• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.941-948
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• 2006

In this study, the new method for reliability estimation is proposed using kriging metamodel. Kriging metamodel can be determined by appropriate sampling range and sampling numbers because there are no random errors in the Design and Analysis of Computer Experiments(DACE) model. The first kriging metamodel is made based on widely ranged sampling points. The Advanced First Order Reliability Method(AFORM) is applied to the first kriging metamodel to estimate the reliability approximately. Then, the second kriging metamodel is constructed using additional sampling points with updated sampling range. The Monte-Carlo Simulation(MCS) is applied to the second kriging metamodel to evaluate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.8
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• pp.711-717
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• 2007

Shape optimization of a staggered herringbone groove micromixer using three-dimensional Navier-Stokes analysis has been carried using Kriging model. The analysis of the degree of mixing is performed by the calculation of spatial data statistics. The calculation of the variance of the mass fraction at various nodes on a plane in the channel is used to quantify mixing. A numerical optimization technique with Kriging model is applied to optimize the shape of the grooves on a single wall of the channel. Three design variables, namely, the ratio of groove width to groove pitch, the ratio of the groove depth to channel height ratio and the angle of the groove, are selected for optimization. A mixing index is used as the objective function. The results of the optimization show that the mixing is very sensitive to the shape of the groove which can be used in controlling mixing in microdevices.

• Geomechanics and Engineering
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• v.18 no.6
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.9
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• pp.733-740
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• 2007

Microchannel heat sink shape optimization is performed using Kriging method. Design variables relating to microchannel width, depth and fin width are selected, and thermal resistance has been taken as objective function. Design points are selected through a three-level fractional factorial design of sampling method. Navier-Stokes and energy equations for laminar flow and conjugate heat transfer are solved at these design points using a finite volume solver. Solutions are carefully validated with experimental results. Using the numerically evaluated objective function, a surrogate model (Kriging) is constructed and optimum point is searched by sequential quadratic programming. The process of shape optimization greatly improves the thermal performance of microchannel heat sink under constant pumping power.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1846-1851
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• 2003

Approximate optimization has become popular in engineering field such as MDO and Crash analysis which is time consuming. To accomplish efficient approximate optimization, accuracy of approximate model is very important. As surrogate model, Kriging have been widely used approximating highly nonlinear system . Because Kriging employs interpolation method, it is adequate for deterministic computer simulation. Because there are no random errors and measurement errors in deterministic computer simulation, instead of classical DOE ,space filling experiment design which fills uniformly design space should be applied. In this work, various space filling designs such as maximin distance design, maximum entropy design are reviewed. And new design improving maximum entropy design is suggested and compared.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.177-183
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• 2013

We describe a new method for selecting design variables for shape optimization of high-voltage gas circuit breaker using a Kriging meta-model and a genetic algorithm. Firstly we sample balance design variables using the Latin Hypercube Sampling. Secondly, we build meta-model using the Kriging. Thirdly, we search the optimal design variables using a genetic algorithm. To obtain the more exact design variable, we adopt the boundary shifting method. With the proposed optimization frame, we can get the improved interruption design and reduce the design time by 80%. We applied the proposed method to the optimization of multivariate optimization problems as well as shape optimization of a high - voltage gas circuit breaker.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.10
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• pp.551-557
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• 2016

Fusing satellite images and site-specific observations have potential to improve a predictive quality of environmental properties. However, the effect of the utilization of satellite images to predict soil properties in a wetland is still poorly understood. For the reason, block kriging and regression kriging were applied to a natural wetland, Water Conservation Area-2A in Florida, to compare the accuracy improvement of continuous models predicting total phosphorus in soils. Field observations were used to develop the soil total phosphorus prediction models. Additionally, the spectral data and derived indices from Landsat ETM+, which has 30 m spatial resolution, were used as independent variables for the regression kriging model. The block kriging model showed $R^2$ of 0.59 and the regression kriging model showed $R^2$ of 0.49. Although the block kriging performed better than the regession kriging, both models showed similar spatial patterns. Moreover, regression kriging utilizing a Landsat ETM+ image facilitated to capture unique and complex landscape features of the study area.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.3
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• pp.381-386
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• 2003

Gradually engineering designers are determined based on computer simulations. Modeling of the computer simulation however is too expensive and time consuming in a complicate system. Thus, designers often use approximation models called metamodels, which represent approximately the relations between design and response variables. There arc general metamodels such as response surface model and kriging metamodel. Response surface model is easy to obtain and provides explicit function. but it is not suitable for highly nonlinear and large scaled problems. For complicate case, we may use kriging model that employs an interpolation scheme developed in the fields of spatial statistics and geostatistics. This class of into interpolating model has flexibility to model response data with multiple local extreme. In this study. metamodeling techniques are adopted to carry out the shape optimization of a funnel of Cathode Ray Tube. which finds the shape minimizing the local maximum principal stress Optimum designs using two metamodels are compared and proper metamodel is recommended based on this research.

• The KSFM Journal of Fluid Machinery
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• v.16 no.6
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• pp.32-39
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• 2013

In the present study, three-dimensional aerodynamic optimization of high pressure turbine nozzle for turbofan engine was performed. For this, Kriging surrogate model was built and refined iteratively by supplying additional experimental points until the surrogate model and CFX result has effective difference on objective function. When the surrogate model satisfied this reliability condition and developed enough, optimum point was investigated. Commercial program PIAnO was used for optimization process and evolutionary algorithm was used for searching optimum point. As a result, difference between estimated value from Kriging surrogate model and CFD result converges within 0.01% and the optimized nozzle shape has 0.83% improved aerodynamic efficiency.