• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.248-251
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• 2006

This paper provides the basic theory and numerical results of shell design optimization considering the appearance of close natural frequencies in optimization process. In this study the fundamental natural frequency to be maximized is considered as the objective function and the initial volume of structures is used as the constraint function. In addition, the constraints related to natural frequency is also adopted to avoid the natural frequency closeness phenomenon during the optimization iteration. The Coon's patch is used to represent the shape and thickness distribution of shells. A degenerated shell finite element is adopted to calculate the fundamental natural frequency of the shells. The SQP available in the optimizer DoT is used to search optimum solution. From numerical results, the introduction of the frequency constraint into shell design optimization can deeply affect on the final optimum shape of shells although it is likely to be used to avoid the frequency closeness phenomenon.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2108-2116
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• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.694-699
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• 2007

The spacer grid set is a part of a nuclear fuel assembly. The set has a spring and the spring supports the fuel rods safely. Although material nonlinearity is involved in the deformation of the spring,nonlinearity has not been considered in design of the spring. Recently a nonlinear response structural optimization method has been developed using equivalent loads. It is called nonlinear response optimization equivalent loads (NROEL). In NROEL, the external loads are teansformed to the equivalent loads (EL) for linear static analysis and linear response optimization is carried out based on the EL in a cyclic manner until the convergence criteria are satisfied. EL is the load set which generates the same response no EL. The objective function is defined by minimizing the maximum stress in the spring while is limited and the support force of the spring is larger than a certain value. The results are verified by nonlinear. ABAQUS is used for nonlinear response analysis and GENESIS is employed for linear response optimization.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4181-4194
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• 2022

Main steam safety valves are commonly used in nuclear power plants to provide final protections from overpressure events. Blowdown and dynamic stability are two critical characteristics of safety valves. However, due to the parameter sensitivity and multi-parameter features of safety valves, using traditional method to design and/or optimize them is generally difficult and/or inefficient. To overcome these problems, a surrogate model-based valve design optimization is carried out in this study, of particular interest are methods of valve surrogate modeling, valve parameters global sensitivity analysis and valve performance optimization. To construct the surrogate model, Design of Experiments (DoE) and Computational Fluid Dynamics (CFD) simulations of the safety valve were performed successively, thereby an ensemble surrogate model (E-AHF) was built for valve blowdown and stability predictions. With the developed E-AHF model, global sensitivity analysis (GSA) on the valve parameters was performed, thereby five primary parameters that affect valve performance were identified. Finally, the k-sigma method is used to conduct the robust optimization on the valve. After optimization, the valve remains stable, the minimum blowdown of the safety valve is reduced greatly from 13.30% to 2.70%, and the corresponding variance is reduced from 1.04 to 0.65 as well, confirming the feasibility and effectiveness of the optimization method proposed in this paper.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.8
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• pp.635-640
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• 2006

An optimizer has been applied for the optimal design of pipe diameters in the pipe flow network problems. Pipe network flow analysis, which is developed separately, is performed within the interface for the optimization algorithm. A pipe network is chosen for the test, and optimizer GenOpt is applied with Holder-Mead-O'Niell's simplex algorithm after solving the network flow problem by the Newton-Raphson method. As a result, optimally do-signed pipe diameters are successfully obtained which minimize the total design cost. Design cost of pipe flow network can be considered as the sum of pipe installation cost and pump operation cost. In this study, a practical and efficient solution method for the pipe network optimization is presented. Test system is solved for the demonstration of the present optimization technique.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1022-1027
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• 2004

In this study, the shape of plate-fin type heat sink is numerically optimized to acquire the minimum pressure drop under the required temperature rise. To do this, a new sequential approximate optimization (SAO) is proposed and it is integrated with the computational fluid dynamics (CFD). In thermal/fluid systems for constrained nonlinear optimization problems, three fundamental difficulties such as high cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are confronted. To overcome these problems, the progressive quadratic response surface method (PQRSM), which is one of the sequential approximate optimization algorithms, is proposed and the heat sink is optimize by means of the PQRSM.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2115-2123
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• 2006

The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.10
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• pp.1597-1604
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• 2001

Alternative computational scheme is presented fur reliability based optimal design using a modified advanced first order second moment (AFOSH) method. Both design variables and design parameters are considered as random variables about their nominal values. Each probability constraint is transformed into a sub -optimization problem and then is resolved with the modified Hasofer- Lind-Rackwitz-Fiessler (HL-RF) method for computational efficiency and convergence. A method of design sensitivity analysis for probability constraint is presented and tested through simple examples. The suggested method is examined by solving several examples and the results are compared with those of other methods.

• Korean Management Science Review
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• v.26 no.1
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• pp.65-76
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• 2009

The undirected Steiner tree problem in graphs is known to be NP-hard. The objective of this problem is to find a shortest tree containing a subset of nodes, called terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step. graph reduction rules eliminate useless nodes and edges which do not contribute to make an optimal solution. In the second step, a max-min ant colony optimization combined with Prim's algorithm is developed to solve the reduced problem. The proposed algorithm is tested in the sets of standard test problems. The results show that the algorithm efficiently presents very correct solutions to the benchmark problems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.938-941
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• 2006

We present a new design method of one-dimensional multi-layered acoustic foams for transmission loss maximization by topology optimization. Multi-layered acoustic foam sequences consisting of acoustic air layers and poroelastic material layers are designed for target frequency values. For successful topology optimization design of multi-layered acoustic foams, the material interpolation concept of topology optimization is adopted. In doing so, an acoustic air layer is modeled as a limiting poroelastic material layer; acoustic air and poroelastic material are handled by a single set of governing equations based on Biot's theory. For efficient analysis of a specific multi-layered foam appearing during optimization, we do not solve the differential equations directly, but we use an efficient transfer matrix approach which can be derived from Biot's theory. Through some numerical case studies, the proposed design method for finding optimal multi-layer sequencing is validated.