• Computers and Concrete
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• 제14권3호
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• pp.247-262
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• 2014

Partial replacement of Portland cement by slag can reduce the energy consumption and $CO_2$ emission therefore is beneficial to circular economy and sustainable development. Compressive strength is the most important engineering property of concrete. This paper presents a numerical procedure to predict the development of compressive strength of slag blended concrete. This numerical procedure starts with a kinetic hydration model for cement-slag blends by considering the production of calcium hydroxide in cement hydration and its consumption in slag reactions. Reaction degrees of cement slag are obtained as accompanied results from the hydration model. Gel-space ratio of hardening slag blended concrete is determined using reaction degrees of cement and slag, mixing proportions of concrete, and volume stoichiometries of cement hydration and slag reaction. Furthermore, the development of compressive strength is evaluated through Powers' gel-space ratio theory considering the contributions of cement hydration and slag reaction. The proposed model is verified through experimental data on concrete with different water-to-binder ratios and slag substitution ratios.

• Computers and Concrete
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• 제11권5호
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• pp.365-382
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• 2013

Although shear reinforcement in beams typically consists of steel bars bent in the form of stirrups or hoops, the addition of deformed steel fibres to the concrete has been shown to enhance shear resistance and ductility in reinforced concrete beams. This paper presents a model that can be used to predict the shear strength of fibrous concrete rectangular members without stirrups. The model is an extension of the plasticity-based crack sliding model originally developed for plain concrete beams. The crack sliding model has been improved in order to take into account several aspects: the arch effect for deep beams, the post-cracking tensile strength of steel fibre reinforced concrete and its ability to control sliding along shear cracks, and the mitigation of the shear size effect due to presence of fibres. The results obtained by the model have been validated by a large set of experimental tests taken from literature, compared with several models proposed in literature, and numerical analyses are carried out showing the influence of fibres on the beam failure mode.

• Structural Engineering and Mechanics
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• 제91권3호
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• pp.239-250
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• 2024

With the aim to provide better predication about fracture behavior, a numerical simulating strategy based on the rigid spring model is proposed for reinforced concrete (RC) structures in this study. According to the proposed strategy, concrete is partitioned into a series of irregular rigid blocks based on the Voronoi diagram, which are connected by interface springs. Steel bars are simulated by bar elements, and the bond slip element is defined at bar element nodes to describe the interaction between reinforcement and concrete. A concrete damage evolution model based on the separation criterion is adopted to describe the weakening process of interface spring between adjacent blocks, while a nonlinear bond slip model is introduced to simulate the synergy behaviour of reinforced steel bars and concrete. In the damage evolution model of concrete, the influence of compressive stress perpendicular to the interface on the shear strength is considered. To check the effectiveness and applicability of the proposed modelling, experimental and numerical studies about a simply-supported RC beam and the two-notched concrete plates in Nooru-Mohamed's experiment are conducted, and the grid sensitivity are investigated.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2001년도 가을 학술발표회 논문집
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• pp.641-646
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• 2001

In early-age concrete, volumetric deformations due to thermal expansion and moisture transfer are restrained by various boundary conditions, and then restraint stresses occur in proportion to developed stiffness. With increase of the age, these stresses are gradually relieved by significant relaxation behavior of early-age concrete. Therefore, it is necessary to consider the stress relaxation in order to analyze the behavior of early-age concrete more accurately. In this paper, we propose a unified algorithm which combines a relaxation model with hydration model, heat conduction model, micropore structure formation model, moisture diffusion model and mechanical properties development model and develop a finite element program based on the algorithm. The program is applied to evaluate stress development if a temperature-stress test machine (TSTM) specimen and a massive concrete structure, and then validity of the program is discussed and evaluated.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 춘계 학술발표회 제16권1호
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• pp.140-143
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• 2004

Heat of hydration of concrete under different curing temperatures can be characterized with knowledge of the thermal activity, the heat rate at the reference temperature, and the total heat of hydration of the mixture. The so-called multi-component hydration model incorporates the effect of following variables: cement chemical composition, cement fineness, secondary cementitious powders, mixture proportions, and concrete properties. However, the model does not consider the use of silica fume as a secondary cementitious powder. Therefore, the model that quantifies the heat of hydration due to the use of silica fume is needed. In this thesis, the effects of silica fume on heat of hydration are evaluated and the influence on the heat of hydration are also quantified to be included in the model, so that the analysis using modified multi-component hydration model for silica fume concrete provides more accurate results than normal concrete.

• Structural Engineering and Mechanics
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• 제18권1호
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• pp.21-40
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• 2004

In this paper, we modify the L-L model (Li et al. 2003) and extend the application of this model to concrete confined by both steel reinforcement and CFRP. Thirty-six concrete cylinders with a dimension of ${\varphi}30{\times}60$ cm were tested to verify the effectiveness of the proposed model. The experimental test results show that different types of steel reinforcement have a great effect on the compressive strength of concrete cylinders confined by steel reinforcement, but the different types of steel reinforcement have very little effect on concrete cylinders confined by both steel reinforcement and CFRP. Compared with the stress-strain curves of confined concrete cylinders, we can conclude that the proposed model can provide more effective prediction than others models.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회논문집(I)
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• pp.285-290
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• 2000

A mathematical model which can simulate biaxial moment-curvature relations for reinforced concrete column is developed. The developed model is capable of tracing the post-peak behavior of a column after peak load. The model can take into account different sectional shapes of a column and various constitutive models of confined concrete. The developed model is used to evaluate constitutive models of confined concrete under concentric loading, suggested by different researchers. Error function which measures the overall constitutive behavior of a confined concrete is intrcduced. The constitutive model minimizing this error function is selected and is incorporated into the developed model in order to investigate the effect of main parameters on the general column behavior.

• Computers and Concrete
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• 제11권4호
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• pp.291-304
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• 2013

By considering the creep characteristics of concrete core under eccentric compression, a creep model of concrete filled steel tubes (CFT) columns under eccentric compressive loads is proposed based on the concrete creep model B3. In this proposed model, a discrete element method is introduced to transform the eccentric loading into axial loading. The validity of the model is verified by comparing the predicting results with the published creep experiments results on CFT specimens under compressive loading, together with the predicting values based on other concrete creep models, such as ACI209, CEB90, GL2000 and elastic continuation and plastic flow theory. By using the proposed model, a parameters study is carried out to analysis the effects of practical design parameters, such as concrete mix (e.g. water to cement ratio, aggregate to cement ratio), steel ratio and eccentricity ratio, on the creep of CFT columns under eccentric compressive loading.

• Computers and Concrete
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• 제7권2호
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• pp.87-102
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• 2010

This paper discusses new capabilities developed for the Virtual Penetration Laboratory (VPL) software package to address the challenges of determining Penetration Resistance (PR) equations for concrete materials. Specifically, the paper introduces a three-invariant concrete constitutive model recently developed by the authors. The Advanced Fundamental Concrete (AFC) model was developed to provide a fast-running predictive model to simulate the behavior of concrete and other high-strength geologic materials. The Continuous Evolutionary Algorithms (CEA) automatic fitting algorithms used to fit the new model are discussed, and then examples are presented to demonstrate the effectiveness of the new AFC model. Finally, the AFC model in conjunction with the VPL software package is used to develop a PR equation for a concrete material.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.73-74
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• 2022

Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.