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Refined microstructure of compo cast nanocomposites: the performance of combined neuro-computing, fuzzy logic and particle swarm techniques
, Article Neural Computing and Applications ; 2014 ; ISSN: 09410643 ; Rahimipour, M. R ; Tofigh, A. A ; Davami, P ; Sharif University of Technology
Abstract
Aluminum metal matrix composites (MMCs) reinforced with nanoceramics are ideal materials for the manufacture of lightweight automotive and other commercial parts. Adaptive neuro-fuzzy inference system combined with particle swarm optimization method is implemented in this research study in order to optimize the parameters in processing of aluminum MMCs. In order to solve the problems associated with poor wettability, agglomeration and gravity segregation of nanoparticles in the melt, a mixture of alumina and aluminum particles was used as the reinforcement instead of raw nanoalumina. Microstructural characterization shows dendritic microstructure for the sand cast and non-dendritic...
Dynamic diversity enhancement in particle swarm optimization (DDEPSO) algorithm for preventing from premature convergence
, Article Procedia Computer Science ; Volume 24 , 2013 , Pages 54-65 ; ISSN: 18770509 ; Bahrampour, A ; Jamshidlou, P ; Sharif University of Technology
2013
Abstract
The problem of early convergence in the Particle Swarm Optimization (PSO) algorithm often causes the search process to be trapped in a local optimum. This problem often occurs when the diversity of the swarm decreases and the swarm cannot escape from a local optimal. In this paper, a novel dynamic diversity enhancement particle swarm optimization (DDEPSO) algorithm is introduced. In this variant of PSO, we periodically replace some of the swarm's particles by artificial ones, which are generated based on the history of the search process, in order to enhance the diversity of the swarm and promote the exploration ability of the algorithm. Afterwards, we update the velocity of the artificial...
Active and reactive power control of a DFIG using a combination of VSC with PSO
, Article World Applied Sciences Journal ; Volume 13, Issue 2 , 2011 , Pages 316-323 ; 18184952 (ISSN) ; Hashemnia, N ; Kashiha, A ; Sharif University of Technology
Abstract
Nowadays, application of renewable energies has taken a rapid trend. Wind energy is among those mostly used for this purpose. Doubly Fed Induction Generators (DFIG) are widely used in wind power plants due to several advantages such as partial rating converter, capability of decoupled active and reactive power control, etc. Application of a suitable control strategy is of great importance in wind power plants. In this paper, the parameters of a hybrid controller are calculated using Particle Swarm Optimization (PSO) subjected to satisfying the required criteria in output active and reactive powers of a DFIG. In the proposed system Direct Power Controller (DPC), Variable Structure Controller...
Control of the cedra brachiation robot using combination of controlled lagrangians method and particle swarm optimization algorithm
, Article Iranian Journal of Science and Technology - Transactions of Mechanical Engineering ; Volume 44, Issue 1 , 2020 , Pages 11-21 ; Vossoughi, G ; Azadi Yazdi, E ; Sharif University of Technology
Springer
2020
Abstract
This paper studies the control of a brachiating robot imitating the locomotion of a long armed ape. The robot has two revolute joints, but only one of them is actuated. In this paper, after deriving dynamic model of the robot, the Controlled Lagrangians (CL) method is used to design a controller for point to point locomotion. The CL method involves satisfying a number of equations called matching conditions. The matching conditions are derived using the extended λ-method in the form of a set of partial differential equations (PDEs). Solving the PDEs, a class of controllers is found that satisfies the matching conditions. The fittest controller in the class of controllers is then chosen by...
