• Structural Engineering and Mechanics
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• 제55권5호
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• pp.953-964
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• 2015

A model has been proposed that can predict the ultimate torsional strength of single-box multi-cell reinforced concrete box girder under combined loading of bending, shear and torsion. Compared with the single-cell box girder, this model takes the influence of inner webs on the distribution of shear flow into account. According to the softening truss theory and thin walled tube theory, a failure criterion is presented and a ultimate torsional strength calculating procedure is established for single-box multi-cell reinforced concrete box girder under combined actions, which considers the effect of tensile stress among the concrete cracks, Mohr stress compatibility and the softened constitutive law of concrete. In this paper the computer program is also compiled to speed up the calculation. The model has been validated by comparing the predicted and experimental members loaded under torsion combined with different ratios of bending and shear. The theoretical torsional strength was in good agreement with the experimental results.

• Computers and Concrete
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• 제33권2호
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• pp.137-145
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• 2024

The technique of experimentally determining concrete's compressive strength for a given mix design is time-consuming and difficult. The goal of the current work is to propose a best working predictive model based on different machine learning algorithms such as Gradient Boosting Machine (GBM), Stacked Ensemble (SE), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), and Deep Learning (DL) that can forecast the compressive strength of ternary geopolymer concrete mix without carrying out any experimental procedure. A geopolymer mix uses supplementary cementitious materials obtained as industrial by-products instead of cement. The input variables used for assessing the best machine learning algorithm not only include individual ingredient quantities, but molarity of the alkali activator and age of testing as well. Myriad statistical parameters used to measure the effectiveness of the models in forecasting the compressive strength of ternary geopolymer concrete mix, it has been found that GBM performs better than all other algorithms. A sensitivity analysis carried out towards the end of the study suggests that GBM model predicts results close to the experimental conditions with an accuracy between 95.6 % to 98.2 % for testing and training datasets.

• Steel and Composite Structures
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• 제10권1호
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• pp.45-67
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• 2010

Composite steel-concrete structures are employed extensively in modern high rise buildings and bridges. This concept has achieved wide spread acceptance because it guarantees economic benefits attributable to reduced construction time and large improvements in stiffness. Even though the combination of steel and concrete enhances the strength and stiffness of composite beams, the time-dependent behaviour of concrete may weaken the strength of the shear connection. When the concrete loses its strength, it will transfer its stresses to the structural steel through the shear studs. This behaviour will reduce the strength of the composite member. This paper presents the development of an accurate finite element model using ABAQUS to study the behaviour of shear connectors in push tests incorporating the time-dependent behaviour of concrete. The structure is modelled using three-dimensional solid elements for the structural steel beam, shear connectors, concrete slab and profiled steel sheeting. Adequate care is taken in the modelling of the concrete behaviour when creep is taken into account owing to the change in the elastic modulus with respect to time. The finite element analyses indicated that the slip ductility, the strength and the stiffness of the composite member were all reduced with respect to time. The results of this paper will prove useful in the modelling of the overall composite beam behaviour. Further experiments to validate the models presented herein will be conducted and reported at a later stage.

• 한국구조물진단유지관리공학회 논문집
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• 제20권6호
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• pp.91-97
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• 2016

초고강도 콘크리트를 이용한 부재의 내화 성능을 검토하기 위해서는 실제부재 단위의 시험에 의한 평가가 요구되고 있다. 그러나 실제부재 실험을 하기 위해서는 재하 능력이 큰 시험 장비가 필요하기 때문에, 재료 모델을 이용한 해석적 연구를 통해 내화 성능을 평가하고 있다. 본 연구에서는 80, 130 및 180 MPa의 초고강도 콘크리트를 대상으로 고온 가열시의 변형 특성을 실험적으로 평가하고 초고강도 콘크리트에 대한 기존 변형 모델의 적용을 검토했다. 그 후, 최소 제곱법에 의해 실험 값과 기존의 변형 모델을 적용한 계산 값의 누적 오차가 가장 작은 상수 값을 도출하고 초고강도 콘크리트에 적용 할 수 있는 변형 모델을 제시했다.

