• Smart Structures and Systems
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• 제15권3호
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Smart Structures and Systems
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• 제22권4호
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• pp.399-411
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• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.

• 한국공간구조학회논문집
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• 제18권4호
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• pp.97-104
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• 2018

A connected control method for the adjacent buildings has been studied to reduce dynamic responses. In these studies, seismic loads were generally used as an excitation. Recently, multi-hazards loads including earthquake and strong wind loads are employed to investigate control performance of various control systems. Accordingly, strong wind load as well as earthquake load was adopted to evaluate control performance of adaptive smart coupling control system against multi-hazard. To this end, an artificial seismic load in the region of strong seismicity and an artificial wind load in the region of strong winds were generated for control performance evaluation of the coupling control system. Artificial seismic and wind excitations were made by SIMQKE and Kaimal spectrum based on ASCE 7-10. As example buildings, two 20-story and 12-story adjacent buildings were used. An MR (magnetorheological) damper was used as an adaptive smart control device to connect adjacent two buildings. In oder to present nonlinear dynamic behavior of MR damper, Bouc-Wen model was employed in this study. After parametric studies on MR damper capacity, optimal command voltages for MR damper on each seismic and wind loads were investigated. Based on numerical analyses, it was shown that the adaptive smart coupling control system proposed in this study can provide very good control performance for Multi-hazards.

• Structural Monitoring and Maintenance
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• 제7권4호
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• pp.319-344
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• 2020

Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

• Smart Structures and Systems
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• 제29권5호
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• pp.729-746
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• 2022

In this paper, a nonlinear structural model updating methodology based on the Deep Belief Network (DBN) is proposed. Firstly, the instantaneous parameters of the vibration responses are obtained by the discrete analytical mode decomposition (DAMD) method and the Hilbert transform (HT). The instantaneous parameters are regarded as the independent variables, and the nonlinear model parameters are considered as the dependent variables. Then the DBN is utilized for approximating the nonlinear mapping relationship between them. At last, the instantaneous parameters of the measured vibration responses are fed into the well-trained DBN. Owing to the strong learning and generalization abilities of the DBN, the updated nonlinear model parameters can be directly estimated. Two nonlinear shear-type structure models under two types of excitation and various noise levels are adopted as numerical simulations to validate the effectiveness of the proposed approach. The nonlinear properties of the structure model are simulated via the hysteretic parameters of a Bouc-Wen model and a Giuffré-Menegotto-Pinto model, respectively. Besides, the proposed approach is verified by a three-story shear-type frame with a piezoelectric friction damper (PFD). Simulated and experimental results suggest that the nonlinear model updating approach has high computational efficiency and precision.

• Structural Engineering and Mechanics
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• 제38권1호
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• pp.39-63
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• 2011

Referring to the formulation of physical stochastic optimal control of structures and the scheme of optimal polynomial control, a nonlinear stochastic optimal control strategy is developed for a class of structural systems with hysteretic behaviors in the present paper. This control strategy provides an amenable approach to the classical stochastic optimal control strategies, bypasses the dilemma involved in It$\hat{o}$-type stochastic differential equations and is applicable to the dynamical systems driven by practical non-stationary and non-white random excitations, such as earthquake ground motions, strong winds and sea waves. The newly developed generalized optimal control policy is integrated in the nonlinear stochastic optimal control scheme so as to logically distribute the controllers and design their parameters associated with control gains. For illustrative purposes, the stochastic optimal controls of two base-excited multi-degree-of-freedom structural systems with hysteretic behavior in Clough bilinear model and Bouc-Wen differential model, respectively, are investigated. Numerical results reveal that a linear control with the 1st-order controller suffices even for the hysteretic structural systems when a control criterion in exceedance probability performance function for designing the weighting matrices is employed. This is practically meaningful due to the nonlinear controllers which may be associated with dynamical instabilities being saved. It is also noted that using the generalized optimal control policy, the maximum control effectiveness with the few number of control devices can be achieved, allowing for a desirable structural performance. It is remarked, meanwhile, that the response process and energy-dissipation behavior of the hysteretic structures are controlled to a certain extent.

• Structural Engineering and Mechanics
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• 제40권3호
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• pp.431-451
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• 2011

Time delay inevitably exists in active control systems, and it may cause the degradation of control efficiency or instability of the systems. So time delay needs to be compensated in control design in order to eliminate its negative effect on control efficiency. Today time delay in linear systems has been more studied and some treating methods had been worked out. However, there are few treating methods for time delay in nonlinear systems. In this paper, an active controller for a nonlinear and hysteretic building structure with time delay is studied. The nonlinear and hysteretic behavior of the system is illustrated by the Bouc-Wen model. By specific transformation and augmentation of state parameters, the motion equation of the system with explicit time delay is transformed into the standard state space representation without any explicit time delay. Then the fourth-order Runge-Kutta method and instantaneous optimal control method are applied to the controller design with time delay. Finally, numerical simulations and comparisons of an eight-story building using the proposed time-delay controller are carried out. Simulation results indicate that the control performance will deteriorate if time delay is not taken into account in the control design. The simulations also prove the proposed time delay controller in this paper can not only effectively compensate time delay to get better control effectiveness, but also work well with both small and large time delay problems.

• 대한토목학회논문집
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• 제28권5A호
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• pp.685-690
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• 2008

최근 대규모의 지진피해로 인해 내진설계에 대한 관심이 높아지면서, LRB(Lead Rubber Bearing), FPS(Friction Pendulum System) 등 다양한 지진격리장치에 대한 연구가 진행되고 있다. 본 연구에서 E-Shape 강재이력댐퍼를 이용한 지진격리장치의 성능 평가를 위해 E-Shape 댐퍼의 동적거동 실험을 수행하였으며, 이를 바탕으로 해석적 연구를 위한 수치모델을 제안하였다. 또한, 제안된 E-Shape 강재이력댐퍼의 수치모델을 6자유도를 가진 5층 건물에 적용하여 LRB 시스템과 이력거동을 비교하여 지진격리성능 평가를 수행하였다. 본 연구를 통하여 제안된 수치모델은 실제 E-Shape 강재이력댐퍼의 동적거동을 적절히 묘사할 수 있으며, E-Shape 강재이력댐퍼는 비선형 거동을 통한 에너지를 적절히 소산시킴으로서 기존 시스템과 비교하여 충분히 지진격리성능을 발휘할 수 있을 것으로 사료된다.