• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.220-227
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• 2016

Marine seismic data have not only primary signals from subsurface but also ghost signals reflected from the sea surface. The ghost decreases temporal resolution of seismic data because it attenuates specific frequency components. For eliminating the ghost signals effectively, the exact ghost delaytimes and reflection coefficients are required. Because of undulation of the sea surface and vertical movements of airguns and streamers, the ghost delaytime varies spatially and randomly while acquiring seismic data. The reflection coefficient is a function of frequency, incidence angle of plane-wave and the sea state. In order to estimate the proper ghost delaytimes considering these characteristics, we compared the ghost delaytimes estimated with L-1 norm, L-2 norm and kurtosis of the deghosted trace and its autocorrelation on synthetic data. L-1 norm of autocorrelation showed a minimal error and the reflection coefficient was calculated using Kirchhoff approximation equation which can handle the effect of wave height. We applied the estimated ghost delaytimes and the calculated reflection coefficients to remove the source and receiver ghost effects. By removing ghost signals, we reconstructed the frequency components attenuated near the notch frequency and produced the migrated stack section with enhanced temporal resolution.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.1
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• pp.30-45
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• 2013

The present work focuses on the unsteady aerodynamics and aeroelastic properties of a small-medium sized wind-turbine blade operating under ideal conditions. A tapered/twisted blade representative of commercial blades used in an experiment setup at the National Renewable Energy Laboratory is considered. The aerodynamic loads are computed using Computational Fluid Dynamics (CFD) techniques. For this purpose, FLUENT$^{(R)}$, a commercial finite-volume code that solves the Navier-Stokes and the Reynolds-Averaged Navier-Stokes (RANS) equations, is used. Turbulence effects in the 2D simulations are modeled using the Wilcox k-w model for validation of the CFD approach. For the 3D aerodynamic simulations, in a first approximation, and considering that the intent is to present a methodology and workflow philosophy more than highly accurate turbulent simulations, the unsteady laminar Navier-Stokes equations were used to determine the unsteady loads acting on the blades. Five different blade pitch angles were considered and their aerodynamic performance compared. The structural dynamics of the flexible wind-turbine blade undergoing significant elastic displacements has been described by a nonlinear flap-lag-torsion slender-beam differential model. The aerodynamic quasi-steady forcing terms needed for the aeroelastic governing equations have been predicted through a strip-theory based on a simple 2D model, and the pertinent aerodynamic coefficients and the distribution over the blade span of the induced velocity derived using CFD. The resulting unsteady hub loads are achieved by a first space integration of the aeroelastic equations by applying the Galerkin's approach and by a time integration using a harmonic balance scheme. Comparison among two- and three- dimensional computations for the unsteady aerodynamic load, the flap, lag and torsional deflections, forces and moments are presented in the paper. Results, discussions and pertinent conclusions are outlined.

• Journal of Korean Society of Forest Science
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• v.83 no.1
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• pp.63-74
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• 1994

One of the essential factors to estimate the stem and stand growth is to correctly portray a stem form (profile). It is also required to numerically approximate a stem form in order to dynamically grasp and represent a stand growth. A whole stem form seems to be a conical form but a stem outline at various positions tapers off differently. Accordingly it is difficult to model a whole stand form with single taper equation. A stem taper equation with different coefficients on each subinterval can be useful tools to accurately portray a stem form. This article presents the derivation method of individual stem taper curve using spline function. It is also in this paper aimed to study how a stand taper curve car, be derived from the population of single stem taper curve in a stand. These taper equations numerically formulated enable to dynamically represent and prognosticate the development process of a stand and prepare the foundation of variety on growth model study and rational forest planning model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.34 no.3
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• pp.17-24
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• 2002

