Sharif Digital Repository

A morphing-body optimization method is introduced to accelerate adjoint-based shape optimization techniques. The optimization process solves the flow and adjoint equations around a continuously deforming body whose shape is controlled by the cost function. Effect of various parameters on the efficiency of the scheme is studied. It is found that, for the best performance of the algorithm, the morphing rate of the airfoil should be restricted, since larger rates foster oscillations and lower values are not computationally feasible. Moreover, the iterative procedure in the adjoint solver should be adapted to the iteration scheme in the flow solver and to the morphing rate  

This paper proposes a new technique to manage congestion in a short-run market model. The method consists of an iterative algorithm to search and apply a sequence of bilateral power exchanges among the generators that would optimally reduce and completely remove the congestions. A combination of fuzzy decision principle and sensitivity analysis is developed to choose the best exchange and AC load flow is used to apply it on the network in the iterations. The effectiveness of the proposed approach is illustrated in a case study on IEEE 118-bus system, and results are discussed in the paper in comparison with the mathematical and evolutionary-based optimization techniques  

An inverse dynamics musculoskeletal model of the lower extremity was combined with an optimization technique to estimate individual muscular forces and powers during stair ascent and descent. Eighteen Hill-type musculotendon actuators per leg were combined into the eleven functional muscle groups based on anatomical classification to drive the model in the sagittal plane. Simulation results illustrate the major functional differences in plantar flexors of the ankle and extensors of the knee and hip joints during ascent and descent. The results of this study not only could be employed to evaluate the rehabilitation results in the elderly but also could be used to design more anthropometric... 

Selection and development of machining features are the core activity in process planning. Usually the machining features development is done by experts according to elementary volumes. Performing this process by experts develops a limited machining features and the optimum solution may be missed. In this study a new method is developed to generate machining features and analyzes them to extract feasible features. The feasible solution is based on technical limitation of parts without any expert's judgments. Also it uses a set covering optimization technique to extract optimum one. Finally, the numerical results are presented and performance of the proposed method is tested by some candidate... 

An inverse dynamics musculoskeletal model of the lower extremity was combined with an optimization technique to estimate individual muscular forces and powers during stair ascent and descent. Eighteen Hill-type musculotendon actuators per leg were combined into the eleven functional muscle groups based on anatomical classification to drive the model in the sagittal plane. Simulation results illustrate the major functional differences in plantar flexors of the ankle and extensors of the knee and hip joints during ascent and descent. The results of this study not only could be employed to evaluate the rehabilitation results in the elderly but also could be used to design more anthropometric... 

Summary Increasing interest in smart grids exhibits its potential benefits for providing reliable, secure, efficient, environmental friendly and sustainable electricity from renewable energy resources. Here, reliability models of four types of renewable and hybrid distributed generation were developed. A fuzzy multi-objective function was suggested for simultaneous optimization of reliability, electricity generation cost, grid loss and voltage profile. This not only considers uncertainty of renewable energy resources but also provides smart generation dispatching. An efficient reliability index consisting of energy and interruption frequency terms was also defined. A novel hybrid heuristic... 

Particle Swarm Optimization (PSO) algorithms recently invented as intelligent optimizers with several highly desirable attributes. In this paper, two new hybrid Particle Swam Optimization schemes are proposed. The proposed hybrid algorithms are based on using the Particle Swarm Optimization techniques in conjunction with the Simulated Annealing (SA) approach. By simulating three different test functions, it is shown how the proposed hybrid algorithms offer the capability of converging toward the global minimum or maximum points. More importantly, the simulation results indicate that the proposed hybrid particle swarm-based simulated annealing approaches have much superior convergence... 

Maintenance scheduling of generating units in restructured power systems is a collaborative and interactive process between independent system operators (ISOs) and generating companies (GENCOs). The ISO should comply with GENCO maintenance preferences subject to targeted system reliability levels. This process might be multistage since the admission of all initial unit outage requests may threaten system reliability. Hence, the ISO accepts some proposals and determines alternatives for the remaining units. The GENCOs are then allowed to confirm the alternatives or revise them. In this paper the ISO problem of generating unit maintenance scheduling is tackled. The objective function is to... 

Accurate knowledge of pure hydrocarbon and natural gas viscosity is essential for reliable reservoir characterization and simulation as well as economic design of natural gas processing and transport units. The most trustable sources of pure hydrocarbon and natural gas viscosity values are laboratory experiments. When there is no available experimental data for the required composition, pressure, and temperature conditions, the use of predictive methods becomes important. In this communication, a novel approach was proposed to develop for prediction of viscosity of pure hydrocarbons as well as gas mixtures containing heavy hydrocarbon components and impurities such as carbon dioxide,... 

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... 

