• Steel and Composite Structures
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• 제42권6호
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• pp.733-745
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• 2022

This study proposed a robust artificial intelligence (AI) model based on the social behaviour of the imperialist competitive algorithm (ICA) and artificial neural network (ANN) for modelling the deflection of reinforced concrete beams, abbreviated as ICA-ANN model. Accordingly, the ICA was used to adjust and optimize the parameters of an ANN model (i.e., weights and biases) aiming to improve the accuracy of the ANN model in modelling the deflection reinforced concrete beams. A total of 120 experimental datasets of reinforced concrete beams were employed for this aim. Therein, applied load, tensile reinforcement strength and the reinforcement percentage were used to simulate the deflection of reinforced concrete beams. Besides, five other AI models, such as ANN, SVM (support vector machine), GLMNET (lasso and elastic-net regularized generalized linear models), CART (classification and regression tree) and KNN (k-nearest neighbours), were also used for the comprehensive assessment of the proposed model (i.e., ICA-ANN). The comparison of the derived results with the experimental findings demonstrates that among the developed models the ICA-ANN model is that can approximate the reinforced concrete beams deflection in a more reliable and robust manner.

• Structural Engineering and Mechanics
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• 제67권2호
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• pp.155-163
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• 2018

The Early-age construction loading and changing properties of concrete, especially in the multi-story structures can affect the slab deflection, significantly. Based on previously conducted experiment on eight simply-supported one-way slabs this paper investigates the effect of concrete type, fiber type and content, loading value, cracking moment, ultimate moment and applied moment on the instantaneous deflection of Self-Compacting Concrete (SCC) slabs. Two distinct loading levels equal to 30% and 40% of the ultimate capacity of the slab section were applied on the slabs at the age of 14 days. A wide range of the existing models of the effective moment of inertia which are mainly developed for conventional concrete elements, were investigated. Comparison of the experimental deflection values with predictions of the existing models shows considerable differences between the recorded and estimated instantaneous deflection of SCC slabs. Calculated elastic deflection of slabs at the ages of 14 and 28 days were also compared with the experimental deflection of slabs. Based on sensitivity analysis of the effective parameters, a new model is proposed and verified to predict the effective moment of inertia in SCC slabs with and without fiber reinforcing under two different loading levels at the age of 14 days.

• Journal of Biosystems Engineering
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• 제18권3호
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• pp.262-269
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• 1993

Stress relaxation behaviors of the cucumber under bending moment were tested with UTM at three levels of loading rate and initial deflection ratio. Sample cucumber was selected from three cultivars of cucumber, Cheongjangmadi, Baekdadagi, and Gyeousalicheongjang, because these cultivars are the most popular grown cultivars in Korea. When the bending moment was applied to the cucumber sample, the effective span between simple supports was held a constant value of 116mm with consideration of the selected sample length. The objectives of this study were to develop the rheological models such as linear and nonlinear models of the stress relaxation for the cucumber samples, and to investigate the effects of loading rate and initial deflection ratio on the stress relaxation behavior of the cucumber. The results of this study may be summarized as follows : 1. Stress relaxation behavior of the cucumber could be well described by the generalized Maxwell model for each level of deflection ratio. But the stress relaxation behavior of the sample was found to be initial deflection ratio and time dependent, and it was represented the nonlinear viscoelastic model as a function of initial deflection ratio and time. 2. Stress relaxation behavior of the cucumber samples was very highly affected by the loading rate and the initial deflection ratio. The more loading rate and initial deflection ratio resulted in the more initial bending stress and after stress relaxation progressed more rapidly. 3. At the same test conditions, it was found that the stress relaxation rate of Cheongjangmadi was faster than that of other cultivars.

• Geomechanics and Engineering
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• 제38권4호
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• pp.409-420
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• 2024

In this research the hygro-thermo-mechanical loading and micromechanical model effects on bending behavior of functionally graded material plates resting on Winkler and Pasternak elastic foundations, the higher order shear deformation theory is used here. The material properties of the plate: young's modulus, thermal coefficient and moisture expansion coefficient are assumed to be graded in the thickness direction according to various micromechanical models starting with the Voigt's model which is commonly used in most functionally graded plates studies to the Reuss's, LRVE's and Mori-Tanaka's models. The principle of virtual displacement is used to determine the equilibrium equations and the a several numerical results are given to validate the precision of the present method for bending behavior of FGM plates subjected to hygro-thermo-mechanical loading resting on elastic foundations. Afterwards, a parametric study is conducted to determine the effect of different parameters on the deflection of the FGM plates like micromechanical models, type of loading and plate geometry. In the lights of the present research, it can be concluded that the present theory is accurate and simple in predicting the deflection behavior of functionally graded plates under hygro-thermo-mechanical effects and micromechanical models.

• Smart Structures and Systems
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• 제26권5호
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• 한국도로학회논문집
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• 제9권1호
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• pp.39-46
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• 2007

동일한 물성을 가지는 포장이라도 포장의 구조적인 형상에 따라 역해석 결과가 다르게 나타난다. 본 논문에서는, 구조적인 형상을 고정하고 동적 하중을 모사하는 3차원 유한요소모델을 만들어 얻어진 최대 처짐과 AREA의 분포를 통해서 물성을 추정하는 수정된 AREA 도표를 제안하였다. 제안된 도표를 이용하여 단일 무한 슬래브에 대한 민감도 분석 결과 노상의 깊이가 질어지면 처짐과 AREA가 증가하는 것으로 나타났고 4.0m이상에서는 큰 차이를 나타내지 않았다. 층별 물성과 노상 깊이가 같은 경우 단일 무한 슬래브 모델과 다중 유한 슬래브 모델을 비교하는 경우 다중 유한 슬래브 모델의 처짐과 AREA가 더 크게 나타났다.

