Intelligent fuzzy inference system approach for modeling of debonding strength in FRP retrofitted masonry elements

Mohsen Khatibinia,Mohammad Reza Mohammadizadeh 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.61 No.2

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.

An efficient approach for optimum shape design of steel shear panel dampers under cyclic loading

Mohsen Khatibinia,Aghdas Ahrari,Sadjad Gharehbaghi,Seyyed Reza Sarafrazi 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.3

The low-cycle fatigue performance of shear panel damper (SPD) highly depends on the geometry of its shape and the criterion considered for its design. The main contribution of the current study is to find the optimum shape of the SPD subjected to cyclic loading by considering two different objective functions. The maximum equivalent plastic strain and the ratio of energy dissipation through plastic deformation to the maximum equivalent plastic strain are selected as the first and second objective functions, respectively. Since the optimization procedure requires high computational efforts, a hybrid computational approach is used to perform two paramount phases of estimating the inelastic responses of the SPD and solving the optimization problem. In the first phase, as an alternative for the time-consuming finite element analysis of the SPD, a weighted-support vector machine model is developed to predict the inelastic responses of the SPDs during the optimization process. In the second phase, the optimum shape of the SPD is found by using the whale optimization algorithm (WOA). The results indicate that both design criteria lead to the optimum-shaped SPDs with a significant improvement in their low cycle fatigue performance in comparing with the initial rectangular shape while a slight reduction in their energy dissipation capacity. Moreover, the second design criterion is slightly better in the performance improvement of the optimum-shaped SPDs compared with the first one. In addition, the weighted-based SVM approach can accurately predict the inelastic responses of the SPDs under cyclic loading, and its combination with WOA results in finding the optimum solutions quickly.

Modeling mechanical strength of self–compacting mortar containing nanoparticles using wavelet–based support vector machine

Mohsen Khatibinia,Abdosattar Feizbakhsh,Ehsan Mohseni,Malek Mohammad Ranjbar 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.18 No.6

The main aim of this study is to predict the compressive and flexural strengths of self–compacting mortar (SCM) containing nano–SiO2, nano–Fe2O3 and nano–CuO using wavelet–based weighted least squares–support vector machines (WLS–SVM) approach which is called WWLS–SVM. The WWLS–SVM regression model is a relatively new metamodel has been successfully introduced as an excellent machine learning algorithm to engineering problems and has yielded encouraging results. In order to achieve the aim of this study, first, the WLS–SVM and WWLS–SVM models are developed based on a database. In the database, nine variables which consist of cement, sand, NS, NF, NC, superplasticizer dosage, slump flow diameter and V–funnel flow time are considered as the input parameters of the models. The compressive and flexural strengths of SCM are also chosen as the output parameters of the models. Finally, a statistical analysis is performed to demonstrate the generality performance of the models for predicting the compressive and flexural strengths. The numerical results show that both of these metamodels have good performance in the desirable accuracy and applicability. Furthermore, by adopting these predicting metamodels, the considerable cost and time–consuming laboratory tests can be eliminated.

Hybrid of topological derivative–based level set method and isogeometric analysis for structural topology optimization

Mehdi Roodsarabi,Mohsen Khatibinia,Seyyed R. Sarafrazi 국제구조공학회 2016 Steel and Composite Structures, An International J Vol.21 No.6

This paper proposes a hybrid of topological derivative-based level set method (LSM) and isogeometric analysis (IGA) for structural topology optimization. In topology optimization a significant drawback of the conventional LSM is that it cannot create new holes in the design domain. In this study, the topological derivative approach is used to create new holes in appropriate places of the design domain, and alleviate the strong dependency of the optimal topology on the initial design. Furthermore, the values of the gradient vector in Hamilton-Jacobi equation in the conventional LSM are replaced with a Delta function. In the topology optimization procedure IGA based on Non-Uniform Rational B-Spline (NURBS) functions is utilized to overcome the drawbacks in the conventional finite element method (FEM) based topology optimization approaches. Several numerical examples are provided to confirm the computational efficiency and robustness of the proposed method in comparison with derivative-based LSM and FEM.

Optimal design of homogeneous earth dams by particle swarm optimization incorporating support vector machine approach

Mirzaei, Zeinab,Akbarpour, Abolfazl,Khatibinia, Mohsen,Siuki, Abbas Khashei Techno-Press 2015 Geomechanics & engineering Vol.9 No.6

The main aim of this study is to introduce optimal design of homogeneous earth dams with oblique and horizontal drains based on particle swarm optimization (PSO) incorporating weighted least squares support vector machine (WLS-SVM). To achieve this purpose, the upstream and downstream slopes of earth dam, the length of oblique and horizontal drains and angle among the drains are considered as the design variables in the optimization problem of homogeneous earth dams. Furthermore, the seepage through dam body and the weight of dam as objective functions are minimized in the optimization process simultaneously. In the optimization procedure, the stability coefficient of the upstream and downstream slopes and the seepage through dam body as the hydraulic responses of homogeneous earth dam are required. Hence, the hydraulic responses are predicted using WLS-SVM approach. The optimal results of illustrative examples demonstrate the efficiency and computational advantages of PSO with WLS-SVM in the optimal design of homogeneous earth dams with drains.

Health monitoring of pressurized pipelines by finite element method using meta-heuristic algorithms along with error sensitivity assessment

Amirmohammad Jahan,Mahdi Mollazadeh,Abolfazl Akbarpour,Mohsen Khatibinia 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.87 No.3

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

Optimum design of a sliding mode control for seismic mitigation of structures equipped with active tuned mass dampers

Hussein Eliasi,Hessam Yazdani,Mohsen Khatibinia,Mehdi Mahmoudi 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.81 No.5

The active tuned mass damper (ATMD) is an efficient and reliable structural control system for mitigating the dynamic response of structures. The inertial force that an ATMD exerts on a structure to attenuate its otherwise large kinetic energy and undesirable vibrations and displacements is proportional to its excursion. Achieving a balance between the inertial force and excursion requires a control law or feedback mechanism. This study presents a technique for the optimum design of a sliding mode controller (SMC) as the control law for ATMD-equipped structures subjected to earthquakes. The technique includes optimizing an SMC under an artificial earthquake followed by testing its performance under real earthquakes. The SMC of a real 11-story shear building is optimized to demonstrate the technique, and its performance in mitigating the displacements of the building under benchmark near- and far-fault earthquakes is compared against that of a few other techniques (proportional-integral-derivative [PID], linear-quadratic regulator [LQR], and fuzzy logic control [FLC]). Results indicate that the optimum SMC outperforms PID and LQR and exhibits performance comparable to that of FLC in reducing displacements.