• International Journal of Naval Architecture and Ocean Engineering
• /
• v.11 no.1
• /
• pp.44-51
• /
• 2019

Designing sophisticate ship structures that satisfy several design criteria simultaneously with minimum weight and cost is an important engineering issue. For a ship structure composed of a shell and stiffeners, this issue is more serious because their mutual effect has to be addressed. In this study, a two-stage optimization method is proposed for the conceptual design of stiffeners in a ship's prow. In the first stage, a topology optimization method is used to determine a potential stiffener distribution based on the optimal results, whereupon stiffeners are constructed according to stiffener generative theory and the material distribution. In the second stage, size optimization is conducted to optimize the plate and stiffener sections simultaneously based on a parametric model. A final analysis model of the ship-prow structure is presented to assess the validity of this method. The analysis results show that the two-stage optimization method is effective for stiffener conceptual design, which provides a reference for designing actual stiffeners for ship hulls.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1006-1011
• /
• 2003

In this study, a novel systematic design procedure by Genetic Algorithm of a two stage relief valve is proposed. First of all, a mathematical model describing the dynamics of a balanced piston type relief valve has been derived. Governing equations such as dynamic equations for the main spool and the pilot spool and flow equations for each orifice are established. The mathematical model is verified by comparing the results of simulation with that of experiments. Furthermore, influences of the parameters on the dynamic characteristics of a relief valve have been investigated by simulation of the proposed model. Major design parameters on the valve response are determined, which affect the system response significantly. And then, using the determined parameters, the optimization of the two stage relief valve by Genetic Algorithm, which is a random search algorithm can find the global optimum without converging local optimum, is performed. The optimal design process of a two stage relief valve is presented to determine the major design parameters. Fitness function reflects the changing pressure according to parameters. It is shown that the genetic algorithms satisfactorily optimized the major design parameters of the two stage relief valve.

• The Korean Journal of Applied Statistics
• /
• v.28 no.1
• /
• pp.93-102
• /
• 2015

The D-optimal design for the nonlinear model typically depends on the unknown parameters to be estimated. Therefore, it is strongly recommended in literature to use a sequential experimental design for estimating the parameters. In this paper two stage experimental design is discussed under many different circumstances including estimating parameters. The method is so universal to be applied to any mixture of objectives for any model including linear model. A hybrid approach is suggested to handle more than 2 objectives in two-stage experimental design. The design is discussed in approximate design framework.

• Communications for Statistical Applications and Methods
• /
• v.15 no.3
• /
• pp.387-402
• /
• 2008

In this thesis we propose a two-stage periodic inspection model for maintaining the reliability of a system in long-term storage. There are two types of tests available; a fallible test and an error-free test. The system is overhauled at detection of failure or when the storage reliability after inspection becomes less than or equal to the prespecified value. The expected cost per unit time until overhaul is derived and a procedure for minimizing the expected cost is suggested. The two-stage periodic inspection model is compared with the one-stage periodic inspection model for various parameters of the cost function when the failure time follows exponential and Weibull distributions. The proposed model is then applied to an existing missile system for comparison with the current inspection policy.

• International Journal of Human Ecology
• /
• v.4 no.2
• /
• pp.77-87
• /
• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.5
• /
• pp.1077-1085
• /
• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• Journal of Korean Society for Atmospheric Environment
• /
• v.12 no.1
• /
• pp.29-41
• /
• 1996

The two-stage numerical model was used to study the relation between three-dimensional local wind model, advection/diffusion model of random walk method and second moment method on Pusan coastal area. The first stage is three dimensional time-dependent local wind model which gives the wind field and vertical dirrusion coefficient. The second stage is advection/diffusion model which uses the results of the first stage as input data. First, wind fields on Pusan coastal area for none synoptic scale wind showed typical land and sea breeze circulation, and convergence zone occured at 1200LST in northern of domain, in succession, moved northward of domain. Emissions from Sinpyeong industrial district were trasnported toward the inland by sea breeze during daytime, and reached the end part of domain about 1800LST. During nighttime, emissions return to sea by land breeze and vertical diffusion also contributes to upward transport. In order to use this model for forecast of air pollution concentration on the Pusan coastal area, it is necessary that computed value must be compared with measured value and wind fields model must also be dealt in detail.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.3
• /
• pp.1-11
• /
• 2016

The present study aims to evaluate transfer resistance factors in railway stations and draw new implications. The data used for the model estimation are RP (revealed preference) data and SP (stated preference) data. Two types of models were used for the analysis: integration model which combined line-haul stage, transfer stage and shuttle stage and separation model which assessed the three stages separately. The results revealed that while bulk freight shippers mainly focused on line-haul stage, they put emphasis on transfer stage as well. It's especially notable that transfer stage was considered more important than shuttle stage. Therefore, in future transportation policies concerning rail freight, it would be crucial not only to enhance the competitiveness of line-haul stage but also make improvements in transfer stage regarding railway stations.

• Coupled systems mechanics
• /
• v.12 no.5
• /
• pp.419-428
• /
• 2023

We have developed a model for estimating the parameters of viscous materials from indirect tensile tests for asphalt. This is a simple Burger nonlinear rheological two-cell model or standard model. At the same time, we begin to develop a more versatile and complex multi-cell model. The simple model is validated using experimental load-displacement results from laboratory tests: The recorded displacements are used as input values and the measured force data are simulated with the model. The optimal model parameters are estimated using the Levenberg-Marquardt method and a very good agreement between the experimental results and the model calculations is shown. However, not all parts of the model are active in the loading phase of the experiment, so we extended the validation of the model to the simulation of the relaxation behaviour. In this stage, the other model parameters are activated and the simulation results are consistent with the literature. At this stage, we have estimated the parameters only for the two-cell uniaxial model, but further work will include results for the multi-cell model.

• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.5
• /
• pp.447-452
• /
• 2015

This paper considers a two-stage make-to-stock production system. The first stage produces a single-component and the second stage produces a make-to-stock product using components. In addition to internal demands, the first stage faces external demands with the option of accepting or rejecting. To ration component inventory, the manufacturer adopts a static rule. This paper analyzes the production controls at both facilities that maximizes the manufacturer's profit. Using the Markov decision process model, we characterize the optimal production policy by two monotonic switching curves.