• Earthquakes and Structures
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• v.23 no.1
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• pp.35-57
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• 2022

This article presents a computationally efficient framework for multi-objective seismic design optimization of steel moment-resisting frame (MRF) structures based on the nonlinear dynamic analysis procedure. This framework employs the uniform damage distribution philosophy to minimize the weight (initial cost) of the structure at different levels of damage. The preliminary framework was recently proposed by the authors based on the single excitation and the nonlinear static (pushover) analysis procedure, in which the effects of record-to-record variability as well as higher-order vibration modes were neglected. The present study investigates the reliability of the previous framework by extending the proposed algorithm using the nonlinear dynamic design procedure (optimization under multiple ground motions). Three benchmark structures, including 4-, 8-, and 12-story steel MRFs, representing the behavior of low-, mid-, and high-rise buildings, are utilized to evaluate the proposed framework. The total weight of the structure and the maximum inter-story drift ratio (IDRmax) resulting from the average response of the structure to a set of seven ground motion records are considered as two conflicting objectives for the optimization problem and are simultaneously minimized. The results of this study indicate that the optimization under several ground motions leads to almost similar outcomes in terms of optimization objectives to those are obtained from optimization under pushover analysis. However, investigation of optimal designs under a suite of 22 earthquake records reveals that the damage distribution in buildings designed by the nonlinear dynamic-based procedure is closer to the uniform distribution (desired target during the optimization process) compared to those designed according to the pushover procedure.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.413-433
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• 2017

The dynamic and structural responses of a 1000-m long circular submerged floating tunnel (SFT) with both ends fixed under survival irregular-wave excitations are investigated. The floater-mooring nonlinear and elastic coupled dynamics are modeled by a time-domain numerical simulation program, OrcaFlex. Two configurations of mooring lines i.e., vertical mooring (VM) and inclined mooring (IM), and four different buoyancy-weight ratios (BWRs) are selected to compare their global performances. The result of modal analysis is included to investigate the role of the respective natural frequencies and elastic modes. The effects of various submergence depths are also checked. The envelopes of the maximum/minimum horizontal and vertical responses, accelerations, mooring tensions, and shear forces/bending moments of the entire SFT along the longitudinal direction are obtained. In addition, at the mid-section, the time series and the corresponding spectra of those parameters are also presented and analyzed. The pros and cons of the two mooring shapes and high or low BWR values are systematically analyzed and discussed. It is demonstrated that the time-domain numerical simulation of the real system including nonlinear hydro-elastic dynamics coupled with nonlinear mooring dynamics is a good method to determine various design parameters.

• Structural Engineering and Mechanics
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• v.12 no.5
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• pp.527-540
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• 2001

A new sort of learning algorithm named whole learning algorithm is proposed to simulate the nonlinear and dynamic behavior of RC members for the estimation of structural integrity. A mathematical technique to solve the multi-objective optimization problem is applied for the learning of the feedforward neural network, which is formulated so as to minimize the Euclidean norm of the error vector defined as the difference between the outputs and the target values for all the learning data sets. The change of the outputs is approximated in the first-order with respect to the amount of weight modification of the network. The governing equation for weight modification to make the error vector null is constituted with the consideration of the approximated outputs for all the learning data sets. The solution is neatly determined by means of the Moore-Penrose generalized inverse after summarization of the governing equation into the linear simultaneous equations with a rectangular matrix of coefficients. The learning efficiency of the proposed algorithm from the viewpoint of computational cost is verified in three types of problems to learn the truth table for exclusive or, the stress-strain relationship described by the Ramberg-Osgood model and the nonlinear and dynamic behavior of RC members observed under an earthquake.

