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Artificial Intelligence Approach in Predicting the Effect of Elevated Temperature on the Mechanical Properties of PET Aggregate Mortars: An Experimental Study

  • Research Article-Civil Engineering
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Abstract

In this study, the effect of high temperature on the flexural and compressive strength of mortars containing waste PET aggregates was investigated experimentally. The mortar samples prepared in 5 different concentrations with a total of 2.5%, 5%, 10%, 20% and 30% PET aggregate substitution were heated up to 100, 150, 200, 250, 300 and 400 °C. After waiting for 1, 2 and 3 h at these temperatures, flexural and compressive strength tests were performed. It was observed that flexural strength and compressive strength values decreased with increasing temperature and PET aggregate amounts in all mixtures. An artificial neural network was designed to estimate flexural and compressive strength values using experimental data. It has been observed that the developed artificial neural network can predict flexural and compressive strengths with an average error of − 0.51%.

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Abbreviations

ANN:

Artificial neural network

HDPE:

High density polyethylene

HSC:

High-strength concrete

MSE:

Mean square error

PET:

Polyethylene terephthalate

PVC:

Polyvinyl chloride

RSM:

Response surface methodology

A c :

Cross-sectional area (mm2)

b :

Narrow edge length of the sample section (mm)

d :

Height of the sample section (mm)

f c :

Compressive strength

L :

The distance between the support rollers (mm)

P :

Applied force (N)

t :

Time (h)

T :

Temperature (°C)

σ :

Flexural strength (MPa)

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Authors and Affiliations

  1. Department of Mechanical Engineering, Engineering Faculty, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey

    Andaç Batur Çolak

  2. Department of Civil Engineering, Engineering Faculty, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey

    Kubilay Akçaözoğlu & Gülhan Beller

  3. Department of Architecture, Faculty of Architecture, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey

    Semiha Akçaözoğlu

Authors
  1. Andaç Batur Çolak
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  2. Kubilay Akçaözoğlu
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  3. Semiha Akçaözoğlu
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  4. Gülhan Beller
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Correspondence to Andaç Batur Çolak.

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Çolak, A.B., Akçaözoğlu, K., Akçaözoğlu, S. et al. Artificial Intelligence Approach in Predicting the Effect of Elevated Temperature on the Mechanical Properties of PET Aggregate Mortars: An Experimental Study. Arab J Sci Eng 46, 4867–4881 (2021). https://doi.org/10.1007/s13369-020-05280-1

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  • DOI: https://doi.org/10.1007/s13369-020-05280-1

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