• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Structural Engineering and Mechanics
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• v.9 no.4
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• pp.397-416
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• 2000

The present study deals with the nonlinear dynamics and stability of autonomous dissipative either imperfect potential (limit point) systems or perfect (bifurcational) non-potential ones. Through a fully nonlinear dynamic analysis, performed on two simple 2-DOF models corresponding to the classes of systems mentioned above, and with the aid of basic definitions of the theory of nonlinear dynamical systems, new important phenomena are revealed. For the first class of systems a third possibility of postbuckling dynamic response is offered, associated with a point attractor on the prebuckling primary path, while for the second one the new findings are chaos-like (most likely chaotic) motions, consecutive regions of point and periodic attractors, series of global bifurcations and point attractor response of always existing complementary equilibrium configurations, regardless of the value of the nonconservativeness parameter.

• Advances in nano research
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• v.9 no.3
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• pp.147-156
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• 2020

This research is related to nonlinear stability analysis of advanced microbeams reinforced by Graphene Platelets (GPLs) considering generic geometrical imperfections and thermal loading effect. Uniform, linear and nonlinear distributions of GPLs in transverse direction have been considered. Imperfection sensitivity of post-bucking behaviors of the microbeam to different kinds of geometric imperfections have been examined. Geometric imperfection is first considered to be identical as the first buckling mode, then a generic function is employed to consider sine-type, local-type and global-type imperfectness. Modified couple stress theory is adopted to incorporate size-dependent behaviors of the beam at micro scale. The post-buckling problem is solved analytically to derive load-amplitude curves. It is shown that post-buckling behavior of microbeam is dependent on the type geometric imperfection and its magnitude. Also, post-buckling load can be enhanced by adding more GPLs or selecting a suitable distribution for GPLs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1319-1329
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• 2012

Globally stabilizing adaptive fuzzy state- and output-feedback controllers for the fully nonaffine pure-feedback nonlinear system are proposed in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis to be considerably simplified. For the global stabilty of the clossed-loop system, the self-structuring fuzzy system whose memebership functions and fuzzy rules are automatically generated and tuned is adopted. The proposed controllers employ only one fuzzy logic system to approximate unknown nonlinear function, which highlights the simplicity of the proposed adaptive fuzzy controller. Moreover, the output-feedback controller of the considered system proposed in this paper have not been dealt with in any literature yet.

• Computers and Concrete
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• v.6 no.4
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• pp.319-341
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• 2009

A new formulation based on lumped plasticity and inelastic hinges is presented in this paper for nonlinear analysis of Reinforced Concrete (RC) frame structures. Inelastic hinge behaviour is described using the principles of Continuum Damage Mechanics (CDM). Member formulation contains provisions to model stiffness degradation due to cracking of concrete and yielding of reinforcing steel. Depending on its nature, cracking is classified as concentrated or distributed. Concentrated cracking is accounted through a damage variable and its growth is defined based on strain energy principles. Presence of distributed flexural cracks in a member is taken care of by modelling it as non-prismatic. Plasticity theory supported by effective stress concept of CDM is applied to describe the post-yield response. Nonlinear quasi-static analysis is carried out on a RC column and a wide two-storey RC frame to verify the formulation. The column is subjected to constant axial load and monotonic lateral load while the frame is subjected to only lateral load. Computed results are compared with those due to experiments or other numerical methods to validate the performance of the formulation and also to highlight the contribution of distributed cracking on global response.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.957-962
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• 2012

Fluid/structure interaction (FSI) analysis is necessary to predict the response of a system in which aerodynamic pressure causes deformation of the structure, and vice versa. In dealing with a nonlinear behavior of the structure, however, a simple iterative algorithm of aerodynamic analysis with structural analysis yields no accurate results since aerodynamic pressure need to be changed in accordance with the deformation of structures. In this study, we explore an efficient and accurate method for integrating FSI analysis into structural nonlinear systems. During the course of nonlinear structural analysis, loading conditions are periodically updated by aerodynamic analysis. The accuracy and efficiency of the method is demonstrated with a high-aspect-ratio flexible wing of Global Hawk.

• Earthquakes and Structures
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• v.5 no.1
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• pp.1-22
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• 2013

Soft storey failure mechanism is a common collapse mode for masonry-infilled (MI) reinforced concrete (RC) buildings subjected to severe earthquakes. Simple analytical equations correlating global with local ductility demands are derived from pushover (PO) analyses for seismic assessments of regular MI RC frames, considering the critical interstorey drift ratio, number of storeys and lateral loading configurations. The reliability of the equations is investigated using incremental dynamic analyses for MI RC frames of up to 7 storeys. Using the analytical ductility relationship and a coefficient-based method (CBM), the response spectral accelerations and period shift factors of low-rise MI RC frames are computed. The results are verified through published shake table test results. In general applications, the analytical ductility relationships thus derived can be used to bypass the onerous PO analysis while accurately predicting the local ductility demands for seismic assessment of regular MI RC frames.

• Structural Engineering and Mechanics
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• v.13 no.4
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• pp.369-385
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• 2002

Ductility capacity is comprehensively studied for steel moment-resisting frames. Local, story and global ductility are being considered. An appropriate measure of global ductility is suggested. A time domain nonlinear seismic response algorithm is used to evaluate several definitions of ductility. It is observed that for one-story structures, resembling a single degree of freedom (SDOF) system, all definitions of global ductility seem to give reasonable values. However, for complex structures it may give unreasonable values. It indicates that using SDOF systems to estimate the ductility capacity may be a very crude approximation. For multi degree of freedom (MDOF) systems some definitions may not be appropriate, even though they are used in the profession. Results also indicate that the structural global ductility of 4, commonly used for moment-resisting steel frames, cannot be justified based on this study. The ductility of MDOF structural systems and the corresponding equivalent SDOF systems is studied. The global ductility values are very different for the two representations. The ductility reduction factor $F_{\mu}$ is also estimated. For a given frame, the values of the $F_{\mu}$ parameter significantly vary from one earthquake to another, even though the maximum deformation in terms of the interstory displacement is roughly the same for all earthquakes. This is because the $F_{\mu}$ values depend on the amount of dissipated energy, which in turn depends on the plastic mechanism, formed in the frames as well as on the loading, unloading and reloading process at plastic hinges. Based on the results of this study, the Newmark and Hall procedure to relate the ductility reduction factor and the ductility parameter cannot be justified. The reason for this is that SDOF systems were used to model real frames in these studies. Higher mode effects were neglected and energy dissipation was not explicitly considered. In addition, it is not possible to observe the formation of a collapse mechanism in the equivalent SDOF systems. Therefore, the ductility parameter and the force reduction factor should be estimated by using the MDOF representation.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.