• 한국방재학회 논문집
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• 제11권2호
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• pp.45-52
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• 2011

고강도 콘크리트의 폭렬현상을 억제하여 내화 성능을 개선하기 위한 방법으로 고온에서 수증기가 콘크리트 표면으로 이동할 수 있도록 경로를 제공하여 주는 섬유를 혼입하는 방안이 있다. 본 연구에서는 섬유혼입 고강도 콘크리트 기둥에 대한 재하 내화 실험을 수행하였고, 내부 철근의 온도분포 예측을 위한 열전달 모델과 고온에서 콘크리트 기둥의 역학적 거동에 대한 재료모델을 제시하였다. 화재 시 콘크리트 내부의 물리적인 현상과 콘크리트의 열적 특성을 고려하여 선행 연구의 재료모델을 수정하였다. 수정한 모델을 이용한 섬유혼입 고강도 콘크리트의 유한요소 해석을 실행하였고, 재하 내화실험과의 비교를 통하여 재료모델을 제안하였다.

• Computers and Concrete
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• 제20권3호
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• pp.329-338
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• 2017

A new simple and practical strut-and-tie model (STM) for predicting the shear strength of RC pile caps is proposed in this paper. Two approaches are adopted to take into account the concrete softening effect. In the first approach, a concrete efficiency factor based on compression field theory is employed to determine the effective strength of a concrete strut, assumed to control the shear strength of the whole member. The second adopted Kupfer and Gerstle's biaxial failure criterion of concrete to derive the simple nominal shear strength of pile caps containing the interaction between strut and tie capacity. The validation of these two methods is investigated using 110 RC pile cap test results and other STMs available in the literature. It was found that the failure criterion approach appears to provide more accurate and consistent predictions, and hence is chosen to be the proposed STM. Finally, the predictions of the proposed STM are also compared with those obtained by using seven other STMs from codes of practice and the literature, and were found to give better accuracy and consistency.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2008년도 추계 학술논문 발표대회
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• pp.93-96
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• 2008

This research performed strength improvement analysis after evaluating strength characteristics by estimated temperatures to evaluate the real time strength performance of 50 to 80 MPa high performance concrete equipped with heat resistance, and the results are as follows. The lesser W/B and the lesser target slump flow value difference, compression strength was shown to increase, and the more curing temperature becomes, the strength increased accordingly. According to the correlation review result of strength improvement analysis by estimated temperature change performed using logistic analysis model, the compression strength value predicted with logistic curve expression and the compression strength value measured in experiment were shown to have similar correlation, and the strength improvement analysis value by logistic model was shown to be estimated good when W/B is high.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 봄 학술발표회 논문집
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• pp.847-852
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• 2000

This paper presents an evaluation of the behavior and strength of two pre-tensioned concrete deep beams tested to failure with using the nonlinear strut-tie model approach. In the approach, the effective prestressing forces represented be equivalent external loads are gradually introduced along its transfer length in the nearest strut-tie model joints, the friction at the interface of main diagonal shear cracks is modeled by diagonal struts along the direction of the cracks in strut tie-model, and additional positioning of concrete ties a the place of steel ties is incorporated. Through the analysis of pre-tensioned concrete deep beams, the nonlinear strut-tie model approach proved to present effective solutions for prediction the essential aspects of the behavior and strength of pre-tensioned concrete deep beams.

• 콘크리트학회지
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• 제5권4호
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• pp.179-187
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• 1993

본 연구에서는 콘크리트의 강도수준에 따른 피로실험을 수행하여 고강도 콘크리트의 피로거동 특성을 분석하였다. 실험변수는 4종류의 강도수준(26 MPa, 54 MPa, 82 MPa, 103 MPa)과 4종류의 최고 응력수준(75%, 80%, 85%, 95%)이며 실험에 사용된 공시체는 ${\phi}100{\times}200mm$의 원통형 공시체로서 총 160개가 제작되었다. 실험결과, 강도수준이 증가함에 따라 피로강도가 감소하였고 강도수준의 영향을 고려한 S-N-f'c 관계식을 제안하였다. 또한 강도수준의 영향 이외에도 변형도율 효과를 도입하여 피로실험과 압축실험에서 발생하는 하중재하율의 차이를 보정하였다. 한편, 피로 비탄성변형도는 강도수준이 증가함에 따라 감소하였으나 반복횟수에 따른 변형도 증가율은 강도수준이 높을수록 큰 것으로 나타났다.

• Advances in Computational Design
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• 제3권3호
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• pp.289-302
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• 2018

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.