Predicting mechanical properties of self-healing concrete with Trichoderma Reesei Fungus using machine learning

Abstract

AbstractTrichoderma Reesei is a mesophilic and filamentous fungus. It is an anamorph of the fungus Hypocrea jecorina, in addition, T. reesei can secrete large amounts of cellulolytic enzymes and form dextrose PDA (potato dextrose agar) and potato injection. After the preparation of fungi, it is added to the cracked samples. The experimental samples were 150 mm3 cubic compression and 70 mm x 30 mm x 15 mm cracks on the surface of each cube. Different fungi water extracts were used with 0, 50.5, 6.37, and 8.42 liters of water per ml. The results show that the addition of 8.42 (ml) of the mushroom extract with one liter of water has the maximum compressive strength with more than 18.99 MPa for 28 days, 16.7 for 14 days, and 14.5 for 7 days. In this study, linear regression, lasso regression, and rigid regression have been used to predict compressive strength, also the cooperation between mushroom juice per milliliter and compressive strength has been predicted. To find the accuracy, Correlation Coefficient (R2), Mean Absolute Errors (MAE), and Root Mean Square Error have been used. The results of machine learning show that the results of linear regression and rigid regression R2 were more than 0.98. In addition, the relationship compressive strength prediction results showed that R2 for fungi broth with one liter of water was 5.05 mL was more than 0.98. Finally, this study shows that the fungus Trichoderma reesei is an effective agent for curing concrete and improving the compressive strength of concrete.

Keywords

• Self-healing concrete
• Trichoderma Reesei Fungus
• fungi
• compressive strength
• machine learning
• Shukla Sanjay Kumar, School of Engineering, Edith Cowan University, Joondalup, Australia