Optimization of foam concrete characteristics using response surface methodology and artificial neural networks

Kurşuncu, Bilal; Gençel, Osman; Bayraktar, Oğuzhan Yavuz; Shi, Jinyan; Nematzadeh, Mahdi; Kaplan, Gökhan

doi:10.1016/j.conbuildmat.2022.127575

Cited by 62 publications

(17 citation statements)

References 60 publications

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“…Thus, using these wastes as additive for concrete is very important for protecting the environment but the number of studies on this subject is very limited. In some of the studies carried out on this subject, the usability of oyster shell [76], olive wastes [77], forest wastes [78], fig wastes [79], rise husk ash [80,81] and some of the other materials [82,83] as concrete additive was examined. Environmental pollution has increased dramatically, especially in the last 30 years [84][85][86] and because of the rapid development of global economy, the type and level of chemical pollution have constantly increased, and this increase has reached a terrifying level for the ecosystems [87,88].…”

Section: Discussionmentioning

confidence: 99%

Usability of Organic Wastes in Concrete Production; Palm Leaf Sample

Bayraktar

2022

KUJES

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Palm leaves are vegetal waste that are not widely used by the society, only piled up and causing odors that mix with the environment. Channeling this waste material into the construction industry helps to overcome waste disposal problems as well as promote sustainability. The most important features expected from the buildings are the creation of the most suitable environmental conditions for the products to be stored or the creatures that will live in them, and they can be used safely for a long time. In the construction of the buildings, materials that are the cheapest possible, safe and capable of creating the optimum environmental conditions should be used. The materials to be selected should have sufficient strength and durability, high heat and sound insulation and lightness. Since single-storey buildings are not subject to excessive load, it is important that the thermal insulation is high and light in material selection. Since the widespread use of concrete as a building material in the world, efforts to make concrete light, cheaper and better insulating have gained importance. Lightweight concrete, which is easy to apply, has been an important building material in recent years. With the use of lightweight concrete as a building material, benefits such as economy in terms of material, earthquake resistance, and the elimination of a second insulation material for heat and sound insulation can be achieved. In this study; Experimental study using Portland cement (CEM I), Palm Leaf, CEN standard sand and water mortar production; sample production, curing, some physical and mechanical experiments were carried out in four stages. The usability of palm leaf, which is a vegetable waste, as aggregate in concrete production by replacing it with CEN standard sand at 0, 5, 10, 20, 30 and 40% as well as 10% with cement has been investigated. The study results show that the addition of both ground palm leaf and palm leaf aggregate significantly altered almost all properties of concrete. These changes are at different levels in terms of physical properties. As a result of the study, it was determined that as the amount of foam increased, the spreading diameter increased, whereas palm leaf addition decreased the spreading diameter. It has been determined that the addition of palm leaf decreases the depth of water treatment depending on time, the porosity of the samples with high level of palm leaf addition increases and the compression and bending strength decreases.

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Section: Discussionmentioning

confidence: 99%

Usability of Organic Wastes in Concrete Production; Palm Leaf Sample

Bayraktar

2022

KUJES

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“…Remaining undegraded in nature for a long time since it has a long half-life, heavy metals that accumulate in bodies of organisms and can be toxic or carcinogenic even when at low concentrations are considered as one of the most dangerous environmental pollution factors [57][58][59][60]. For this reason, use of waste materials (especially heavy metals), many of which are important environmental pollutants, as a concrete additive is very important since it decreases the cost of concrete and it contributes to the reduction of environmental pollution by eliminating the environmental pollutants through recycling [61][62][63][64]. For this reason, many studies examining the use of various waste materials as concrete additives were carried out in recent years [65][66][67].…”

Section: Discussionmentioning

confidence: 99%

Assessing the Co, Bi, and Mg Contents of Some Mineral Concrete Additives in terms of Environmental Effects

Şevik

2022

KUJES

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Concrete additives started to be used commonly in order to reduce the cost of concrete, which is widely used in construction industry, and to recycle some wastes that are harmful to the environment. However, these additives might include heavy metals that are very harmful to human and environmental health and the number of studies on this subject is very limited. Besides the health of individuals working in this industry, it also creates a lack of knowledge about the environmental effects of construction activities. In the present study, among the heavy metals that can be very harmful to human and environmental health, Co, Bi, and Mg concentrations in some concrete additives were examined. The results showed that heavy metal concentrations in various concrete additives including copper slag, vermiculite, brick dust, Cem III cement, and blast furnace slag were very high. It might pose a risk to the health of individuals working in this industry, as well as the environmental health.

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“…Hosein et al, [21] explained the operation of ANN in a detailed manner. Bilal et al, [14] used both RSM and ANN methods for optimization of process parameters, from results they concluded that both RSM and ANN could estimate the responses but only RSM could effectively determine the parameters. The present work focuses on the effect of reinforcement wt.% and aging temperature on the hardness variation of LM4 + Si3N4 composites.…”

Section: Response Surface Methodology (Rsm) and Artificial Neural Net...mentioning

confidence: 99%

Optimization and prediction of the hardness behaviour of LM4 + Si3N4 composites using RSM and ANN: A comparative study

et al. 2022

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In the present work, LM4 + Si3N4 (1, 2, and 3 wt.%) composites were fabricated using the two-stage stir casting method. Precipitation hardening treatment was carried out on the cast composites and hardness results were compared with as-cast specimens. Microstructural analysis was performed using Scanning Electron Microscope (SEM) images to validate the existence and homogenous distribution of reinforcement in the matrix. LM4 + 3 wt.% Si3N4 composite with multistage solution heat treatment (MSHT) and aging at 100°C showed higher hardness viz., 124% improvement when compared to as-cast LM4 due to the uniform distribution of Si3N4 and precipitation of metastable phases during the heat treatment process. The microhardness values of the fabricated composites was investigated using Artificial Neural Network (ANN) and Response Surface Methodology (RSM). Both RSM and ANN models predicted hardness values close to experimental values with minimum error, and the prominence of aging temperature in the improvement of hardness was observed. The data obtained illustrate that the proposed regression model can accurately predict hardness values within the constraints of the factors under consideration. Based on the error values it can be concluded that the ANN model can deliver results with higher accuracy than the RSM model.

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Optimization of foam concrete characteristics using response surface methodology and artificial neural networks

Cited by 62 publications

References 60 publications

Usability of Organic Wastes in Concrete Production; Palm Leaf Sample

Usability of Organic Wastes in Concrete Production; Palm Leaf Sample

Assessing the Co, Bi, and Mg Contents of Some Mineral Concrete Additives in terms of Environmental Effects

Optimization and prediction of the hardness behaviour of LM4 + Si3N4 composites using RSM and ANN: A comparative study

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