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Dampers can reduce structural response under dynamic loads. Since dampers are costly, the design of structures equipped with dampers should make their application economically justifiable. Among the effective cost reduction factors is optimal damper placement. Hence, this study intended to find the optimal viscous damper placement using efficient optimization methods. Taking into account the nonlinear behavior of structure, this optimal distribution can be determined through meeting story-wise damping requirements such that the structure provides the minimum dynamic response and becomes economically justified. To compare the effect of different damper placement layouts on structural response and determine the objective function of optimization, the ratio of peak structural displacement to yield displacement was used as the damage index and objective function of optimization. Colliding Bodies' Optimization (CBO) algorithm was used for optimal damper placement. In this study, the 3- and 4-story concrete frames with different damper placement conditions were studied. Results confirmed the efficiency of the proposed method and algorithm in optimal viscous damper placement in each story. It was also discovered that the application of dampers on higher stories partially uniforms height-wise damage distribution and works towards the design goals.

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The utilization of passive energy dissipation systems has been created a revolution in the structural engineering industry due to their advantages. Fluid Viscous Damper (FVD) is one of these control systems. It has been used in many different industries, such as the army, aerospace, bridge, and building structures. One of the essential questions about this system is how it can combine with the bracing system to enhance its abilities. In this paper, a comparison between the responses of a twelve-story steel building retrofitted by four layouts of bracings systems (i.e., chevron, diagonal, toggle, and X-brace) is studied. These bracing systems are equipped by FVD to find the optimum layout for these systems. Buildings are modeled nonlinearity and excited by an earthquake (Manjil earthquake). For this purpose, the Fast Nonlinear Analysis (FNA) is performed using the SAP2000 software. The results show that FVD alters some of the structural behaviors such as inter-story drift when combining with a chevron-bracing system. As a result, it can decrease the motion induced by the earthquake significantly. Besides, the results show that the chevron model has the best performance for the high-rise building in comparison with the other studied systems. As a result, for toggle, chevron, and diagonal bracing systems, the formation of link damper could absorb 66%, 72%, and 79% of input energy instead of modal damping energy, respectively.

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Economy and safety are two important components in structural design process and stablishing a balance between them indeed results in improved structural performance specially in large-scale structures including space lattice domes. Topology optimization of geometrically nonlinear single-layer lamella, network, and geodesic lattice domes is implemented using enhanced colliding-bodies optimization algorithm for three different spans and two different dead loading conditions. Collapse reliability index of these optimal designs is evaluated to assess the safety of the structures against overall collapse using Monte-Carlo simulation method. The numerical results of this study indicate that the reliability index of most of the optimally designed nonlinear lattice domes is low and this means that the safety of these structures against overall collapse is questionable.

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Nowadays, the behavior of designed structures is mostly studied using numerical software products. It is important that the models are sufficiently simple, but the calculated values approximate well the real behavior of the structures. In order for a numerical model to realistically describe the structural behavior, the software used must have material models that are parametrized accordingly. The primary purpose of this article is to create various prefabricated reinforced concrete specific joints in a simply prefabricated RC frame. Thus, in the present study, we examined prefabricated column-cup foundation and column-beam connections. The numerical analyses were carried out in the ATENA 3D software, in which the modeling technique we have developed can be used to examine reinforced concrete structures and structural details at a high level. In these studies, we highlight the differences between linear and nonlinear numerical methodologies. During our investigations, we analyze the joints of the examined frame in separate models on which we operate monotonically increasing vertical and horizontal loads. We examine the obtained load-displacement graphs, the failure of the connections, and the behavior of the elements that make up each connection.
Finally, we extended the relationship by modeling the beam of the frame position, pointing out the behavior of the entire structure.

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The multiple tuned mass dampers (MTMDs) are considered among the control systems used for reducing the vibration of buildings under seismic excitations. A large number of the previous studies have mainly emphasized on the utilization and effectiveness of MTMD on linear structure responses, and few of them have investigated the effectiveness of MTMD on nonlinear multi-degree of freedom structures. Thus, in this paper, the effectiveness of MTMD on nonlinear buildings have been investigated. The effectiveness of the MTMD systems lies in their parameters, and the location of dampers in buildings. Accordingly, the optimization of MTMD’s properties, as well as its location, are taken into account in the present study. The Mouth Brooding Fish algorithm, which is a new optimization method is utilized for optimizing the properties corresponding to the MTMD system. The effectiveness levels of the MTMDs were compared with the efficiency of an equal optimally tuned mass damper (TMD), which was placed on the top of the building. The results of these comparisons revealed that MTMDs have provided a better efficiency compared to TMDs in reducing the maximum displacement of nonlinear structures. Moreover, MTMDs have a higher effectiveness when placed on different floors of the building.

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In present study, the effects of optimization on seismic energy spectra including input energy, damping energy and yielding hysteretic energy are parametrically discussed. To this end, 12 generic steel moment-resisting frames having fundamental periods ranging from 0.3 to 3s are optimized by using uniform damage and deformation approaches subjected to a series of 40 non-pule strong ground motions. In order to obtain the optimum distribution of structural properties, an iterative optimization procedure has been adopted. In this approach, the structural properties are modified so that inefficient material is gradually shifted from strong to weak areas of a structure. This process is continued until a state of uniform damage is achieved. Then, the maximum energy demand parameters are computed for different structures designed by optimum load pattern as well as code-based pattern, and the mean energy spectra, energy-based reduction factor and the dispersion of the results are compared and discussed. Results indicate that optimum seismic load pattern can significantly affect the energy demands spectra especially in inelastic range of response. In addition, using energy-based reduction factors of optimum structures in short-period and long-period regions will result in respectively overestimation and underestimation of the required input energy demands for code-based structures, reflecting the difference dose exists in reality between the conventional forced-based methodology and energy-based seismic design approach that can more realistically incorporate the frequency content and duration of earthquake ground motions.
 

