• Coupled systems mechanics
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• 제8권1호
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• pp.1-17
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• 2019

The present paper deals with delamination fracture analyses of the multilayered functionally graded non-linear elastic Symmetric Split Beam (SSB) configurations. The material is functionally graded in both width and height directions in each layer. It is assumed that the material properties are distributed non-symmetrically with respect to the centroidal axes of the beam cross-section. Sine laws are used to describe the continuous variation of the material properties in the cross-sections of the layers. The delamination fracture is analyzed in terms of the strain energy release rate by considering the balance of the energy. A comparison with the J-integral is performed for verification. The solution derived is used for parametric analyses of the delamination fracture behavior of the multilayered functionally graded SSB in order to evaluate the effects of the sine gradients of the three material properties in the width and height directions of the layers and the location of the crack along the beam width on the strain energy release rate. The solution obtained is valid for two-dimensional functionally graded non-linear elastic SSB configurations which are made of an arbitrary number of lengthwise vertical layers. A delamination crack is located arbitrary between layers. Thus, the two crack arms have different widths. Besides, the layers have individual widths and material properties.

• Structural Engineering and Mechanics
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• 제45권4호
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• pp.439-454
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• 2013

Hollow cylindrical tubes with a prismatic sandwich lining designed to replace the solid cross-sections are studied in this paper. The sections are divided by a number of revolving periodic unit cells and three topologies of unit cells (Square, Triangle and Kagome) are proposed. Some types of multiple-topology designed materials are also studied. The feasibility and accuracy of a homogenization method for obtaining the equivalent parameters are investigated. As the curved elements of a unit cell are represented by straight elements in the method and the ratios of the lengths of the curved elements to the lengths of the straight elements vary with the changing number of unit cells, some errors may be introduced. The frequencies of the first five modes and responses of the complete and equivalent models under an internal static pressure and an internal step pressure are compared for investigating the scope of applications of the method. The lower bounds and upper bounds of the number of Square, Triangular and Kagome cells in the sections are obtained. It is shown that treating the multiple-topology designed materials as a separate-layer structure is more accurate than treating the structure as a whole.

• 국제초고층학회논문집
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• 제9권3호
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• pp.221-233
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• 2020

Based on past experiences of natural disasters and fires in Japan, it is stipulated by law that fire-resistant buildings larger than a certain size should be unique in the world. Recent interest in global environmental issues has led to the active introduction of wooden buildings also in Japan, and it is expected that wooden buildings will become larger and higher in size. This paper introduces the background of the development of fire-resistant laminated timber with a "Self-Charring-Stop layer", the contents of this development including other related developments, and the application of these technologies. In addition, towards the realization of much larger and higher buildings in the future, the current problems and issues to be solved are set and the necessity of the future technological development is described. Finally, a conceptual model of wooden high-rise building is proposed, which will be able to be constructed in 2025 by the further technological development.

• 한국공간구조학회논문집
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• 제23권3호
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• 한국지반공학회논문집
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• 제22권11호
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• pp.37-45
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• 2006

1970년대 중반부터 bender elements를 이용하여 흙 공시체의 전단파 속도를 측정하는 기술이 발전되어 왔다. 얇은 피에조 세라믹판과 탄성 매질을 겹쳐서 만든 bender elements는 삼축입축시험장치의 저판(base)와 top cap에 설치하여 액츄에이터와 트랜스듀스로 각각 사용하여 공시체의 전단파 속도를 측정하고 있다. bender elements를 현장에 적용하는 예비 단계로, 최적의 벤더 제작과 기하학적 배치에 대한 연구를 실내 카올리나이트 토조에서 수행하였다. 이 예비시험에서 개발된 bender element를 사용하여 갯벌에서 크로스홀 방식과 인홀 방식으로 탄성파 시험을 수행하였다. 일련의 bender elements를 깊이 2m까지 삽입하여 현장시험의 적용성을 확인하였다. 추후 깊은 심도까지 삽입할 수 있는 맨드렐(mandrel)과 관입장치를 개발하여 연약지반의 탄성파 속도 측정 장치 개발을 완성하고자 한다.

• Steel and Composite Structures
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• 제51권4호
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• 대한조선학회논문집
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• 제49권5호
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• pp.410-415
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• 2012

An experimental study is carried out to investigate the near-wake characteristics of a NACA 0018 foil with a flat plate. Two-frame grey-level cross correlation PIV method is used to measure the local flow characteristic around a pitch damping foil to control the vertical motion of high speed crafts in a circulating water channel. The analysis also includes angles of attack 10 and 20 degrees respectively. Reynolds number $Re{\fallingdotseq}3.5{\times}10^4$ based on the chord length(C=100mm) of NACA0018 has been applied during the whole experiments. The distance between the foil and the flat plate is D/C=0.5, 1.0 and 1.5 respectively. The channel effect according as the distance between the foil and the flat plate has a close relation with the velocity distributions around the foil. In the wake of 20-degree of attack, the complex turbulent flow and a thick boundary layer are formed due to the processes of vortex generation and dissipation.

• 한국정밀공학회지
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• 제12권6호
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• pp.120-127
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• 1995

A nonlinear empirical state-space model of the Artificial Neural Network(ANN) has been developed. The nonlinear model structure incorporates characteristic, so as to enable identification of the transient response, as well as the steady-state response of a dynamic system. A hybrid feedfoward/feedback neural network, namely a Local Time Delayed Recurrent Multi-layer Perception(RMLP), is the model structure developed in this paper. RMLP is used to identify nonlinear dynamic system in an input/output sense. The feedfoward protion of the network architecture provides with the well-known curve fitting factor, while local recurrent and cross-talk connections provides the dynamics of the system. A dynamic learning algorithm is used to train the proposed network in a supervised manner. The derived dynamic learning algorithm exhibit a computationally desirable characteristic; both network sweep involved in the algorithm are performed forward, enhancing its parallel implementation. RMLP state-space and its associate learning algorithm is demonstrated through a simple examples. The simulation results are very encouraging.

• 대한조선학회논문집
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• 제49권5호
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• pp.440-446
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• 2012

A twisted cylinder has been newly designed by rotating the elliptic cross section along the spanwise direction in order to reduce the drag and vorticies in wake region. The flow around the twisted cylinder at a subcritical Reynolds number (Re) of 3000 is investigated to analyze the effect of twisted spiral pattern on the drag reduction and vortex suppression using large eddy simulation (LES). The instantaneous wake structures of the twisted cylinder are compared with those of a circular and a wavy cylinder at the same Re. The shear layer of the twisted cylinder covering the recirculation region is more elongated than that of the circular and the wavy cylinder. Successively, vortex shedding of the twisted cylinder is considerably suppressed, compared with those of the circular and the wavy cylinder. Consequently, the mean drag coefficient and the fluctuating lift of the twisted cylinder are less than those of the circular and the wavy cylinder.

• 전기학회논문지
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• 제67권1호
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.