• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.8 s.239
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• pp.903-910
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• 2005

Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and finite-difference Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach that adopts the hybrid genetic algorithm as an initial value selector and uses the finite-difference Newton method as an optimization procedure.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.539-551
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• 2021

With the continuous increase of computational capacity, more and more complex nonlinear elastoplastic constitutive models were developed to study the mechanical behavior of elastoplastic materials. These constitutive models generally contain a large amount of physical and phenomenological parameters, which often require a large amount of computational costs to determine. In this paper, an inverse parameter determination method is proposed to identify the constitutive parameters of elastoplastic materials, with the consideration of both strain rate effect and temperature effect. To carry out an efficient design, a hybrid optimization algorithm that combines the genetic algorithm and the Nelder-Mead simplex algorithm is proposed and developed. The proposed inverse method was employed to determine the parameters for an elasto-viscoplastic constitutive model and Johnson-cook model, which demonstrates the capability of this method in considering strain rate and temperature effect, simultaneously. This hybrid optimization algorithm shows a better accuracy and efficiency than using a single algorithm. Finally, the predictability analysis using partial experimental data is completed to further demonstrate the feasibility of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.10
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• pp.1516-1523
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• 2003

An inverse radiation analysis is presented for the estimation of the boundary emissivities for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. The finite-volume method is employed to solve the radiative transfer equation for a two-dimensional irregular geometry. A hybrid genetic algorithm is proposed for improving the efficiency of the genetic algorithm and reducing the effects of genetic parameters on the performance of the genetic algorithm. After verifying the performance of the proposed hybrid genetic algorithm, it is applied to inverse radiation analysis in estimating the wall emissivities in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. The effect of measurement errors on the estimation accuracy is examined.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1081-1103
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• 2014

Real-time hybrid simulation (RTHS) has emerged as an important tool for testing large and complex structures with a focus on rate-dependent specimen behavior. Due to the real-time constraints, accurate dynamic control of servo-hydraulic actuators is required. These actuators are necessary to realize the desired displacements of the specimen, however they introduce unwanted dynamics into the RTHS loop. Model-based actuator control strategies are based on linearized models of the servo-hydraulic system, where the controller is taken as the model inverse to effectively cancel out the servo-hydraulic dynamics (i.e., model-based feedforward control). An accurate model of a servo-hydraulic system generally contains more poles than zeros, leading to an improper inverse (i.e., more zeros than poles). Rather than introduce additional poles to create a proper inverse controller, the higher order derivatives necessary for implementing the improper inverse can be calculated from available information. The backward-difference method is proposed as an alternative to discretize an improper continuous time model for use as a feedforward controller in RTHS. This method is flexible in that derivatives of any order can be explicitly calculated such that controllers can be developed for models of any order. Using model-based feedforward control with the backward-difference method, accurate actuator control and stable RTHS are demonstrated using a nine-story steel building model implemented with an MR damper.

• Journal of Magnetics
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• v.16 no.3
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• pp.240-245
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• 2011

A new hybrid ON/OFF method is presented for the fast solution of electromagnetic inverse problems in high frequency domains. The proposed method utilizes both topological sensitivity (TS) and material sensitivity (MS) to update material properties in unit design cells. MS provides smooth design space and stable convergence, while TS enables sudden changes of material distribution when MS slows down. This combination of two sensitivities enables a reduction in total computation time. The TS and MS analyses are based on a variational approach and an adjoint variable method (AVM), which permits direct calculation of both sensitivity values from field solutions of the primary and adjoint systems. Investigation of the formulations of TS and MS reveals that they have similar forms, and implementation of the hybrid ON/OFF method that uses both sensitivities can be achieved by one optimization module. The proposed method is applied to dielectric material reconstruction problems, and the results show the feasibility and effectiveness of the method.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1288-1293
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• 2004

Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach of adopting the genetic algorithm as an initial value selector, whereas using the conjugate-gradient method and Newton method to reduce their dependence on the initial value.

• Steel and Composite Structures
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• v.20 no.5
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• pp.1119-1131
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• 2016

As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2476-2481
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• 2007

An inverse radiation analysis is presented for the estimation of the wall emissivities for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. In this study, a repulsive particle swarm optimization(RPSO) algorithm which is a relatively recent heuristic search method is proposed as an effective method for improving the search efficiency for unknown parameters. To verify the performance of the proposed RPSO algorithm, it is compared with a basic particle swarm optimization(PSO) algorithm and a hybrid genetic algorithm(HGA) for the inverse radiation problem with estimating the wall emissivities in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. A finite-volume method is applied to solve the radiative transfer equation of a direct problem to obtain measured temperatures.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1639-1644
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• 2003

A hybrid genetic algorithm is developed for estimating the wall emissivities for an absorbing, emitting, and scattering media in a two-dimensional irregular geometry with diffusely emitting and reflecting opaque boundaries by minimizing an objective function, which is expressed by the sum of square errors between estimated and measured temperatures at only four data positions. The finite-volume method was employed to solve the radiative transfer equation for a two-dimensional irregular geometry. The results show that a developed hybrid genetic algorithms reduce the effect of genetic parameters on the performance of genetic algorithm and that the wall emissivities are estimated accurately without measurement errors.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.659-668
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• 2017

The inverse Weibull distribution (IWD) can be readily applied to a wide range of situations including applications in medicines, reliability and ecology. It is generally known that the lifetimes of test items may not be recorded exactly. In this paper, therefore, we consider the maximum likelihood estimation (MLE) and Bayes estimation of the entropy of a IWD under generalized progressive hybrid censoring (GPHC) scheme. It is observed that the MLE of the entropy cannot be obtained in closed form, so we have to solve two non-linear equations simultaneously. Further, the Bayes estimators for the entropy of IWD based on squared error loss function (SELF), precautionary loss function (PLF), and linex loss function (LLF) are derived. Since the Bayes estimators cannot be obtained in closed form, we derive the Bayes estimates by revoking the Tierney and Kadane approximate method. We carried out Monte Carlo simulations to compare the classical and Bayes estimators. In addition, two real data sets based on GPHC scheme have been also analysed for illustrative purposes.