• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.270-287
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• 2015

According to the increase of the operating cost and material cost of a ship due to the change of international oil price, a demand for the lightening of the ship weight is being made from various parties such as shipping companies, ship owners, and shipyards. To satisfy such demand, many studies for a light ship are being made. As one of them, an optimal design method of an existing hull structure, that is, a method for lightening the ship weight based on the optimization technique was proposed in this study. For this, we selected a hatch cover of a bulk carrier as an optimization target and formulated an optimization problem in order to determine optimal principal dimensions of the hatch cover for lightening the bulk carrier. Some dimensions representing the shape of the hatch cover were selected as design variables and some design considerations related to the maximum stress, maximum deflection, and geometry of the hatch cover were selected as constraints. In addition, the minimization of the weight of the hatch cover was selected as an objective function. To solve this optimization problem, we developed an optimization program based on the Sequential Quadratic Programming (SQP) using C++ programming language. To evaluate the applicability of the developed program, it was applied to a problem for finding optimal principal dimensions of the hatch cover of a deadweight 180,000 ton bulk carrier. The result shows that the developed program can decrease the hatch cover's weight by about 8.5%. Thus, this study will be able to contribute to make energy saving and environment-friendly ship in shipyard.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.2
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• pp.178-182
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• 2011

Generally in order to reduce the steel weight of stiffened plate, stiffener spaces tend to be narrow and the plate gets thin. However, it will involve more fabrication cost because it can lead to the increase of welding length and the number of structural members. In the yard, the design which is able to reduce the total fabrication cost is needed, although it requires more steel weight. The purpose of this study is to find optimum stiffener spaces to minimize the fabrication cost for the cargo tank of LPG Carriers. Global optimization methods such as ES(Evolution Strategy) and GA(Genetic Algorithm) are introduced to find a global optimum solution and the sum of steel material cost and labor cost is selected as main objective function. Convergence degree of both methods in according to the size of searching population is examined and an efficient size is investigated. In order to verify the necessity of the optimum design based on the cost, minimum weight design and minimum cost design are carried out.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.211-232
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• 2013

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

• International Journal of Fluid Machinery and Systems
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• v.2 no.2
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• pp.179-188
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• 2009

Recent development of high speed computers and use of optimization techniques have given a big momentum of turbomachinery design replacing expensive experimental cost as well as trial and error approaches. The surrogate based optimization techniques being used for aerodynamic turbomachinery designs coupled with Reynolds-averaged Navier-Stokes equations analysis involve single- and multi-objective optimization methods. The objectives commonly tried to improve were adiabatic efficiency, pressure ratio, weight etc. Presently coupling the fluid flow and structural analysis is being tried to find better design in terms of weight, flutter and vibration, and turbine life. The present article reviews the surrogate based optimization techniques used recently in turbomachinery shape optimizations.

• Journal of Ocean Engineering and Technology
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• v.23 no.3
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• pp.1-5
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• 2009

It is necessary to develop an efficient optimization technique to optimize engineering structures that have given design spaces, discrete design values, and several design goals. In this study, an optimum algorithm based on the genetic algorithm was applied to the multi-object problem to obtain an optimum solution that simultaneously minimizes the structural weight and construction cost of panel blocks in ship structures. The cost model was used in this study, which includes the cost of adjusting the weld-induced deformation and applying the deformation control methods, in addition to the cost of the material and the welding cost usually included in the normal cost model. By using the proposed cost model, more realistic optimum design results can be expected.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.245-253
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• 1998

Recently, the importance of multi-objective optimization techniques and stochastic search methods is increasing. The stochastic search methods have the concepts of the survival of the fittest and natural selection such as genetic algorithms(GA), simulated annealing(SA) and evolution strategies (ES). As many accidents of oil tankers cause marine pollution, oil tankers of double hull or mid deck structure are being built to minimize the marine pollution. For the improvement of oil tanker design technique, an efficient optimization technique is proposed in this study. Multi-objective optimization problem of weight and cost of double hull and mid deck tanker is formulated. Discrete design variables are used considering real manufacturing, and the concept of relative production cost is also introduced. The ES method is used as an optimization technique, and the ES algorithm was developed to generate a more efficient Pareto optimal set.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.13-20
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• 2022

