• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.439-448
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• 2000

A multi-level design synthesis (MLDA) algorithm for efficiently optimizing orthotropic steel deck bridges is proposed in the paper, because it is usually very difficult to optimize orthotropic steel deck bridges using a conventional single-level (CSL) algorithn since the bridges have a large number of members and show complex structural behaviors. In the proposed MLDS algorithms a coordination method is introduced to divide the bridges into main girders and orthotropic steel decks and decomposition method is also used to reduce the number of design variables of the decks for system level optimization. For efficient optimization of the bridges the MLDS algorithm incorporates the crucial approximation techliques such as constraints deletion and stress reanalysis. The constraint deletion technique for deflection is found to be very useful for the optimization problem of the bridges, since a deflection constraint is usually inactive in the design. Considering the complex system of the bridges, the proposed the efficient stress reanalysis technique may prove to be a very effective method, since it does not require expensive design sensitivity analyses. The applicability and robustness of the MLDS algorithm is demonstrated using various numerical examples and compared with other algorithm presently available so far.

• Structural Engineering and Mechanics
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• v.72 no.2
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• pp.181-190
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• 2019

Topology optimization of structures seeking the best distribution of mass in a design space to improve the structural performance and reduce the weight of a structure is one of the most comprehensive issues in the field of structural optimization. In addition to structures stiffness as the most common objective function, frequency optimization is of great importance in variety of applications too. In this paper, an efficient multi-objective Bi-directional Evolutionary Structural Optimization (BESO) method is developed for topology optimization of frequency and stiffness in continuum structures simultaneously. A software package including a Matlab code and Abaqus FE solver has been created for the numerical implementation of multi-objective BESO utilizing the weighted function method. At the same time, by considering the weaknesses of the optimized structure in single-objective optimizations for stiffness or frequency problems, slight modifications have been done on the numerical algorithm of developed multi-objective BESO in order to overcome challenges due to artificial localized modes, checker boarding and geometrical symmetry constraint during the progressive iterations of optimization. Numerical results show that the proposed Multiobjective BESO method is efficient and optimal solutions can be obtained for continuum structures based on an existent finite element model of the structures.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.262-265
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• 2005

A shape optimization of flow guide is accomplished to minimize the wear rate of die in three-dimensional flat-die extrusion processes. In order to achieve the balanced flow and the uniformed distribution of the effective strain during the extrusion, a multi-objective optimization is implemented. During the process of optimization formulation, the flow balance and the deviation of strain is considered as constrained conditions. The proposed approach is applied to an extrusion of H section. Through the optimization, it has been confirmed that the wear rate of die can be minimized satisfying the constraint.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2120-2133
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• 2013

In this paper, we address the problem of linear minimum mean-squared error (MMSE) transmitter design for the cognitive radio (CR) multi-user multiple-input single-output (MU-MISO) broadcasting channel (BC), where the cognitive users are subject to not only a sum power constraint, but also a interference power constraint. Evidently, this multi-constraint problem renders it difficult to solve. To overcome this difficulty, we firstly transform it into its equivalent formulation with a single constraint. Then by utilizing BC-MAC duality, the problem of BC transmitter design can be solved by focusing on a dual MAC problem, which is easier to deal with due to its convexity property. Finally we propose an efficient two-level iterative algorithm to search the optimal solution. Our simulation results are provided to corroborate the effectiveness of the proposed algorithm and show that this proposed CR MMSE-based scheme achieves a suboptimal sum-rate performance compared to the optimal DPC-based algorithm with less computational complexity.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2150-2158
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• 2002

A recent research and development has the requirement for the optimization to shorten design time of modified or new product model and to obtain more precise engineering solution. General optimization problem must consider many conflicted objective functions simultaneously. Multi-objective optimization treats the multiple objective functions and constraints with design change. But, real engineering problem doesn't describe accurate constraint and objective function owing to the limit of representation. Therefore this study applies variance analysis on the basis of structure analysis and DOE to the vertical roller mill fur portland cement and proposed statistical design model to evaluate the effect of structural modification with design change by performing practical multi-objective optimization considering mass, stress and deflection.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2339-2348
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• 1994

The objective of this paper is to develop a solution method for the differential-algebraic equation(DAE) derived from constrained muti-body dynamic systems. Mechanical systems are often modeled as bodies and joints. Differential equations of motion are formulated for bodies. Since the bodies are connected by joint, the differential variables must satisfy the kinematic constraint equations that come from the joints. Difficulties are arised due to drift of the differential variables off the constraint equations. An optimization method is adopted to correct the drift of the differential variables. To demonstrate the efficiency of the proposed method a slider-crank mechanism is analyzed dynamically. Identical results are obtained as these from the commercial program DADS. Dynamic analysis of a High Mobility Multi-purpose Wheeled. Vehicle(HMMWV) is carried out to show the practicalism of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.168-173
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• 2000

Design of experiments is utilized for exploring the design space and for building response surface models in order to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient means to rapidly model the trade-off among many conflicting goals. In robust design, it is important not only to achieve robust design objectives but also to maintain the robustness of design feasibility under the effects of variations, called uncertainties. However, the evaluation of feasibility robustness often needs a computationally intensive process. To reduce the computational burden associated with the probabilistic feasibility evaluation, the first-order Taylor series expansions are used to derive individual mean and variance of constraints. For robust design applications, these constraint response surface models are used efficiently and effectively to calculate variances of constraints due to uncertainties. Robust optimization of automotive seat is used to illustrate the approach.

• Journal of Ocean Engineering and Technology
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• v.26 no.6
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• pp.80-85
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• 2012

The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.