An efficient particle swarm optimization-joint probability distribution optimization method for structural reliability analysis

2020 ◽  
pp. 095440622094155
Author(s):  
Hossein Mansourinejad ◽  
Kamran Daneshjou
Keyword(s):  
Particle Swarm Optimization ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Particle Swarm ◽  
Joint Probability ◽  
Joint Probability Distribution ◽  
Engineering Structures ◽  
Swarm Optimization ◽  
Highly Nonlinear ◽  
Conventional Methods

The performance function of many engineering structures and mechanisms is usually complex, highly nonlinear, and described in the implicit form. The reliability analysis of these structures using common methods requires high cost and time. In this paper, a new approach for reliability analysis of engineering structures and mechanisms by using the particle swarm optimization algorithm is presented. The advantages of this method in comparison with the conventional methods are its simplicity and accuracy. In addition, the limitations of the common previously presented methods are eliminated by the proposed method. This approach is based on a new redefinition of most probable point in the reliability analysis. To evaluate the performance and validity of the proposed method, some examples in the reliability analysis of various functions are employed. Finally, the superiority of the proposed method in performance and accuracy is demonstrated and compared to the conventional methods and it can be used for reliability analysis of complicated engineering structures.

Assessing the performances of recent global search algorithms using analytic objective functions and seismic optimization problems

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R767-R781 ◽  
Author(s):  
Mattia Aleardi ◽  
Silvio Pierini ◽  
Angelo Sajeva
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Model Space ◽  
Global Search ◽  
Objective Functions ◽  
Swarm Optimization ◽  
Fireworks Algorithm ◽  
Highly Nonlinear ◽  
Whale Optimization

We have compared the performances of six recently developed global optimization algorithms: imperialist competitive algorithm, firefly algorithm (FA), water cycle algorithm (WCA), whale optimization algorithm (WOA), fireworks algorithm (FWA), and quantum particle swarm optimization (QPSO). These methods have been introduced in the past few years and have found very limited or no applications to geophysical exploration problems thus far. We benchmark the algorithms’ results against the particle swarm optimization (PSO), which is a popular and well-established global search method. In particular, we are interested in assessing the exploration and exploitation capabilities of each method as the dimension of the model space increases. First, we test the different algorithms on two multiminima and two convex analytic objective functions. Then, we compare them using the residual statics corrections and 1D elastic full-waveform inversion, which are highly nonlinear geophysical optimization problems. Our results demonstrate that FA, FWA, and WOA are characterized by optimal exploration capabilities because they outperform the other approaches in the case of optimization problems with multiminima objective functions. Differently, QPSO and PSO have good exploitation capabilities because they easily solve ill-conditioned optimizations characterized by a nearly flat valley in the objective function. QPSO, PSO, and WCA offer a good compromise between exploitation and exploration.

scholarly journals Particle Swarm Optimization Based Highly Nonlinear Substitution-Boxes Generation for Security Applications

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 116132-116147 ◽  
Author(s):  
Musheer Ahmad ◽  
Ishfaq Ahmad Khaja ◽  
Abdullah Baz ◽  
Hosam Alhakami ◽  
Wajdi Alhakami
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Security Applications ◽  
Substitution Boxes ◽  
Highly Nonlinear

Reliability analysis of a telecommunication tower

1999 ◽  
Vol 26 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Kamal El-Fashny ◽  
Luc E Chouinard ◽  
Ghyslaine McClure
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Joint Probability ◽  
Distribution Functions ◽  
Sensitivity Analyses ◽  
Ice Thickness ◽  
Joint Probability Distribution ◽  
Type I

This study presents a structural reliability analysis of a microwave tower subject to wind and freezing-rain hazards. The tower (name code CEBJ, owned by Hydro-Québec) is a 66 m tall, three-legged, steel lattice structure located in the James Bay area. The reliability analysis is performed conditionally with respect to wind speed and ice thickness accretion, and the results are integrated over the domain of wind and ice values using their joint probability distribution. This approach makes it possible to perform sensitivity analyses with respect to various assumptions on the joint probability distribution function of the climatological variable, without having to repeat the detailed coupled reliability - structural analysis of the tower. The probability distribution functions assumed for the wind speed and the ice thickness accretion on the tower members are both extreme-value type I (Gumbel) distributions. Adopting a weakest link model, the failure of the tower is assumed to occur when any of the members fails either in tension, compression, or global buckling. Without loss of generality, the proposed procedure can be applied with more refined probability distribution functions.Key words: reliability, telecommunication towers, wind, ice.

Optimized Fuzzy Logic Controller for Semi-Active Control of Buildings Using Particle Swarm Optimization

2011 ◽  
Vol 255-260 ◽  
pp. 2505-2509 ◽  
Author(s):  
Mohammadreza Ostadali Makhmalbaf ◽  
Mohammad Amin Tutunchian ◽  
Masoud Zabihi Samani
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Active Control ◽  
Fuzzy Logic Controller ◽  
Particle Swarm ◽  
Engineering Structures ◽  
Swarm Optimization ◽  
Mr Dampers ◽  
Control Devices ◽  
Current Monitoring

Control devices can be used in structures to attenuate undesirable vibration on engineering structures. In order to mitigate the response of structures during the earthquakes and high intensity winds semi active control has been widely used. Semi-active control need less energy in compare with active control. So they are more reliable and more effective in mitigating the effects of earthquakes. MR damper are semi active control devices that are managed by sending external voltage supply. The inducing current monitoring of MR dampers are intelligently managed by fuzzy logic control (FLC). Validation of fuzzy logic controller that is optimized by a particle swarm optimization(PSO) is pursued in this study. Finally, optimal fuzzy logic controller is identified and validated through numerical simulation for seismic excitation. In 3-storey benchmark building, results showed that optimized fuzzy logic controller was robust and effective in reduction of both displacement and acceleration responses.

scholarly journals Solution of Economic Load Dispatch problem using Conventional methods and Particle Swarm Optimization

2020 ◽  
Vol 9 (10) ◽  
pp. 243-249
Keyword(s):  
Particle Swarm Optimization ◽  
Gradient Method ◽  
Power Output ◽  
Particle Swarm ◽  
Design Parameters ◽  
Economic Load Dispatch ◽  
Swarm Optimization ◽  
Network Cost ◽  
Conventional Methods ◽  
B Coefficients

Economic load dispatch is the method to find the optimum power output of the generators in a network cost-effectively with adherence to all the constraints. In this paper, the Economic Load Dispatch (ELD) problem has been tested on IEEE 14 Bus System by implementing conventional methods like Classical Coordination method, Gradient method, Modified Coordination method, and Particle Swarm Optimization (PSO). Conventional methodologies provide the solution in the simplest way but it does not handle the constraints effectively. Modified coordination method provides a better solution without the use of B-coefficients and the calculation of penalty factors is much easier because they can be obtained from the already available solution of FDLF involving some computations. PSO also provides a better solution but the initial design parameters are slightly difficult to determine. The performance of all the methods is compared and results reveal that the Modified coordination method proves to be the fastest among other solutions particularly if larger systems are involved.

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