• Steel and Composite Structures
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• v.52 no.6
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• pp.695-711
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• 2024

Suspension bridges are critical to urban transportation, but those in earthquake-prone areas face unique challenges. In the event of a moderate or strong earthquake, conventional linear theory-based approaches for detecting bridge damage become inadequate. This study presents an efficient method for identifying damage in suspension bridges using time history nonlinear inelastic analysis. A practical advanced analysis program is employed to model cable-supported bridges with low computational cost, generating a dataset for four hybrid models: PSO-DT, PSO-RF, PSO-XGB, and PSO-CGB. These models combine decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with particle swarm optimization (PSO) to capture nonlinear correlations between displacement response and damage. Principal component analysis reduces dataset dimensions, and PSO selects the optimal model. A numerical case study of a suspension bridge under simulated earthquake conditions identifies PSO-XGB as the best model for predicting stiffness reduction. The results demonstrate the method's robustness for nonlinear damage detection in suspension bridges under earthquake excitation.

• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.513-521
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• 2019

With rapid climate change and increasing global warming, the distribution of evergreen broad-leaved trees (EBLTs) is gradually expanding to the inland regions of Korea. The aim of the present study was to analyze the survival rate of 148 EBLT plantations measuring 180 ha and to determine the optimal plantation size that would help in coping with climate change in the warm, temperate climate zone of the Korean peninsula. For enhancing the reliability of our estimated survival model, we selected a set of 11 control variables that may have also influenced the survival rates of the EBLTs in the 148 plantations. The results of partial correlation analysis showed that the survival rate of 67.0±26.9 of the EBLTs in the initial plantation year was primarily correlated with plantation type by the crown closure of the upper story of the forest, wind exposure, and precipitation. For predicting the probability of survival by quantification theory, 148 plots were surveyed and analyzed with 11 environmental site factors. Survival rate was in the order of plantation type by the crown closure of upper story of the forest, wind exposure, total cumulative precipitation for two weeks prior to planting, and slope stiffness in the descending order of score range in the estimated survival model for the EBLTs with the fact that survival rate increased with shade rate of upper story to some extent.