• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.303-304
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• 2023

확률론적 위험성 평가는 하중, 재료특성 등과 같은 불확실성 인자를 고려하여 구조물의 안전성을 평가하는 기법이지만 모든 불확실성을 고려하는 것은 현실적으로 불가능하다. 또한 원전 격납건물은 콘크리트, 철근, 라이너, 텐던이 복잡하게 결합되어 있다. 따라서 전역민감도 분석을 통해 격납건물의 불확실성 인자 검토하고 선정하는 작업은 필요하다. 따라서 본 연구는 대리모델을 기반으로 축소규모 원전 격납건물의 전역 민감도 분석을 수행하고 격납건물의 주요 영향인자를 분석하고자 한다. 유한요소 해석 모델을 기반으로 대리모델의 학습데이터를 생성하였으며 구축된 대리모델의 성능지표를 분석하였을 때 높은 회귀성능을 갖는 것으로 판단된다. 대리모델을 기반으로 전역 민감도 분석을 수행한 결과 콘크리트의 인장균열이 발생하는 내압수준에서 민감도 지수는 콘크리트의 압축강도가 높지만, 전체적인 내압 구간에서 민감도 지수는 텐던의 탄성계수 및 항복강도가 높은 것으로 나타났다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.5
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• pp.483-488
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• 2016

Plug-In Digital Framework is a system response analysis tool that is employed when system components are composed of black-box modules. Generally, the dynamic characteristics of joints between the system components significantly affect system responses, and they lead to displacement- and frequency-dependent stiffness and loss factor. Thus, the sensitivity of each joint parameters should be estimated from a global perspective. In this study, we introduce a global sensitivity analysis procedure under the Plug-In Digital Framework. To efficiently calculate the system responses, we introduce the frequency response function (FRF)-based substructuring method. Using the random balance designs (RBD), we generate the system responses and estimate the global first-order sensitivities for each joint stiffness. We apply the proposed global sensitivity analysis method to an interior noise problem of a passenger car, and we evaluate the efficiency of the global sensitivity analysis method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.397-406
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• 1999

A new solution procedure for approximate reanalysis, using the staged hybrid methods with substructuring, is proposed in this study. Displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. Stresses are evaluated from the displacements by matrix transformation. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.81-88
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• 2009

This paper alined at the development of a lateral drift control method that is able to quantitatively control the lateral drift of global node. For this, we applied an efficient partial reanalysis algorithm. By using this algorithm, we could recalculate the displacement and member force of the specific node without reanalyzing the entire structure when member stiffness changes partially. The theoretical concepts of the algorithm are so simple that it is not necessary to solve the complicate differential equation or to repeat the analysis of entire structure. The proposed method calculates the drift contribution of each member for the global displacement according to the variation of section sizes by using the algorithm. Then by changing the member sizes as the order of drift contribution, we could control the lateral drift of global node with a minimum quantity of materials. 20 story braced frame structure system is presented to illustrate the usefulness of proposed method. It is shown that the proposed method is very effective in lateral drift control and the results obtained by proposed method are consistent with those of commercial analysis program.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.210-218
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• 2003

MDO (multidisciplinary design optimization) technology has been proposed and applied to solve large and complex optimization problems where multiple disciplinaries are involved. In this research. an MDO problem is defined for automobile design which has crashworthiness analyses. Crash model which are consisted of airbag, belt integrated seat (BIS), energy absorbing steering system .and safety belt is selected as a practical example for MDO application to vehicle system. Through disciplinary analysis, vehicle system is decomposed into structure subspace and occupant subspace, and coupling variables are identified. Before subspace optimization, values of coupling variables at given design point must be determined with system analysis. The system analysis in MDO is very important in that the coupling between disciplines can be temporary disconnected through the system analysis. As a result of system analysis, subspace optimizations are independently conducted. However, in vehicle crash, system analysis methods such as Newton method and fixed-point iteration can not be applied to one. Therefore, new system analysis algorithm is developed to apply to crashworthiness. It is conducted for system analysis to determine values of coupling variables. MDO algorithm which is applied to vehicle crash is MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Then, structure and occupant subspaces are independently optimized by using MDOIS.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.976-983
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• 2023

Purpose: The dynamic behavior of a bridge structure under seismic loading depends on many uncertainties, such as the nature of the seismic waves and the material and geometric properties. However, not all uncertainties have a significant impact on the dynamic behavior of a bridge structure. Since probabilistic seismic performance evaluation considering even low-impact uncertainties is computationally expensive, the uncertainties should be identified by considering their impact on the dynamic behavior of the bridge. Therefore, in this study, a global sensitivity analysis was performed to identify the main parameters affecting the dynamic behavior of bridges with I-curved girders. Method: Considering the uncertainty of the earthquake and the material and geometric uncertainty of the curved bridge, a finite element analysis was performed, and a surrogate model was developed based on the analysis results. The surrogate model was evaluated using performance metrics such as coefficient of determination, and finally, a global sensitivity analysis based on the surrogate model was performed. Result: The uncertainty factors that have the greatest influence on the stress response of the I-curved girder under seismic loading are the peak ground acceleration (PGA), the height of the bridge (h), and the yield stress of the steel (fy). The main effect sensitivity indices of PGA, h, and fy were found to be 0.7096, 0.0839, and 0.0352, respectively, and the total sensitivity indices were found to be 0.9459, 0.1297, and 0.0678, respectively. Conclusion: The stress response of the I-shaped curved girder is dominated by the uncertainty of the input motions and is strongly influenced by the interaction effect between each uncertainty factor. Therefore, additional sensitivity analysis of the uncertainty of the input motions, such as the number of input motions and the intensity measure(IM), and a global sensitivity analysis considering the structural uncertainty, such as the number and curvature of the curved girders, are required.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.367-374
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• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.739-744
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• 2012

The genetic algorithm (GA) is regarded as one of the best ways for determining a global solution. Because it does not require calculating the design sensitivity differently from the ordinary gradient-based method, it is appropriate for the design problem in the ultra-high frequency range; the ordinary gradient-based method has difficulty in calculating the sensitivity in this range. This paper deals with nano-aperture grating topology optimization based on the GA and the ON/OFF method. The objective of this study is to maximize the transmittance in the measuring area. The simulation and optimization processes are carried out by using the commercial package COMSOL associated with Matlab programming. The final optimal design gives around 21% performance improvement, compared with the initial model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1513-1519
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• 2013

A genetic algorithm (GA) is an optimization technique based on natural evolution theory to find the global optimal solution. Unlike the gradient-based method, it can design nanoscale structures in the electric field because it does not require sensitivity calculation. This research intends to design a nanoaperture with an unprecedented shape by the topology optimization scheme based on the GA and ON/OFF method in the visible frequency range. This research mainly aims to maximize the transmission rate at a measuring area located 10nm under the exit plane and to minimize the electric distribution at other locations. The finite element analysis (FEA) and optimization process are performed by using the commercial package COMSOL combined with the Matlab programming. The final results of the optimized model are analyzed by a comparison of the electric field intensity and the spot size of near field with those of the initial model.