• Advances in concrete construction
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• v.1 no.4
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• pp.273-288
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• 2013

The main objective of this research was to evaluate the potentials of self-compacting concrete (SCC) mixes to develop bond strength. The investigated mixes incorporated relatively high contents of dolomite powder replacing Portland cement. Either silica fume or fly ash was used along with the dolomite powder in some mixes. Seven mixes were proportioned and cast without vibration in long beams with 10 mm and 16 mm steel dowels fixed vertically along the flowing path. The beams were then broken into discrete test specimens. A push-put configuration was adopted for conducting the bond test. The variation of the ultimate bond strength along the flowing path for the different mixes was evaluated. The steel-concrete bond adequacy was evaluated based on normalized bond strength. The results showed that the bond strength was reduced due to Portland cement replacement with dolomite powder. The addition of either silica fume or fly ash positively hindered further degradation as the dolomite powder content increased. However, all SCC mixes containing up to 30% dolomite powder still yielded bond strengths that were adequate for design purpose. The test results demonstrated inconsistent normalized bond strength in the case of the larger diameter compared to the smaller one.

• Computers and Concrete
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• v.15 no.2
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• pp.215-229
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• 2015

The emerging technology of self compacting concrete, fiber reinforcement together reduces vibration and substitute conventional reinforcement which help in improving the economic efficiency of the construction. The objective of this work is to find the regression model to determine the response surface of mix proportioning Steel Fiber Reinforced Self Compacting Concrete (SFSCC) using statistical investigation. A total of 30 mixtures were designed and analyzed based on Design of Experiment (DOE). The fresh properties of SCC and mechanical properties of concrete were studied using Response Surface Methodology (RSM). The results were analyzed by limited proportion of fly ash, fiber, volume combination ratio of two steel fibers with aspect ratio of 50/35: 60/30 and super plasticizer (SP) dosage. The center composite designs (CCD) have selected to produce the response in quadratic equation. The model responses included in the primary stage were flowing ability, filling ability, passing ability and segregation index whereas in harden stage of concrete, compressive strength, split tensile strength and flexural strength at 28 days were tested. In this paper, the regression model and the response surface plots have been discussed, and optimal results were found for all the responses.

• Computers and Concrete
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• v.13 no.6
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• pp.781-798
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• 2014

Estimating the workability of self-compacting concrete (SCC) is very important both in laboratories and on construction site. A method using visual information during the mixing process was proposed in this paper to estimate the workability of SCC. First, fourteen specimens of concrete were produced by a single-shaft mixer. A digital camera was used to record all the mixing processes. Second, employing the digital image processing, the visual information from mixing process images was extracted. The concrete pushed by the rotating blades forms two boundaries in the images. The shape of the upper boundary and the vertical distance between the upper and lower boundaries were used as two visual features. Thirdly, slump flow test and V-funnel test were carried out to estimate the workability of each SCC. Finally, the vertical distance between the upper and lower boundaries andthe shape of the upper boundary were used as indicators to estimate the workability of SCC. The vertical distance between the upper and lower boundaries was related to the slump flow, the shape of the upper boundary was related to the V-funnel flow time. Based on these relationships, the workability of SCC could be estimated using the mixing process images. This estimating method was verified by three more experiments. The experimental results indicate that the proposed method could be used to automatically estimate SCC workability.

• Structural Engineering and Mechanics
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• v.67 no.2
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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.

• Computers and Concrete
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• v.24 no.4
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• pp.283-293
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• 2019

The limited availability of raw materials and increasing service demands for pavements pose a unique challenge in terms of pavement design and concrete material selection. The self-compacting rubberized concrete (SCRC) can be used in pavement design. The SCRC pavement slab has advantages of excellent toughness, anti-fatigue and convenient construction. On the premise of satisfying the strength, the SCRC can increase the ductility of pavement slab. The aim of this investigation is proposing a new method to predict the crack growth and flexural capacity of large-scale SCRC slabs. The mechanical properties of SCRC are obtained from experiments on small-scale SCRC specimens. With the increasing of the specimen depth, the bearing capacity of SCRC beams decreases at the same initial crack-depth ratio. By constructing extended finite element method (XFEM) models, crack growth and flexural capacity of large-scale SCRC slabs with different fracture types and force conditions can be predicted. Considering the diversity of fracture types and force conditions of the concrete pavement slab, the corresponding test was used to verify the reliability of the prediction model. The crack growth and flexural capacity of SCRC slabs can be obtained from XFEM models. It is convenient to conduct the experiment and can save cost.

