• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.585-595
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• 2001

A second-order response surface model is often used to approximate the relationship between a response factor and a set of explanatory factors. In this article, we deal with canonical analysis in response surface models. For the interpretation of the geometry of second-order response surface model, standard errors and confidence intervals for the eigenvalues of the second-order coefficient matrix play an important role. If the confidence interval for some eigenvalue includes 0 or the estimate of some eigenvalue is very small (near to 0) with respect to other eigenvalues, then we are able to delete the corresponding canonical factor. We propose a formulation of criterion which can be used to select canonical factors. This criterion is based on the IMSE(=Integrated Mean Squared Error). As a result of this method, we may approximately write the canonical factors as a set of some important explanatory factors.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.2
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• pp.155-162
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• 2003

Design optimization of a transonic compressor rotor (NASA rotor 37) using response surface method and three-dimensional Navier-Stokes analysis has been carried out in this work. Baldwin-Lomax turbulence model was used in the flow analysis. Three design variables were selected to optimize the stacking line of the blade. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, adiabatic efficiency was successfully improved. It is also found that the design process provides reliable design of a turbomachinery blade with reasonable computing time.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.225-233
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• 2004

In this study, the seismic safety of containment building is assessed using response surface method. The structural analyses considering random variables such as load, resistance and analysis by ABAQUS are performed to obtain the structural response. The structural response is represented by polynomial of random variables, and the reliability analysis is performed by Level II method. Drucker-Prager failure criterion is applied as limit state function to take bi-axial stress states into account in the concrete. The lifetime probability of failure is evaluated by considering the lifetime of containment building, the annual occurrence rate of earthquake and the conditional probability of failure. Also the sensitivity analysis on the selection of sampling points is performed to obtain the steady results from response surface method.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.6
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• pp.1-11
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• 2003

For an accurate shock response analysis of a floating structure such as a naval surface ship subjected to an UNDEX(UNDerwater Explosion), the cavitation effects due to reflected wave at free surface and wetted structural surface should be considered. In this study, for the consideration of cavitation effects an effective method using LS-DYNA/USA and its theoretical background were presented. Through the application of the analysis of bulk cavitation phenomena in the free field, it could be confirmed that almost the same results were obtained between LS-DYNA/USA code and the analytical method. for the investigation of cavitation effects from the structural shock response characteristics, three dimensional UNDEX shock response analysis of an idealized ship model was also carried out It could be found that the cavitation Phenomena gave significant effects on the structural shock response characteristics, and especially that the shock loadings calculated at the installed location of shipboard equipment were underestimated in the case of no consideration of the cavitation effects, which might cause the severe mistake in its shock-resistance design.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.286-289
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• 2008

Mass of generator is one of the most important characteristic value especially direct drive type wind turbine. This paper introduce how to decease mass of generator rotor frame without declining generator performance. To obtain optimal design of rotor frame, sensitivity analysis using Taguchi method and RSM(response surface method) are have been performed.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.375-394
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• 2008

This paper discusses two user-friendly reliability techniques that could be implemented easily using the ubiquitous EXCEL. The techniques are First-Order Reliability Method with non-Gaussian random variables expressed using Hermite polynomials and collocation-based stochastic response surface method. It is believed that ease of implementation would popularize use of reliability-based design in practice.

• 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.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.21-28
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• 2014

In this study, evaluated ware the strength and durability of the vegetated water purification channel concrete to which recycled aggregates, hawang-toh and jute were applied. Box-Behnken method of response surface analysis in statistics was applied to the experimental design. Experimental variables are as follows, recycled coarse aggregates, hawang-toh, blast-furnace slag and jute fiber. In the experiment, conducted were the tests of compressive strength, chloride ion penetration, abrasion resistance and impact resistance the replacement rate effects of the recycled aggregates, blast-furnace slag and hwang-toh on the performance of vegetated water purification channel concrete were analyzed by using the response surface analysis method on the basis of the experimental results. In addition, an optimum mixing ratio of vegetated water purification channel concrete was determined by using the experimental results. The optimum mixing ratio was determined to be in 10.0% recycled coarse aggregates, 60.0% blast-furnace slag, 10.1% hwang-toh and 0.16% jute fiber. The compressive strength, chloride ion penetration, abrasion rate, and impact number of fracture test results of the optimum mixing ratio were 24.1 MPa, 999 coulombs, 10.30 g/mm3, and 20 number, respectively.

• Korean Management Science Review
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• v.24 no.2
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• pp.73-80
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• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.