This paper presents a method to maximize the output power of a DFIG wind turbine. In this method, an optimization technique based on mathematical analysis has been used. The modeling of DFIG is performed using MATLAB. To evaluate the maximum output power of a DFIG, detailed expressions for output power and losses are derived as functions of generator slip, the magnitude and phase angle of rotor excitation voltage in various wind velocities. The outcomes of this method demonstrate that maximum output power of a DFIG wind turbine do not happen in the maximum input power (the mechanical power of wind turbine)  

In this work, the goal is to find the optimum working point for intelligent wells that is equipped with down-hole chokes and producing from a multi-layer reservoir under pressure maintenance process. Two evolutionary optimization algorithms are used and results are compared from different points of view. Therefore, the differential evolution technique and genetic algorithm has been used in conjugation with a reservoir simulator. The overall optimization technique is applied to heterogeneous example problems involving smart and multi segment wells. Improvement of predicted performance, which is as high as 7% in one case is demonstrated for all of the examples studied  

In this paper, an optimized control strategy is proposed for a split parallel hydraulic hybrid truck. The model of the vehicle was simulated in Simulink. According to a global optimization technique, a fuzzy control strategy is developed for the vehicle. This strategy shows flexibility for different drive cycles and a desirable fuel consumption reduction, especially for a low speed drive cycle, which is extracted according to an urban utility vehicle mission  

Response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. The main idea of RSM is to use a set of designed experiments to obtain an optimal response. RSM tries to simplify the original problem through some polynomial estimation over small sections of the feasible area, elaborating on optimum provision through a well known optimization technique, say Gradient Method. As the real world problems are usually very complicated, polynomial estimation may not perform well in providing a good representation of the objective function. Also, the main problem of the Gradient Method, getting trapped in local minimum (maximum),... 

In this paper, two adaptive refinement techniques are presented for enhancing the capability of the new kind of finite volume method called meshless finite volume (MFV) method in which the moving least squares (MLS) approximation technique is employed. The proposed algorithms perform by inserting new nodes in large error regions identified using the Zienkiewicz-Zhu (Z-Z) error estimator and the T-Belytschko (TB) stress recovery scheme. In the first method referred as CV-based adaptive refinement, the new nodes are inserted at the vertices of control volumes with higher errors. The second method, referred as GA-based adaptive refinement, contains two schemes where an adaptive refinement... 

Workspace of a mechanism is generally defined as the region of space which end-effector of that mechanism can reach. Determination of workspace is an important task in the design of a mechanism. However, for parallel mechanisms, due to the complexity of solving the forward kinematic equations, determination of workspace is much more complicated than for serial mechanisms. In the literature, time-consuming numerical methods, such as point-by-point searching, are usually employed for this purpose. In this paper, an optimization-based algorithm is introduced for the boundary determination of inclusive and constant orientation workspaces of parallel mechanisms. In the proposed algorithm, thanks... 

In this research work, an ultrasonic assisted drilling system is employed to apply both rotation and vibration to drill bits. The transducer horn transfers power very efficiently and changes tools effortlessly. The setup used to conduct drilling tests is Inconel 738LC with depth-to-diameter ratios from 2 to 10 by conventional drilling (CD), ultrasonic assisted drilling (UAD), and electro discharge drilling (EDD). The effects of ultrasonic vibration amplitude, spindle speed, and number of steps to drill each hole on machining force and surface roughness in UAD are investigated. The results demonstrate not only a significant improvement in tool life (by applying ultrasonic vibration to the... 

Nowadays, the need for industrial processes with sufficient accuracy, efficiency, and flexibility to compete world markets is inevitable. On the other hand, the advent of control techniques and increased computation power of CPUs allow implementation of complex controllers using optimization techniques to provide higher efficiency and economic productivity. Model predictive control refers to a wide range of optimization-based control methods applying explicit models to predict its prospective use. These methods of control compute control signal by minimizing the cost function so that the process output becomes very close to the optimal path. In this paper, we use a new model predictive... 

Inverse method and artificial neural network were employed in modeling the rheological behavior of the AZ61 Mg alloy. The hot deformation behavior of these alloys was investigated by compression tests in the temperature range 250-350 °C and strain rate range 0.0005-0.1 s-1. Investigation of stress-strain curves and microstructure of the compression specimen illustrate occurrence of dynamic recrystallization. To determining parameters of two suggested constitutive equations global optimization technique, genetic algorithm, was used. The predicted results by inverse method and ANN depicted a good agreement with the experimental data even if the ANN results has shown the best predicted... 

In the contemporary sustainable urban set up, one of the critical issues adversely affecting the quality of life in urban areas and inflicting immense costs on cities is traffic congestion. Traffic congestion is an outgrowth of increased traffic flow in certain locations of large cities. Recently, urban decision-makers and transportation planners resort to one-way traffic system as an effective traffic management strategy, which has a profound effect on reducing traffic congestion and improving traffic flow, leading to urban sustainability. In the present paper, the authors endeavored to develop a novel methodological framework based on optimization techniques in order to mitigate traffic...