• Computers and Concrete
• /
• v.5 no.1
• /
• pp.21-36
• /
• 2008

Steel fiber reinforced concrete is increasingly used day by day in various structural applications. An extensive experimentation was carried out with w/cm ratio ranging from 0.25 to 0.40, and fiber content ranging from zero to1.5 percent by volume with an aspect ratio of 80 and silica fume replacement at 5%, 10% and 15%. The influence of steel fiber content in terms of fiber reinforcing index on the compressive strength of high-performance fiber reinforced concrete (HPFRC) with strength ranging from 45 85 MPa is presented. Based on the test results, equations are proposed using statistical methods to predict 28-day strength of HPFRC effecting the fiber addition in terms of fiber reinforcing index. A strength model proposed by modifying the mix design procedure, can utilize the optimum water content and efficiency factor of pozzolan. To examine the validity of the proposed strength model, the experimental results were compared with the values predicted by the model and the absolute variation obtained was within 5 percent.

• Steel and Composite Structures
• /
• v.21 no.4
• /
• pp.921-947
• /
• 2016

Concrete Filled Fibre Reinforced Polymer Tube (CFFT) for new columns construction has attracted significant research attention in recent years. The CFFT acts as a formwork for new columns and a barrier to corrosion accelerating agents. It significantly increases both the strength capacity (Strength enhancement ratio) and the ductility (Strain enhancement ratio) of reinforced concrete columns. In this study, based on predefined selection criteria, experimental investigation results of 134 circular CFFT columns under axial compression have been compiled and analysed from 599 CFFT specimens available in the literature. It has been observed that actual confinement ratio (expressed as a function of material properties of fibres, diameter of CFFT and compressive strength of concrete) has significant influence on the strength and ductility of circular CFFT columns. Design oriented models have been proposed to compute the strength and strain enhancement ratios of circular CFFT columns. The proposed strength and strain enhancement ratio models have significantly reduced Average Absolute Error (AAE), Mean Square Error (MSE), Relative Standard Error of Estimate (RSEE) and Standard Deviation (SD) as compared to other available strength and strain enhancement ratios of circular CFFT column models. The predictions of the proposed strength and strain enhancement ratio models match well with the experimental strength and strain enhancement ratios investigation results in the compiled database.

• Journal of The Korean Digital Architecture Interior Association
• /
• v.11 no.4
• /
• pp.21-27
• /
• 2011

These materials in architecturally glass or metal have weaknesses such as inadequate insulating quality, combustibility and toxic gases in fires substance. However, Autoclaved Lightweight Concrete(ALC) has excellent thermal insulation properties and seem to possess the superb insulating quality as substitute of existing exterior materials. This research is to compare experimentally to the kind of the strength properties of ALC materials which mixed with blast furnace slag pounder and silica fume. For the purpose of increasing the strength, the plastic states of ALC evaluate the physical characteristics as microstructure and strength according to various specific gravity. According to the quicklime quantity the compressive strength is proportionate depend on the absolute dried specific gravity. When not putting in 10% quicklime, the compressive strength appeared most lowly with 14.0MPa. When putting in the quicklime, the strength appeared higher with 15.1MPa. And strength of specimen containing 2.25% silica fume is 15.6MPa increased 10.3% than reference specimen 14.0MPa.

• Magazine of the Korea Concrete Institute
• /
• v.4 no.1
• /
• pp.127-134
• /
• 1992

Generally speaking, the internal moisture of concrete is mainly distributed in inner part and concrete surface which is exposed are dned according to influence of temperature and humidity. So, the properties which are compressive strength, modular elasticity, and volume change are different at each part even in same concrete. This is because moisture distribution is changed according to the evaporation and move ment of moisture, exist in the inner porosity of concrete. Therefore, it is necessary that we investigate the properties of concrete according to moisture distribution. The purpose of this study is investigating correlation between the moisture content and mechanical properties in concrete. Compressive and tenslle strength decrease according to increasing moisture content, but modular elas ticity increase. Those increasing or decreasing ratio at drying ratio 100% (absolute dries) is as follows in comparative of drying ratio 0 % (saturated condition).tion).