An unsteady-state moisture diffusion through cellulosic fibers in paper was characterized from the moisture sorption experiment and the mathematical modeling. The sorption experiment was conducted by exposing thin dry paper specimens to a constant temperature-humidity environment. Oven dried blotting papers and filter papers were used as test samples and the gains of their weights were constantly monitored and recorded as a function of sorption time. For a mathematical approach, the moisture transport was assumed to be an one-dimensional diffusion in thickness direction through the geometrically symmetric structure of paper. The model was asymptotically simplified with a short-term approximation. It gave us a new insight into the moisture uptake phenomena as a function of square root of sorption time. The fiber-phase moisture diffusivities(FPMD) of paper samples were then determined by correlating the experimental data with the unsteady-state diffusion model obtained. Their values were found to be on the order of magnitude of $10^{-6}-10^{-7}cm^2$/min., which were equivalent to the hypothetical effective diffusion coefficients at the limit of zero porosity. The moisture sorption curve predicted from the model fairly agreed with that obtained from the experiment at some limited initial stages of the moisture uptake process. The FPMD value of paper significantly varied depending upon the current moisture content of paper. The mean FPMD was about 0.7-0.8 times as large as the short-term approximated FPMD.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.1
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• pp.106-115
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• 1988

A numerical procedure for determining the airfoil shape that maximizes the lift is presented. The structure of the flow field is calculated by iteratively coupling potential flow and boundary analysis using the viscous-inviscid interaction method. The potential flow field is obtained by the vortex panel method and boundary layer flow is analyzed by means of integral approximation method which is capable of handling the laminar, transition and turbulent flow regimes. As the result of this study, it is found that the calculated flow regimes have good agreement with the existing experimented data. Davidon-Fletcher-Powell method and Augmented Lagrange Multiplier method are used for the optimal techniques. NACA 23012, NACA 65-3-21, NACA 64-2-415, NACA 64-2-A215 airfoils are used for determining the optimal airfoil shapes as a basic and compensate airfoils. Optimal design showed that the lift coefficients are increased by 17.4% at M$_{0}$=0.2 and 29% at M$_{0}$=0.3, compared with those of basic airfoil.oil.

• Steel and Composite Structures
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• v.27 no.2
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• pp.201-216
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• 2018

In this paper, three-dimensional (3D) elasticity theory in conjunction with nonlocal strain gradient theory (NSGT) is developed for mechanical analysis of anisotropic nanoparticles. The present model incorporates two scale coefficients to examine the mechanical characteristics much accurately. All the elastic constants are considered and assumed to be the functions of (r, ${\theta}$, ${\varphi}$), so all kind of anisotropic structures can be modeled. Moreover, all types of functionally graded spherical structures can be investigated. To justify our model, our results for the radial vibration of spherical nanoparticles are compared with experimental results available in the literature and great agreement is achieved. Next, several examples of the radial vibration and wave propagation in spherical nanoparticles including nonlocal strain gradient parameters are presented for more than 10 different anisotropic nanoparticles. From the best knowledge of authors, it is the first time that 3D elasticity theory and NSGT are used together with no approximation to derive the governing equations in the spherical coordinate. Moreover, up to now, the NSGT has not been used for spherical anisotropic nanoparticles. It is also the first time that all the 36 elastic constants as functions of (r, ${\theta}$, ${\varphi}$) are considered for anisotropic and functionally graded nanostructures including size effects. According to the lack of any common approximations in the displacement field or in elastic constant, present theory can be assumed as a benchmark for future works.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.4
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• pp.224-231
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• 2013

The concept of the natural frequency is useful for understanding the characters of oscillating systems. However, when a circular cylinder floating horizontally on the water surface is heaving, due to the hydrodynamic forces, the system is not governed by the equation like that of the harmonic one. In this paper, in order to shed some lights on the more correct use of the concept of the natural frequency, a problem of the heaving circular cylinder is analyzed in the time domain. The equation of motion, an integro-differential equation, was derived following the fashion of Cummins (1962), and its coefficients including the retardation function were obtained using the numerical solution of Lee (2012). The equation was solved numerically, and the experiment was also carried out in the CNU flume. Using our numerical and experimental results, the natural frequency was defined as its average value given by the motion data excluding those of the initial stage. Our results were then compared with those of the existing investigations such as Maskell and Ursell (1970), Ito (1977) and Yeung (1982) as well as the newly obtained results of Lee (2012). Comparison showed that the natural frequency obtained here agrees well with that of Lee (2012), which was found through the frequency domain analysis. It was also shown that the approximation of heaving motion by a damped harmonic oscillation, which was regarded as suitable by most previous investigators, is not physically suitable for the reason that can be clearly shown through comparing the shape of MCFRs(Modulus of Complex Frequency Response). Furthermore, we found that although the previous approximations yield the damping ratio significantly different from our result the magnitude of natural frequency is not much different from our result.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.