• Smart Structures and Systems
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• 제33권5호
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• pp.333-347
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• 2024

There has been an increasing interest in the construction of smart buildings that can actively monitor and react to their surroundings. The capacity of these intelligent structures to precisely predict and respond to deflection is a crucial feature that guarantees both their structural soundness and efficiency. Conventional techniques for determining deflection often depend on intricate mathematical models and computational simulations, which may be time- and resource-consuming. Artificial intelligence (AI) algorithms have become a potent tool for anticipating and controlling deflection in intelligent structures in response to these difficulties. The term "deflection-aware smart structures" in this sense refers to constructions that have AI algorithms installed that continually monitor and analyses deflection data in order to proactively detect any problems and take appropriate action. These structures anticipate deflection across a range of operating circumstances and environmental factors by using cutting-edge AI approaches including deep learning, reinforcement learning, and neural networks. AI systems are able to predict real-time deflection with high accuracy by using data from embedded sensors and actuators. This capability enables the systems to identify intricate patterns and linkages. Intelligent buildings have the potential to self-correct in order to reduce deflection and maximize performance. In conclusion, the development of deflection-aware smart structures is a major stride forward for structural engineering and has enormous potential to enhance the performance, safety, and dependability of designed systems in a variety of industries.

• 콘크리트학회논문집
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• 제23권4호
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• pp.413-420
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• 2011

휨 보강근의 종류 및 조합, 섬유 혼입을 변수로 하는 고강도 콘크리트 보의 구조 실험 결과를 균열 모멘트, 극한 모멘트, 처짐 등에 대해 각종 설계기준 및 가이드라인, 여러 연구자들에 의한 예측식과 비교 검토하였다. 섬유를 혼입하지 않은 FRP 보강근 보강 보의 극한 모멘트 이론값은 실험값을 과소평가하였다. 강섬유가 혼입된 FRP 보강근보강보에 대한 ACI 544.4R, Campione의 모델은 섬유 보강 콘크리트의 증가된 극한 압축 변형률을 고려하지 않고 있어 극한 모멘트를 부정확하게 예측하였다. 섬유가 혼입되지 않은 부재에 대해 Bischoff의 처짐 모델은 섬유가 혼입되지 않은 부재들의 사용 하중 하에서의 처짐을 정확하게 예측한 반면, ACI 440 위원회 모델은 사용 하중 하에서의 처짐을 비보수적으로 예측하였다. 이질 보강근이 동시에 적용된 부재에 대해 Bischoff 모델과는 달리 ACI 440 위원회의 처짐 모델은 직접적인 적용이 불가능하기 때문에 ACI 440 위원회 식을 이용하여 이질 보강근이 동시에 적용된 부재의 처짐을 예측하는 방법을 제안하였다. 또한 철근과 FRP 보강근이 동시에 보강된 보에서 철근이 항복한 이후의 처짐을 예측할 수 있는 방법을 제안하였다.

• Structural Engineering and Mechanics
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• 제59권4호
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• pp.775-793
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• 2016

This paper presents a numerical method for estimating the curvature, deflection and moment capacity of FRP-reinforced concrete encased steel composite beams (FRP-RCS). A sectional analysis is first carried out to predict the moment-curvature relationship from which beam deflection and moment capacity are then calculated. Comparisons between theoretical and experimental results of tests conducted elsewhere show that the proposed numerical technique can accurately predict moment capacity and deflection of FRP-RCS composite beam. The numerical results also indicated that beam ductility and stiffness are improved when encased steel is added to FRP reinforced concrete beams. ACI, ISIS and Bischoff models for deflection prediction compared well at low load, however, significantly underestimated the experimental results for high load levels.

• 한국구조물진단유지관리공학회 논문집
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• 제18권2호
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• pp.47-53
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• 2014

이 연구에서는 중소지간 합성형 강거더교량에 대한 신뢰성 해석을 위해 강거더와 콘크리트슬래브의 강성을 토대로 처짐을 고려한 한계 함수를 구축하여 신뢰성해석을 수행하였다. 확률적 하중과 저항모델을 통해 처짐을 예측하기 위해 계산에 필요한 변수들을 확률변수로 고려하였다. 강재의 부식에 의한 단면의 감소, 그리고 콘크리트의 크리프는 합성형교의 처짐에 많은 영향을 미친다. 따라서 이 연구에서는 AASHTO LRFD 기준으로 설계된 교량에 대해 시간에 따른 변수를 고려하여 강재단면의 감소와 크리프의 영향을 통계적 모델에 반영하기 위해 몬테-카를로 시뮬레이션 기법을 이용하였으며, 처짐과 사용성을 고려하여 다양한 지간과 거더간격을 가진 교량에 신뢰성 해석을 수행하였다. 그 결과, 장지간 교량의 경우, 단지간 교량과 비교해 보았을 때 상대적으로 크리프와 강재단면감소의 처짐에 대한 영향이 작았으며, 이에 반해 단지간 거더 교량의 경우 크리프의 진행에 따라 처짐에 많은 영향을 미친다는 것을 알 수 있었다.