الفهرس 
AbstractOnly 14 pages are availabe for public view
 |  | from | 314 |  |  |
| | | from | 314 | | |
Abstract
from the concrete cracking point of view, self-healing of concrete is important to regain the performance of concrete structurally. Bio concrete, a type of self-healing concrete, can be utilized to deal with cracks by providing a special type of bacteria along with a calcium-based nutrient to the ingredients of the concrete during the mixing process. Once the cracks seem, bacteria in the concrete would be activated by help oxygen and water then begin calcium carbonate (calcite) precipitation which can fill the pores and cracks inside concrete which help making the concrete resistive to be penetrated so self-healing concrete is considered a relatively “smart” material. -Research scope : This thesis investigated the relationships between the proportions of nutrients, bacteria, and the bacterial concentration on the properties of self-healing concrete and mortar. -Research objective: produced self-healing concrete and mortar by using three types of bacteria. Investigate the effects of varying proportions of five factors (type of bacteria and nutrients, concentration of bacteria, and bacteria and nutrients/cement ratio) on the properties of self-healing concrete and mortar. Investigate the steps of bacteria culture and the preparation of cell suspensions of bacteria with various concentrations. to obtain self-healing of invisible cracks in concrete and mortar. Investigate the performance of self-healing concrete and mortar under the influence of a solution of sodium sulfate by assessing changes in compressive strength. Investigate machine learning models using the Python programming language to predict the properties of self-healing concrete. -Steps of study : This thesis assesses the mechanical properties and durability. The microstructure analysis of the bacteria concrete has been done utilized SEM, Energy Dispersive Spectrometer (EDS), and XRD to ensure that calcium carbonate has indeed filled the cracks. Thermogravimetric analysis (TGA) was performed to determine the degree of hydration. The PyCharm software was used to train, test, and run the different models. -Conclusions: The results show a tremendous development in all the properties of self-healing concrete and mortar, this can be attributed to the filling of cracks by calcite which was confirmed by SEM, EDS, and XRD. Also, the results confirmed that bacteria reduce chloride penetration into the concrete and improved the resistance to sulfate attack. The results of python models demonstrate that python can be successfully applied to establish accurate and reliable prediction models.