• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.700-703
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• 2004

A reliability analysis and design procedure based on the design of experiment (DOE) is combined with the response surface method (RSM) for numerical efficiency. The procedure established is based on a 3$^n$ full factorial DOE for numerical quadrature using explicit formula of optimum levels and weights derived for general distributions. The full factorial moment method (FFMM) shows good performance in terms of accuracy and ability to treat non-normally distributed random variables. But, the FFMM becomes very inefficient because the number of function evaluation required increases exponentially as the number of random variables considered increases. To enhance the efficiency, the response surface moment method (RSMM) is proposed. In RSMM, experiments only with high probability are conducted and the rest of data are complemented by a quadratic response surface approximation without mixed terms. The response surface is updated by conducting experiments one by one until the value of failure probability is converged. It is calculated using the Pearson system and the four statistical moments obtained from the experimental data. A measure for checking the relative importance of an experimental point is proposed and named as influence index. During the update of response surface, mixed terms can be added into the formulation.

• Composites Research
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• v.23 no.2
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• pp.40-47
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• 2010

In this paper, the hybrid response surface method(HRSM) is proposed and examined. Hybrid response surface method calculate a approximate model repeatedly based on MPP coordinates. To verify the performance, probability of failure, MPP(Most Probable failure Point) and reliability index are calculated for nonlinear function and composite laminated plate by using reliability analysis method and compared with results by using typical response surface method(RSM). Probability of failure is calculated under the assumption of the nonlinear limit state equation and given failure criterion. The results of proposed method shows performance improvement in estimating the probability of failure.

• Smart Structures and Systems
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• v.24 no.6
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• pp.693-707
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• 2019

This paper proposes an integrated safety assessment method that can take multiple sources data into consideration based on a data fusion approach. Data cleaning using the Kalman filter method (KF) was conducted first for monitoring data from each sensor. The inclination data from the four tilt sensors of the same monitoring section have been associated to synchronize in time. Secondly, the finite element method (FEM) model was established to physically correlate the external forces with various structural responses of the shield tunnel, including the measured inclination. Response surface method (RSM) was adopted to express the relationship between external forces and the structural responses. Then, the external forces were updated based on the in situ monitoring data from tilt sensors using the extended Kalman filter method (EKF). Finally, mechanics parameters of the tunnel lining were estimated based on the updated data to make an integrated safety assessment. An application example of the proposed method was presented for an urban tunnel during a nearby deep excavation with multiple source monitoring plans. The change of tunnel convergence, bolt stress and segment internal forces can also be calculated based on the real time deformation monitoring of the shield tunnel. The proposed method was verified by predicting the data using the other three sensors in the same section. The correlation among different monitoring data has been discussed before the conclusion was drawn.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.143-150
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• 2004

An optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen for design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size for each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1628-1633
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• 2016

This paper derives an effective shape of the ferromagnetic pole pieces (low-speed rotor) for the reduction of transmission torque ripple in a magnetic-geared machine based on a Box-Behnken design (BBD). In particular, using a non-linear finite element method (FEM) based on 2-D numerical analysis, we conduct a numerical investigation and analysis between independent variables (selected by the BBD) and reaction variables. In addition, we derive a regression equation for reaction variables according to the independent variables by using multiple regression analysis and analysis of variance (ANOVA). We assess the validity of the optimized design by comparing characteristics of the optimized model derived from a response surface analysis and an initial model.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1055-1056
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• 2011

This paper deals with optimum design criteria for maximum torque density & minimum current density of a single phase line-start permanent-magnet motor (LSPMM) using RSM (Response Surface Methodology) & FEM (Finite Element Method). The focus of this paper is to find a design solution through the comparison of torque density and minimum current density resulting from rotor shape variations. And then, a central composite design (CCD) mixed resolution is introduced, and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.688_689
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• 2009

This paper presents a multi-objective optimal design process for an in-wheel permanent magnet synchronous motor (PMSM) for high performance. In order to improve the characteristics of the PMSM such as the cogging torque, torque ripple and the back-EMF, the modified Taguchi method and the response surface method (RSM) are utilized. In addition, results of the proposed model are compared with the initial design and it is verified by 2D FEM.

• Steel and Composite Structures
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• v.9 no.5
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• pp.445-455
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• 2009

This study proposes a system identification technique for a fiber-reinforced polymer deck with neural networks. Neural networks are trained for system identification and the identified structure gives training data in return. This process is repeated until the identified parameters converge. Hence, the proposed algorithm is called an iterative neural network scheme. The proposed algorithm also relies on recent developments in the experimental design of the response surface method. The proposed strategy is verified with known systems and applied to a fiber-reinforced polymer bridge deck with experimental data.

• 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.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.96-101
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• 2009

The aim of this research was to apply experimental design methodology to optimizetion the photolytic degradation of N-nitrosodimethylamine (NDMA). Reactions were mathematically described as a function of parameters such as pH, initial NDMA concentration, and UV intensity using the Box-Behnken method. The results showed that the responses of NDMA removal (%) in photolysis were significantly affected by the synergistic effect of linear term of pH, initial NDMA concentration and UV intensity. The application of Response Surfase Methodology (RSM) using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal (%) of NDMA and test variables in coded unit: Y = 50.929 + 16.073(UV) - 7.909(NDMA) - 27.432(pH) - 11.385(UV)(NDMA) - 7.363(UV)(pH) +13.811(NDMA)(pH). The model predictions agreed well with the experimentally observed result ($R_2(ad.)=89%$).