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RISS 인기검색어
- 검색키워드
- 저자 : Bahman Farahmand Azar (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
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Optimal Design of MR Damper Based on Tuning Bouc-Wen Model Parameters Using Hybrid Algorithms
Bahman Farahmand Azar,Hedayat Veladi,Siamak Talatahari,Farzad Raeesi 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.3
This paper presents a useful approach to optimally design magnetorheological (MR) dampers used in structural buildings. To fulfill this aim, damper parameters are regarded as the design variables whose values can be obtained through an optimization process. To improve the quality of searching for the optimum parameters of MR dampers, charged system search (CSS) and grey wolf (GW) algorithms, two of the most widely utilized meta-heuristic algorithms, are used together, and hybrid CSS-GW is presented. To show the authenticity and robustness of the new algorithm in solving optimization problems, some benchmark test functions are tested, at first. Then, an eleven-story benchmark building equipped with 3 MR dampers is considered to get the optimum design of the MR damper using the hybrid CSS-GW. Results show that the developed hybrid algorithm can successfully figure out the optimum parameters of the MR dampers.
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Seismic Performance of Composite RCS Special Moment Frames
Bahman Farahmand Azar,Hosein Ghaffarzadeh,Nima Talebian 대한토목학회 2013 KSCE Journal of Civil Engineering Vol.17 No.2
Composite Reinforced Concrete-Steel (RCS) frames which consist of Reinforced Concrete (RC) columns and Steel (S) beams were represented to combine the advantages of pure RC and steel frames. This system permits the primary steel beam to run continuous through the reinforced concrete column. This paper evaluates seismic performance of RCS frames based on FEMA-356,considering plastic rotations as acceptance criteria. The effect of joint deformations on overall behavior of RCS frames is studied through nonlinear static analysis (Pushover) that is performed in OpenSees software. It is concluded that the RCS joint behavior increases lateral load capacity of frame. Additionally, 3 RC frames are compared to RCS frames with columns similar to those of RC frames. The results show a great improvement on overall behavior since steel beams is used instead of RC beams.
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Bahman Farahmand Azar,Ali Hadidi,Amin Rafiee 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.55 No.5
This paper proposes a novel reliability analysis method which computes reliability index, most probable point and probability of failure of uncertain systems more efficiently and accurately with compared to Monte Carlo, first-order reliability and response surface methods. It consists of Initial and Simulation steps. In Initial step, a number of space-filling designs are selected throughout the variables space, and then in Simulation step, performances of most of samples are estimated via interpolation using the space-filling designs, and only for a small number of the samples actual performance function is used for evaluation. In better words, doing so, we use a simple interpolation function called “reduced” function instead of the actual expensive-to-evaluate performance function of the system to evaluate most of samples. By using such a reduced function, total number of evaluations of actual performance is significantly reduced; hence, the method can be called Reduced Function Evaluations method. Reliabilities of six examples including series and parallel systems with multiple failure modes with truncated and/or non-truncated random variables are analyzed to demonstrate efficiency, accuracy and robustness of proposed method. In addition, a reliabilitybased design optimization algorithm is proposed and an example is solved to show its good performance.
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Prediction of bond strength between concrete and rebar under corrosion using ANN
Amir Shirkhani,Daniel Davarnia,Bahman Farahmand Azar 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.23 No.4
Corrosion of the rebar embedded in concrete has a fundamental role in the determination of life and durability of the concrete structures. Researches have demonstrated that artificial neural networks (ANNs) can effectively predict issues such as expected damage in concrete structures in marine environment caused by chloride penetration, the potential of steel embedded in concrete under the influence of chloride, the corrosion of the steel embedded in concrete and corrosion current density in steel reinforced concrete. In this study, data from different kind of concrete under the influence of chloride ion, are analyzed using the neural network and it is concluded that this method is able to predict the bond strength between the concrete and the steel reinforcement in mentioned condition with high reliability.
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Upgraded salp swarm algorithm for optimal design of semi-active MR dampers in buildings
Farzad Raeesi,Hedayat Veladi,Bahman Farahmand Azar,Sina Shirgir,Baharak Jafarpurian 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.86 No.2
In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.
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