• 한국구조물진단유지관리공학회 논문집
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• 제7권4호
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• pp.159-169
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• 2003

춤이 깊은 보 설계를 위한 현행 ACI 기준은 콘크리트 압축강도 40MPa이하의 실험결과를 바탕으로 한 반 경험적인 제안식으로서 40MPa이상 고강도콘크리트의 사용이 증가됨에 따라 현행 기준의 고강도 깊은 보에 대한 적용성 평가가 요구되고 있다. 고강도 깊은 보의 전단강도 예측을 위하여 본 연구에서는 콘크리트강도와 모멘트효과를 고려한 수정 연화 스트럿-타이 모델을 제시하였다. 제안모델 평가를 위하여 4개의 시험체를 제작하였으며, 콘크리트 압축강도 49~78MPa로 제작된 74개의 기존 실험 데이터를 적용하여 ACI 318-99 11.8기준, ACI 318-02 부록 A STM의 해석결과와 비교 평가하였다.

• Computers and Concrete
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• 제31권2호
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• pp.85-95
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• 2023

Natural pozzolans are used as additives in cement to develop more durable and high-performance concrete. Pozzolanic activity index (PAI) is important for assessing the performance of a pozzolan as a binding material and has an important effect on the compressive strength, permeability, and chemical durability of concrete mixtures. However, the determining of the 28 days (short term) and 90 days (long term) PAI of concrete mixtures is a time-consuming process. In this study, to reduce extensive experimental work, it is aimed to predict the short term and long term PAIs as a function of the chemical compositions of various natural pozzolans. For this purpose, the chemical compositions of various natural pozzolans from Central Anatolia were determined with X-ray fluorescence spectroscopy. The mortar samples were prepared with the natural pozzolans and then, the short term and the long term PAIs were calculated based on compressive strength method. The effect of the natural pozzolans' chemical compositions on the short term and the long term PAIs were evaluated and the PAIs were predicted by using multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) model. The prediction model results show that both reactive SiO₂ and SiO₂+Al₂O₃+Fe₂O₃ contents are the most effective parameters on PAI. According to the performance of prediction models determined with metrics such as root mean squared error (RMSE) and coefficient of correlation (R²), ANFIS models are more feasible than the multiple regression model in predicting the 28 days and 90 days pozzolanic activity. Estimation of PAIs based on the chemical component of natural pozzolana with high-performance prediction models is going to make an important contribution to material engineering applications in terms of selection of favorable natural pozzolana and saving time from tedious test processes.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 봄 학술발표회 논문집
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• pp.565-570
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• 2000

The objective of this paper is to analyse the high-strength concrete columns subjected to reversed cyclic and axial loads by using nonlinear analysis model and compare the experimental results with analysis. The analytical parameters are the compressive strength of concrete, spacing of lateral reinforcement and lateral reinforcement ratio. In this study, the proposed analytical model takes ito account the influence of confined concrete, tension stiffening and strain hardening of steel. The high-strength concrete columns are used to model fiber section element. The analysis results are shown comparatively good prediction on envelope curve, accumulative dissipated energy, deformability and so on.

• Computers and Concrete
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• 제19권6호
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• pp.631-639
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• 2017

This study experimentally investigated the flexural capacity of a concrete beam reinforced with a newly developed GFRP bar that overcomes the lower modulus of elasticity and bond strength compared to a steel bar. The GFRP bar was fabricated by thermosetting a braided pultrusion process to form the outer fiber ribs. The mechanical properties of the modulus of elasticity and bond strength were enhanced compared with those of commercial GFRP bars. In the four-point bending test results, all specimens failed according to the intended failure mode due to flexural design in compliance with ACI 440.1R-15. The effects of the reinforcement ratio and concrete compressive strength were investigated. Equations from the code were used to predict the deflection, and they overestimated the deflection compared with the experimental results. A modified model using two coefficients was developed to provide much better predictive ability, even when the effective moment of inertia was less than the theoretical $I_{cr}$. The deformability of the test beams satisfied the specified value of 4.0 in compliance with CSA S6-10. A modified effective moment of inertia with two correction factors was proposed and it could provide much better predictability in prediction even at the effective moment of inertia less than that of theoretical cracked moment of inertia.

