Thermal Behavior and Energy Efficiency of Modified Concretes in the Tropical Climate: A Systemic Review

Numerical Analysis of Experimental Research in a Lightweight Floor System (LFS) with Heat Diffuser

The article presents the results of research on a lightweight floor system (LFS) with a heat diffuser made of metal lamellae. It differs from traditional layered floors in the absence of a screed layer, which reduces thermal inertia and predisposes it to be used with renewable energy sources. As part of the research, a real model of the floor, consisting of nine ceramic tiles, was made. Polyurethane adhesive was used to connect the individual layers of this composite. The model was subjected to a thermal action. It was constructed with the measuring equipment consisting of strain gauges. These were located at the boundaries of the composite layers and measured the material's deformation. The measurement results were verified by numerical calculations. For this purpose, a computational model was made using FEM (finite element method). Comparable results of deformations were obtained (the differences did not exceed 6.1%), which made it possible to perform numerical calculations of light floor materials stresses. Additionally, the displacement of the tested model was measured and numerically verified. The results of these verifications can be useful not only in the heated/cooled LFS with aluminium lamellae, but also in other building partitions inside and outside the building.

Effect of Steel Fiber on the Strength and Flexural Characteristics of Coconut Shell Concrete Partially Blended with Fly Ash

The construction industry relies heavily on concrete as a building material. The coarse aggregate makes up a substantial portion of the volume of concrete. However, the continued exploitation of granite rock for coarse aggregate results in an increase in the future generations’ demand for natural resources. In this investigation, coconut shell was used in the place of conventional aggregate to produce coconut shell lightweight concrete. Class F fly ash was used as a partial substitute for cement to reduce the high cement content of lightweight concrete. The impact of steel fiber addition on the compressive strength and flexural features of sustainable concrete was investigated. A 10% weight replacement of class F fly ash was used in the place of cement. Steel fiber was added at 0.25, 0.5, 0.75, and 1.0% of the concrete volume. The results revealed that the addition of steel fibers enhanced the compressive strength by up to 39%. The addition of steel fiber to reinforced coconut shell concrete beams increased the ultimate moment capacity by 5–14%. Flexural toughness was increased by up to 45%. The span/deflection ratio of all fiber-reinforced coconut shell concrete beams met the IS456 and BS 8110 requirements. Branson’s and the finite element models developed in this study agreed well with the experimental results. As a result, coconut shell concrete with steel fiber could be considered as a viable and environmentally-friendly construction material.

Effects of Admixtures on Energy Consumption in the Process of Ready-Mixed Concrete Mixing

The production and utilization of concrete and concrete-based products have drastically increased with the surge of construction activities over the last decade, especially in countries such as China and India. Consequently, this has resulted in a corresponding increase in the energy used for the production of ready-mixed concrete. One approach to reduce the cost of concrete manufacturing is to reduce the energy required for the manufacturing process. The main hypothesis of this study is that the power required for mixing the concrete can be reduced through the use of mineral admixtures in the mix design. Optimization of energy consumption during mixing using admixtures in concrete manufacturing is the predominant focus of this article. To achieve this objective, power consumption data were measured and analyzed throughout the concrete mixing process. The power consumption curve is the only source to distinguish the behavior of the different materials used in the concrete in a closed chamber. In the current research, fly ash and ground granulated blast-furnace slag (GGBS) were used as mineral admixtures to produce ready-mixed concrete. The experimental study focused on the influence of GGBS and fly ash on power consumption during concrete mixing. The results indicated that the use of a higher content of GGBS is more beneficial in comparison to the use of fly ash in the mix due to the lower mixing time required to achieve homogeneity in the mixing process. It was found that the amount of energy required for mixing is directly related to the mixing time for the mix to achieve homogeneity.

Artificial Neural Network-Forecasted Compression Strength of Alkaline-Activated Slag Concretes

The utilization of ordinary Portland cement (OPC) in conventional concretes is synonymous with high carbon emissions. To remedy this, an environmentally friendly concrete, alkaline-activated slag concrete (AASC), where OPC is completely replaced by ground granulated blast-furnace slag (GGBFS) industrial waste, is one of the currently pursued research interests. AASC is not commonly used in the construction industry due to limitations in experience and knowledge on the mix proportions and mechanical properties. To circumvent great labour in the experimental works toward the determination of the optimal properties, this study, therefore, presents the compressive strength prediction of AASC by employing the back-propagation artificial neural network (ANN) modelling technique. To construct this model, a sufficiently equipped experimental databank was built from the literature covering varied mix proportion effects on the compressive strength of AASC. For this, four model variants with different input parameter considerations were examined and the ideal ANN architecture for each model with the best input number–hidden layer neuron number–output number format was identified to improve its prediction accuracy. From such a setting, the most accurate prediction model with the highest determination coefficient, R2, of 0.9817 was determined, with an ANN architecture of 8-18-1 containing inputs such as GGBFS, a fine to total aggregate ratio, sodium silicate, sodium hydroxide, mixing water, silica modulus of activator, percentage of sodium oxide and water–binder ratio. The prediction accuracy of the optimal ANN model was then compared to existing ANN-based models, while the variable selection was compared to existing AASC models with other machine learning algorithms, due to limitations in the ANN-based model. To identify the parametric influence, the individual relative importance of each input variable was determined through a sensitivity analysis using the connection weight approach, whose results indicated that the silica modulus of the activator and sodium silicate greatly affected the AASC compressive strength. The proposed methodology demonstrates that the ANN-based model can predict the AASC compressive strength with a high accuracy and, consequently, aids in promoting the utilization of AASC in the construction industry as green concrete without performing destructive tests. This prediction model can also accelerate the use of AASC without using a cement binder in the concrete matrix, leading to produce a sustainable construction material.

A Sustainable Reuse of Agro-Industrial Wastes into Green Cement Bricks

The fabrication of bricks commonly consumes relatively high natural resources. To reduce the carbon footprint in the brick production industry, repurposing industrial wastes in the making of sustainable bricks is a recent trend in research and application. Local wastes, such as oil palm shell (OPS), palm oil fuel ash (POFA), and quarry dust (QD), are massively produced annually in the palm oil-exporting countries. Moreover, QD from mining industries is hazardous to both water and air quality. For better waste management in marching towards sustainability, these wastes should be given their second life as construction materials. Therefore, this paper investigates the possibility of incorporating agro-industrial wastes into the brick mixture by examining their properties by means of several standardized tests. For the mix design, a 100% replacement of coarse aggregate with OPS, 20% replacement of cement with POFA, 20% cement weight of limestone as admixture, and 0 to 50% replacements of fine aggregate with QD are experimentally considered. The optimum mix of these wastes is preliminarily determined by focusing on high compressive strength as an indicator. Other examinations include splitting tensile, flexural strength, water absorption, and efflorescence tests. Although the agro-industrial waste cement brick is 18% lower in the strength to weight ratio compared to that of conventional, it is observed that it has better late strength development due to its POFA pozzolanic properties. Moreover, the proposed green cement brick is further checked for compliance with several standards for feasible use in the construction industry. Financially, the cost for the brick with the new mix design is almost equivalent to that of conventional. Hence, this green cement brick is reasonable to be employed in the construction industry to promote material sustainability for better waste management.