• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.679-688
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• 2010

The major objective of the present study is to extend the applications of inverse analysis to more realistic engineering fields with a complex combustion process rather than the traditional simple heat-transfer problems. In order to do this, the unknown initial mass fractions of $CH_4/O_2$ are estimated from the temperature measurement data by inverse analysis in the practical diffusion-controlled turbulent combustion problem. In order to ensure efficient inverse analysis, the repulsive particle swarm optimization (RPSO) method, which belongs to the class of stochastic evolutionary global optimization methods, is implemented as an inverse solver. Based on this study, it is expected that useful information can be obtained when inverse analysis is used in the diagnosis, design, or optimization of real combustion systems involving unknown parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.229-238
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• 2006

Observed field behaviors are frequently different from the behaviors predicted in the design state due to several uncertainties involved in soil properties, numerical modeling, and error of measuring system even though a sophisticated numerical analysis technique is applied to solve the consolidation behavior of drainage-installed soft deposits. In this study, genetic algorithms are applied to back-analyze the soil properties using the observed behavior of soft clay deposit composed of multi layers that shows complex consolidation characteristics. Utilizing the program, one might be able to appropriately predict the subsequent consolidation behavior from the measured data in an early stage of consolidation of multi layered soft deposits. Example analyses for drainage-installed multi-layered soft deposits are performed to examine the applicability of proposed back-analysis method.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.218-218
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• 1998

• Journal of the Korean Geotechnical Society
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• v.17 no.2
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• pp.51-57
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• 2001

지하수위의 상승에 따른 간극수압의 증가는 사면의 불안정을 야기할 수 있다. 그러나 모델링 오차, 계측오차, 모델변수의 불확실성 등과 같은 오차로 인하여 사면에서의 지하수위 변동을 예측하는 것은 매우 어렵다. 이러한 불확실성을 극복하고 지하수위 변동을 평가하기 위한 최적의 모델변수를 구하기 위하여 역해석 기법이 사용되고 있다. 본 논문에서는 사면에서의 지하수위 변동을 예측하기 위하여 포화대에서의 지하수 흐름과 불포화대에서의 지하수 흐름을 동시에 고려할 수 있는 수치해석 모델과 변수예측기법을 적용하였다. 따라서, 본 논문에서는 포화투수계수($K_{s}$ ), 포화흡인력($\psi$$_{e}$) 및 불포화 투수계수의 함수에 사용되는 경험적인 상수(b)를 주요 매개변수로 선정하여 역해석을 실시하였다. 그리고, 역해석 기법 가운데 Maximum Likelihood(MK), Maximum-A-Posterior(MAP) 및 Extended Bayesian Method(EBM)에 대하여 비교연구를 실시하였다. 위의 세가지 방법 가운데 EBM은 가상의 변수(Hyperparameter) $\beta$를 도입함으로써 현장계측치와 사전정보를 가장 잘 조화시키는 방법으로 다른 ML, MAP 보다 탁월한 방법인 것을 알 수 있었다.

• Journal of Korean Society of Steel Construction
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• v.21 no.2
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• pp.165-173
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• 2009

Hanger cables in suspension bridges are constrained by the horizontal clamp. So, the accuracy of estimated tension of hange cable using existing methods based on the simple mathematical model of singel cable decreases as the length of cable decreases because of the flexural rigidity. Therefore, back analysis and system identification techniques based on the finite element model are proposed recently. In this paper, the applicability of the back analysis and system identification techniques are compared using the hanger cable of Gang-An Bridge. The experimental results show that the back analysis and system identification techniques are more reliable than the existing string theory and linear regression method in the view point of the error of natural frequencies. However, the estimation error of tension can be varied according to the accuracy of finite element model in the model based methods. Especially, the boundary condition is more affective when the length of cable is short, so it is important to identify the boundary condition through experiment if it is possible. The tension estimation method using system identification technique is more attractive because it can easily consider the boundary condition and it is not sensitive to the number of input measured natural frequencies.

• Economic and Environmental Geology
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• v.21 no.1
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• pp.107-113
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• 1988

We present a precedure for interpreting dipole-dipole apparent resistivity data. The procedure is constructed by combining a forward two-dimensional finite element modeling and an inverse technique with Householder's transformation. In the interpretation, subsurface structure is divided into some blocks with constant resistivities. Our inversion technique is tested on synthetic and field data. We found that geologic constraint is required for successful interpretation.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.397-402
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• 2012

The objective of this study is the estimation of the two unknown thermal conductivity and thermal diffusivity by an inverse heat conduction analysis using the Levenberg-Marguardt method. One dimensional formulation of heat conduction problem in the model was applied. Two point transient temperature of test pieces and heat flux of inflow were measured under the high enthalpy flow environment. Estimated thermal conductivity and thermal diffusivity by an inverse analysis were compared with the known values of graphite test piece. It showed the effectiveness of proposed experimental inverse analysis.

• Journal of Ocean Engineering and Technology
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• v.13 no.3 s.33
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• pp.21-28
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• 1999

In this paper, a finite element method for the determination of initial blank shape in sheet metal forming process will be introduced. The initial blank shape is determined by the only one step from the final to the initial blank. The used finite element inverse method adopted Henky's deformation theory, Hill's anisotropic yield criterion and simplified boundary conditions. Based on this theory. a three-dimensional membrane finite element code was developed. The developed code will be applied to several sheet metal forming examples for the demonstration of its validity.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.1
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• pp.81-87
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• 2008

This study is about the back analysis to optimize the uncertain parameters of geotechnical properties used in stability analysis of cut and cover tunnel. The Simplex algorithm, Powell algorithm, Rosenbrock algorithm, and Levenberg-Marquardt algorithm are applied for artificial problems of ground excavation. Furthermore, results are compared in the matter of the reliability of optimal solutions with a certain accuracy and the computation speed for evaluations of variables. As shown in results of numerical analysis, all of four algorithms are converged to exact solution satisfying the allowable criteria. And Levenberg-Marquardt's and Rosenbrock's algorithms are identified to be the more efficient methods in the evaluations of functions. After the back analysis for Poisson ratio and Young's modulus for cut and cover tunnel has been performed, design parameters have been correctly estimated and computation time has been improved while the number of measure points is increased.