• Computational Structural Engineering
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• v.32 no.1
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• pp.15-24
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• 2019

• Computational Structural Engineering
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• v.36 no.1
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• pp.15-23
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• 2023

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.81-86
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• 2004

For the development of system framework which provides multidisciplinary design environment, the integration of analysis codes written in various computer languages, the integration of CAD and DBMS, and the development of complex GUI are indispensible In this study, three different design frameworks which have been developed in Konkuk University with the aids of a company and other university, are compared and analyzed with respect to the analysis code integration method and the module interface technique. Moreover, the way to develop an efficient framework is proposed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.10a
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• pp.127-132
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• 1991

The purpose of this study is to integrate a structural design Process of framed steel structures. It is composed of analysis, design, drafting and construction management. However each step of these works involved with a large amount of data and man hour resources. The aim of this study is to alleviate time consuming efforts mentioned above by integrating the different stage of works. Very successful results have been achieved by setting up a common database in whole process and applying the techniques of knowledge base system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.106-112
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• 1993

This paper presents the optimum design of reinforced concrete conical shell which is fixed at the base and free at the top. The calculation of stresses is done using the SMAP(Segmented Matrix Analysis Package)program which uses the simple finite element method of analysis. The objective function contains the ratios of the unit cost of reinforcements and formwork to that of concrete. To Simplify the optimization procedure, the final optimum design of conical shell is obtained by combining the result of each element. The results are presented and discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.119-126
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• 1999

In this paper, The program of design technique of Influence surface is presented for analysis of moving(live) load of long-span bridges such as suspension bridges. This program is verified by comparing with various numerical examples. The proposed program is calculated the design conditions for the initial equilibrium state of suspension bridges, hence it can be used to analysis of various 3-dimensional frame structure with cable system.

• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.379-384
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• 2003

A turbo blower directly driven by a variable-speed BLDC motor was designed and tested to investigate performance characteristics. Computational analysis and performance tests validated the design method for the present turbo blower. Experimental measurements showed that the blower has an enough stability margin. This paper gives an outline of design, computational flow analysis and performance test for aerodynamic performance of the blower

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.327-332
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• 2007

An engineering design problem involving Multi-Disciplinary Analysis(MDA) generally requires a large amounts of CPU time for the entire design process, and therefore Multiple Processing System (MPS) are essential to reduce the completion time. However, when applying conventional parallel processing techniques, all of the CAE S/W required for the MDA should be installed on all the servers making up NIPS because of characteristic of MDA and it would be a great expense in CAE S/W licenses. To solve this problem, we propose a Weight-based Multiqueue Load Balancing algorithm for a heterogeneous MPS where performance of servers and CAE S/W installed on each server are different of each other. To validate the performance, a computational experiments comparing the First Come First Serve algorithm and our proposed algorithm was accomplished.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.704-711
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• 2005

Recently Life Cycle Cost Analysis for civil infrastructures such as pavements, bridges, and dams has been emphasized However, so far, there are few systems available for life cycle cost analysis of bridges at design stage. Therefore, the objective of this paper is to develop a user-friendly life-cycle cost analysis system for LCC-effective optimal design decision making at design stage. The program is based on the proposed LCC model, formulation, analysis modules and systematic procedure that suit Korean construction conditions. It is expected that the developed system can be effectively utilized for more LCC-effective design of bridges. It is applied to an actual bridge design project in order to demonstrate its effectiveness and applicability.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.10a
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• pp.57-62
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• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.