• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.7
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• pp.2347-2355
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• 1996

Purpose of the present study is to develop a computational design program for shape optimization, combining the numerical optimization technique with the flow analysis code. The present methodology is then validated in three cases of aerodynamic shape optimization. In the numerical optimization, a feasible direction optimization algorithm and shape functions are considered. In the flow analysis, the Navier-Stokes equations are discretized by a cell-centered finite volume method, and Roe's flux difference splitting TVD scheme and ADI method are used. The developed design code is applied to a transonic channel flow over a bump, and an external flow over a NACA0012 airfoil to minimize the wave drag induced by shock waves. Also a separated subsonic flow over a NACA0024 airfoil is considered to determine a maximum allowable thickness of the airfoil without separation.

• ETRI Journal
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• v.46 no.3
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• pp.367-378
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• 2024

We propose a number-theory-based quantized mathematical optimization scheme for various NP-hard and similar problems. Conventional global optimization schemes, such as simulated and quantum annealing, assume stochastic properties that require multiple attempts. Although our quantization-based optimization proposal also depends on stochastic features (i.e., the white-noise hypothesis), it provides a more reliable optimization performance. Our numerical analysis equates quantization-based optimization to quantum annealing, and its quantization property effectively provides global optimization by decreasing the measure of the level sets associated with the objective function. Consequently, the proposed combinatorial optimization method allows the removal of the acceptance probability used in conventional heuristic algorithms to provide a more effective optimization. Numerical experiments show that the proposed algorithm determines the global optimum in less operational time than conventional schemes.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.463-467
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• 2008

Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

• Elastomers and Composites
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• v.57 no.4
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• pp.147-156
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• 2022

In this study, we chose a flat die to optimize a general die geometry. The optimization was aimed at obtaining a uniform velocity distribution across the exit of the die. For the optimization, the input and output design parameters were randomly computed, and response surfaces were generated to obtain statistical data for the minimum and maximum sensitivities computed during optimization. Subsequently, object functions with constraints were numerically computed to obtain the minimum errors in the velocity difference (i.e., variable "Outp" in this study). Finally, we obtained the candidate optimized dataset. Note that the current numerical computations were simultaneously conducted for an entire extruder, i.e., screw plus die. The numerical outlet velocity distributions in the modified die geometry tended to be much more uniform than the conventional distributions in the current optimization processes for this specific flat die.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.905-908
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• 2009

In the management of groundwater in coastal areas, saltwater intrusion associated with extensive groundwater pumping, is an important problem. The groundwater optimization model is an advanced method to study the aquifer and decide the optimal pumping rates or optimal well locations. Cheng and Park gave the analytical solutions to the optimization problems basing on Strack's analytical solution. However, the analytical solutions have some limitations of the property of aquifer, boundary conditions, and so on. A simulation-optimization numerical method presented in this study can deal with non-homogenous aquifers and various complex boundary conditions. This simulation-optimization model includes the sharp interface solution which solves the same governing equation with Strack's analytical solution, therefore, the freshwater head and saltwater thickness should be in the same conditions, that can lead to the comparable results in optimal pumping rates and optimal well locations for both of the solutions. It is noticed that the analytical solutions can only be applied on the infinite domain aquifer, while it is impossible to get a numerical model with infinite domain. To compare the numerical model with the analytical solutions, calculation of the equivalent boundary flux was planted into the numerical model so that the numerical model can have the same conditions in steady state with analytical solutions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1230-1233
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• 1993

Numerical solution of inverse problem of Takagi-Sugeno fuzzy model is proposed. The method is located on the application of numerical optimization to the fuzzy model. Steepest descent method is used for the numerical optimization. We use the linear approximation of fuzzy model, called pseudo first order approximation, by fixing the membership value on the neighborhood of the corresponding input. It is introduced in order to reduce the difficulty of optimization process. The efficiency of this method is shown by a numerical experiment.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.10
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• pp.135-142
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• 2019

Ant colony optimization(ACO) technique is utilized in truss size optimization with frequency constraints. Total weight of truss to be minimized is considered as the objective function and multiple natural frequencies are adopted as constraints. The modified traveling salesman problem(TSP) is adopted and total length of the TSP tour is interpreted as the weight of the structure. The present ACO-based design optimization procedure uses discrete design variables and the penalty function is introduced to enforce design constraints during optimization process. Three numerical examples are carried out to verify the capability of ACO in truss optimization with frequency constraints. From numerical results, the present ACO is a very effective way of finding optimum design of truss structures in free vibration. Finally, we provide the present numerical results as future reference solutions.

• The KSFM Journal of Fluid Machinery
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• v.14 no.5
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• pp.63-68
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• 2011

This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

• Journal of Ocean Engineering and Technology
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• v.16 no.3
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• pp.28-33
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• 2002

Optimization of marine propellers of constant pitch is studied, with the help of the infinite dimensional optimization (Jang and Kinoshita, 2000a), which is based on the Hilbert space theory. As a numerical example, the MAU type propeller is considered and used as he initial guess for the optimization method. The numerical computations for an optimal marine propeller are performed for the constant pitch distribution. In addition, a new optimization is suggested with the constraint of constant pitch during optimization.