• Smart Structures and Systems
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• v.26 no.1
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• pp.23-33
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• 2020

Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

• Structural Engineering and Mechanics
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• v.44 no.1
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• pp.1-13
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• 2012

In this paper the dynamic behavior of a viscoelastic Timoshenko beam subjected to a concentrated moving load are studied analytically and numerically. The viscoelastic properties of the beam obey the linear standard model in shear and incompressible in bulk. The governing equation for Timoshenko beam theory is obtained in viscoelastic form using the correspondence principle. The analytical solution is based on the Fourier series and the numerical solution is performed with finite element method. The effects of the material properties and the load velocity are investigated on the responses by numerical and analytical methods. In addition, the results are compared with the Euler beam results.

• The KSFM Journal of Fluid Machinery
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• v.6 no.1 s.18
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• pp.23-29
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• 2003

Three-dimensional flow through a tubular centrifugal fan with airfoil type blades is analyzed, and the effects of turbulence model and numerical scheme on the results are investigated. Standard $k-{\epsilon}$ model and k - w model are tested as turbulence closures. The numerical schemes for convection terms, i.e., Upwind Differencing Scheme (UDS), Mass Weighted Skewed upstream differencing scheme (MWS), Linear Profile Skewed upstream differencing scheme (LPS), and Modified Linear Profile Skewed upstream differencing scheme (MLPS) are also tested, and the performances of these schemes coupled with two turbulence models are evaluated. The static pressure distributions are compared with experimental data obtained in this work, which shows that the $k-{\epsilon}$ model gives better results than the k-w model.

• Journal of environmental and Sanitary engineering
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• v.23 no.4
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• pp.83-93
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• 2008

The non-linear least squares model(NLSM) has long been the standard technique used by hydrologists for constructing rating curves. The reasons for its adaptation are vague, and its appropriateness as a method of describing discharge measurement uncertainty has not been well investigated. It is shown in this paper that the classical method of NLSM can model only a very limited class of variance heterogeneity. Furthermore, this lack of flexibility often leads to unaccounted heteroscedasticity, resulting in dubious values for the rating curve parameters and estimated discharge. By introducing a heteroscedastic maximum likelihood model(HMLM), the variance heterogeneity is treated more generally. The maximum likelihood model stabilises the variance better than the NLSM approach, and thus is a more robust and appropriate way to fit a rating curve to a set of discharge measurements.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.419-422
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• 2005

In this note, the Takagi-Sugeno (T-S) fuzzy-model-based state estimator using standard Kalman filter theory is investigated. In that case, the dynamic system model is represented the T-S fuzzy model with the fuzzy state estimation. The steady state solutions can be found for proposed modeling method and dynamic system for maneuvering targets can be approximated as locally linear system. And then, modeled filter is corrected by the fuzzy gain which is a fuzzy system using the relation between the filter residual and its variation. This paper studies the T-S fuzzy model-based state estimator which the dynamic system can be approximated as linear system.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.479-484
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• 2000

A Navier-stokes based finite volume method has been developed to analyze an incompressible, steady state, turbulent wall-jet flow. The standard k-e model, the RNG ${\kappa}-{\varepsilon}$ model and their nonlinear counterparts are adopted as a closure relationship. Comparison with the experimental data shows that a linear ${\kappa}-{\varepsilon}$ model performs satisfatorily for two-dimensional wall-jet flows. However, as the flow becomes three dimensional, the linear model fails to predict the spanwise jet growth accurately and the nonlinear model needs to be adopted to capture three-dimensional flow characteristics.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.366-372
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• 2009

Creep life prediction has been commonly used by a time-temperature parameter (TTP) which is correlated to an applied stress and temperature, such as Larson-Miller (LM), Orr-Sherby-Dorn (OSD), Manson-Haferd (MH) and Manson-Succop (MS) parameters. A stress-temperature linear model (STLM) based on Arrhenius, Dorn and Monkman-Grant equations was newly proposed through a mathematical procedure. For this model, the logarithm time to rupture was linearly dependent on both an applied stress and temperature. The model parameters were properly determined by using a technique of maximum likelihood estimation of a statistical method, and this model was applied to the creep data of Alloy 617. From the results, it is found that the STLM results showed better agreement than the Eno’s model and the LM parameter ones. Especially, the STLM revealed a good estimation in predicting the long-term creep life of Alloy 617.

• Smart Structures and Systems
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• v.18 no.1
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• pp.1-16
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• 2016

Model Order Reduction (MOR) denotes the theory by which one tries to catch a model of order lower than that of the real model. This is conveniently pursued in view of the design of an efficient structural control scheme, just passive within this paper. When the nonlinear response of the reference structural system affects the nature of the reduced model, making it dependent on the visited subset of the input-output space, standard MOR techniques do not apply. The mathematical theory offers some specific alternatives, which however involve a degree of sophistication unjustified in the presence of a few localized nonlinearities. This paper suggests applying standard MOR to the linear parts of the structural system, the interface remaining the original unreduced nonlinear components. A case study focused on the effects of a helicopter land crash is used to exemplify the proposal.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.271-279
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• 1994

This paper descbibes a fuzzy multiobjective linear programming, which is a relatively new approach in forestry in solving forest management problems. At first, the fuzzy set theory is explained briefly and the fuzzy linear programming(FLP) and the fuzzy multiobjective linear programming(FMLP) are introduced conceptionally. With the information obtained from the study area in Thailand, a standard linear programming problem is formulated, and optimal solutions (present net worth) are calculated for four groups of timber price by this LP model, respectively. This LP model is reformulated to a fuzzy multiobjective linear programming model to accommodate uncertain timber values and with this FMLP model a compromise solution is attained. Optimal solutions of four objective functions for four timber price groups and the compromise solution are compared and discussed.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.