• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.82-96
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• 2019

A semi-submersible structure has been widely used for offshore drilling and production of oil and gas. The small water plane area makes the structure very sensitive to weight increase in terms of payload and stability. Therefore, it is necessary to lighten the substructure from the early design stage. This study aims at an optimization of hull structure based on a sophisticated yield and buckling strength in accordance with classification rules. An in-house strength assessment system is developed to automate the procedure such as a generation of buckling panels, a collection of required panel information, automatic buckling and yield check and so on. The developed system enables an automatic yield and buckling strength check of all panels composing the hull structure at each iteration of the optimization. Design variables are plate thickness and stiffener section profiles. In order to overcome the difficulty of large number of design variables and the computational burden of FE analysis, various methods are proposed. The steepest descent method is selected as the optimization algorithm for an efficient search. For a reduction of the number of design variables and a direct application to practical design, the stiffener section variable is determined by selecting one from a pre-defined standard library. Plate thickness is also discretized at 0.5t interval. The number of FE analysis is reduced by using equations to analytically estimating the stress changes in gradient calculation and line search steps. As an endeavor to robust optimization, the number of design variables to be simultaneously optimized is divided by grouping the scantling variables by the plane. A sequential optimization is performed group by group. As a verification example, a central column of a semi-submersible structure is optimized and compared with a conventional optimization of all design variables at once.

• Earthquakes and Structures
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• v.14 no.1
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• pp.1-10
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• 2018

Seismic retrofitting of existing buildings and design of earth-quake resistant buildings are important issues associated with earthquake-prone zones. Use of metallic-yielding dampers as an energy dissipation system is an acceptable method for controlling damages in structures and improving their seismic performance. In this study, the optimal distribution of dampers for reducing the seismic response of steel frames with multi-degrees freedom is presented utilizing the uniform distribution of deformations. This has been done in a way that, the final configuration of dampers in the frames lead to minimum weight while satisfying the performance criteria. It is shown that such a structure has an optimum seismic performance, in which the maximum structure capacity is used. Then the genetic algorithm which is an evolutionary optimization method is used for optimal arrangement of the steel dampers in the structure. In continuation for specifying the optimal accurate response, the local search algorithm based on the gradient concept has been selected. In this research the introduced optimization methods are used for optimal retrofitting in the moment-resisting frame with inelastic behavior and initial weakness in design. Ultimately the optimal configuration of dampers over the height of building specified and by comparing the results of the uniform deformation method with those of the genetic algorithm, the validity of the uniform deformation method in terms of accuracy, Time Speed Optimization and the simplicity of the theory have been proven.

• Radiation Oncology Journal
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• v.12 no.1
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• pp.109-115
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• 1994

The purpose of this paper is to develop an efficient method for the quick determination of multiple isocenters plans to provide optimal dose distribution in sterotactic radiosurgery. A Spherical dose model was developed through the use of fit to the exact dose data calculated in a 18cm diameter of spherical head phantom. It computes dose quickly for each spherical part and is useful to estimate dose distribution for multiple isocenters. An automatic computer search algorithm was developed using the relationship between the isocenter move and the change of dose shape, and adapted with a spherical dose model to determine isocenter separation and cellimator sizes quickly and automatically. A spheric81 dose model shows a comparable isodose distribution with exact dose data and permits rapid calculations of 3-D isodoses. the computer search can provide reasonable isocenter settings more quickly than trial and error types of plans, while producing steep dose gradient around target boundary. A spherical dose model can be used for the quick determination of the multiple isocenter plans with 3 computer automatic search. Our guideline is useful to determine the initial multiple isocenter plans.

• Korean Journal of Ecology and Environment
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• v.56 no.1
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• pp.36-44
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• 2023

Environmental DNA (eDNA) can exist in both intracellular and extracellular forms in natural ecosystems. When targeting harmful cyanobacteria, extracellular eDNA indicates the presence of traces of cyanobacteria, while intracellular eDNA indicates the potential for cyanobacteria to occur. However, identifying the "actual" potential for harmful cyanobacteria to occur is difficult using the existing sediment eDNA analysis method, which uses silica beads and cannot distinguish between these two forms of eDNA. This study analyzes the applicability of a density gradient centrifugation method (Ludox method) that can selectively analyze intracellular eDNA in sediment to overcome the limitations of conventional sediment eDNA analysis. PCR was used to amplify the extracted eDNA based on the two different methods, and the relative amount of gene amplification was compared using electrophoresis and Image J application. While the conventional bead beating method uses sediment as it is to extract eDNA, it is unknown whether the mic gene amplified from eDNA exists in the cyanobacterial cell or only outside of the cell. However, since the Ludox method concentrates the intracellular eDNA of the sediment through filtration and density gradient, only the mic gene present in the cyanobacteria cells could be amplified. Furthermore, the bead beating method can analyze up to 1 g of sediment at a time, whereas the Ludox method can analyze 5 g to 30 g at a time. This gram of sediments makes it possible to search for even a small amount of mic gene that cannot be searched by conventional bead beating method. In this study, the Ludox method secured sufficient intracellular gene concentration and clearly distinguished intracellular and extracellular eDNA, enabling more accurate and detailed potential analysis. By using the Ludox method for environmental RNA expression and next-generation sequencing (NGS) of harmful cyanobacteria in the sediment, it will be possible to analyze the potential more realistically.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1192-1200
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.185-191
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• 2008

Optimal damping layout of the constrained viscoelastic damping layer on beam is identified with temperatures by using a gradient-based numerical search algorithm. An optimal design problem is defined in order to determine the constrained damping layer configuration. A finite element formulation is introduced to model the constrained layer damping beam. The four-parameter fractional derivative model and the Arrhenius shift factor are used to describe dynamic characteristics of viscoelastic material with respect to frequency and temperature. Frequency-dependent complex-valued eigenvalue problems are solved by using a simple re-substitution algorithm in order to obtain the loss factor of each mode and responses of the structure. The results of the numerical example show that the proposed method can reduce frequency responses of beam at peaks only by reconfiguring the layout of constrained damping layer within a limited weight constraint.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1235-1242
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.377-382
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• 2007

This paper proposes a training algorithm for global optimization of the parameters of radial basis function networks. Since conventional training algorithms usually perform only local optimization, the performance of the network is limited and the final network significantly depends on the initial network parameters. The proposed hybrid simulated annealing algorithm performs global optimization of the network parameters by combining global search capability of simulated annealing and local optimization capability of gradient-based algorithms. Via experiments for function approximation problems, we demonstrate that the proposed algorithm can find networks showing better training and test performance and reduce effects of the initial network parameters on the final results.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.605-618
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• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.411-418
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• 2020

In this paper, approximation and optimization methods are proposed for the structural performance of the composite fan blade. Using these methods, we perform the optimal design of the stacking sequence to maximize stiffnesses without changing the mass and the geometric shape of the composite fan blade. In this study, the lamination parameters are introduced to reduce the design variables and space. From the characteristics of lamination parameters, we generate response surface model having a high fitness value. Considering the requirements of the optimal stacking sequence, the multi-objective optimization problem is formulated. We apply the two-step optimization method that combines gradient-based method and genetic algorithm for efficient search of an optimal solution. Finally, the finite element analysis results of the initial and the optimized model are compared to validate the approximation and optimization methods based on the lamination parameters.