Thermoeconomic analysis and multi-objective optimization of an integrated solar system for hydrogen production using particle swarm optimization algorithm
, Article Journal of Thermal Engineering ; Volume 7, Issue 4 , 2021 , Pages 746-760 ; 21487847 (ISSN) ; Assareh, E ; Moltames, R ; Taghipour, A ; Barati, H ; Sharif University of Technology
Yildiz Technical University
2021
Abstract
This study aims to investigate the hydrogen production process using an integrated system based on solar energy. This system includes an evacuated tube collector to absorb solar energy as input energy of the system. A parametric analysis was conducted to determine the most important design parameters and evaluate these parameters' impact on the system's objective functions. For identifying the optimum system conditions, multi-objective optimization was performed using particle swarm optimization (PSO) algorithm. The results obtained from the parametric analysis show that an increment in the collector mass flow rate and the turbine inlet temperature, as well as a decrement in the collector...
Numerical-Experimental geometric optimization of the Ahmed body and analyzing boundary layer profiles
, Article Journal of Optimization Theory and Applications ; 2021 ; 00223239 (ISSN) ; Mashhadian, A ; Amiri, S ; Esfahanian, V ; Afshin, H ; Sharif University of Technology
Springer
2021
Abstract
The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a...
Numerical-Experimental geometric optimization of the ahmed body and analyzing boundary layer profiles
, Article Journal of Optimization Theory and Applications ; 2021 ; 00223239 (ISSN) ; Mashhadian, A ; Amiri, S ; Esfahanian, V ; Afshin, H ; Sharif University of Technology
Springer
2021
Abstract
The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a...
GPH: A group-based partitioning scheme for reducing total power consumption of parallel buses
, Article Microprocessors and Microsystems ; Volume 35, Issue 1 , 2011 , Pages 68-80 ; 01419331 (ISSN) ; Koohi, S ; Hessabi, S ; Sharif University of Technology
2011
Abstract
Two main sources for power dissipation in parallel buses are data transitions on each wire and coupling between adjacent wires. So far, many techniques have been proposed for reducing the self and coupling powers. Most of these methods utilize one (or more) control bit(s) to manage the behavior of data transitions on the parallel bus. In this paper, we propose a new coding scheme, referred to as GPH, to reduce power dissipation of these control bits. GPH coding scheme employs partitioned Bus Invert and Odd Even Bus-Invert coding techniques. This method benefits from Particle Swarm Optimization (PSO) algorithm to efficiently partition the bus. In order to reduce self and coupling powers of...
A novel partitioned encoding scheme for reducing total power consumption of parallel bus
, Article 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 90-97 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN) ; Koohi, S ; Hessabi, S ; Sharif University of Technology
2008
Abstract
Two main sources for power dissipation in parallel buses are data transitions on each wire and coupling between adjacent wires. There are many techniques for reducing the transition and coupling powers. These methods utilize extra control bits to manage the behavior of data transitions on parallel bus. In this paper, we propose a new coding scheme which tries to reduce power dissipation of control bits. The proposed method employs partitioned Bus Invert and Odd Even Bus Invert coding techniques. This method benefits from Particle Swarm Optimization (PSO) algorithm to efficiently partition the bus. In order to reduce transition and coupling power of control bits, it finds partitions with...
Towards optimization of toeplitz matrices for compressed sensing
, Article 2013 Iran Workshop on Communication and Information Theory ; May , 2013 , Page(s): 1 - 5 ; 9781467350235 (ISBN) ; Aghagolzadeh, A ; Marvasti, F ; Sharif University of Technology
2013
Abstract
ABSTRACT Compressed sensing is a new theory that samples a signal below the Nyquist rate. While Gaussian and Bernoulli random measurements perform quite well on the average, structured matrices such as Toeplitz are mostly used in practice due to their simplicity. However, the signal compression performance may not be acceptable. In this paper, we propose to optimize the Toeplitz matrices to improve its compression performance to recover sparse signals. We establish the optimization on minimizing the coherence of the measurement matrix by an intelligent optimization method called Particle Swarm Optimization. Our simulation results show that the optimized Toeplitz matrix outperforms the...
