• Structural Engineering and Mechanics
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• v.26 no.3
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• pp.251-262
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• 2007

This paper examines the application of artificial neural networks (ANN) to the response prediction of geometrically nonlinear truss structures. Two types of analysis (deterministic and probabilistic analyses) are considered. A three-layer feed-forward backpropagation network with three input nodes, five hidden layer nodes and two output nodes is firstly developed for the deterministic response analysis. Then a back propagation training algorithm with Bayesian regularization is used to train the network. The trained network is then successfully combined with a direct Monte Carlo Simulation (MCS) to perform a probabilistic response analysis of geometrically nonlinear truss structures. Finally, the proposed ANN is applied to predict the response of a geometrically nonlinear truss structure. It is found that the proposed ANN is very efficient and reasonable in predicting the response of geometrically nonlinear truss structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.241-248
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• 2015

There are a lot of equipment related to safety and electric power production in nuclear power plants. The structure and equipment in NPPs were generally designed considering a high safety factor to remain in the elastic zone under earthquake load. However it is needed to revaluate the seismic capacity of the structure and equipment as the magnitude of earthquake was recently increased. In this study the floor response due to the nonlinear behaviors of structure was analyzed and the inelastic structural response factor was calculated by the nonlinear time history analysis. The inelastic structural response factor was calculated by the EPRI method and the nonlinear analysis method to realistically evaluate the seismic fragility for the equipment. According to the analysis result, it was represented that the inelastic structural response factor was affected by the natural frequency of equipment, the location of equipment and the dynamic property of structure.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.119-126
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• 2006

Capacity spectrum method(CSM) of ATC-40(1996) and displacement coefficient method(DCM)of FEMA-273(1997) are applied to evaluate the seismic performance of bridges. In this study, equivalent response is obtained from nonlinear static analysis for the 3spans continues bridge and nonlinear maximum displacement response is calculated using CSM and DCM. Nonlinear maximum displacement response of DCM is larger than this of CSM. It is method that DCM can evaluate target displacement and ductility of structural to be easy and simple, but tend to overestimate the maximum displacement response. Therefore, this method is mainly used at preparation design level to evaluate the structural response. It is not desirable to evaluate the seismic performance using DCM.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.559-565
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• 2003

A spectral element model-based structural damage identification method (SDIM) was derived in the previous study by using the damage-induced changes in frequency response functions. However the previous SDIM often provides poor damage identification results because the nonlinear effect of damage magnitude was not taken into account. Thus, this paper improves the previous SDIM by taking into account the nonlinear effect of damage magnitude. Accordingly an iterative solution method is used in this study to solve the nonlinear matrix equation for local damages distribution. The present SDIM is evaluated through the numerically simulated damage identification tests.

• Smart Structures and Systems
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• v.15 no.3
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• pp.847-862
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• 2015

Typical base isolated buildings are designed so that the superstructure remains elastic in design-level earthquakes, though the isolation layer is often quite nonlinear using, e.g., hysteretic elements such as lead-rubber bearings and friction pendulum bearings. Similarly, other well-performing structural control systems keep the structure within the linear range except during the most extreme of excitations. Design optimization of these isolators or other structural control systems requires computationally-expensive response simulations of the (mostly or fully) linear structural system with the nonlinear structural control devices. Standard nonlinear structural analysis algorithms ignore the localized nature of these nonlinearities when computing responses. This paper proposes an approach for the computationally-efficient optimal design of passive isolators by extending a methodology previously developed by the authors for accelerating the response calculation of mostly linear systems with local features (linear or nonlinear, deterministic or random). The methodology is explained and applied to a numerical example of a base isolated building with a hysteretic isolation layer. The computational efficiency of the proposed approach is shown to be significant for this simple problem, and is expected to be even more dramatic for more complex systems.

• Structural Engineering and Mechanics
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• v.91 no.4
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• pp.349-355
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• 2024

This paper investigates the influence of the torsional component of earthquake on the nonlinear structural behavior of reinforced concrete (RC) buildings. It also estimates the equivalent additional eccentricity that results from this component. For this purpose, we generate torsional accelerograms from translational ones and conduct nonlinear seismic analysis on both regular and irregular structures. The results show that the torsional component has a significant impact on the structural response, especially for irregular structures. The equivalent additional eccentricity of the cases studied was higher than 5% which is the value of accidental eccentricity suggested by many seismic codes.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.523-528
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• 2001

The Capacity Spectrum Method (CSM) was first introduced in the 1970's as rapid evaluation procedure. The procedure compares the capacity of the structure (in the form of a pushover curve) with the demands on the structure (in the form of a response spectrum). The graphical intersection of the two curves approximates the response of the structure. In order to account for nonlinear inelastic behavior of the structural system, effective ductility ratios(μ) are applied to the elastic-linear response spectrum to imitate an inelastic response spectrum. CSM in ATC-40 has deficiencies such as performance point does not converge and the peak deformation of inelastic systems is to be inaccurate when compared against results of nonlinear response history analysis. The purpose of this paper is to investigate the variation of performance points of Capacity Spectrum Method (CSM) are investigated with respect to the different sets of earthquake ground motions. The earthquake sets were used in this study selected by Miranda(1993), Riddell(1991), Seed et al. (1976).

• Steel and Composite Structures
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• v.6 no.3
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• pp.183-202
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• 2006

The behavior of steel-concrete composite beams is strongly influenced by the type of shear connection between the steel beam and the concrete slab. For accurate analytical predictions, the structural model must account for the interlayer slip between these two components. This paper focuses on a procedure for response sensitivity analysis using state-of-the-art finite elements for composite beams with deformable shear connection. Monotonic and cyclic loading cases are considered. Realistic cyclic uniaxial constitutive laws are adopted for the steel and concrete materials as well as for the shear connection. The finite element response sensitivity analysis is performed according to the Direct Differentiation Method (DDM); its analytical derivation and computer implementation are validated through Forward Finite Difference (FFD) analysis. Sensitivity analysis results are used to gain insight into the effect and relative importance of the various material parameters in regards to the nonlinear monotonic and cyclic response of continuous composite beams, which are commonly used in bridge construction.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.361-368
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• 2000

This paper demonstrates how nonlinear soil behavior in a soil-structure interaction system can be realistically incorporated by using a hybrid method in a nonlinear time-domain analysis. The hybrid method employs a general-purpose nonlinear finite element program coupled with a linear SSI program for the unbounded layered soil medium In order to verify the validity and applicability of the hybrid method, nonlinear earthquake response analyses are carried out for the Hualien free-field problem, in which the ground and underground accelerations were measured during several earthquake events, and for a 2-D subway station. It is found that the nonlinear earthquake responses predicted for the Hualien free-field using the hybrid method compare very well with the observed responses whereas the subway station example gives reasonable results.