• Honam Mathematical Journal
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• v.32 no.2
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• pp.193-202
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• 2010

We investigate the estimation of the moisture transfer coefficients in porous media by optimization technique which minimizes the functional defined by the squares error of the numerical solution of an inverse diffusion problem from their experimental values of the moisture content at the some time-steps. In this paper, we solve a diffusion equation numerically by the control volume finite element methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1679-1688
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• 1990

The method of nonlinear parameter estimation(NPE), which is a statistical and an inverse method, is used to estimate the thermal diffusivity of the porous insulation material. In order to apply the NPE method for measuring the thermal diffusivity, and algorithm for programing suitable to IBM personal computer is established, and is studied the statistical treatment of experimental data and theory of estimation. The experimental data obtained by discrete measurement using a constant heat flux technique are used to find the boundary conditions, initial conditions, and the thermal diffusivity, and then the final values are compared with the values obtained by some different methods. The results are presented as follows:(1) NPE method is used to establish the estimation of the thermal diffusivity and compared results with experimental output shows, that this method can be applicable to define the thermal diffusivity without considering hear flux types. (2) Because of all of the temperatures obtained by the discrete measurement on each steps of time are used to estimate the thermal diffusivity. Although some error in the temperature measurements of temperature are included in estimating process, its influences on the final value are minimzed in NPE method. (3) NPE method can reduce the experimental time including the time of data collecting in a few minutes and can take smaller specimen compared with steady state method. If the tube-type furnace is used, also the adjusting time of surrounding temperature can be reduced.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.175-180
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• 2003

An inverse problem to determine two-dimensional total heat exchange factor is studied for the prediction of the billet temperature in the reheating furnace. Temperature measurements by the experiment are used in the inverse analysis. This inverse analysis employs the conjugate gradient method. The total heat exchange factors for 12-zones of the cross-section of the billet are estimated. The estimated temperatures at measurement locations are in good agreements with the measured temperatures.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.11 s.242
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• pp.1257-1264
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• 2005

An inverse problem to determine two-dimensional total heat exchange factor is studied for the prediction of the slab temperature in the reheating furnace. Temperature measurements by the experiment are used in the inverse analysis. This inverse analysis employs the conjugate gradient method. The overall heat absorptances for 12-zones of the cross-section of the slab are estimated. The estimated temperatures at measurement locations are in good agreements with the measured temperatures.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1040-1048
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• 2013

In this paper, a sensorless pitch angle control method for a wind generation system is suggested. One-step-ahead prediction control law is adopted to control the pitch angle of a wind turbine in order for electric output power to track target values. And it is shown that this control scheme using the inverse dynamics of the controlled system enables us to predict current wind speed without an anemometer, to a considerable precision. The inverse input-output of the controlled system is realized by use of an artificial neural network. The proposed control and wind speed prediction method is applied to a Double-Feed Induction Generation system connected to a simple power system through computer simulation to show its effectiveness. The simulation results demonstrate that the suggested method shows better control performances with less control efforts than a conventional Proportional-Integral controller.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.211-216
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• 1997

An inverse method with regularization has been developed to determine the viscoelastic properties of trabecular bone. A series of stress relaxation experiments were performed under the condition of uniaxial compression stress state. Optimization has been formulated within the framework of nonlinear least-squares and a modified Gauss-Newton method with a zeroth-order regularization technique. The stress relaxation behavior of trabecular bone was analyzed using a standard viscoelastic model. The present study clearly shows that trabecular bone exhibits typical viscoelastic stress relaxation behavior, and the obtained material parameters well represent the viscoelastic behavior of trabecular bone.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.19-29
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• 1995

The surface velocities were estimated by the Maximum Cross Correlation(MCC) method and an inverse method from AVHRR/SST. In the results of MCC, discontinuous flow fields were estimated in the case that cross correlation coefficient was above 0.5 but these flow pattern disappeared when cross correlation coefficient was above 0.9. This estimation was conspicuous near SST patterns of eddies. In the results of inverse method, flow field was continuous and eddy motion was estimated definitely but the velocity was overstimated in compared with MCC result over the area of small temperature gradient. This result may be due to temperature error included in SST calculated and spatial variation of heat flux.

• Journal of the Korean Geotechnical Society
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• v.26 no.1
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• pp.5-19
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• 2010

Geo-layer information is important to determine pile length and estimate residual settlement in the construction site. An overall spatial distribution of geo-layers in the entire construction site can be predicted using drill-log information. In this study, the geo-layer distribution at Song-do area was estimated by kriging and inverse distance weighting methods, and a cross validation was adopted to verify the reliability of estimation results. The analysis results indicate that the best fitted theoretical variogram model to the experimental variogram does not always provide the most reliable estimation in the kriging method. The proper $\alpha$ value of inverse distance weighting method must be determined by types of geo-layer, because the $\alpha$ value is affected by types of geo-layer. Results of the kriging method show more reliable results than those of inverse distance weighting method, and the structure of geo-layer distribution could be evaluated by variogram in the kriging method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1202-1208
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• 2009

An inverse finite element (FE) model parameter estimation algorithm can be used to characterize mechanical properties of biological tissues. Using this algorithm, we can consider the influence of material nonlinearity, contact mechanics, complex boundary conditions, and geometrical constraints in the modeling. In this study, biomechanical experiments on macro and micro samples are conducted and characterized with the developed algorithm. Macro scale experiments were performed to measure the force response of porcine livers against mechanical loadings using one-dimensional indentation device. The force response of the human liver cancer cells was also measured by the atomic force microscope (AFM). The mechanical behavior of porcine livers (macro) and human liver cancer cells (micro) were characterized with the algorithm via hyperelastic and linear viscoelastic models. The developed models are suitable for computing accurate reaction force on tools and deformation of biomechanical tissues.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.503-512
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• 2006

In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.