Data Mining Technology for Structural Control Systems: Concept, Development, and Comparison

Structural control systems are classified into four categories, that is, passive, active, semi-active, and hybrid systems. These systems must be designed in the best way to control harmonic motions imposed to structures. Therefore, a precise powerful computer-based technology is required to increase the damping characteristics of structures. In this direction, data mining has provided numerous solutions to structural damped system problems as an all-inclusive technology due to its computational ability. This chapter provides a broad, yet in-depth, overview in data mining including knowledge view (i.e., concept, functions, and techniques) as well as application view in damped systems, shock absorbers, and harmonic oscillators. To aid the aim, various data mining techniques are classified in three groups, that is, classification-, prediction-, and optimization-based data mining methods, in order to present the development of this technology. According to this categorization, the applications of statistical, machine learning, and artificial intelligence techniques with respect to vibration control system research area are compared. Then, some related examples are detailed in order to indicate the efficiency of data mining algorithms. Last but not least, capabilities and limitations of the most applicable data mining-based methods in structural control systems are presented. To the best of our knowledge, the current research is the first attempt to illustrate the data mining applications in this domain

Optimal design of double skin façades as vibration absorbers

In this paper, several layouts of double skin façades (DSF) used as mass dampers to reduce the vibrations in structures under seismic events are discussed. Firstly, the mathematical coupled problem is studied considering a non-classically damped system excited by a set of accelerogram records. The design problem aims to determine the optimal values of four parameters, namely the flexural stiffness and damping of the DSF panel and the stiffnesses of the elements that connect the DSF to the primary structure. Secondly, four objective functions are presented. Two of these functions aim to minimise respectively the displacements and the accelerations of the primary structure for each earthquake. The remaining two, instead, minimise the average of the displacements and accelerations calculated for all the accelerograms given. Finally, numerical analysis are performed on a six-storey building and four DSF designs are proposed. The Particle Swarm Optimisation (PSO) is used to estimate the optimal parameters. Comparisons among the DSF layouts are presented in terms of minima of the objective functions and in terms of the power transfer functions. Moreover, a simplified design method for the connection elements is discussed

Optimization of a reinforced concrete structure subjected to dynamic wind action

This work proposes a methodology to optimize a reinforced concrete structure. For this, the Whale Optimization Algorithm (WOA) algorithm was used, an algorithm from the group of metaheuristic algorithms, which presents an easy computational implementation. As a study object, a frame structure adapted from a real reinforced concrete building was used, subjected to the dynamic action of artificially generated synoptic wind. The objective function is to reduce the volume of concrete of the structure. For that, the dimensions of the cross-sections were used as design variables, and the maximum displacement at the top imposed by the ASCE / SEI 7-10 standard as a lateral constraint, as well as the maximum story drift between floors. In addition to this structural optimization, it was also proposed the use and optimization of Tuned Mass Dampers (TMD), in different quantities, positions and parameters, improving the dynamic response of the reinforced concrete building. The results show that for this situation it was possible to reduce the concrete volume of the structure by approximately 24%, respecting the maximum limit of displacement at the top required by the standard

Optimization of a reinforced concrete structure subjected to dynamic wind action

This work proposes a methodology to optimize a reinforcedconcrete structure. For this, the Whale Optimization Algorithm (WOA)algorithm was used, an algorithm from the group of metaheuristicalgorithms, which presents an easy computational implementation. As astudy object, a frame structure adapted from a real reinforced concretebuilding was used, subjected to the dynamic action of artificially generatedsynoptic wind. The objective function is to reduce the volume of concreteof the structure. For that, the dimensions of the cross-sections were used asdesign variables, and the maximum displacement at the top imposed by theASCE / SEI 7-10 standard as a lateral constraint, as well as the maximumstory drift between floors. In addition to this structural optimization, it wasalso proposed the use and optimization of Tuned Mass Dampers (TMD), indifferent quantities, positions and parameters, improving the dynamicresponse of the reinforced concrete building. The results show that for thissituation it was possible to reduce the concrete volume of the structure byapproximately 24%, respecting the maximum limit of displacement at thetop required by the standard

PSO based TMD & ATMD control for high-rise structure excited by simulated fluctuating wind field

This paper reports a novel control strategy combined with artificial intelligence for wind-induced vibration control of a high-rise structure and also provides a broader idea for traditional structural vibration control. The fast Fourier transform based on decimation-in-time was used to optimize the waves with a weighted amplitude method, and the wind speed field was numerically generated according to a Davenport - type fluctuating wind speed spectrum. A second-generation benchmark structure was selected as the high-rise building model. Tuned mass damper (TMD) and active tuned mass damper (ATMD) served as the controller, and the linear- quadratic- Gaussian algorithm served as the active control algorithm for ATMD. Simultaneously, the particle swarm  optimization algorithm was introduced, and the integral of the absolute value of the error based on the relative displacement of floors with regard to the ground level was defined as a performance index for optimizing. The numerical results reveal that both of the two proposed controllers have excellent capability in reducing wind-induced vibrations in high-rise buildings; moreover, the PSO-based ATMD performed better than PSO-based TMD

