Properties and Strength Prediction Modeling of Green Mortar with Brick Powder Subjected to a Short-Term Thermal Shock at Elevated Temperatures
| Autor: | Roman Fediuk, Renata Polak, Maciej Szeląg, Joanna Styczeń |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Thermal shock
Technology Materials science mechanical properties intelligent modeling Article Flexural strength Thermal brick powder General Materials Science Composite material Porosity Cement Brick Microscopy QC120-168.85 QH201-278.5 Engineering (General). Civil engineering (General) Intelligent modeling TK1-9971 Descriptive and experimental mechanics mortar Electrical engineering. Electronics. Nuclear engineering Mortar TA1-2040 |
| Zdroj: | Materials, Vol 14, Iss 6331, p 6331 (2021) Materials Volume 14 Issue 21 |
| ISSN: | 1996-1944 |
| Popis: | The cement industry is responsible for 8% of global CO2 production. Therefore, a clear trend has been observed recently to replace to some extent the main binder of cement composites with environmentally friendly or recycled materials with a lower carbon footprint. This paper presents the effect of brick powder (BP) on the physico-chemical and mechanical properties of cement mortars. The effect of a short-term thermal shock on morphology and strength properties of green mortars was investigated. BP addition caused increase in porosity and decrease in compressive and flexural strength of mortars. The best results were obtained for samples with 5% wt. BP addition. Above this addition the strength decreased. The mechanical performance of the samples subjected to thermal loading increased compared to the reference samples, which is the result of a process called as the “internal autoclaving”. The BP addition positively affects the linear shrinkage, leading to its reduction. The lowest linear shrinkage value was achieved by the mortar with the highest BP addition. An intelligent modeling approach for the prediction of strength characteristics, depending on the ultrasonic pulse velocity (UPV) is also presented. To solve the model problem, a supervised machine-learning algorithm in the form of an SVM (support vector machines) regression approach was implemented in this paper. The results indicate that BP can be used as a cement replacement in cement mortars in limited amounts. The amount of the additive should be moderate and tuned to the features that mortars should have. |
| Databáze: | OpenAIRE |
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