Optimizing compressive behavior of concrete containing fine recycled refractory brick aggregate together with calcium aluminate cement and polyvinyl alcohol fibers exposed to acidic environment

Nematzadeh, Mahdi; Dashti, Javad; Ganjavi, Behnoud

doi:10.1016/j.conbuildmat.2017.12.230

Cited by 58 publications

(21 citation statements)

References 25 publications

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“…Many studies of the properties of RMA and its effect on the mechanical properties of RAC have been published [3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. It has been recognized that RMA differs from NA mainly in terms of water absorption, density, and resistances, for instance, resistance to wear, abrasion resistance, or freeze–thaw resistance [24].…”

Section: Introductionmentioning

confidence: 99%

The Utilization of Recycled Masonry Aggregate and Recycled EPS for Concrete Blocks for Mortarless Masonry

et al. 2019

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The main aim of this paper is to carry out the environmentally based enhancement of a concrete mixture containing recycled materials whilst considering natural resource consumption as well as mechanical and thermal property levels. The developed concrete is intended to be used in mortarless masonry wall structures. Ten concrete mixtures with different types and replacement rates of recycled masonry aggregate and recycled expanded polystyrene were prepared, and their mechanical and thermal properties were experimentally investigated. It was found that the use of recycled masonry aggregate led to better thermal properties while maintaining sufficient mechanical properties. On the contrary, the addition of recycled expanded polystyrene did not significantly affect the thermal properties of concrete, but the mechanical properties considerably declined. For this reason, the recycled masonry aggregate is suitable to use as an aggregate for concrete masonry blocks for wall structures.

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Section: Introductionmentioning

confidence: 99%

The Utilization of Recycled Masonry Aggregate and Recycled EPS for Concrete Blocks for Mortarless Masonry

et al. 2019

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“…This parameter is attributed to the capillary action of materials, keeping the water content within their pores at 100% relative humidity. Indeed, the free water content value is lower than the maximum water content owing to the trapped air in materials' pores [35,50]. Concerning this, a method proposed by researchers [51,52] was used to obtain the free water content value for IMSWA and substrate.…”

Section: Materials Propertiesmentioning

confidence: 99%

“…The use of natural materials for the drainage layer of green roof systems can impose a heavy impact on the environment. By using recycled materials for the drainage layer, the burden on both the cost of construction process and the environment can be reduced by saving natural resources [32][33][34][35][36][37][38]. Concerning this, the thermal performance effect of rubber crumbs and pozzolana as a drainage layer on roofing systems was assessed by Coma et al [39,40].…”

Section: Introductionmentioning

confidence: 99%

Heat Transfer Measurement within Green Roof with Incinerated Municipal Solid Waste Aggregates

2021

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A green roof is composed of a substrate and drainage layers which are fixed on insulation material and roof structure. The global heat resistance (Rc) within a green roof is affected by the humidity content of the substrate layer in which the coarse recycled materials can be used. Moreover, the utilization of recycled coarse aggregates such as incinerated municipal solid waste aggregate (IMSWA) for the drainage layer would be a promising solution, increasing the recycling of secondary resources and saving natural resources. Therefore, this paper aims to investigate the heat transfer across green roof systems with a drainage layer of IMSWA and a substrate layer including recycled tiles and bricks in wet and dry states according to ISO-conversion method. Based on the results, water easily flows through the IMSWAs with a size of 7 mm. Meanwhile, the Rc-value of the green roof system with the dry substrate (1.26 m2 K/W) was 1.7 times more than that of the green roof system with the unsaturated substrate (0.735 m2 K/W). This means that the presence of air-spaces in the dry substrate provided more heat resistance, positively contributing to heat transfer decrease, which is also dependent on the drainage effect of IMSWA. In addition, the Rc-value of the dry substrate layer was about twice that of IMSWA as the drainage layer. No significant difference was observed between the Rc-values of the unsaturated substrate layer and the IMSWA layer.

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“…e response surface method is among the most widely used approaches for concrete mixture design optimization [21][22][23][24][25] owing to its simplicity in illustrating the response-related equations to analyze the relationship between the required factors and the required response by using 3D plots. In addition, a few studies [15,16] pertaining to the field of concrete property predictive models popularized the use of the RMS to represent the reliable behavior pertaining to the concrete property in input-output predictive relationships.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Prediction of Compressive Strength Behavior of Ground Bottom Ash Concrete by an Artificial Neural Network

Tuntisukrarom

Cheerarot

2020

Advances in Materials Science and Engineering

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The objective of this work was to examine the compressive strength behavior of ground bottom ash (GBA) concrete by using an artificial neural network. Four input parameters, specifically, the water-to-binder ratio (WB), percentage replacement of GBA (PR), median particle size of GBA (PS), and age of concrete (AC), were considered for this prediction. The results indicated that all four considered parameters affect the strength development of concrete, and GBA with a high fineness can act as a good pozzolanic material. The optimal ANN model had an architecture with two hidden layers, with six neurons in the first hidden layer and one neuron in the second hidden layer. The proposed ANN-based explicit equation represented a highly accurate predictive model, for which the statistical values of R2 were higher than 0.996. Moreover, the compressive strength behavior determined using the optimal ANN model closely followed the trend lines and surface plots of the experimental results.

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Optimizing compressive behavior of concrete containing fine recycled refractory brick aggregate together with calcium aluminate cement and polyvinyl alcohol fibers exposed to acidic environment

Cited by 58 publications

References 25 publications

The Utilization of Recycled Masonry Aggregate and Recycled EPS for Concrete Blocks for Mortarless Masonry

The Utilization of Recycled Masonry Aggregate and Recycled EPS for Concrete Blocks for Mortarless Masonry

Heat Transfer Measurement within Green Roof with Incinerated Municipal Solid Waste Aggregates

Prediction of Compressive Strength Behavior of Ground Bottom Ash Concrete by an Artificial Neural Network

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