is combined and in the second, SSVDO, a vibration-damping optimisation (VDO) algorithm is united. The Taguchi method... 

Production planning is one of the most important issues in manufacturing. The nature of this problem is complex and therefore researchers have studied it under several and different assumptions. In this paper, applied production planning problem is studied in a general manner and it is assumed that there exists an optimal control problem that its production planning strategy is a digital controller and must be optimized. Since this is a random problem because of stochastic values of sales in future, it is modeled as a stochastic dynamic programming and then it is transformed to a linear programming model using successive approximations. Then, it is proved that these two models are... 

This paper presents a particle swarm optimization (PSO) based fuzzy stochastic long term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level, and reduction in voltage deviation are simultaneously considered as the objective functions. At first these objectives are fuzzified and designed to be comparable with each other, then they are introduced to a PSO... 

Different sources of uncertainty in power systems, i.e., the uncertainties associated with bus loading and component availability is reflected in uncertainties in different system variables through system physical and economical relationships. A stochastic power flow algorithm can be used to model the stochastic nature of power systems. The algorithm introduced in this paper calculates the probability density function (pdf) of marginal prices of different market services. These pdfs provide the market participant with some valuable information to reduce the risk of their decisions and actions. The algorithm linearizes the optimal power flow formulation and uses the Gram-Charlier method to... 

Particle capture at porous media in cross-flow microfiltration is studied to investigate permeability reduction as a function of membrane pore size and particle size distribution. A new model in pore scale and its pertinent mathematical expressions, which consider pore and particle size distribution, are provided. Permeability reduction of the membrane because of size exclusion during particulate suspension flow was predicted using the developed model. It is assumed that the size exclusion is the dominant mechanism of particle retention causes pore blocking and permeability reduction in the porous media.The exact analytical solution of the stochastic model for size exclusion is used to... 

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the... 

In this paper, we develop the multi-product, multi-constraint, Single Period Problem (SPP) with uncertain demands, considering an incremental discount situation. Three new models are presented for multi-product, multi-constraint SPP in fuzzy, stochastic and rough environments. We consider constraints, such as service rate, restriction on order quantity and restrictions on warehouse space and budget. We also consider that the order quantity is a multiplier of predefined batch size. Furthermore, three kinds of solution algorithm, (1) harmony search, (2) hybrid intelligent based on harmony search and fuzzy simulation and (3) hybrid intelligent based on harmony search and rough simulation, are... 

Pricing coordination and due-date management are managerial challenges in today's competitive marketplace. Segmenting orders into classes and allocating resources based on their sensitivity to time and price can increase a firm's profit and its capacity utilization. In addition, other parameters such as production policy, inventory holding and delivery system should be considered in pricing and due-date decisions. In this paper, we consider the role of flexibility in price, lead-time and delivery in the make-to-order environment, where limited production capacity under a stochastic demand function is allowed. We develop a two-stage stochastic programming model to determine the price,... 

Prediction of the vibration response due to defects on rolling element bearings requires having an accurate representative vibration model. In this paper, a new model for vibration generation in the rolling element bearings has been introduced. The proposed model assumes a stochastic source of vibration excitation, which is produced as a result of metallic contact between bearing elements during rolling. This model explains high frequency vibration in the acceleration spectrum clearly. When a defect grows in the bearing, the roughness of the contacting surfaces increases locally and stochastic excitation becomes stronger in the defective area. The increased vibration level at the defective... 

Uncertainties associated with bus loading and components' availability lead to uncertainties in different system variables based on the system physical and economical relationships. Line flows, bus voltages, different prices, and other variables and indices, such as available transfer capacity (ATC), are stochastic and cannot be expressed as a determined quantity. Traditionally, in order to model the stochastic nature of power systems, a stochastic power flow algorithm is used. In this paper, stochastic-algebraic method is applied to find the probability density function (pdf) of ATC. The algorithm linearizes the optimal power flow formulation and uses Gram-Charlier expansion to find the pdf... 

This paper presents an improved stochastic simulation method for calculating current dependent energy losses in distribution networks. The method is based on power load curves and integrates the stochastic nature of the load curves with power and voltage covariance matrices. The method reduces calculation effort using the factor analysis of covariance matrices and provides a few quantities needed to calculate energy losses. The method has no limitation for network configuration and gives accurate results several times faster than other existing methods. Therefore, it is appropriate for considering losses in optimization and decision making purposes in operating and planning of distribution... 

This paper investigates the optimal operation of distribution feeder reconfiguration (DFR) strategy in the smart grids with high penetration of plug-in electric vehicles (PEVs) and correlated wind power generation. The increased utilization of PEVs in the system with stochastic volatile behavior along with the high penetration of renewable power sources such as wind turbines (WTs) can create new challenges in the system that will affect the DFR strategy greatly. In order to reach the most efficiency from the PEVs, the idea of vehicle-to-grid (V2G) is employed in this paper to make a bidirectional power flow (either charging/discharging or idle mode) strategy when providing the main charging... 

Operational and planning studies of high-wind penetrated power systems have well come to the light as a major concern of future energy systems. This paper focuses on the procedure of determining required static reserve of the high-wind penetrated power systems which has not been well accompanied by comprehensive analysis and proper modeling tools. To reach this goal, first, a probabilistic algorithm has been proposed to effectively model the variations in output generation of wind turbines. In this algorithm, the fuzzy c-means clustering method (FCM) is exploited as an efficient as well as robust clustering method to find the multi-state model of wind turbines output generation. Based on... 

In this paper, a multiproduct single vendor-single buyer supply chain problem is investigated based on the economic production quantity model developed for the buyer to minimize the inventory cost. The model to be more applicable for real-world supply chain problems contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. The objective is to find the optimal order quantities of the products such that the total inventory cost is minimized while the constraints are satisfied. The recently-developed sequential quadratic programming (SQP), as one of the best optimization methods available in the literature, is used to solve the... 

Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed in this paper. The network consists of manufacturing plants, distribution centers (DCs), and customer nodes. To bring the problem closer to reality, the majority of the parameters in this network including fixed and variable costs, customer demand, available production time, set-up and production times, all are considered stochastic. The goal is to determine the quantities of the products produced by the manufacturing plants in different periods, the number and locations of the warehouses, the quantities of products transported between the supply chain entities, the inventory of...