• 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 Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.104-108
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• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.99-107
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• 2007

We consider (worst-case) robust optimization versions of the Economic Order Quantity (EOQ) model with decreasing cost functions. Two variants of the EOQ model are discussed, in which the purchasing costs are decreasing power functions in either the order quantity or demand rate. We develop the corresponding worst-case robust optimization models of the two variants, where the parameters in the purchasing cost function of each model are uncertain but known to lie in an ellipsoid. For the robust EOQ model with the purchasing cost being a decreasing function of the demand rate, we derive the analytical optimal solution. For the robust EOQ model with the purchasing cost being a decreasing function of the order quantity, we prove that it is a convex optimization problem, and thus lends itself to efficient numerical algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1243-1252
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• 2005

A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.6
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• pp.114-121
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• 2010

This paper presents a design process of light-weighted fuel cell vehicle (FCV) frame to meet design target of natural frequency in early design stage. At first, using validated FE model for the current design, thickness optimization was carried out. Next. optimization process, comprised of beam model size optimization, shell model design and shell model thickness optimization, was investigated for two frame types. In addition, in order to ensure hydrogen tanks safety against rear impact load, structural collapse characteristics was estimated for the rear frame model finally produced from the previous optimization process and, with the target of equal collapse characteristics to the current design model, structural modification with small weight increase was studied through static structural collapse analyses. The same attempt was applied to the front side frame. The results explain that the proposed process enables to design light-weighted frames with high structural performance in early stage.

• 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 Mechanical Engineers B
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• v.31 no.8
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• pp.711-717
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• 2007

Shape optimization of a staggered herringbone groove micromixer using three-dimensional Navier-Stokes analysis has been carried using Kriging model. The analysis of the degree of mixing is performed by the calculation of spatial data statistics. The calculation of the variance of the mass fraction at various nodes on a plane in the channel is used to quantify mixing. A numerical optimization technique with Kriging model is applied to optimize the shape of the grooves on a single wall of the channel. Three design variables, namely, the ratio of groove width to groove pitch, the ratio of the groove depth to channel height ratio and the angle of the groove, are selected for optimization. A mixing index is used as the objective function. The results of the optimization show that the mixing is very sensitive to the shape of the groove which can be used in controlling mixing in microdevices.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.452-460
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• 2001

Most of researches of tolerance optimization have used a simple sum of tolerance-cost functions with several constraint equations as an optimization model. However, if there is a machining sequence with more than one processes to complete a part, and machining failure, i.e., out-of-tolerance occurs at one of the intermediate processes, the tolerance-cost of this process should be added by the machining cost of all the previous processes already completed on the part. In this study, an accumulated scrap cost model(ASCM) is proposed considering the scrapped machining cost, and applied to a simple assembly example. The result of tolerance optimization using ASCM is compared with that of using a traditional optimization model to confirm its effectiveness.

• Structural Engineering and Mechanics
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• v.70 no.5
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• pp.513-524
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• 2019

This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.173-183
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• 2018

This paper proposes a developed optimization model for steel frames with semi-rigid beam-to-column connections and fixed bases using teaching-learning-based optimization (TLBO) and genetic algorithm (GA) techniques. This method uses rotational deformations of frame members ends as an optimization variable to simultaneously obtain the optimum cross-sections and the most suitable beam-to-column connection type. The total cost of members plus connections cost of the frame are minimized. Frye and Morris (1975) polynomial model is used for modeling nonlinearity of semi-rigid connections, and the $P-{\Delta}$ effect and geometric nonlinearity are considered through a stepped analysis process. The stress and displacement constraints of AISC-LRFD (2016) specifications, along with size fitting constraints, are considered in the design procedure. The developed model is applied to three benchmark steel frames, and the results are compared with previous literature results. The comparisons show that developed model using both LTBO and GA achieves better results than previous approaches in the literature.