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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.8
• /
• pp.989-996
• /
• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• Journal of Navigation and Port Research
• /
• v.34 no.7
• /
• pp.553-558
• /
• 2010

This study presents the optimization design process of a segment ball valve that involves the reduction of the flow resistance coefficient and the satisfaction of the strength requirement. Numerical analysis of fluid flow and structural analysis have been performed to predict the flow resistance coefficient and the maximum stress of a segment ball valve. In this study, a segment ball valve incorporating the advantages of a ball valve and a butterfly valve has been devised. In general, ball valves are installed in a pipe system where tight shut off is required. Butterfly valves having smaller end-to-end dimension than ball valve can be installed in narrow spaces in a pipe system. The metamodels for the shape design of a segment ball valve are built by the response surface method and the Kriging interpolation model.

• Journal of the military operations research society of Korea
• /
• v.25 no.2
• /
• pp.1-14
• /
• 1999

Metamodels using response surface methodology (RSM) are used for the optimality analysis of linear programming (LP). They have the form of a simple polynomial, and predict the optimal objective function value of an LP for various levels of the constraints. The metamodelling techniques for optimality analysis of LP can be applied to large-scale LP models. What is needed is some large-scale application of the techniques to verify how accurate they are. In this paper, we plan to use the large scale LP model, strategic transport optimal routing model (STORM). The developed metamodels of the large scale LP can provide some useful information.

• Structural Engineering and Mechanics
• /
• v.67 no.3
• /
• pp.301-310
• /
• 2018

In this paper, a multi-objective multiparameter optimization procedure is developed by combining rigorously developed metamodels with an evolutionary search algorithm-Genetic Algorithm (GA). Response surface methodology (RSM) is used for developing the metamodels to replace the tedious finite element analyses. A nine-node isoparametric plate bending element is used for conducting the finite element simulations. Highly accurate numerical data from an author compiled FORTRAN finite element program is first used by the RSM to develop second-order mathematical relations. Four material parameters-${\frac{E_1}{E_2}}$, ${\frac{G_{12}}{E_2}}$, ${\frac{G_{23}}{E_2}}$ and ${\upsilon}_{12}$ are considered as the independent variables while simultaneously maximizing fundamental frequency, ${\lambda}_1$ and frequency separation between the $1^{st}$ two natural modes, ${\lambda}_{21}$. The optimal material combination for maximizing ${\lambda}_1$ and ${\lambda}_{21}$ is predicted by using a multi-objective GA. A general sensitivity analysis is conducted to understand the effect of each parameter on the desired response parameters.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.6
• /
• pp.461-468
• /
• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Smart Structures and Systems
• /
• v.14 no.5
• /
• pp.811-830
• /
• 2014

A numerical study has been carried out to simulate an innovative monitoring procedure to detect and localize damage in reinforced concrete beams retrofitted with carbon fiber reinforced polymer (CFRP) unidirectional laminates. The main novelty of the present simulation is its ability to conduct the electromechanical admittance monitoring technique by considerably compressing the amount of data required for damage detection and localization. A FEM simulation of electromechanical admittance-based sensing technique was employed by applying lead zirconate titanate (PZT) transducers to acquire impedance spectrum signatures. Response surface methodology (RSM) is finally adopted as a tool for solving inverse problems to estimate the location and size of damaged areas from the relationship between damage and electromechanical admittance changes computed at PZT transducer surfaces. This statistical metamodel technique allows polynomial models to be produced without requiring complicated modeling or numerous data sets after the generation of damage, leading to considerably lower cost of creating diagnostic database. Finally, a numerical example is carried out regarding a steel-reinforced concrete (RC) beam model monotonically loaded up to its failure which is also retrofitted by a CFRP laminate to verify the validity of the present metamodeling monitoring technique. The load-carrying capacity of concrete is predicted in the present paper by utilizing an Ottosen-type failure surface in order to better take into account the passive confinement behavior of retrofitted concrete material under the application of FRP laminate.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.501-506
• /
• 2001

Computer modeling is essential to evaluate possible design of suspension for a railway vehicles. By creating a simulation, the engineers are able to assess the feasibility of a given design and change the design factors to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have turned to surrogate modeling. A surrogate model is essentially a regression performed on a data sampling of the simulation. In the most general sense, metamodels(surrogate model) take the form $y(x)=f(x)+{\varepsilon}$, where y(x) is the true simulation output, f(x) is the metamodel output, and $\varepsilon$ is the error between the two. In this paper, a second order polynomial equation is partially used as a metamodel to represent the forty-six dynamic performances for high speed train. The number of factors as design variables of the metamodel is twenty-nine, which are composed the dynamic characteristics of suspension. This metamodel is used to search the optimum values of suspension characteristics which minimize the dynamic responses for high speed train. This optimization is a multi-objective problem which have many design variables. This paper shows that the response surface model which is made through the design of analysis of computer experiments method is very efficient to solve this complex optimization problem.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.387-392
• /
• 2005

Double-deck train have studied in the next generation train in KRRI. Double-deck train have more seat capacities compared with single deck vehicles and is a efficient, reliable and comfortable alternative train. Because of heavy weight, weight minimization of double-deck train carbody is imperative to reduce cost and extend life-time of train. Weight minimization problem of the double-deck train car-body is required to decide 66 design variables of thicknesses for large aluminum extruded panel while satisfying stress constraints. Design variables are too many and one execution of structural analysis of double-deck train carbody is time-consuming. Therefore, we adopt approximation technique to save computational cost of optimization process. Metamodels such as response surface model (RSM) and kriging model are used to approximate model-based optimization is described. RSM is easy to obtain and expressed explicit function, but this is not suitable for highly nonlinear and large scaled problems. Kriging model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. Target of this design is to find optimum thickness of AEP to minimize weight of doulbe-deck train carbody. In this study, meta model techniques are introduced to carry out weight minimization of a double-deck train car-body.

• Journal of Ocean Engineering and Technology
• /
• v.34 no.4
• /
• pp.253-262
• /
• 2020

This study provides a comparative analysis of experiments-based enhancements and sensitivity evaluations for the structural design of an automatic ocean salt collector under various load conditions. The sizing variables of the structural members were considered as design factors. The strength and weight performances were selected as output responses. The design of experiments used in the comparative study consisted of the orthogonal array design, Box-Behnken design, and central composite design. The response surface model, one of the metamodels, was applied to the approximate model generation. The design enhancement performance metrics, including numerical costs and weight minimization, according to the design of experiments, were compared from the best design case results. The central composite design method showed the most enhanced design results for the structural design of the automatic ocean salt collector.