Showing papers on "Mortar published in 2021"

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

Abstract: Despite the extensive use of mortars materials in constructions over the last decades, there is not yet a reliable and robust method, available in the literature, which can estimate its strength based on its mix parameters. This limitation is due to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques toward the prediction of the compressive strength of cement-based mortar materials with or without metakaolin has been investigated. Specifically, surrogate models (such as artificial neural network, ANN and adaptive neuro-fuzzy inference system, ANFIS models) have been developed to the prediction of the compressive strength of mortars trained using experimental data available in the literature. The comparison of the derived results with the experimental findings demonstrates the ability of both ANN and ANFIS models to approximate the compressive strength of mortars in a reliable and robust manner. Although ANFIS was able to obtain higher performance prediction to estimate the compressive strength of mortars compared to ANN model, it was found through the verification process of some other additional data, the ANFIS model has overfitted the data. Therefore, the developed ANN model has been introduced as the best predictive technique for solving problem of the compressive strength of mortars. Furthermore, using the optimum developed model an ambitious attempt to reveal the nature of mortar materials has been made.

Development of nano-silica treatment methods to enhance recycled aggregate concrete

Abstract: The reuse of recycled aggregates (RA) for producing recycled aggregate concrete (RAC) is a promising way to alleviate the environmental impacts and improve construction sustainability. Because of the inferior properties of RA than natural aggregate, pre-treatments of RA are commonly considered to improve the performance of RAC. In this study, three nano-silica (NS) treatment methods, i.e., pre-spraying plus air-drying, pre-spraying without air-drying and pre-soaking plus air-drying, were adopted and evaluated systematically by varying the dosage and the particle size of NS suspension. The mechanical properties and durability of RAC such as compressive strength, elastic modulus, rate of water absorption and chloride penetration resistance were evaluated. For the microstructural assessment, the micro-hardness test was conducted to investigate the influence of these NS treatment methods on the old mortar and the new mortar near the interface. The experimental results showed that the NS pre-spraying treatments were superior to the NS pre-soaking method and the pre-spraying without air-drying was the best in terms of the enhancement in mechanical properties and durability. The optimum dosage of NS suspension for pre-spraying was 3% of RA by mass and a larger particle size of NS would be more effective. In addition, the microhardness of both the old mortar and the new mortar near the interface were enhanced after using the three NS treatment methods, and the microstructure enhancement of the latter played a more important role for the enhancement of the performance of RAC.

Performance of cement mortars and concretes containing coal bottom ash: A comprehensive review

Abstract: Cement composites like mortar and concrete are the most widely used construction material in the world. Around 90% of the total carbon footprints of concrete manufacturing comes from cement production. The conventional ingredients of the concrete are primarily derived from natural resources like rocks and river beds resulting in the degradation of the natural resources. The growing energy requirements are generally met from the thermal power plants resulting in the generation of an enormous amount of coal ashes that further leads to environmental degradation. An attempt to minimize the environmental impacts of the aforementioned industries requires the utilization of the by-products from the thermal power plants in the manufacturing of mortar and concrete. Coal Bottom Ash (CBA), heavier coarse ash generated and collected from the thermal power plants can be utilized in mortar and concrete manufacturing in two different capacities. The present study summarizes the investigations carried out on fresh, mechanical, and durability properties of the mortar and concrete mixes with CBA as a replacement of fine aggregates and cement. Most of the investigations carried out on the use of CBA encourage the idea of utilizing it as a green material in the manufacturing of mortar and concrete. The present study includes some of the contradictory results, future challenges, and research gaps related to the application of CBA in the construction industry. Further, this review is an effort to provide a substantial base of knowledge, future scopes, and the challenges related to the potential use of CBA as fine aggregates and cement replacement in mortar and concrete, to promote sustainability and cleaner production in the construction sector.

