• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.551-560
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• 2010

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

• Journal of KSNVE
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• v.9 no.6
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• pp.1240-1246
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• 1999

A prior error estimator which is solving structural dynamic problems and which is based on the generalized-method, is developed. Since the proposed error estimator is computed with only previous information, the time step size can be adaptively selected without the feedback mechanism. This paper shows that the automatic time stepping algorithm using the error estimator performs an efficient time integration. To verify its efficiency, several examples are numerically investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.95-102
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• 1994

This paper presents a Cable Stayed Bridge Construction Management System, which consists of Structural System Identification Method (SSIM), Error Sensitivity Analysis and Optimum Error Adjustment & Prediction System. The 1st System Identification Method builds an error influence matrix using the linear superposition of each error modes. The 2nd SSIM also considers the second error mode term, which shows good error factor estimation. The optimal cable adjustment can be accomplished within the allowable range of both cable tension and camber. The Post processor, constituted with Motif and GL library on SGI platform, is useful for monitoring construction stage management by displaying construction data, adjustment and prediction results at each construction step.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.34-42
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• 2001

In this paper, we study on a modified mesh generation method based on the pollution error estimate. This method is designed for the control of the pollution error in any patch of elements of interest. It is a well-known fact that the pollution error estimates are much more than the local one. Reliable a posteriori error estimation is possible by controlling the pollution error in the patch through proper design of the mesh outside the patch. This design is possible by equally distributing the pollution error indicators over the mesh outside the patch. The conventional feedback pollution-adaptive mesh generation algorithm needs many iterations. Therefore, the solution time is significant. But we use the remeshing scheme in the proposed method. We will also show that the pollution error reduces less than the local error.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.60-65
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• 2021

Human error is often in part in the cause of accidents and the result of various factors in an organization. Accidents should be investigated to elucidate all causes. Therefore, to reduce accidents, it is necessary to identify which factors affect human error within the organization. In this study, five groups of influencing factors on human error were selected using previousresearch, and operational definitions were made based on them. In addition, a questionnaire for measuring latent variables by operational definition was developed as an observation variable, and responses were received from employees of chemical companies in Ulsan. Based on SEM (structural equation modeling) analysis, 1) confirmatory factor analysis of variables in the human error model, 2) reliability and validity of latent variables, 3) correlations among latent variables, 4) influencing coefficients among influence factors, and 5) the verification results of the paths that these influencing factors have on human error are introduced in this study.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.44-54
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• 2001

This paper describes the antenna alignment method of the tracking antenna system for LEO satellite. The purpose of the antenna alignment is to reduce the angular error due to the structural alignment and the monopulse null point alignment error. The angular error of 3 axis tracking system is the key performance parameter that should be minimized to accurately track satellite movement. The angular error is analyzed via a simulation and boresight measurement. The simulation is done with formulas to be derived from vector concept for 3-axis movement. The formulas of the structural alignment are verified by comparing the formula result with the field measurement. Also, the angular error due to monopulse null shift is obtained via boresight measurement. Based on the analyzed and measured results, the antenna alignment was performed and was verified via tracking test of operating LEO satellite.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.492-499
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• 2004

The purpose of this paper is to present a design procedure of coulomb friction dampers for controlling elastic and inelastic responses of building structures. The equivalent damping and frequency increased by the friction damper are estimated using ATC-40 and ATC-55 procedures which provide equivalent linear system for bilinear one, and then a design formula to achieve target performance response level by friction damper is presented. It is identified that there exists error between the responses obtained by this formula and by performing nonlinear analysis and the features of the error vary according to the hardening ratio, yield strength ratio, and structural period. Equations for compensating this er개r are reposed based on the least square method, and the results from numerical analyses indicate that the error is significantly reduced, and the proposed formula can be used without much error for designing coulomb friction damper for retrofitting a structure showing elastic or inelastic behavior.