• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.1
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• pp.145-152
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• 2001

Thermal deformation of a machine tool structure can be evaluated from the analysis of the whole temperature field. However, it is extremely inefficient and impossible to know the whole temperature field by measuring temperatures at every point. So, the temperature estimator is required, which can predict the whole temperature field from the temperatures of just a few points. In this paper, a 1-dimensional heat transfer problem is modeled with modal analysis and state space equations. And then the state observer is designed to estimate the intensity of heat source and the whole temperature field in real time. The reliability of the estimator is verified by making comparison between solutions obtained from the proposed method and the exact solutions of examples. The proposed method is applied to the estimation of temperature distribution in a ball screw system.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.483-492
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• 2004

This paper presents an efficient algorithm for the estimation of damage location and severity in bridge structures using Probabilistic Neural Network (PNN). Generally, the Back Propagation Neural Network (BPNN)-based damage detection methods need a lot of training patterns for neural network learning process and the optimum architecture of a BPNN is selected by trial and error. In this paper, the PNN instead of the conventional BPNN is used as a pattern classifier. The modal properties of damaged structure are somewhat different from those of undamaged one. The basic idea of proposed algorithm is that the PNN classifies a test pattern which consists of the modal characteristics from damaged structure, how close it is to each training pattern which is composed of the modal characteristics from various structural damage cases. In this algorithm, two PNNs are sequentially used. The first PNN estimates the damage location using mode shape and the results of the first PNN are put into the second PNN for the damage severity estimation using natural frequency. The proposed damage assessment algorithm using the PNN is applied to a cable-stayed bridge to verify its applicability.

• Journal of the Korean Regional Science Association
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• v.32 no.4
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• pp.39-49
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• 2016

The main objective of this paper is to analyze university students' modal shift for commuting trip due to the introduction of new urban rail transit in a satellite city of metropolitan area. The paper uses SP(2011)/RP(2013) data collected from Yeungnam University in Gyeongsan City, which is a satellite city of Deagu Metropolitan City. So far few researches, especially using before-and-after individual SP/RP travel survey, have been conducted on analyzing university students' modal shift due to the introduction of new urban rail transit. For this research, some descriptive statistical analyses were conducted. Furthermore, some empirical logit models were estimated for analyzing factors affecting the modal shift. Finally, some important findings and policy implications are discussed. The significant findings from this research are summarized as follows. From the descriptive statistical analyses of SP and RP data, it is found that the rate of modal shift to rail transit is relatively high especially for bus travellers. Furthermore, from the empirical SP model estimation, it is found that time saving is the most important factor affecting the modal shift to urban rail transit. On the other hand, from the empirical RP model estimation, it is found that residential location is the most important factor affecting the modal shift to urban rail transit.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.66-70
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• 1989

Methods for identification of modal properties of linear structures are presented. The extended Kalman filtering technique is empolyed. The state equation is formulated by two different ways, namely by the time domain and frequency domain approaches. Verifications are carried out by using simulated records of ground acceleration and structural response. Then the techniques are applied to the estimation of modal parameters of a scaled model for a 3-story building which is installed on a shaking table.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.461-468
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• 2004

Modal participation factor(MPF) is essential to analyze structural response under earthquake load. MPF of real structure differs from that of analytic mathematical model due to the error induced from analytical assumption and construction. In this study, a identification method is proposed to calculate the MPF of real structure based on H∞ optimal model reduction. The MPF is obtained from the relationship between observability, controllability matrix of realized from S.I. and typical 2-degree state space model. The proposed method is verified thorough examples.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.4 no.1
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• pp.11-22
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• 2000

Nonhysteretic infiltration in nonswelling soil is modelled by the Burgers equation under appropriate physical conditions. For this nonlinear partial differential equation the modal approximation scheme is used for estimating parameters such as soil water diffusivity and hydraulic conductivity. The parameter estimation convergence is proved, and numerical experiments are performed.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.218-225
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• 2000

This paper presents intermediate results of an on-going research for identification of the modal and the stiffness parameters of a bridge based on the ambient vibration data caused by the traffic loadings. The main algorithms consist of the random decrement method incorporating band-pass filters for estimation of the free vibration signals the cross spectral density method for identification of the modal parameters and the neural networks technique for estimation of the element-level stiffness changes. An experimental study is carried out on a scaled bridge model with a composite section subjected to various moving vehicle loadings. Vertical accelerations are measured at several locations on the girder. The estimated frequencies and mode shapes are found to be well-compared with those obtained from the impact tests. The estimated stiffness changes using the neural networks are found to be very good for the case with the simulated data. However the accuracy is found to be not quite satisfactory for the case with the experimental data particularly for the small value of the stiffness changes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.244-249
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• 1998

The present paper improves the direct identification scheme based upon the equation error formulation with incomplete modal data. First, an indirect estimation technique is considered for estimating unmeasured elements of latent vectors by the combined use of a model and measured incomplete eigen vectors. It is used for estimating the other elements of eigen vectors, which are essential for identification but not available. Next an index is introduced here to indicate the quality of estimation with respect to the mode and the measured positions. A sensitivity formula for eigenvalues with respect to the unknown joint coefficient is also derived to select the modes appropriate for identification. An identification strategy is suggested to meet with practical problems with the help of the index and sensitivity formula. The index and the sensitivity are proved to be useful for selecting measurement positions and modes appropriate for identification A comprehensive simulation study is performed to test the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1314-1319
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• 2009

The design methods of mechanical systems are largely classified into deterministic methods and stochastic methods. In deterministic methods, design parameters are assumed to have fixed values. On the other hand, in stochastic methods, design parameters are assumed to be statistically distributed. When a stochastic method is employed, statistical characteristics of the populations of design variables are assumed to be known. However, very often, it is almost impossible or very expensive to obtain the statistical characteristics of the populations. Therefore a sample survey method is usually employed for stochastic methods. This paper describes the procedure of estimating the statistical characteristics of populations by employing sample data sets. An example of AFM micro cantilever beam is employed to show the effectiveness of the procedure.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.635-640
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• 2000

Thermal deformation of machine tools can be evaluated from the analysis of the whole temperature field. However, it is extremely inefficient and impossible to acquire the whole temperature field by measuring temperatures of every point. So, a temperature estimator, which can estimate the whole temperature field from the temperatures of just a few points, is required. In this paper, 1-dimensional heat transfer problem is modeled with modal analysis and state space equations. and then state observer is designed to estimate the intensity of heat source and the whole temperature field in real-time. The reliability of this estimator is verified by making a comparison between solutions by the proposed method and the exact solutions of examples. The proposed method is applied to the estimation of temperature distribution in a ball screw system.