• Proceedings of the Korea Concrete Institute Conference
• /
• 2001.11a
• /
• pp.665-668
• /
• 2001

Generally, according to rising of atmospheric temperature, a consistency of concrete decreases, and a slump property of concrete is changed to be large. Also, in the strength development of concrete, the strength development rate of long-term age(28day) in comparison to strength of early age(7day) and the absolute compressive strength decreases. Accordingly, in this study, experiments about quality evaluation of concrete utilizing Ordinary Portland Cement is carried out. As a result of experiments, there were a conspicuous change in slump of concrete due to temperature increase. In conclusion, the rising of atmospheric temperature was very important factor in affecting the quality fluctuation of hot weather concrete.

• Computers and Concrete
• /
• v.24 no.1
• /
• pp.7-17
• /
• 2019

The complex phenomenon of the bond formation in geopolymer is not well understood and therefore, difficult to model. This paper present applied statistical models for evaluating the compressive strength of geopolymer. The applied statistical models studied are divided into three different categories - linear regression [least absolute shrinkage and selection operator (LASSO) and elastic net], tree regression [decision and bagging tree] and kernel methods (support vector regression (SVR), kernel ridge regression (KRR), Gaussian process regression (GPR), relevance vector machine (RVM)]. The performance of the methods is compared in terms of error indices, computational effort, convergence and residuals. Based on the present study, kernel based methods (GPR and KRR) are recommended for evaluating compressive strength of Geopolymer concrete.

• Computers and Concrete
• /
• v.8 no.4
• /
• pp.445-463
• /
• 2011

In the design of reinforced concrete (RC) beams, apart from providing adequate strength, it is also necessary to provide a minimum deformability even for beams not located in seismic regions. In most RC design codes, this is achieved by restricting the maximum tension steel ratio or neutral axis depth. However, this empirical deemed-to-satisfy method, which was developed based on beams made of normal-strength concrete (NSC) and normal-strength steel (NSS), would not provide a consistent deformability to beams made of high-strength concrete (HSC) and/or high-strength steel (HSS). More critically, HSC beams would have much lower deformability than that provided previously to NSC beams. To ensure that a consistent deformability is provided to all RC beams, it is proposed herein to set an absolute minimum rotation capacity to all RC beams in the design. Based on this requirement, the respective maximum limits of tension steel ratio and neutral axis depth for different concrete and steel yield strengths are derived based on a formula developed by the authors. Finally for incorporation into design codes, simplified guidelines for designing RC beams having the proposed minimum deformability are developed.

• Computers and Concrete
• /
• v.13 no.2
• /
• pp.255-270
• /
• 2014

Impact performance of high-performance concrete (HPC) and SFRC at 28-day and 56-day under the action of repeated dynamic loading was studied. Silica fume replacement at 10% and 15% by mass and crimped steel fiber ($V_f$ = 0.5%- 1.5%) with aspect ratios of 80 and 53 were used in the concrete mixes. Results indicated that addition of fibers in HPC can effectively restrain the initiation and propagation of cracks under stress, and enhance the impact strengths and toughness of HPC. Variation of fiber aspect ratio has minor effect on improvement in impact strength. Based on the experimental data, failure resistance prediction models were developed with correlation coefficient (R) = 0.96 and the estimated absolute variation is 1.82% and on validation, the integral absolute error (IAE) determined is 10.49%. On analyzing the data collected, linear relationship for the prediction of failure resistance with R= 0.99 was obtained. IAE value of 10.26% for the model indicates better the reliability of model. Multiple linear regression model was developed to predict the ultimate failure resistance with multiple R= 0.96 and absolute variation obtained is 4.9%.

• Computers and Concrete
• /
• v.20 no.1
• /
• pp.31-38
• /
• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Computers and Concrete
• /
• v.13 no.4
• /
• pp.531-545
• /
• 2014

The purpose of this paper is to develop a prediction model for the compressive strength of waste LCD glass applied in concrete by analyzing a series of laboratory test results, which were obtained in our previous study. The hyperbolic function was used to perform the nonlinear-multivariate regression analysis of the compressive strength prediction model with the following parameters: water-binder ratio w/b, curing age t, and waste glass content G. According to the relative regression analysis, the compressive strength prediction model is developed. The calculated results are in accord with the laboratory measured data, which are the concrete compressive strengths of different mix proportions. In addition, a coefficient of determination $R^2$ value between 0.93 and 0.96 and a mean absolute percentage error MAPE between 5.4% and 8.4% were obtained by regression analysis using the predicted compressive analysis value, and the test results are also excellent. Therefore, the predicted results for compressive strength are highly accurate for waste LCD glass applied in concrete. Additionally, this predicted model exhibits a good predictive capacity when employed to calculate the compressive strength of washed glass sand concrete.