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Summary: Tensegrity systems are construction system that offers solutions for lighter designs compared with a standard truss system consisting of tension and compression elements. Due to their structure, they are recommended in the design of space structures due to the use of lighter and easy‐to‐assemble structural elements such as cables, ropes, and similar to provide the desired durability. In this study, energy minimization was carried out to solve the structural element displacements. It is expected to reduce the total potential energy of the system with minimization. By minimizing the total potential energy of the tensegrity system models, the displacement of each building element is found for the equilibrium condition. Tensegrity models were analyzed by minimizing energy via the adaptive harmony search (AHS) algorithm. In this research, two distinct tensegrity structure specimens were employed. One comprised a cantilever beam, while the other adopted a cyclic model, forming eight equal octagons from eight nodes at both the base and the top. Additionally, an examination was conducted on a two‐layer iteration of the cyclic model. The method is robust for both space and planar tensegrity structures, allowing the determination of deformed shapes under various loads without design assumptions. The TPO/MA method demonstrates superiority in handling nonlinear and barely stable systems, as evidenced by examples illustrating its efficacy in maintaining structural form under increasing loads and challenging conditions. [ABSTRACT FROM AUTHOR]

Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures. The base isolators may lose their damping capacity over time due to environmental or dynamic effects. This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-term isolator life. In this study, an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time. With the developed model, the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity, and the decrease in the damping property was tried to be determined. For this purpose, a data set was created by collecting the behavior of structures with single degrees of freedom (SDOF), different stiffness, damping ratio and natural period isolated from the foundation under far fault earthquakes. The data is divided into 5 different damping classes varying between 10% and 50%. Machine learning model was trained in damping classes with the data on the structure's response to random seismic vibrations. As a result of the isolator behavior under randomly selected earthquakes, the recorded motion and structural acceleration of the structure against any seismic vibration were examined, and the decrease in the damping capacity was estimated on a class basis. The performance loss of the isolators, which are separated according to their damping properties, has been tried to be determined, and the reductions in the amounts to be taken into account have been determined by class. In the developed prediction model, using various supervised machine learning classification algorithms, the classification algorithm providing the highest precision for the model has been decided. When the results are examined, it has been determined that the damping of the isolator structure with the machine learning method is predicted successfully at a level exceeding 96%, and it is an effective method in deciding whether there is a decrease in the damping capacity. [ABSTRACT FROM AUTHOR]

Summary: Tuned liquid dampers provide structure control with the help of the liquid mass in tanks that are attached to the structure. The mass ratio affects the optimum tuned liquid damper (TLD) parameters. This study examines the effect of mass ratio on the control performance of TLD devices in providing seismic control of structures with different damping ratios. For this purpose, TLD devices with different mass ratios were placed on two different single‐story steel and reinforced concrete structure models, and their performance under earthquake excitation was investigated. TLD parameters for obtaining the optimum displacement level in the 0.5‐ and 1.0‐s structure natural period for both structure types were optimized with the Jaya algorithm (JA), which is a metaheuristic algorithm. By using the optimum TLD parameters, the structural displacement and total acceleration values were obtained by the critical earthquake analysis. When the results are examined, it is understood that TLD mass increase from a 20% mass ratio for both structure types and selected structure periods does not have a significant effect on TLD control performance. [ABSTRACT FROM AUTHOR]

In this study, a seismic isolator placed on the base of a structure was optimized under various earthquake records using an adaptive harmony search algorithm (AHS). As known, the base-isolation systems with very low stiffness provide a rigid response of superstructure, so it was assumed that the structure is rigid and the base-isolated structure can be considered as a single-degree of freedom structure. By using this assumption, an optimization method that is independent of structural properties but specific to the chosen earthquake excitation set is proposed. By taking three different damping ratio limits and isolator displacement limits, the isolator period and damping ratio were optimized so that the acceleration of the structure was minimized for nine cases. In the critical seismic analysis performed with optimum isolator parameters, the results obtained for different damping ratios and isolator periods were compared. From the results, it is determined that isolators with low damping ratios require more ductility, and as the damping ratio increases, further restriction of the movement of the isolator increases the control efficiency. Thus, it is revealed that increasing the ductility of the isolator is effective in reducing the total acceleration in the structure. [ABSTRACT FROM AUTHOR]

This study focuses on tuned liquid dampers (TLDs) using liquids with different characteristics optimized with the adaptive harmony search algorithm (AHS). TLDs utilize the characteristic features of the liquid to absorb the dynamic forces entering the structure and benefit from the sloshing movement and the spring stiffness created by the liquid mass. TLDs have been optimized to investigate the effect of liquid characteristics on the control by analyzing various liquids. For optimization, the memory consideration ratio (HMCR) and fret width (FW) values were adapted from the classical harmony search (HS) algorithm parameters. The TLDs were used on three types of structure models, such as single-story, 10, and 40 stories. The contribution of the liquid characteristics to the damping performance was investigated by optimizing the minimum displacement under seismic excitation. According to the results, it was understood that the liquid density and kinematic viscosity do not affect single-story structures alone. However, two characteristic features should be evaluated together. As the structure mass increases, the viscosity and density become more prominent. [ABSTRACT FROM AUTHOR]

In this study, the tuned liquid damper (TLD) device was optimized by the harmony search (HS) and adaptive harmony search algorithms (AHS). Using the harmony search algorithm, seismic excitations were directed at single and ten-story structures, and TLD parameters were optimized to minimize building movement. To improve design parameters, the optimization process was repeated by adapting the design factors of the harmony search algorithm. For this purpose, both the harmony memory consideration ratio (HMCR) and fret width (FW) were gradually reduced by providing an initial value, and optimum algorithm parameters were obtained. As a result of both optimizations, in a critical seismic analysis, the displacements of the adaptive harmony search showed smaller means and standard deviations than those of the classical harmony search. [ABSTRACT FROM AUTHOR]

Summary: This study focuses on the optimization of tuned liquid dampers (TLDs) by using metaheuristic methods using a natural phenomenon as inspiration. Unlike tuned mass dampers (TMDs), TLDs consist of two parts of bodies that contain the passive liquid that is stationary and the active part of the liquid that involves in sloshing. To optimize the amount of optimum active and passive liquids by finding the best dimensional properties of the liquid tank, a two‐degree‐of‐freedom (DOF) model was used as TLD in the dynamic analysis used in the optimization that aims to reduce the maximum displacement of the structure under earthquake excitations. For this purpose, water, oil, and glycerin liquids were selected for TLD. TLD parameters were optimized with the help of Jaya algorithm, flower pollination algorithm (FPA), harmony search (HS) algorithm, and teaching–learning‐based optimization (TLBO). Total acceleration and maximum displacement were evaluated after optimization. The performance of TLD under earthquake excitations has been also compared with TMDs. According to the results, the optimized TLD has a better performance than TMD, and Jaya algorithm has a slightly better performance than the other algorithms. [ABSTRACT FROM AUTHOR]