• Smart Structures and Systems
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• 제15권3호
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Structural Engineering and Mechanics
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• 제32권6호
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• pp.725-740
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• 2009

A new simple relation for the estimation of modal correlation coefficients is presented. It is obtained from the decomposition of covariances of modal responses into background and resonant contributions, as it is commonly done for the variances. Thanks to appropriate assumptions, the modal correlation coefficients are estimated as weighted sums of two limit values, corresponding to the background and resonant responses respectively. The weighting coefficients are expressed as functions of the background-to-resonant ratios, which makes the proposed formulation convenient and easily accessible. The simplicity of the mathematical formulation facilitates the physical interpretation. It is for example proved that modal correlation coefficients can be non negligable even in case of well separated natural frequencies, which is sometimes unclear in the litterature. The new relation is mainly efficient in case of large finite element models. It is applied and validated on a finite element buffeting analysis of the Viaduct of Millau, the highest bridge deck ever built so far.

• Proceedings of the KSR Conference
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1123-1125
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• 2006

As Kyoto protocol has been effective in 2005, the reduction of $CO_2$ emission is a global urgent problem. In Korea, the $CO_2$ emission of transportation increases continuously, which can be solved partially by the use of railroad. Therefore, it is necessary to calculate exactly the $CO_2$ emission of railroad through life cycle approach. In this study, the $CO_2$ emission of electric motor unit (EMU) was evaluated with its carboy material using life cycle inventory analysis (LCIA). Among the life cycles of EMU, $CO_2$ emission was the highest in the running phase. As the total weight of EMU was lowered, $CO_2$ emission was reduced. In conclusion, the light-weighting of EMU can reduce $CO_2$ emission efficiently.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제36권11호
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• pp.813-818
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• 1987

In this paper, high resolution spectral estimation by AR modelling and principal comonent analysis is proposed. The given data can be expanded by the eigenvectors of the estimated covariance matrix. The eigenspectrum is obtained for each eigenvector using the Autoressive(AR) spectral estimation technique. The final spectrum estimate is obtained by weighting each eigenspectrum with the corresponding eigenvalue and summing them. Although the proposed method increases in computational complexity, it shows good frequency resolution especially for short data records and narrow-band data whose signal-to-noise ratio is low.

• Journal of Korean Society for Quality Management
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• 제25권2호
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• pp.169-188
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• 1997

The purpose of this study is concerned with suggesting a new a, pp.oach to evaluating the overall product quality in the sense of the relative efficiency of products, whose quality is measured with 8-dimensional attributes, suggested by Garvin. The attributes included 8 quality measures, that is, performance, features, reliability, conformance, durability, serviceabilit, aesthetics, and perceived quality. This study, also, introduced DEA(Data Envelopment Analysis) as an evaluation tool to tackle the problem of how to measure one product against another when each product can be measured along a number of dimensions, and given that there exists no a priori satisfactory weighting scheme to combine these dimensions into an overall rating for each products. In order to a, pp.y the DEA to evaluating the products, we must define two concepts, such as DMU(Decision Making Units) and input-output relationship. Finally, the suggested method in this study was validated through a case study of the electric jar, and this DEA a, pp.oach can be used in evaluating the other products with multi-attrribute quality.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.922-926
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• 2001

This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to frequency changing. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method according to frequency changing. Experiments and analysis were executed to estimate the ability to recognize objects according to frequency changing. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.217-222
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• 2005

Active vibration control of smart hull structure using Macro Fiber Composite (MFC) actuator is performed. Finite element modeling is used to obtain governing equations of motion and boundary effects of end-capped smart hull structure. Equivalent interdigitated electrode model is developed to obtain piezoelectric couplings of MFC actuator. Modal analysis is conducted to investigate the dynamic characteristics of the hull structure, and compared to the results of experimental investigation. MFC actuators are attached where the maximum control performance can be obtained. Active controller based on Linear Quadratic Gaussian (LQG) theory is designed to suppress vibration of smart hull structure. It is observed that closed loop damping can be improved with suitable weighting factors in the developed LQG controller and structural vibration is controlled effectively.

• Advances in aircraft and spacecraft science
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• 제3권1호
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• pp.45-59
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• 2016

In this paper, the condensation method which is based on the Rayleigh-Ritz method, is described for the free vibration analysis of axially loaded slightly curved beams subject to partial axial restraints. If the longitudinal inertia is neglected, some of the Rayleigh-Ritz minimization equations are independent of the frequency. These equations can be used to formulate a relationship between the weighting coefficients associated with the lateral and longitudinal displacements, which leads to "connection coefficient matrix". Once this matrix is formed, it is then substituted into the remaining Rayleigh-Ritz equations to obtain an eigenvalue equation with a reduced matrix size. This method has been applied to simply supported and partially clamped beams with three different shapes of imperfection. The results indicate that for small imperfections resembling the fundamental vibration mode, the sum of the square of the fundamental natural and a non-dimensional axial load ratio normalized with respect to the fundamental critical load is approximately proportional to the square of the central displacement.

• Journal of Preventive Medicine and Public Health
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• 제55권2호
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• pp.116-124
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• 2022

Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

• Structural Monitoring and Maintenance
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• 제9권1호
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• pp.59-80
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• 2022

In the present study, the objective is to detect the structural damages using the responses obtained from the sensors at the optimal location under uncertainty conditions. Reducing the error rate in damage detection process due to responses' noise is an important goal in this study. In the proposed algorithm for optimal sensor placement, the noise of responses recorded from the sensors is initially reduced using the principal component analysis. Afterward, the optimal sensor placement is obtained by the damage detection equation based sensitivity analysis. The sensors are placed on degrees of freedom corresponding to the minimum error rate in structural damage detection through this procedure. The efficiency of the proposed method is studied on a truss bridge, a space dome, a double-layer grid as well as a three-story experimental frame structure and the results are compared. Moreover, the performance of the suggested method is compared with three other algorithms of Average Driving Point Residue (ADPR), Effective Independence (EI) method, and a mass weighting version of EI. In the examples, young's modulus, density, and cross-sectional areas of the elements are considered as uncertainty parameters. Ultimately, the results have demonstrated that the presented algorithm under uncertainty conditions represents a high accuracy to obtain the optimal sensor placement in the structures.