Application of novel ANFIS-PSO approach to predict asphaltene precipitation
, Article Petroleum Science and Technology ; Volume 36, Issue 2 , 2018 , Pages 154-159 ; 10916466 (ISSN) ; Taherpour, A ; Bemani, A ; Hamule, T ; Sharif University of Technology
Taylor and Francis Inc
2018
Abstract
Asphaltene precipitation is known as one of the challenging problems in petroleum industries which have significant effects on production such as formation damage and wellbore plugging. To solve this problem, calculation of precipitated asphaltene becomes highlighted so in the present study a novel approach is proposed based on ANFIS algorithm to estimate precipitated asphaltene in terms of dilution ration, carbon number of precipitants and temperature. The particle swarm optimization (PSO) method is applied to optimize ANFIS algorithm parameters. The proposed model was evaluated based on statistical parameters and the calculated R2, AARD and RMSE for the total data are 0.90309, 9.4908 and...
Optimal placement of switching and protection devices in radial distribution networks to enhance system reliability using the AHP-PSO method
, Article Turkish Journal of Electrical Engineering and Computer Sciences ; Volume 27, Issue 1 , 2019 , Pages 181-196 ; 13000632 (ISSN) ; Fotuhi Firuzabad, M ; Sharif University of Technology
Turkiye Klinikleri Journal of Medical Sciences
2019
Abstract
This paper presents a new method to determine the optimal number and locations of autorecloser and sectionalizer switches (AR/S) in distribution networks. The costs of AR/S investment, switch maintenance, and undistributed energy as well as reliability coefficients are considered in the objective function. Reliability parameters such as SAIFI, SADI, MAIFI, and ENS are evaluated in the case study system. As a new method, the weights of the reliability parameters are obtained by decision-makers using the analytical hierarchy process (AHP). The optimal size, type, and location of automatic switches are determined by minimizing the objective function using the particle swarm optimization (PSO)...
Flowshop sequence-dependent group scheduling with minimisation of weighted earliness and tardiness
, Article European Journal of Industrial Engineering ; Volume 13, Issue 1 , 2019 , Pages 54-80 ; 17515254 (ISSN) ; Salmasi, N ; Varmazyar, M ; Sharif University of Technology
Inderscience Enterprises Ltd
2019
Abstract
In this research, we approach the flowshop sequence-dependent group scheduling problem with minimisation of total weighted earliness and tardiness as the objective for the first time. A mixed integer linear programming model is developed to solve the problem optimally. Since the proposed research problem is proven to be NP-hard, a hybrid meta-heuristic algorithm based on the particle swarm optimisation (PSO) algorithm, enhanced with neighbourhood search is developed to heuristically solve the problem. Since the objective is a non-regular, a timing algorithm is developed to find the best schedule for each sequence provided by the metaheuristic algorithm. A lower bounding method is also...
Optimization of the K-Out-of-N Systems using Particle Swarm Optimization Method
, M.Sc. Thesis Sharif University of Technology ; Eshraghniaye Jahromi, Abdolhamid (Supervisor)
Abstract
In this study, redundancy allocation problem for a system with y subsystem including k-out-of-n structure is investigated. Due to existing repairable components in each subsystem, the model consists of selecting number of repairman and redundancy level for each subsystem. The model is constructed based on Markovian process and the goal is maximization of steady-state availability under constraints such as cost, weight, and volume. In this model, two type of costs are considered; cost of employing repairmen and cost of preparing components and decision variables of the model are number of repairman and number of component in each subsystem.The model is located into integer non-linear...
Optimal design and operation of a photovoltaic-electrolyser system using particle swarm optimisation
, Article International Journal of Sustainable Energy ; 2014 ; ISSN: 14786451 ; Maroufmashat, A ; Roshandel, R ; Khavas, S. S
Abstract
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...