• Earthquakes and Structures
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• v.26 no.4
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• pp.251-259
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• 2024

In this paper, the thermal post-buckling behavior of graphene platelets reinforced metal foams (GPLRMFs) plate with initial geometric imperfections on nonlinear elastic foundations are studied. First, the governing equation is derived based on the first-order shear deformation theory (FSDT) of plate. To obtain a single equation that only contains deflection, the Galerkin principle is employed to solve the governing equation. Subsequently, a comparative analysis was conducted with existing literature, thereby verifying the correctness and reliability of this paper. Finally, considering three GPLs distribution types (GPL-A, GPL-B, and GPL-C) of plates, the effects of initial geometric imperfections, foam distribution types, foam coefficients, GPLs weight fraction, temperature changes, and elastic foundation stiffness on the thermal post-buckling characteristics of the plates were investigated. The results show that the GPL-A distribution pattern exhibits the best buckling resistance. And with the foam coefficient (GPLs weight fraction, elastic foundation stiffness) increases, the deflection change of the plate under thermal load becomes smaller. On the contrary, when the initial geometric imperfection (temperature change) increases, the thermal buckling deflection increases. According to the current research situation, the results of this article can play an important role in the thermal stability analysis of GPLRMFs plates.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.3
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• pp.74-79
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• 2010

Automotive industries are interested in material development with low weight and recycling. Grommet is made from EPDM at rubber and used as an automotive component. The nonlinear material properties of rubber are important to predict the behaviors of rubber product. This study concerns material property test to achieve stress-strain curve. Curve fitting is carried out to obtain the nonlinear material constant. The nonlinear material constants of rubber are used for the nonlinear finite element analysis. The results of finite element analysis is executed to predict the behavior property of grommet.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.189-195
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• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.8-14
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• 2016

The optimal estimation of a bearing only target tracking problem be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Recently, a nonlinear filtering algorithm using a direct quadrature method of moments in which the associated Fokker-Planck equation can be propagated efficiently and accurately was proposed. Although this approach has demonstrated its promising in the field of nonlinear filtering in several examples, the "degeneracy" phenomenon, similar to that which exists in a typical particle filter, occasionally appears because only the weights are updated in the modified Bayesian rule in this algorithm. Therefore, in this paper to enhance the performance, a more stable measurement update process based upon the update equation in the Extended Kalman filters and a more accurate initialization and re-sampling strategy for weight and abscissas are proposed. Simulations are used to show the effectiveness of the proposed filter and the obtained results are promising.

• Structural Engineering and Mechanics
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• v.43 no.5
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• pp.583-605
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• 2012

This paper presents a spatial catenary cable element for the nonlinear analysis of cable-supported structures. An incremental-iterative solution based on the Newton-Raphson method is adopted for solving the equilibrium equation. As a result, the element stiffness matrix and nodal forces are determined, wherein the effect of self-weight and pretension are taken into account. In the case of the initial cable tension is given, an algorithm for form-finding of cable-supported structures is proposed to determine precisely the unstressed length of the cables. Several classical numerical examples are solved and compared with the other available numerical methods or experiment tests showing the accuracy and efficiency of the present elements.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.32-39
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• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.

• Structural Engineering and Mechanics
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• v.88 no.5
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• pp.405-417
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• 2023

This paper reveals theoretical research to the nonlinear dynamic response and initial geometric imperfections sensitivity of the spinning graphene platelets reinforced metal foams (GPLRMF) cylindrical shell under different boundary conditions in thermal environment. For the theoretical research, with the framework of von-Karman geometric nonlinearity, the GPLRMF cylindrical shell model which involves Coriolis acceleration and centrifugal acceleration caused by spinning motion is assumed to undergo large deformations. The coupled governing equations of motion are deduced using Euler-Lagrange principle and then solved by a combination of Galerkin's technique and modified Lindstedt Poincare (MLP) model. Furthermore, the impacts of a set of parameters including spinning velocity, initial geometric imperfections, temperature variation, weight fraction of GPLs, GPLs distribution pattern, porosity distribution pattern, porosity coefficient and external excitation amplitude on the nonlinear harmonic resonances of the spinning GPLRMF cylindrical shells are presented.