• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.4
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• pp.353-363
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• 1994

In order to give a useful guide for engineering applications on numerical models based on nonlinear stream function wave theory. collocation method and least squares method are directly compared input parameters of the revised Dean's Table (Chaplin, 1980). Two models ive both accurate and almost same results for all the cases except very long or nearly breaking waves. Overall comparison seems to favor the least squares method for general use.

• Smart Structures and Systems
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• v.22 no.3
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• pp.315-326
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• 2018

This paper presents a novel time-domain method for the identification of plastic rotations and stiffness parameters of single-bay frames with nonlinear plastic hinges. Each plastic hinge is modelled as a pseudo-semi-rigid connection with nonlinear hysteretic moment-curvature characteristics at an element end. Through the comparison of the identified end rotations of members that are connected together, the plastic rotation that furnishes information of the locations and plasticity degrees of plastic hinges can be identified. The force consideration of the frame members may be used to relate the stiffness parameters to the elastic rotations and the excitation. The damped-least-squares method and damped-and-weighted-least-squares method are adopted to estimate the stiffness parameters of frames. A noise-removal strategy employing a de-noising technique based on wavelet packets with a smoothing process is used to filter out the noise for the parameter estimation. The numerical examples show that the proposed method can identify the plastic rotations and the stiffness parameters using measurements with reasonable level of noise. The unknown excitation can also be estimated with acceptable accuracy. The advantages and disadvantages of both parameter estimation methods are discussed.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.413-413
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• 2019

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.563-573
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• 2018

Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.438-447
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• 2008

This study is focused on reliability based design optimization (RBDO) using moving least squares. A response surface is used to derive a limit-state equation for reliability based design optimization. Response surface method (RSM) with least square method (LSM) or Kriging will be used as a response surface. RSM is fast to make the response surface. On the other hand, RSM has disadvantage to make the response surface of nonlinear equation. Kriging can make the response surface in nonlinear equation precisely but needs considerable amount of computations. The moving least square method (MLSM) is made of both methods (RSM with LSM+Kriging). Numerical results by MLSM are compared with those by LMS in Rosenbrock function and six-hump carmel back function. The RBDO of engine duct of smart UAV is pursued in this paper. It is proved that RBDO is useful tool for aerospace structural optimal design problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.957-963
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• 2007

In this paper, Nonlinear Autoregressive (NAR) method based on Least Square-Support Vector Regression (LS-SVR) is introduced and tested for nonlinear sustained vowel modeling. In the database of total 43 sustained vowel of Benign Vocal Fold Lesions having aperiodic waveform, this nonlinear synthesizer near perfectly reproduced chaotic sustained vowels, and also conserved the naturalness of sound such as jitter, compared to Linear Predictive Coding does not keep these naturalness. However, the results of some phonation are quite different from the original sounds. These results are assumed that single-band model can not afford to control and decompose the high frequency components. Therefore multi-band model with wavelet filterbank is adopted for substituting single band model. As a results, multi-band model results in improved stability. Finally, nonlinear sustained vowel modeling using NAR based on LS-SVR can successfully reconstruct synthesized sounds nearly similar to original voiced sounds.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.1147-1157
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• 1996

Nonlinear ill-posed problems arise in many application including parameter estimation and inverse scattering. We introduce a least squares regularization method to solve nonlinear ill-posed problems with constraints robustly and efficiently. The regularization method uses Trust-Region approach to handle the constraints on variables. The Generalized Cross Validation is used to choose the regularization parameter in computational tests. Numerical results are given to exhibit faster convergence of the method over other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.102.1-102
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• 2001

In this work, extensions to partial least squares (PLS) for wastewater treatment (WWT) process monitoring are discussed. Conventional data gathered by monitoring WWT systems are usually time varying, high dimensional, correlated and nonlinear, PLS has been shown to be an efficient approach in modeling and monitoring high dimensional and correlated data. To represent dynamic and nonlinear features of the data several kinds of dynamic nonlinear PLS (DNLPLS) models have been proposed. However, the complexity and ambiguity of the models make them unsuitable for WWT monitoring, Recently, dynamic fuzzy PLS (DFPLS) was proposed ...

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.237-239
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• 2018

This paper proposes an on-line estimation algorithm of internal resistance of Li-ion battery based on the recursive least squares method to prevent the overvoltage and undervoltage casing degradation of life cycle of battery. An equivalent circuit model with single time constant is adopted, and under assumptions that the terminal voltage, current and SOC are measured accurately, the discrete time based nonlinear equation of the model can be converted to the linear equation which can be applied to recursive least squares method. Since the coefficients of the discrete time linear equation can be expressed by the parameters of the equivalent circuit model, it is shown that an internal resistance (Ri) can be estimated in real time using the least square method.

• Wind and Structures
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• v.17 no.4
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• pp.451-464
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• 2013

This study develops an extended inverse input estimation algorithm with intelligent adaptive fuzzy weighting to effectively estimate the unknown input wind load of nonlinear structural systems. This algorithm combines the extended Kalman filter and recursive least squares estimator with intelligent adaptive fuzzy weighting. This study investigated the unknown input wind load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying larger input wind load. Numerical simulation cases involving different input wind load types are studied in this paper. The simulation results verify the nonlinear characteristics of the structural system. This algorithm is effective in estimating unknown input wind loads.