• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.1 s.53
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• pp.161-168
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• 2009

In this study, the concrete, in which the steel fiber(SF) with different volume-surface ratios and lengths was intermixed in High flowing Self-Compacting Concrete(HSCC), was produced to compare with steel fiber reinforced concrete as a part of plan to improve the workability and the quality of steel fiber reinforced concrete. As the result of experiment, the flowing and passing characteristics of HSCC intermixed with SF was highly improved as there was no fiber ball phenomenon due to the effect of high flowability and the viscosity, and in the identical range of compressive strength, it showed the tendency that the splitting and flexural strength was increasing as the length was getting longer regardless of volume-surface ratio when compared with HSCC which was intermixed with SF. It is estimated that in case of application of HSCC intermixed with steel fiber to work sites, it would be possible to improve the workability and the quality which would be better than that of steel fiber reinforced concrete which has been used.

• Advances in concrete construction
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• v.13 no.6
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• pp.433-450
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• 2022

The conventional disposal methods of waste tires are harmful to the environment. Moreover, the recycling/reuse of waste tires in domestic and industrial applications is limited due to parent product's quality control and environmental concerns. Additionally, the recycling industry often prefers powdered rubber particles (<0.60 mm). However, the processing of waste tires yields both powdered and coarser (>0.60 mm) size fractions. Reprocessing of coarser rubber requires higher energy increasing the product cost. Therefore, the waste tire rubber (WTR) less favored by the recycling industry is encouraged for use in construction products as one of the environment-friendly disposal methods. In this study, WTR fiber >0.60 mm size fraction is collected from the industry and sorted into 0.60-1.18, 1.18-2.36-, and 2.36-4.75-mm sizes. The effects of different fiber size fractions are studied by incorporating it as fine aggregates at 10%, 20%, and 30% in the self-compacting rubberized concrete (SCRC). The experimental investigations are carried out by performing fresh and hardened state tests. As the fresh state tests, the slump-flow, T500, V-funnel, and L-box are performed. As the hardened state tests, the scanning electron microscope, compressive strength, flexural strength and split tensile strength tests are conducted. Also, the water absorption, porosity, and ultrasonic pulse velocity tests are performed to measure durability. Furthermore, SCRC's energy absorption capacity is evaluated using the falling weight impact test. The statistical significance of content and size fraction of WTR fiber on SCRC is evaluated using the analysis of variance (ANOVA). As the general conclusion, implementation of various size fraction WTR fiber as fine aggregate showed potential for producing concrete for construction applications. Thus, use of WTR fiber in concrete is suggested for safe, and feasible waste tire disposal.

• Advances in concrete construction
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• v.6 no.3
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• pp.285-296
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• 2018

In the present paper, the results of an experimental study of the bond between repair materials and mortar substrate subjected to hot climate is presented. Half-prisms of size $40{\times}40{\times}80mm$, serving as a substrate mortar samples (SUBM) were manufactured in the laboratory and then stored at an ambient temperature for 6 months. Five self compacting mortar mixes (SCMs) incorporating 0%, 10%, 20%, 30%, and 40% of natural pozzolana as white cement replacement were used as repair materials. Repaired composite samples (SCMs/SUBM) were cured at hot climate for different lengths of time (28 and 56-days). During the first week of curing, the composite samples were watered twice a day. The test carried out to assess the bond between SCMs and SUBM was based on three-point bending (3 PB) test. The obtained results have proved that it was feasible to produce compatible repair materals in this curing environment by using up to 30% natural pozzolana as white cement replacement.

• Advances in concrete construction
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• v.5 no.4
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• pp.359-375
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• 2017

This paper presents a study of the properties and behavior of self-compacting concretes (SCC) in the hot climate. The effect of curing environment and the initial water curing period on the properties and behavior of SCC such as compressive strength, ultrasonic pulse velocity (UPV) and sorptivity of the SCC specimens were investigated. Three Water/Binder (W/B) ratios (0.32, 0.38 and 0.44) have been used to obtain three ranges of compressive strength. Five curing methods have been applied on the SCC by varying the duration and the conservation condition of SCC. The results obtained on the compressive strength show that the period of initial water curing of seven days followed by maturation in the hot climate is better in comparison with the four other curing methods. The coefficient of sorptivity is influenced by W/B ratio and the curing methods. It is also shown that the sorptivity coefficient of SCC specimens is very sensitive to the curing condition. The SCC specimens cured in water present a low coefficient of sorptivity regardless of the ratio W/B. Furthermore, the results show that there is a good correlation between ultrasonic pulse velocity and the compressive strength.