An evolutionary decoding method for HMM-based continuous speech recognition systems using particle swarm optimization
, Article Pattern Analysis and Applications ; Vol. 17, issue. 2 , 2014 , pp. 327-339 ; Razzazi, F ; Sameti, H ; Sharif University of Technology
Abstract
The main recognition procedure in modern HMM-based continuous speech recognition systems is Viterbi algorithm. Viterbi algorithm finds out the best acoustic sequence according to input speech in the search space using dynamic programming. In this paper, dynamic programming is replaced by a search method which is based on particle swarm optimization. The major idea is focused on generating initial population of particles as the speech segmentation vectors. The particles try to achieve the best segmentation by an updating method during iterations. In this paper, a new method of particles representation and recognition process is introduced which is consistent with the nature of continuous...
A Model for optimizing railway alignment considering bridge costs, tunnel costs, and transition curves
, Article Urban Rail Transit ; Volume 5, Issue 4 , 2019 , Pages 207-224 ; 21996687 (ISSN) ; Shafahi, Y ; Hashemian, S. E ; Sharif University of Technology
Springer
2019
Abstract
Owing to wide-ranging searches (there are various alignments between two points) as well as complex and nonlinear cost functions and a variety of geometric constraints, the problem of optimal railway alignment is classified as a complex problem. Thus, choosing an alignment between two points is usually done based on a limited number of alignments designed by experts. In recent years, the study of railway alignment optimization has shown the importance of optimization and the introduction of various algorithms and their usefulness in solving different problems. It is expected that applying meta-heuristic optimization algorithms such as methods based on swarm intelligence can lead to better...
Suppression of torsional vibrations in drilling systems by using the optimization-based adaptive back-stepping controller
, Article International Journal of Mechanics and Control ; Volume 20, Issue 1 , 2019 , Pages 105-110 ; 15908844 (ISSN) ; Fakhar, M ; Sharif University of Technology
Levrotto and Bella
2019
Abstract
Stick-slip oscillations are one of the main sources of system failure and bit damage in a rotary drilling system. Thus, suppressing such vibrations is of great importance. There are different modelling approaches demonstrating drill string dynamics, among which lumped parameter models are more common in control studies due to faster computations. Since the system dynamic includes uncertain terms, in this paper an adaptive back-stepping controller is proposed. To tune controller gains, particle swarm optimization algorithm has been employed which guarantees a better control performance. The simulation results demonstrate the feasibility of the designed controller. The results have been also...
Numerical investigation of stability of deep excavations supported by soil-nailing method
, Article Geomechanics and Geoengineering ; 2019 ; 17486025 (ISSN) ; Maleki, J ; Aghakhani, N ; Yousefi, M ; Sharif University of Technology
Taylor and Francis Ltd
2019
Abstract
Deep excavation in urban areas can cause instability problems due to significant settlement at the ground surface and large movements at the excavation facing walls. One of the most popular methods used to stabilise these excavations is utilising soil-nailing method. This method has also been widely used to stabilise natural slopes and earth retaining structures. Because of the complexity involved in the mechanism of this stabilising system due to interacting effects of the soil, nails, grout and shotcrete, numerical modelling with high accuracy should be used to analyse the behaviour of the soil-nailed walls. Considering all aspects of soil-structure interaction in the present research, a...
Numerical investigation of stability of deep excavations supported by soil-nailing method
, Article Geomechanics and Geoengineering ; 2019 ; 17486025 (ISSN) ; Maleki, J ; Aghakhani, N ; Yousefi, M ; Sharif University of Technology
Taylor and Francis Ltd
2019
Abstract
Deep excavation in urban areas can cause instability problems due to significant settlement at the ground surface and large movements at the excavation facing walls. One of the most popular methods used to stabilise these excavations is utilising soil-nailing method. This method has also been widely used to stabilise natural slopes and earth retaining structures. Because of the complexity involved in the mechanism of this stabilising system due to interacting effects of the soil, nails, grout and shotcrete, numerical modelling with high accuracy should be used to analyse the behaviour of the soil-nailed walls. Considering all aspects of soil-structure interaction in the present research, a...