• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.12
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• pp.693-699
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• 2013

This paper describes a method for size optimization of the major design variables for solar water heating systems at the stage of concept design. The widely used RETScreen simulation tool was used for optimization. Currently, the RETScreen tool itself does not provide a function for optimization of the design parameters. In this study, an optimizer was combined with the software. A comparative study was performed to evaluate the RETScreen-based approach with the case study of a solar heating system in an office building. The optimized results using the RETScreen model were compared to previously published results with the TRNSYS model. The objective function of the optimization is the life-cycle cost of the system. The optimized design results from the RETScreen model showed good agreement with the optimized TRNSYS results for the solar collector area and storage volume, but presented a slight difference for the collector slope angle in terms of the converged direction of the solutions. The energy cost, life-cycle cost, and thermal performance regarding collector efficiency, system efficiency, and solar fraction were compared as well, and the RETScreen model showed good agreement with the TRNSYS model for the conditions of the base case and optimized design.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.123-130
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• 2004

The automobile suspension system is composed of parts that affect performances of a vehicle such as ride quality, handling characteristics, straight performance and steering effort, etc. Moreover, by using the finite element analysis the cost for the initial design step can be decreased. In the design of a suspension system, usually system vibration and structural rigidity must be considered simultaneously to satisfy dynamic and static requirements simultaneously. In this paper, we consider the weight reduction and the increase of the first eigen-frequency of a suspension part, the upper control arm, especially using topology optimization and size optimization. Firstly, we obtain the initial design to maximize the first eigen-frequency using topology optimization. Then, we apply the multi-objective parameter optimization method to satisfy both the weight reduction and the increase of the first eigen-frequency. The design variables are varying during the optimization process for the multi-objective. Therefore, we can obtain the deterministic values of the design variables not only to satisfy the terms of variation limits but also to optimize the two design objectives at the same time. Finally, we have executed reliability based optimal design on the upper control arm using the Monte-Carlo method with importance sampling method for the optimal design result with 98％ reliability.

• Steel and Composite Structures
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• v.17 no.5
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• pp.705-719
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• 2014

Composite steel-concrete box girders are frequently used in bridge construction for their economic and structural advantages. An integrated metaheuristic based optimization procedure is proposed for discrete size optimization of straight multi-span steel box girders with the objective of minimizing the self-weight of girder. The metaheuristic algorithm of choice is the Cuckoo Search (CS) algorithm. The optimum design of a box girder is characterized by geometry, serviceability and ultimate limit states specified by the American Association of State Highway and Transportation Officials (AASHTO). Size optimization of a practical design example investigates the efficiency of this optimization approach and leads to around 15% of saving in material.

• Steel and Composite Structures
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• v.33 no.5
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• pp.747-753
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• 2019

Metaheuristic algorithm is used to solve the weight minimization problem of truss structures considering shape, and sizing design variables. The cross-sectional areas of the line element in trusses are the design variables for size optimization and the changeable joint coordinates are the shape optimization used in this study. The design of plane and spatial truss structures are optimized by metaheuristic technique named Teaching-Learning-Based Optimization (TLBO). Finite element analyses of structures and optimization process are carried out by the computer program visually developed by the authors coded in MATLAB. The four benchmark problems (trusses 2D ten-bar, 3D thirty-seven-bar, 3D seventy-two-bar and 2D two-hundred-bar) taken from literature are optimized and the optimal solution compared the results given by previous studies.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.515-525
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• 2000

The purpose of this paper was to develop size & shape optimization programming algorithm of plane trusses. The optimum techniques applied in this study were extended penalty method of Sequential Unconstrained Minimization Techniques(SUMT) and direct search method with multi-variables proposed by Hooke & Jeeves. Upper mentioned two methods were used iteratively at each level of size and shape optimization routines. The design variables of size optimization were circular steel tube(structural member) diameter and thickness, those of shape optimization were joint coordinates, and the objective function was represented as total weight of truss. During the optimum design, two level procedures of size and shape optimization were interacted iteratively until the final optimum values were attained. At the previous studies about shape optimization of truss, the member sectional areas and coordinates were applied as design variables. So that they could not apply the buckling effect of compression member. In this paper, actual sizes of member and nodal coordinates are used as design variables to consider the buckling effect of compression member properly.

• Composites Research
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• v.32 no.1
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• pp.29-36
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• 2019

The purpose of this paper is to suggest a lightweight design for the aluminum extrusion carbody structure of a double deck high-speed train using material substitution and size optimization method. In order to conduct material substitution, the topology optimization was used to determine the application parts of sandwich composites at the carbody structures. The results of analysis showed that sandwich composites could be applied at roof and 2nd underframe. The size optimization was used to determine thickness of the aluminum extruded and carbon/epoxy composite. The design variable, state constraint and objective function were formulated to solve the size optimization, and then, the feasible design was presented by these conditions. The results of the lightweight design showed that the weight of double deck high-speed train hybrid carbody could be reduced by 2.18(17.70%) tons.

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.795-821
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• 2012

The size and topology of geometrically nonlinear dome structures are optimized thereby minimizing both its entire weight & joint (node) displacements and maximizing load-carrying capacity. Design constraints are implemented from provisions of American Petroleum Institute specification (API RP2A-LRFD). In accordance with the proposed design constraints, the member responses computed by use of arc-length technique as a nonlinear structural analysis method are checked at each load increment. Thus, a penalization process utilized for inclusion of unfeasible designations to genetic search is correspondingly neglected. In order to solve this complex design optimization problem with multiple objective functions, Non-dominated Sorting Genetic Algorithm II (NSGA II) approach is employed as a multi-objective optimization tool. Furthermore, the flexibility of proposed optimization is enhanced thereby integrating an automatic dome generating tool. Thus, it is possible to generate three distinct sphere-shaped dome configurations with varying topologies. It is demonstrated that the inclusion of brace (diagonal) members into the geometrical configuration of dome structure provides a weight-saving dome designation with higher load-carrying capacity. The proposed optimization approach is recommended for the design optimization of geometrically nonlinear dome structures.

• Steel and Composite Structures
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• v.26 no.2
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• pp.163-170
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• 2018

The purpose of this paper is to present a new and efficient optimization algorithm called Jaya for optimum design of steel grillage structure. Constrained size optimization of this type of structure based on the LRFD-AISC is carried out with integer design variables by using cross-sectional area of W-shapes. The objective function of the problem is to find minimum weight of the grillage structure. The maximum stress ratio and the maximum displacement in the inner point of steel grillage structure are taken as the constraint for this optimization problem. To calculate the moment and shear force of the each member and calculate the joint displacement, the finite elements analysis is used. The developed computer program for the analysis and design of grillage structure and the optimization algorithm for Jaya are coded in MATLAB. The results obtained from this study are compared with the previous works for grillage structure. The results show that the Jaya algorithm presented in this study can be effectively used in the optimal design of grillage structures.