Technological Perspective for Use the Natural Pineapple Fiber in Mortar to Repair Structures

Abstract: The use of natural fiber in cementitious materials can contribute to the improvement of technological properties and environmental issues related to the reuse of agro-industrial waste. World pineapple production is approximately 12.8 million tons per year, generating large environmental impacts, because the disposal natural fibers in landfills. The objective of this research was to evaluate the potential of reusing the natural fiber from the pineapple crown as a reinforcement element in eco-friendly mortar for the purpose of recovering building structures committed to coastal environments, evaluating the influence of the fiber surface treatment process with NaOH and its durability in laboratory conditions, in addition to avoiding the disposal of this waste in landfills. The natural fibers were characterized physically, morphologically and chemically, in the treated and untreated (natural) condition, for further technological evaluation of mortars in the fresh state, such as consistency, specific mass, incorporated air and water retention. Comprehensive studies of the hardened state were also carried out to study mechanical strength (compressive, flexural and tensile), water absorption due to capillarity and immersion, as well as durability by evaluating mass loss and mechanical strength after exposure conditions. The results showed that the fiber treatment process improved its characteristics for application in mortar with addition of 2.5% fiber treated in cement mass, causing the better in the technological and durability properties, and a proposed new means of disposing of agro-industrial waste, contributing to a circular economy.

Feasibility of glass/basalt fiber reinforced seawater coral sand mortar for 3D printing

Abstract: In remote islands and coastal areas, where there are no freshwater and river sand, the use of locally available seawater and marine sediments in mortar and concrete for building construction may be a better solution. Moreover, if there are no local materials for fabricating the formwork, 3D mortar/concrete printing may be considered. However, study on 3D printing using mortar/concrete made of seawater and marine sediments is still lacking. In this study, a series of mortar mixes made of seawater, coral sand, and glass or basalt fibers were produced to test their fresh and hardened properties for the purpose of developing 3D printable glass/basalt fiber reinforced seawater coral sand mortars. It was found that by adjusting the water reducer dosage, all the mortar mixes exhibited good buildability. The addition of glass or basalt fibers improved the flexural strength to some extent but slightly reduced the compressive strength. However, the flexural and compressive strengths of the printed specimens were significantly lower than those of the standard un-printed specimens. Overall, the fiber reinforced seawater coral sand mortar exhibits great potential to be applied as 3D printable cement-based material for use in remote areas.

Compound utilization of construction and industrial waste as cementitious recycled powder in mortar

Abstract: This paper investigates the utilization of powder recycled from construction and industrial waste in the construction industry. To alleviate the negative environmental impact of cement industry, recycled concrete powder (RCP) and spontaneous combustion gangue powder (SCGP) were used as supplementary materials to substitute part of the cement. Six recycled mortar mixes were designed with various contents of RCP and SCGP. In this test, the total replacement ratio of the recycled powder (RCP and SCGP) varied from 0 to 50%. The mechanical and durability properties of the recycled mortar were investigated in combination with microstructure analysis. The findings reveal that 15% RCP and 15% SCGP is a suitable combination for the recycled mortar to maintain mechanical properties comparable to those of the control mix. When the total substitution ratio of RCP and SCGP does not exceed 30%, their incorporation leads to better durability properties of the recycled mortar compared to those of the mix containing one type of recycled powder. Consistent with the mechanical and durability analyses, the microstructure analysis reveals that the combination of 15% RCP and 15% SCGP contributes to a dense structure of the mortar, which benefits from the synergetic effect of the relatively high pozzolanic reactivity of SCGP and the filling ability of RCP.

Prediction of cement-based mortars compressive strength using machine learning techniques

Abstract: The application of artificial neural networks in mapping the mechanical characteristics of the cement-based materials is underlined in previous investigations. However, this machine learning technique includes several major deficiencies highlighted in the literature, such as the overfitting problem and the inability to explain the decisions. Hence, the present study investigates the applicability of other common machine learning techniques, i.e., support vector machine, random forest (RF), decision tree, AdaBoost and k-nearest neighbors in mapping the behavior of the compressive strength (CS) of cement-based mortars. To this end, a big experimental database has been compiled based on experimental data available in the literature considering, namely the cement grade, which is an important parameter for the modeling of mortar’s CS. Other important parameters are namely the age, the water-to-binder ratio, the particle size distribution of the sand and the amount of plasticizer. Many models based on the influential factors affecting machine learning techniques have been developed, and their prediction capacities have been assessed using performance indexes. The present research highlights the potential of AdaBoost and RF models as useful tools which can assist in mortar design and/or optimization. In addition, mapping the development of mortar characteristics can assist in revealing the influence of the different mortar mix parameters on the compressive strength.