Aircraft weight is an important factor affecting performance and fuel efficiency. In the conceptual design stage of the aircraft, the process of balancing cost and weight is performed using empirical formulas such as fuel consumption cost per weight in estimating element weight. In addition, when an airline operates an aircraft, it promotes fuel efficiency improvement, fuel saving and carbon reduction through weight management activities. The relationship between changes in aircraft weight and changes in fuel consumption is called the cost of weight, and the cost of weight is used to evaluate the effect of adding or reducing weight to an aircraft on fuel consumption. In this study, the problems of the existing cost of weight calculation method are identified, and a new cost of weight calculation method is introduced to solve the problem. Using Breguet's Range Formula and actual flight data of the A350-900 aircraft, two weight costs are calculated based on take-off weight and landing weight. In conclusion, it was suggested that it is reasonable to use the cost of weight based on the take-off weight and the landing weight for other purposes. In particular, the cost of weight based on the landing weight can be used as an empirical formula for estimating element weight and optimizing cost and weight in the conceptual design stage of similar aircraft.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2162-2171
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• 1993

Geneal Structure optimization is utilized to minimize the weight of structures while satisfying constraints imposed on stress, displacements and natural frequencies, etc. Sandwich structures consist of inside core and outside face sheets. The selected sandwich structures are isotropic sandwich beams and isotropic sandwich plate. The face sheets are treated as membrane and assumed to carry only tensions, while the core is assumed to carry only transverse shear. The characteristic of the varying area are considered by adding the projected component of the tension to the transverse shear. The bending theory and energy method are adopted for analyzing sandwich beams and plates, respectively. In the optimization process, the cost function is the weight of a structure, and a deflection and stress constraints are considered. Design variable are thickness and tapering coefficients which determine the shape of a structure. An existing optimization code is used for solving the formulated problems.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.174-185
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• 2002

The automotive industry faces many competitive challenges including weight and cost reduction to meet need for higher fuel economy. Tailored blanks offer the opportunity to decrease door weight, reduce manufacturing costs, and improve door stiffness. Optimization technology is applied to the inner panel of a door which is made by tailored blanks. The design of tailored blanks door starts from an existing door. At first, the hinge reinforcement and inner reinforcement are removed to use tailored blanks technology. The number of parts and the welding lines are determined from intuitions and the structural analysis results of the existing door. Size optimization is carried out to find thickness while the stiffness constraints are satisfied. The door hinge system is optimized using design of experiment approach. A commercial optimization software MSC/NASTRAN is utilized for the structural analysis and the optimization processes.

• Structural Engineering and Mechanics
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• v.45 no.1
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• pp.111-127
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• 2013

In this paper, a new version of gravitational search algorithm based on opposition-based learning (OBGSA) is introduced and applied for optimum design of reinforced concrete retaining walls. The new algorithm employs the opposition-based learning concept to generate initial population and updating agents' position during the optimization process. This algorithm is applied to minimize three objective functions include weight, cost and $CO_2$ emissions of retaining structure subjected to geotechnical and structural requirements. The optimization problem involves five geometric variables and three variables for reinforcement setups. The performance comparison of the new OBGSA and classical GSA algorithms on a suite of five well-known benchmark functions illustrate a faster convergence speed and better search ability of OBGSA for numerical optimization. In addition, the reliability and efficiency of the proposed algorithm for optimization of retaining structures are investigated by considering two design examples of retaining walls. The numerical experiments demonstrate that the new algorithm has high viability, accuracy and stability and significantly outperforms the original algorithm and some other methods in the literature.