• Smart Structures and Systems
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• v.9 no.5
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• pp.411-426
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• 2012

Thin-walled adaptive structures render a large and important group of adaptive structures. Typical material system used for them is a composite laminate that includes piezoelectric material based sensors and actuators. The piezoelectric active elements are in the form of thin patches bonded onto or embedded into the structure. Among different types of patches, the paper considers those polarized in the thickness direction. The finite element method (FEM) imposed itself as an essential technical support for the needs of structural design. This paper gives a brief description of a developed shell type finite element for active/adaptive thin-walled structures and the element is, furthermore, used as a tool to consider the aspect of mesh distortion over the surface of actuators and sensors. The aspect is of significance for simulation of behavior of adaptive structures and implementation of control algorithms.

• Smart Structures and Systems
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• v.20 no.4
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• pp.441-450
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• 2017

The objective of this work is to present a conceptual design and the modelling of a distributed sensor system based on fiber optic devices (Fiber Bragg Grating, FBG), aimed at measuring span-wise and chord-wise variations of an adaptive (morphing) trailing edge. The network is made of two different integrated solutions for revealing deformations of the reference morphing structure. Strains are confined to typical values along the span (length) but they are expected to overcome standard ranges along the chord (width), up to almost 10%. In this case, suitable architectures may introduce proper modulations to keep the measured deformation low while preserving the information content. In the current paper, the designed monitoring system combines the use of a span-wise fiber reinforced patch with a chord-wise sliding beam. The two elements make up a closed grid, allowing the reconstruction of the complete deformed shape under the acceptable assumption that the transformation refers to regular geometry variations. Herein, the design logic and some integration issues are reported. Preliminary experimental test results are finally presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.447-455
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• 1999

An adaptive mesh generation scheme is developed for effective non-linear analysis of the shell structures under large deformation. In particular, based on a posteriori error estimation, remeshing method on each load step is of primary interest here. An advancing front method, called paving method, is adopted for remeshing. It can be known that the adaptive mesh generation using contours of spacing values obtained from stress errors has an advantage in the adaptive analysis of the shell structures.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• Structural Engineering and Mechanics
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• v.24 no.2
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• pp.269-273
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• 2006

• Smart Structures and Systems
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• v.15 no.4
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• pp.1041-1062
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• 2015

In this paper a method of finding optimal positions for piezoelectric actuators and sensors on different structures is presented. The genetic algorithm and multi-objective genetic algorithm are selected for optimization and $H_{\infty}$ norm is defined as a cost function for the optimization process. To optimize the placement concerning the selected modes simultaneously, the multi-objective genetic algorithm is used. The optimization is investigated for two different structures: a cantilever beam and a simply supported plate. Vibrating structures are controlled in a closed loop with feedback gains, which are obtained using optimal LQ control strategy. Finally, output of a structure with optimized placement is compared with the output of the structure with an arbitrary, non-optimal placement of piezoelectric patches.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.275-290
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• 2014

In this paper, Simple Adaptive Control (SAC) method is used to mitigate the detrimental effects of earthquakes on MR-damper equipped structures. Acceleration Feedback (AF) is utilized since measuring the acceleration response of structures is known to be reliable and inexpensive. The SAC is simple, fast and as an adaptive control scheme, is immune against the effects of plant and environmental uncertainties. In the present study, in order to translate the desired control force into an applicable MR damper command voltage, a neural network inverse model is trained, validated and used through the simulations. The effectiveness of the proposed AF-based SAC control system is compared with optimal H2/LQG controllers through numerical investigation of a three-story model building. The results indicate that the SAC controller is substantially effective and reliable in both undamaged and damaged structural states, specifically in reducing acceleration responses of seismically excited buildings.

• Smart Structures and Systems
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• v.5 no.5
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• pp.507-515
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• 2009

The present work is an alternative methodology in order to balance a nonlinear highly flexible rotor by using neural networks. This procedure was developed aiming at improving the performance of classical balancing methods, which are developed in the context of linearity between acting forces and resulting displacements and are not well adapted to these situations. In this paper a fully experimental procedure using neural networks is implemented for dealing with the adaptive balancing of nonlinear rotors. The nonlinearity results from the large displacements measured due to the high flexibility of the foundation. A neural network based meta-model was developed to represent the system. The initialization of the learning procedure of the network is performed by using the influence coefficient method and the adaptive balancing strategy is prone to converge rapidly to a satisfactory solution. The methodology is tested successfully experimentally.

• Smart Structures and Systems
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• v.19 no.5
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• pp.577-585
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• 2017

In this paper, an adaptive fuzzy sliding mode controller (AFSMC) is designed to reduce dynamic responses of seismically excited structures. In the conventional sliding mode control (SMC), direct implementation of switching-type control law leads to chattering phenomenon which may excite unmodeled high frequency dynamics and may cause vibration in control force. Attenuation of chattering and its harmful effects are done by using fuzzy controller to approximate discontinuous part of the sliding mode control law. In order to prevent time-consuming obtaining of membership functions and reduce complexity of the fuzzy rule bases, adaptive law based on Lyapunov function is designed. To demonstrate the performance of AFSMC method and to compare with that of SMC and fuzzy control, a linear three-story scaled building is investigated for numerical simulation based on the proposed method. The results indicate satisfactory performance of the proposed method superior to those of SMC and fuzzy control.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.271-274
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• 2007

The finite element linear buckling analysis of folded plate structures using adaptive h-refinement methods is presented in this paper. The variable-node flat shell element used in this study possesses the drilling D.O.F. which, in addition to improvement of the element behavior, permits an easy connection to other elements with six degrees of freedom per node. The Box-typed structures can be analyzed using these developed flat shell elements. By introducing the variable node elements some difficulties associated with connecting the different layer patterns, which are common in the adaptive h-refinement on quadrilateral mesh, can be overcome. To obtain better stress field for the error estimation, the super-convergent patch recovery is used. The convergent buckling modes and the critical loads associated with these modes can be obtained.