• Title/Summary/Keyword: global fitting function

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Global Fitting Functions for Kinetics of Fe-Selective Chlorination in Ilmenite and Successive Chlorination of Beneficiated TiO2 (일메나이트 중 철의 선택적 염화와 선광된 TiO2의 추가 염화반응에 대한 글로벌 피팅함수)

  • Chung, Dong-Kyu;Won, Yong Sun;Kim, Yong-Ha;Jung, Eun-Jin;Song, Duk-Yong
    • Korean Journal of Materials Research
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    • v.29 no.7
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    • pp.412-424
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    • 2019
  • Global fitting functions for Fe-selective chlorination in ilmenite($FeTiO_2$) and successive chlorination of beneficiated $TiO_2$ are proposed and validated based on a comparison with experimental data collected from the literature. The Fe-selective chlorination reaction is expressed by the unreacted shrinking core model, which covers the diffusion-controlling step of chlorinated Fe gas that escapes through porous materials of beneficiated $TiO_2$ formed by Fe-selective chlorination, and the chemical reaction-controlling step of the surface reaction of unreacted solid ilmenite. The fitting function is applied for both chemical controlling steps of the unreacted shrinking core model. The validation shows that our fitting function is quite effective to fit with experimental data by minimum and maximum values of determination coefficients of $R^2$ as low as 0.9698 and 0.9988, respectively, for operating parameters such as temperature, $Cl_2$ pressure, carbon ratio and particle size that change comprehensively. The global fitting functions proposed in this study are expressed simply as exponential functions of chlorination rate(X) vs. time(t), and each of them are validated by a single equation for various reaction conditions. There is therefore a certain practical merit for the optimal process design and performance analysis for field engineers of chlorination reactions of ilmenite and $TiO_2$.

New Global Curve-Fitting Method Using Frequency Response Function (주파수 전달함수를 이용한 신 포괄 곡선맞춤법)

  • Min, Cheon-Hong;Park, Han-Il;Bae, Soo-Ryong;Jeon, Jae-Jin
    • Journal of Ocean Engineering and Technology
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    • v.23 no.6
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    • pp.82-86
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    • 2009
  • Several damping materials have been employed to reduce the vibration of structures. While it is important to estimate the damping matrix when analyzing damped composite structures using the finite element method (FEM), at present, there is no FEM program that can correctly estimate the damping matrix. In this paper, a new global curve-fitting method is proposed for identifying the system parameters of non-proportional damping structures using a frequency response function. An experimental test for a cantilever beam attached damping material was carried out to verify the performance of the method proposed in this study.

Vibration transfer characteristic of foaming sponge chair seat (발포스펀지 의자시트의 진동전달 특성)

  • Kim, S.H.;Kang, H.J.;Kim, T.K.;Moon, D.H.
    • Journal of Power System Engineering
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    • v.16 no.1
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    • pp.24-29
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    • 2012
  • Recently, in the movie theater, the special chair is installed to maximize the viewing effect of movies. It is structured to convey a vibrational stimulus to a specially-designated parts of human body by attaching a vibration transducer to a existing theater chair. This paper describes the analysis of the vibration transfer characteristic of a foaming sponge seat for the design of the special chair. We could not apply the structural analysis S/W because it is difficult to obtain the mechanical properties and damping coefficients of the various type sponges. And then we computed the transfer functions by the global curve fitting program based on experimental modal analysis. The experimental response results comparatively coincide with those by the global curve fitting program. We also could obtain the natural frequencies, the modal damping coefficient ratio, the modal vectors and the whole transfer functions. Therefore we could analyze the dynamic characteristic for design of foaming sponge seat.

IMPROVEMENT OF RIDE AND HANDLING CHARACTERISTICS USING MULTI-OBJECTIVE OPTIMIZATION TECHNIQUES

  • KIM W. Y.;KIM D. K.
    • International Journal of Automotive Technology
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    • v.6 no.2
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    • pp.141-148
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    • 2005
  • In order to reduce the time and costs of improving the performance of vehicle suspensions, the techniques for optimizing damping and air spring characteristic were proposed. A full vehicle model for a bus is constructed with a car body, front and rear suspension linkages, air springs, dampers, tires, and a steering system. An air spring and a damper are modeled with nonlinear characteristics using experimental data and a curve fitting technique. The objective function for ride quality is WRMS (Weighted RMS) of the power spectral density of the vertical acceleration at the driver's seat, middle seat and rear seat. The objective function for handling performance is the RMS (Root Mean Squares) of the roll angle, roll rate, yaw rate, and lateral acceleration at the center of gravity of a body during a lane change. The design variables are determined by damping coefficients, damping exponents and curve fitting parameters of air spring characteristic curves. The Taguchi method is used in order to investigate sensitivity of design variables. Since ride and handling performances are mutually conflicting characteristics, the validity of the developed optimum design procedure is demonstrated by comparing the trends of ride and handling performance indices with respect to the ratio of weighting factors. The global criterion method is proposed to obtain the solution of multi-objective optimization problem.

