Since 2006, the Delft University of Technology has been working on the development of bacterial self-healing concrete (BSHC). The self-healing ability of this concrete is based on a biological mechanism, in which mineral producing bacteria are added to repair cracks autonomously.
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Since 2006, the Delft University of Technology has been working on the development of bacterial self-healing concrete (BSHC). The self-healing ability of this concrete is based on a biological mechanism, in which mineral producing bacteria are added to repair cracks autonomously. This not only improves the durability of concrete structures, but could also reduce the need for crack-limiting reinforcement. So far, bacterial self-healing technology has been used in variety of applications, especially watertight structures, but always only as an additional safety measure. Hence, the full crack-sealing capacity, related to the reinforcement reduction potential, could not be proven. This will have to be resolved in a dedicated full-scale demonstrator project. For this demonstrator project, a rectangular water reservoir has to be designed, which will essentially serve as a test case for the newly developed bacterial self-healing technology. This thesis aims to devise the concrete mixture and reinforcement layout for the side walls of this reservoir in such a way that imposed deformations induce a given degree of cracking at an early-age, which allows to demonstrate the crack-sealing capacity and reinforcement reduction potential of BSHC. The design of a concrete mixture intended for the side walls of the reservoir led to four different mixtures, all of which have a cement content of 418 kg/m³ (26% of CEM I 52.5 R and 74% CEM III/B 42.5 N), but vary in the addition of filler in the form of limestone powder and healing agent; a mixture of bacteria and calcium lactate encapsulated in PLA strings. The mixtures with healing agent, which represent BSHC, are meant for side wall A, whereas the mixtures without healing agent representing ordinary concrete can be used for side wall B, so it can serve as a reference. To investigate the effect of these additions, as well as to verify the designs and quantify the relevant physical and mechanical properties of the concrete mixtures, several tests were conducted. These revealed that the mixtures with filler exhibit a higher consistency, improved cohesiveness and more prosperous strength development compared to the mixtures without filler. Both the fresh properties and strength development were not affected by the addition of healing agent. Furthermore, it was found that the addition of filler causes autogenous shrinkage to increase by about 15%, whereas the addition of healing agent causes autogenous shrinkage to decrease by about 20%. From the cracking calculations it is concluded that it is very likely that the early-age cracking of the side walls of the reservoir occurs as a consequence of imposed deformations. Cement hydration causes a large temperature rise, resulting in significant thermal shrinkage due to the subsequent temperature drop. The imposed deformations are restrained by the floor of the reservoir, as well as the foundation material underneath. This results in a maximum probability of cracking of 65% and 93% according to two different methods. In order to demonstrate the true crack-sealing capacity of BSHC, if is preferred to obtain various crack widths along the length of the side walls and the reinforcement layout must be configured to allow this to happen. Therefore, several methods that deal with the prediction of crack widths are implemented in this case. Based on the average of all prediction methods it is found that the following crack widths occur given the longitudinal reinforcement distribution in brackets: 0.09 (Ø20-100), 0.20 (Ø20-160), 0.31 (Ø20-210) and 0.43 mm (Ø20-250). However, it was also discovered that the mutual differences between the prediction methods are very large, in particular at lower reinforcement ratios. But then again, a reinforcement layout divided into multiple sections, consisting of the aforementioned longitudinal reinforcement distributions, offers the best chance of demonstrating self-healing ability.