• Computers and Concrete
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• v.16 no.2
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• pp.223-243
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• 2015

Self-compacting concrete (SCC) can be placed and compacted under its own weight with little or no compaction. It is cohesive enough to be handled without segregation or bleeding. Modifications in the mix design of SCC may significantly influence the material's mechanical properties. Therefore, it is vital to investigate whether all the assumed hypotheses about conventional concrete (CC) are also valid for SCC structures. The aim in this paper is to develop analytical models for flexural cracking that describe in appropriate detail the observed cracking behaviour of the reinforced concrete flexural one way slabs tested. The crack width and crack spacing calculation procedures outlined in five international codes, namely Eurocode 2 (1991), CEB-FIP (1990), ACI318-99 (1999), Eurocode 2 (2004), and fib-Model Code (2010), are presented and crack widths and crack spacing are accordingly calculated. Then, the results are compared with the proposed analytical models and the measured experimental values, and discussed in detail.

• Computers and Concrete
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• v.30 no.4
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• pp.257-267
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• 2022

Two different types of rubber aggregates (40 mesh rubber powder and 1-4 mm rubber particles respectively) were devised to substitute fine aggregates at 10%, 15%, 20% and 30% by volume in self-compacting concrete to investigate their basic mechanical properties. The results show that with the increase of rubber content, the reduction of compressive strength, splitting tensile strength and static modulus of elasticity gradually increase, and energy dissipation performance gradually increase. The rubber addition significantly reduces brittleness and decelerates damaged process. Whilst, the effect of rubber particles is greater when they are finer. Considering the mechanical properties, the optimal rubber content is 10%. It is recommended that the rubber volume content in rubberized concrete (RC) should not be higher than 20%. In addition, a constitutive model under uniaxial compression was proposed basing on the strain equivalent principle of Lemaitre and the damage theory, which was in good agreement with the test curves.

• Advances in materials Research
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• v.7 no.1
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• pp.45-72
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• 2018

In the present study, a special attention has been paid to the effects regarding the use of different superplasticizers in different dosages. To do so, 36 mixes of normal and self-compacting concrete with two water/binder ratios of 0.35 and 0.45, four different types of superplasticizer including melamine-formaldehyde, naphthalene-formaldehyde, carboxylic-ether and poly-carboxylate, four different superplasticizer/cement ratios of 0.4%, 0.8%, 1.2% and 1.6% and two silica fume/cement ratios of 0% and 10% have been cast. Moreover, the initial and final setting time of the pastes have been tested. For self-compacting mixes, flow time, slump flow, V-funnel, J-ring and L-box tests have been carried out as well as testing the compressive strength and rupture modulus. For normal concrete mixes,slump test has been conducted to assess the workability of the mix and then for each mix, the compressive strength and rupture modulus have been determined. The results indicate that in addition to the important role of superplasticizer type and dosage on fresh state properties of concrete, these parameters as well as the use of silica fume could affect the hardened state properties of the mixes. For instance, the mixes whose superplasticizer were poly-carboxylic-ether based showed better compressive and tensile strength than other mixes. Besides, the air contents showed robust dependency to the type of the superplasticizer. However, the use of silica fume decreased the air contents of the mixes.

• Journal of the Korea Concrete Institute
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• v.20 no.2
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• pp.175-183
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• 2008

Domestically, application of High Flowing Self-Compacting Concrete (HSCC) is limited to building structures and it is difficult to find examples of application in civil infrastructural constructions. However, in the case of North America and Europe, by introducing precast and prestressed system, HSCC is being used for high-density reinforced bridge members. Hence it is assessed that broadening the utilization of HSCC into areas such as bridges and civil construction is required. Therefore in this research, to apply HSCC to high-density reinforced bridge members, ground granulated blast-furnace slag and fly ash were mixed in binary and ternary systems. Also the dynamical characteristics of HSCC, following 1st class regulations of Japan Society of Civil Engineers (JSCE), were assessed to enable application on high-density reinforced structures. The test results revealed ternary system mixture showed better mechanical characteristics than binary system mixture and the application on high-density reinforced precast bridge members seems possible.

• Computers and Concrete
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• v.25 no.5
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• pp.401-409
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• 2020

Artificial neural networks are used as a useful tool in distinct fields of civil engineering these days. In order to control long-term quality of Self-Compacting Semi-Lightweight Concrete (SCSLC), the 90 days compressive strength is considered as a key issue in this paper. In fact, combined artificial neural networks are used to predict the compressive strength of SCSLC at 28 and 90 days. These networks are able to re-establish non-linear and complex relationships straightforwardly. In this study, two types of neural networks, including Radial Basis and Multilayer Perceptron, were used. Four groups of concrete mix designs also were made with two water to cement ratios (W/C) of 0.35 and 0.4, as well as 10% of cement weight was replaced with silica fume in half of the mixes, and different amounts of superplasticizer were used. With the help of rheology test and compressive strength results at 7 and 14 days as inputs, the neural networks were used to estimate the 28 and 90 days compressive strengths of above-mentioned mixes. It was necessary to add the 14 days compressive strength in the input layer to gain acceptable results for 90 days compressive strength. Then proper neural networks were prepared for each mix, following which four existing networks were combined, and the combinatorial neural network model properly predicted the compressive strength of different mix designs.