• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.7 s.250
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• pp.603-611
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• 2006

This paper presents the response surface optimization method using three-dimensional Wavier-Stokes analysis to optimize the blade shape of an axial flow fan. Reynolds-averaged Wavier-Stokes equations with $k-{\epsilon}$ turbulence model are discretized with finite volume approximations using the unstructured grid. Regression analysis is used for generating response surface, and it is validated by ANOVA and t-statistics. Four geometric variables, i.e., sweep and lean angles at mean and tip respectively were employed to improve the efficiency. The computational results are compared with experimental data and the comparisons show generally good agreements. As a main result of the optimization, the total efficiency was successfully improved. Also, detailed effects of sweep and lean on the axial flow fan are discussed.

• Computers and Concrete
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• v.17 no.4
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• pp.477-488
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• 2016

This paper aims to model the effects of five different variables which includes: cement content (C), the steel fiber amount (F), the silica fume amount (SF), the superplasticizer (SP), the silica fume amount (SF), and the water to cementitious ratio (w/c) on 28 days flexural toughness of Ultra High Performance Concrete (UHPC) as well as, a study on the variable interactions and correlations by using analyze of variance (ANOVA) and response surface methodology (RSM). The variables were compared by fine aggregate mass. The model will be valid for the mixes with 0.18 to 0.32 w/c ratio, 4 to 8 percent steel fiber, 7 to 13 percent cement, 15 to 30 percent silica fume, and 4 to 8 percent superplasticizer by fine aggregate mass.

• Structural Engineering and Mechanics
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• v.34 no.4
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• pp.417-447
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• 2010

The uncertainty often observed in experimental strengths of masonry constituents makes critical the selection of the appropriate inputs in finite element analysis of complex masonry buildings, as well as requires modelling the building ultimate load as a random variable. On the other hand, the utilization of expensive Monte Carlo simulations to estimate collapse load probability distributions may become computationally impractical when a single analysis of a complex building requires hours of computer calculations. To reduce the computational cost of Monte Carlo simulations, direct computer calculations can be replaced with inexpensive Response Surface (RS) models. This work investigates the use of RS models in Monte Carlo analysis of complex masonry buildings with random input parameters. The accuracy of the estimated RS models, as well as the good estimations of the collapse load cumulative distributions obtained via polynomial RS models, show how the proposed approach could be a useful tool in problems of technical interest.

• Transactions of Materials Processing
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• v.10 no.6
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• pp.493-499
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• 2001

An optimal robust design methodology has been developed to minimize warpage in injection-molded pats. The response surface methodology was applied to obtain a functional relationship between design variables and warpage value, and the modified complex method was used as an optimization tool to search for an optimal design solution over prescribed design region. To attain robustness against process variations, Taguchi's SN ratio was introduced as the design metric. The proposed optimal design procedure was applied to an actual part, the Guide-ASF model of a fax machine, and the usefulness of the methodology was shown through the CAE simulation using a commercial injection molding software package.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.894-899
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• 2000

Optimization of 26 design variables selected from suspension characteristics for Korean High Speed Train (KHST) is performed according to the minimization of 58 responses which represent running safety and ride comfort for KHST and analyzed by using the each response surface model from stochastic design experiments. Sensitivity of design variables is also analyzed through the response surface model which ineffective design prameters to the performance index are screened by using stepwise regression method. The response surface models are used for optimizing design variables through simplex algorism. Values of performance index simulated by optimized design parameters are totally lower than those by initial design parameters. It shows that this method is effective for optimizing multi-design variables to multi-object function.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.185-190
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• 2005

This work presents a numerical procedure to optimize the elliptic-shaped pin fin arrays to enhance turbulent heat transfer. The response surface method is used as an optimization technique with Reynolds-averaged Navier Stokes analysis of flow and heat transfer. Shear stress transport (SST) turbulence model is used as a turbulence closure. Computational results for average heat transfer rate show a reasonable agreement with the experimental data. Four variables including major axis length, minor axis length, pitch and the pin fin length nondimensionalized by duct height are chosen as design variables. The objective function is defined as a linear combination of heat transfer and friction-loss related terms with weighting factor. D-optimal design is used to reduce the data points, and, with only 28 points, reliable response surface is obtained. Optimum shapes of the pin-fin arrays have been obtained in the range from 0.0 to 0.1 of weighting factor.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.578-582
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• 2004

This paper presents the response surface optimization method using three-dimensional Navier-Stokes Analysis to optimize the shape of a axial flow fan. Reynolds-averaged Navier-Stokes equations with k-$\epsilon$ turbulence model are discretized with finite volume approximations. Regression analysis is used for generating response surface, and it is validated by ANOVA. Five geometric variables, i.e., distribution of sweep angle at mean and tip, lean angle at mean and tip, and spanwise location of mean were employed to optimize the efficiency. The computational results are compared with experiment data. As a main result of the optimization, the efficiency was successfully improved.

• Structural Engineering and Mechanics
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• v.21 no.5
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• pp.507-518
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• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• Nuclear Engineering and Technology
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• v.18 no.1
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• pp.38-47
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• 1986

A statistical procedure, which uses response surface method and Monte Carlo simulation technique, is proposed for analyzing the thermal margin of light water reactor core. The statistical thermal margin analysis method performs the best.estimate thermal margin evaluation by the probabilistic treatment of uncertainties of input parameters. This methodology is applied to KNU-1 core thermal margin analysis under the steady state nominal operating condition. Also discussed are the comparisons with conventional deterministic method and Improved Thermal Design Procedure of Westinghouse. It is deduced from this study that the response surface method is useful for performing the statistical thermal margin analysis and that thermal margin improvement is assured through this procedure.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.167-174
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• 2005

The design for cold extrusion dies is very important, because the die insert is subjected to very high radial and hoop stresses. The design of cold extrusion dies has many constrained conditions. In this paper, the used assumptions are such that the yield strength of each ring is selected according to the allowable tensile or compressive hoop stress in each ring and the maximum allowable inner pressure, when yielding occurs in one ring of the dies, is obtained by the proposed equation. In order to obtain design variables, such as diameter ratios and interferences, using the maximum inner pressure, the flexible tolerance method was used for shrink-fitted thick-walled cylinders. ANSYS APDL was used to perform the repeated analysis of deformation of the dies due to the variation of the design variables. The response surface methodology is utilized to analyze the relationship between the design variables and the maximum radial displacement of the die insert during extrusion. From the results, it is found that outer diameter of the die insert has the largest effect on the minimization of maximum radial displacement at the inner surface of the dies.