• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.71-75
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• 1999

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity geometrical size and die velocity of model materials are different from those of real materials. Actually the forming load of yoke which is an automobile part made of aluminum alloys(Al-6061) is predicted by using this approximate similarity theory. Firstly upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061) and a suitable model material is selected for model material test of Al-6061 And then and forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material which has been selected from above upset forging tests, The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• Journal of Ocean Engineering and Technology
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• v.35 no.2
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• pp.131-140
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• 2021

The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.204-208
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• 2000

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity, geometrical size, and die velocity of model materials are different from those of real materials. Actually, the forming load of yoke, which is an automobile part made of aluminum alloys(Al-6061), is predicted by using this approximate similarity theory. Firstly, upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061), and a suitable model material is selected for model material test of Al-6061. And then hot forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material, which has been selected from above upset forging tests. The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.109-117
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• 2021

In this paper, the meta-model based approximate optimization was carried out for the structure design of an ocean automatic salt collector in order to minimize the structure weight. The structural analysis was performed by using the finite element method to evaluate the strength performance of the ocean automatic salt collector in its initial design. In the structural analysis, it was evaluated the strength performance of the design load conditions. The optimum design problem was formulated so that design variables of main structure thickness would be determined by minimizing the structure weight subject to strength performance constraints. The meta-models used in the approximate optimization were the response surface method, Kriging model, and Chebyshev orthogonal polynomials. Regarding to the numerical characteristics, the solution results from approximate optimization techniques were compared to the results of non-approximate optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the ocean automatic salt collector.

• Water Engineering Research
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• v.4 no.4
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• pp.175-185
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• 2003

A numerical model to analyze dam break flows has been developed based on approximate Riemann solver. The governing equations of the model are the nonlinear shallow-water equations. The governing equations are discretized explicitly by using finite volume method and the numerical flux are reconstructed with weighted averaged flux (WAF) method. The developed model is verified. The first verification problem is about idealized dam break flow on wet and dry beds. The second problem is about experimental data of dam break flow. From the results of the verifications, very good agreements have been observed

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.471-486
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• 2022

Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.31-43
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• 2021

In this study, approximate design optimization using various meta-models was performed for the structural design of active type deck support frame. The active type deck support frame was newly developed to facilitate both transportation and installation of 20,000 ton class offshore plant topside. Structural analysis was carried out using the finite element method to evaluate the strength performance of the active type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions that were regulated in ship classification organization. The approximate optimum design problem based on meta-model was formulated such that thickness sizing variables of main structure members were determined by achieving the minimum weight of the active type deck support frame subject to the strength performance constraints. The meta-models used in the approximate design optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. The results from approximate design optimization were compared to actual non-approximate design optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate design optimization represented the most pertinent optimum design results for the structure design of the active type deck support frame.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.1-11
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• 2004

Two approximate methods for a cosmic radiation shielding calculation in low earth orbits were developed and assessed. Those are a sectoring method and a chord-length distribution method. In order to simulate a change in cosmic radiation environments along the satellite mission trajectory, IGRF model and AP(E)-8 model were used. When the approximate methods were applied, the geometrical model of satellite structure was approximated as one-dimensional slabs, and a pre-calculated dose-depth conversion function was introduced to simplify the dose calculation process. Verification was performed with mission data of KITSAT-1 and the calculated results were also compared with detailed 3-dimensional calculation results using Monte Carlo calculation. Dose results from the approximate methods were conservatively higher than Monte Carlo results, but were lower than experimental data in total dose rate. Differences between calculation and experimental data seem to come from the AP-8 model, for which it is reported that fluxes of proton are underestimated. We confirmed that the developed approximate method can be applied to commercial satellite shielding calculations. It is also found that commercial products of semi-conductors can be damaged due to total ionizing dose under LEO radiation environment. An intensive shielding analysis should be taken into account when commercial devices are used.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.33-43
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• 2021

A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.

• Computational Structural Engineering
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• v.10 no.2
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• pp.273-281
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• 1997

In the structural analysis, artificial neural networks as a parallel computational model that is similar to the human brain and can self-organize complex nonlinear relationships without making assumptions is introduced. The purpose of this paper is to develop the Neural Network for Approximate Structural Analysis(NNASA) to predict the behaviour of the stub-girder system. As an initial stage, the paper presents the development of the prototype of NNASA based on the problem related to the deflection of a simple beam, and shows the verification of this model by two examples.