• Computers and Concrete
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• v.18 no.5
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• pp.969-982
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• 2016

This paper investigates the compressive fatigue behaviour of polypropylene fibre reinforced self compacting concrete with Granite Sawing Waste (GSW). An experimental programme was conducted to obtain the fatigue lives of fibre reinforced self compacting concrete (FRSCC) at various stress levels. The stress ratio was kept constant as 0.3. Compressive fatigue test was conducted on 60 cubic specimens with 100mm edge length and 0.1% of polypropylene fibres at a frequency of 0.05Hz. The test results indicate that the fatigue lives of concretes containing granite sawing waste follow the double-parameter Weibull distribution. The fatigue strength equations have been developed based on different probabilities of failure.

• Computers and Concrete
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• v.5 no.1
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• pp.61-74
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• 2008

Digital image processing algorithms for the analysis and characterization of grains and voids in cemented materials were developed using toolbox functions of a mathematical software package. Utilization of grayscale, color and watershed segmentation algorithms and their performances were demonstrated on artificially prepared self-compacting concrete (SCC) samples. It has been found that color segmentation was more advantageous over the gray scale segmentation for the detection of voids whereas the latter method provided satisfying results for the aggregate grains due to the sharp contrast between their colors and the cohesive matrix. The watershed segmentation method, on the other hand, appeared to be very efficient while separating touching objects in digital images.

• Computers and Concrete
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• v.5 no.5
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• pp.461-473
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• 2008

The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

• Advances in concrete construction
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• v.2 no.4
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• pp.301-308
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• 2014

The present research work is on the effect of sawdust ash (SDA) on the mechanical strengths of self compacting concrete (SCC) using naphthalene sulfonate (NS) as a plasticizer. Experiments on compressive, flexural and splitting tensile strengths are conducted and the data analyzed using the Minitab 15 software. The results showed that SDA can defer the reaction of cement hydration and prolong the setting times of cement paste. This was very much pronounced on the flexural and splitting tensile strengths at 90 days of curing which are 36 % and 33 % higher than the control strengths, respectively. The study has proposed strength relations of mortar compressive strength with the flexural and splitting tensile strengths and these are, 5 and 7 times respectively. The flexural strength is 1.5 times that of the splitting tensile. Finally, linear models were developed on these relationships.

• Structural Engineering and Mechanics
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• v.57 no.2
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• pp.357-367
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• 2016

This paper illustrates an experimental study on a self compacting polymer concrete called isobeton made of polyurethane foam and expanded clay. Several experiments were conducted to characterize the physic-mechanical properties of the considered material. Application of the Linear Elastic Fracture Mechanics (LEFM) and determining the toughness of two isobetons based on Belgian and Italian clay, was conducted to determine the stress intensity factor $K_{IC}$ and the rate of releasing energy $G_{IC}$. The material considered was tested under static and dynamic loadings for two different samples with $10{\times}10{\times}40$ and $10{\times}15{\times}40cm$ dimensions. The result obtained by the application of the Linear Elastic Fracture Mechanics (LEFM) shows that is optimistic and fulfilled the physic-mechanical requirement of the study.

• Computers and Concrete
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• v.24 no.5
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• pp.399-412
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• 2019

In this investigation, Elman neural networks were utilized for predicting the mechanical properties of Self-Compacting Concretes (SCCs). Elman models were designed by using experimental data of many different concrete mixdesigns of various types of SCC that were collected from the literature. In order to investigate the effectiveness of the selected input variables on the network performance in predicting intended properties, utilized data in artificial neural networks were considered in two sets of 8 and 140 input variables. The obtained outcomes showed that not only can the developed Elman ANNs predict the mechanical properties of SCCs with high accuracy, but also for all of the desired outputs, networks with 140 inputs, compared to ones with 8, have a remarkable percent improvement in the obtained prediction results. The prediction accuracy can significantly be improved by using a more complete and accurate set of key factors affecting the desired outputs, as input variables, in the networks, which is leading to more similarity of the predicted results gained from networks to experimental results.