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The main purpose of this paper was to use a combination of Energy-based design method and whale algorithm (WOA), hereinafter referred to as E-WOA, to optimize steel moment frames and improve the seismic performance. In E-WOA, by properly estimating the seismic input energy and determining the optimal mechanism for the structure, steel frames are designed based on the energy balance method; according to the results, in a suitable search space, optimization is performed using the WOA algorithm. The objective function of the WOA algorithm, in addition to the frame weight, is meant to improve the behavior of the structure based on the performance level criteria of the ASCE41-17 standard and the uniformity of the drift distribution at the frame height. The results show that the initial design of the Energy method reduces the computational volume of the WOA algorithm to achieve the optimal solution and the plastic hinge pattern in frame is more favorable in the E-WOA method than in the design done by the Energy method.
 

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Explosions are inevitable in today’s world; therefore, building structures may be dynamically loaded by an intense loading during the explosion. This is why regulatory bodies have provided instructions for determining the response of structures under the explosion load. Previous research has shown that when the explosion happens close to a structure, the ground explosion load can be modeled as tensile and compressive loads. This research investigates the response of an elastic-plastic single-degree-of-freedom system subjected to different explosive loads with different positive durations. The maximum intensity of blast load and blast duration remains constant, and the positive phase duration is the only variable that changes. The nonlinear dynamic responses of a single-degree-of-freedom system (i.e., displacement, velocity, acceleration, and ductility) are calculated using the linear acceleration method. The results show that increasing the positive phase duration and the amount of positive impact can increase the maximum displacement and ductility of the system. Also, it can be concluded that the maximum acceleration of the studied systems remains constant when the values for the blast impact and positive phase durations change.
 

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The real-world applications addressing the nonlinear functions of multiple variables could be implicitly assessed through structural reliability analysis. This study establishes an efficient algorithm for resolving highly nonlinear structural reliability problems. To this end, first a numerical nonlinear optimization algorithm with a new simple filter is defined to locate and estimate the most probable point in the standard normal space and the subsequent reliability index with a fast convergence rate. The problem is solved by using a modified trust-region sequential quadratic programming approach that evaluates step direction and tunes step size through a linearized procedure. Then, the probability expectation method is implemented to eliminate the linearization error. The new applications of the proposed method could overcome high nonlinearity of the limit state function and improve the accuracy of the final result, in good agreement with the Monte Carlo sampling results. The proposed algorithm robustness is comparatively shown in various numerical benchmark examples via well-established classes of the first-order reliability methods. The results demonstrate the successive performance of the proposed method in capturing an accurate reliability index with higher convergence rate and competitive effectiveness compared with the other first-order methods.
 

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Despite the advantages of the plastic limit analysis of structures, this robust method suffers from some drawbacks such as intense computational cost. Through two recent decades, metaheuristic algorithms have improved the performance of plastic limit analysis, especially in structural problems. Additionally, graph theoretical algorithms have decreased the computational time of the process impressively. However, the iterative procedure and its relative computational memory and time have remained a challenge, up to now. In this paper, a metaheuristic-based artificial neural network (ANN), which is categorized as a supervised machine learning technique, has been employed to determine the collapse load factors of two-dimensional frames in an absolutely fast manner. The numerical examples indicate that the proposed method's performance and accuracy are satisfactory.
 

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Most industrial-practical projects deal with nonlinearity phenomena. Therefore, it is vital to implement a nonlinear method to analyze their behavior. The Finite Element Method (FEM) is one of the most powerful and popular numerical methods for either linear or nonlinear analysis. Although this method is absolutely robust, it suffers from some drawbacks. One of them is convergency issues, especially in large deformation problems. Prevalent iterative methods such as the Newton-Raphson algorithm and its various modified versions cannot converge in certain problems including some cases such as snap-back or through-back. There are some appropriate methods to overcome this issue such as the arc-length method. However, these methods are difficult to implement. In this paper, a computational framework is presented based on meta-heuristic algorithms to improve nonlinear finite element analysis, especially in large deformation problems. The proposed method is verified via different benchmark problems solved by commercial software. Finally, the robustness of the proposed algorithm is discussed compared to the classic methods.
 

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Most industrial-practical projects deal with nonlinearity phenomena. Therefore, it is vital to implement a nonlinear method to analyze their behavior. The Finite Element Method (FEM) is one of the most powerful and popular numerical methods for either linear or nonlinear analysis. Although this method is absolutely robust, it suffers from some drawbacks. One of them is convergency issues, especially in large deformation problems. Prevalent iterative methods such as the Newton-Raphson algorithm and its various modified versions cannot converge in certain problems including some cases such as snap-back or through-back. There are some appropriate methods to overcome this issue such as the arc-length method. However, these methods are difficult to implement. In this paper, a computational framework is presented based on meta-heuristic algorithms to improve nonlinear finite element analysis, especially in large deformation problems. The proposed method is verified via different benchmark problems solved by commercial software. Finally, the robustness of the proposed algorithm is discussed compared to the classic methods.

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