Teaching-learning based optimization for parameter estimation of double tuned mass dampers

The classical methods for parameter estimation of tuned mass dampers are well known simple formulations, but these formulations are only suitable for multiple degree of freedom structures by considering a single mode. If special range limitation of tuned mass dampers and inherent damping of the main structure are considered, the best way to estimate the parameters is to use a numerical method. The numerical method must have a good convergence and computation time. In that case, metaheuristic methods are effective on the problem. Generally, metaheuristic method is inspired from a process of life and it is formulated for several steps in order to reach an optimal goal. Differently from the single tuned mass dampers, double tuned mass dampers can be also used for the reduction of vibrations. In civil structures, earthquake excitation is a major source of vibrations. In this study, optimum double tuned mass dampers are investigated for seismic structures by using a wide range of earthquake records for global optimum. As an optimization algorithm, teaching learning based optimization is employed. In this algorithm, the teaching and learning phases of a class are modified for optimization problems. The optimization of double tuned mass damper is more challenging than the single ones since the number of design variable is doubled and the design constraint about the stroke of the both masses must be considered. The proposed method is compared with the existing approaches and the methodology is feasible for parameter estimation of double tuned mass dampers

Comparing H2 and H∞ Algorithms for Optimum Design of Tuned Mass Dampers under Near-Fault and Far-Fault Earthquake Motions

In this study, the robust optimum design of Tuned Mass Damper (TMD) is established. The H2 and H∞ norm of roof displacement transfer function are implemented and compared as the objective functions under Near-Fault (NF) and Far-Fault (FF) earthquake motions. Additionally, the consequences of different characteristics of NF ground motions such as forward-directivity and fling-step are investigated on the behavior of a benchmark 10-story controlled structure. The Colliding Bodies Optimization (CBO) is employed as an optimization technique to calculate the optimum parameters of the TMDs. The resulting statistical assessment shows that the H∞ objective function is rather superior to H2 objective function for optimum design of TMDs under NF and FF earthquake excitations. Finally, the robustness of the designed TMDs is evaluated under a large set of natural ground motions

Optimal Design of Passive and Active Control Systems in Seismic-excited Structures Using a New Modified TLBO

Vibration control devices have recently been used in structures subjected to wind and earthquake excitations. The optimal design problems of the passive control device and the feedback gain matrix of the controller for the seismic-excited structures are some attractive problems for researches to develop optimization algorithms with the advancement in terms of simplicity, accuracy, speed, and efficacy. In this paper, a new modified teaching–learning-based optimization (TLBO) algorithm, known as MTLBO, is proposed for the problems. For some benchmark optimization functions and constrained engineering problems, the validity, efficacy, and reliability of the MTLBO are firstly assessed and compared to other optimization algorithms in the literature. The undertaken statistical indicate that the MTLBO performs better and reliable than some other algorithms studied here. The performance of the MTLBO will then be explored for two passive and active structural control problems. It is concluded that the MTLBO algorithm is capable of giving better results than conventional TLBO. Hence, its utilization as a simple, fast, and powerful optimization tool to solve particular engineering optimization problems is recommended

Active control for machinery equipment induced structural vibration using H∞ criterion and PSO technique

In this paper, machinery equipment induced structural vibration was investigated and a composite system for structure and equipment was proposed. Tuned mass damper (TMD) and active tuned mass damper (ATMD) were respectively performed for vibration control, in addition, particle swarm optimization (PSO) was utilized for pursuing an optimal active control. Numerical results confirmed that the presented active control strategy could achieve a better vibration suppression compared to TMD control. The PSO based active control also gave inspiration for improving the traditional vibration control

Invited Review: Recent developments in vibration control of building and bridge structures

This paper presents a state-of-the-art review of recent articles published on active, passive, semi-active and hybrid vibration control systems for structures under dynamic loadings primarily since 2013. Active control systems include active mass dampers, active tuned mass dampers, distributed mass dampers, and active tendon control. Passive systems include tuned mass dampers (TMD), particle TMD, tuned liquid particle damper, tuned liquid column damper (TLCD), eddy-current TMD, tuned mass generator, tuned-inerter dampers, magnetic negative stiffness device, resetting passive stiffness damper, re-entering shape memory alloy damper, viscous wall dampers, viscoelastic dampers, and friction dampers. Semi-active systems include tuned liquid damper with floating roof, resettable variable stiffness TMD, variable friction dampers, semi-active TMD, magnetorheological dampers, leverage-type stiffness controllable mass damper, semi-active friction tendon. Hybrid systems include shape memory alloys-liquid column damper, shape memory alloy-based damper, and TMD-high damping rubber