Assessment of speckle image through particle size and image sharpness

  • Qian, Boxing;Liang, Jin;Gong, Chunyuan
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.659-668
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    • 2019
  • In digital image correlation, speckle image is closely related to the measurement accuracy. A practical global evaluation criterion for speckle image is presented. Firstly, based on the essential factors of the texture image, both the average particle size and image sharpness are used for the assessment of speckle image. The former is calculated by a simplified auto-covariance function and Gaussian fitting, and the latter by focusing function. Secondly, the computation of the average particle size and image sharpness is verified by numerical simulation. The influence of these two evaluation parameters on mean deviation and standard deviation is discussed. Then, a physical model from speckle projection to image acquisition is established. The two evaluation parameters can be mapped to the physical devices, which demonstrate that the proposed evaluation method is reasonable. Finally, the engineering application of the evaluation method is pointed out.

A method of overcomplete representation for distributed data (분산 자료에 대한 초완비 표현 방법)

  • Lee, Sang-Cheol;Park, Jong-Woo;Kwak, Chil-Seong
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.457-458
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    • 2007
  • This paper propose a method for representing distributed data of sensor networks. The proposed method is based on a general distributed regression framework that models sensor data by fitting a global function to each of the local measurements and explores the possible extensions of distribution regression by using complex signal representations. In order to reduce the amount of processed data and the required communication, the signal model has to be as compact as possible, with the ability to restore the arbitrary measurements. To achieve this requirement, data compression step is included, where the basis function set is changed to an overcomplete set. This have better advantages in case of nonstationary signal modeling than complete base representation.

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Effects of Tropospheric Mapping Functions on GPS Data Processing

  • Won, Ji-Hye;Park, Kwan-Dong;Ha, Ji-Hyun;Cho, Jung-Ho
    • Journal of Astronomy and Space Sciences
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    • v.27 no.1
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    • pp.21-30
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    • 2010
  • In processing space geodetic data, mapping functions are used to convert the tropospheric signal delay along the zenith direction to the line of sight direction. In this study, we compared three mapping functions by evaluating their effects on the tropospheric signal delay and position estimates in GPS data processing. The three mapping functions tested are Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), and Global Mapping Function (GMF). The tropospheric delay and height estimates from VMF1 and GMF are compared with the ones obtained with NMF. The differences among mapping functions show annual signals with the maximum occurring in February or August. To quantitatively estimate the discrepancies among mapping functions, we calculated the maximum difference and the amplitude using a curve fitting technique. Both the maximum difference and amplitude have high correlations with the latitude of the site. Also, the smallest difference was found around $30^{\circ}N$ and the amplitudes increase toward higher latitudes. In the height estimates, the choice of mapping function did not significantly affect the vertical velocity estimate, and the precision of height estimates was improved at most of the sites when VMF1 or GMF was used instead of NMF.

Preliminary Study of Deep Learning-based Precipitation

  • Kim, Hee-Un;Bae, Tae-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.5
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    • pp.423-430
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    • 2017
  • Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.

Development of Vibroacoustic Stimulation Seat for a Movie Theater Chair (영화관 의자용 음향진동자극 시트의 개발)

  • Moon, Deok-Hong
    • Journal of Power System Engineering
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    • v.17 no.1
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    • pp.42-49
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    • 2013
  • The global movie industry is continuing rapid growth through application of the latest technology. 3D movies are being produced and shown for a more effective viewing experience. Special chairs for audiences are being experimentally manufactured and installed for the greatest viewing effect. This special chair has a structure that applies vibrating stimuli to specific parts of the body by attaching vibration transducers to theater chairs and synchronizing it with each scene of the movie. In a previous study, it has been confirmed that we can analyze the vibration transfer characteristics of sponge seats through the application of an experimental modal analysis method and obtain design variables easily. In this paper, we examine the major design parameters needed in the development of a foaming sponge seat in which auxiliary springs are inserted to improve the vibration transfer effect of a chair seat. Through analyzing several prototypes by applying experimentation as well as the experimental modal analysis method, it was confirmed that the effect of vibration transfer can be improved through the use of an auxiliary member.

A Study on Nonlinear Parameter Optimization Problem using SDS Algorithm (SDS 알고리즘을 이용한 비선형 파라미터 최적화에 관한 연구)

  • Lee, Young-J.;Jang, Young-H.;Lee, Kwon-S.
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.623-625
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    • 1998
  • This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

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