Elaboration and characterization of fiber-reinforced self-consolidating repair mortar containing natural perlite powder

Benyahia, A.,Ghrici, M.,Mansour, M. Said,Omran, A. Techno-Press 2017 Advances in concrete construction Vol.5 No.1

This research project aimed at evaluating experimentally the effect of natural perlite powder as an alternative supplementary cementing material (SCM) on the performance of fiber reinforced self-consolidating repair mortars (FR-SCRMs). For this purpose, four FR-SCRMs mixes incorporating 0%, 10%, 20%, and 30% of natural perlite powder as cement replacements were prepared. The evaluation was based on fresh (slump flow, flow time, and unit weight), hardened (air-dry unit weight, compressive and flexural strengths, dynamic modulus of elasticity), and durability (water absorption test) performances. The results reveal that structural repair mortars confronting the performance requirements of class R4 materials (European Standard EN 1504-3) could be designed using 10%, 20%, and 30% of perlite powder as cement substitutions. Bonding results between repair mortars containing perlite powder and old concrete substrate investigated by the slant shear test showed good interlocking justifying the effectiveness of these produced mortars.

Effect of curing treatments on the material properties of hardened self-compacting concrete

Salhi, M.,Ghrici, M.,Li, A.,Bilir, T. Techno-Press 2017 Advances in concrete construction Vol.5 No.4

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.

Behaviour of self compacting repair mortars based on natural pozzolana in hot climate

Benyahia, A.,Ghrici, M. Techno-Press 2018 Advances in concrete construction Vol.6 No.3

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.

Effect of temperature on the behavior of self-compacting concretes and their durability

Salhi, M.,Li, A.,Ghrici, M.,Bliard, C. Techno-Press 2019 Advances in concrete construction Vol.7 No.4

The formulation of self-compacting concretes (SCC) and the study of their properties at the laboratory level were currently well mastered. The aim of this work is to characterize SCC under hot climatic conditions and their effects on the properties of fresh and hardened SCC. Particularly, the effect of the initial wet curing time on the mechanical behavior such as the compressive strength and the durability of the SCCs (acid and sulfate attack) as well as the microstructure of SCCs mixtures. In this study, we used two types of cement, Portland cement and slag cement, three water/binder (W/B) ratio (0.32, 0.38 and 0.44) and five curing modes. The obtained results shows that the compressive strength is strongly influenced by the curing methods, 7-days of curing in the water and then followed by a maturing in a hot climate was the optimal duration for the development of a better compressive strength, regardless of the type of binder and the W/B ratio.

Compressive strength prediction of limestone filler concrete using artificial neural networks

Ayat, Hocine,Kellouche, Yasmina,Ghrici, Mohamed,Boukhatem, Bakhta Techno-Press 2018 Advances in computational design Vol.3 No.3

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.

Predicting concrete properties using neural networks (NN) with principal component analysis (PCA) technique

B. Boukhatem,A.T. Hamou,Dj. Ziou,M. Ghrici,S. Kenai 사단법인 한국계산역학회 2012 Computers and Concrete, An International Journal Vol.10 No.6

This paper discusses the combined application of two different techniques, Neural Networks (NN) and Principal Component Analysis (PCA), for improved prediction of concrete properties. The combination of these approaches allowed the development of six neural networks models for predicting slump and compressive strength of concrete with mineral additives such as blast furnace slag, fly ash and silica fume. The Back-Propagation Multi-Layer Perceptron (BPMLP) with Bayesian regularization was used in all these models. They are produced to implement the complex nonlinear relationship between the inputs and the output of the network. They are also established through the incorporation of a huge experimental database on concrete organized in the form Mix-Property. Thus, the data comprising the concrete mixtures are much correlated to each others. The PCA is proposed for the compression and the elimination of the correlation between these data. After applying the PCA, the uncorrelated data were used to train the six models. The predictive results of these models were compared with the actual experimental trials. The results showed that the elimination of the correlation between the input parameters using PCA improved the predictive generalisation performance models with smaller architectures and dimensionality reduction. This study showed also that using the developed models for numerical investigations on the parameters affecting the properties of concrete is promising.