• Computers and Concrete
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• 제26권6호
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• pp.467-482
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• 2020

This research focused on analyzing the post-fire behavior of high-performance concrete-filled steel tube (CFST) columns, with the concrete containing tire rubber and steel fibers, under axial compressive loading. The finite element (FE) modeling of such heated columns containing recycled aggregate is a branch of this field which has not received the proper attention of researchers. Better understanding the post-fire behavior of these columns by measuring their residual strength and deformation is critical for achieving the minimum repair level required for structures damaged in the fire. Therefore, to develop this model, 19 groups of confined and unconfined specimens with the variables including the volume ratio of steel fibers, tire rubber content, diameter-to-thickness (D/t) ratio of the steel tube, and exposure temperature were considered. The ABAQUS software was employed to model the tested specimens so that the accurate behavior of the FE-modeled specimens could be examined under test conditions. To achieve desirable results for the modeling of the specimens, in addition to the novel procedure described in this research, the modified versions of models presented by previous researchers were also utilized. After the completion of modeling, the load-axial strain and load-lateral strain relationships, ultimate strength, and failure mode of the modeled CFST specimens were evaluated against the test data, through which the satisfactory accuracy of this modeling procedure was established. Afterward, using a parametric study, the effect of factors such as the concrete core strength at different temperatures and the D/t ratio on the behavior of the CFST columns was explored. Finally, the compressive strength values obtained from the FE model were compared with the corresponding values predicted by various codes, the results of which indicated that most codes were conservative in terms of these predictions.

• Computers and Concrete
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• 제14권3호
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• pp.327-345
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• 2014

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

• 한국도로학회:학술대회논문집
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• 한국도로학회 2010년 추계학술대회 논문집
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• pp.99-107
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• 2010

A permanent deformation model was developed in this study based on the shear properties of asphalt mixtures such as cohesion and friction angle. Triaxial compressive strength (TCS) and repeated load permanent deformation (RLPD) tests on the three types of asphalt mixtures are performed at various loading and temperature conditions to correlate shear properties of asphalt mixtures to rutting performance. It is observed from the tests results that the ratio of shear stress to strength accurately identifies the mixture rutting performance. It could take care of not only mixture types but also load and temperature conditions dependences. Three different versions of the permanent deformation model based on different input levels are proposed and verified using the tests data. The proposed model based on the ratio of shear stress to strength can successfully predict the permanent deformation of various asphalt mixtures all the way up to the 10% of permanent strain including all three stages of permanent deformation in a wide range of loading and temperature conditions without changing model coefficients.

• Steel and Composite Structures
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• 제39권3호
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• pp.319-335
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• 2021

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R² = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R² = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

• Computers and Concrete
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• 제28권6호
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• pp.621-634
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• 2021

For the reliable strut-and-tie model (STM) design of disturbed regions of concrete members, structural designers must accurately determine the strength of concrete struts to check the strength conditions of a selected STM el and the anchorage of reinforcing bars in nodal zones. In this study, the author proposed a consistent numerical method for strut strength, applicable to all two-dimensional STMs. The proposed method includes the effects of a biaxial stress state associated with tensile strains in reinforcing bars crossing a strut, deviation angle between strut orientation and compressive principal stress flow, and degree of confinement provided by reinforcement. The author examined the method's validity through the STM prediction of the ultimate strengths of 517 reinforced concrete (RC) deep beams, 24 RC panels, and 258 RC corbels, all tested to failure.

• 대한기계학회논문집A
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• 제37권4호
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• pp.503-509
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• 2013

탄소섬유강화 복합재료는 일반적으로 압축하중과 재료의 면에 수직한 방향의 충격에 매우 취약하다는 단점을 가지고 있다. 특히 항공기의 운항 중 조류와의 충돌이나 정비 중 공구의 낙하로 인한 충격손상은 항공기 구조물의 강도저하의 원인이 된다. 따라서 본 연구에서는 복합재료(CFRP) 시험편에 충격에너지와 충격자 직경을 변화시키면서 충격손상을 가한 후 압축시험을 수행하여 충격후 압축잔류강도를 평가하였으며, 시험 결과를 비교하여 충격에너지에 따른 충격후 압축잔류강도 예측식을 제안하였다.