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In the case of presence of deep micro-cracks within the composite structures, they must be replaced. The self-healing phenomenon which is inspired from the biological systems such as vascular networks in plants or capillary networks in animals, is an appropriate strategy to control the defects and micro-cracks. In the present research, by taking accounts the advantages of self-healing concept, an attempt has been made to control the micro-cracks and damages which were created in composite structures. To do so, series of micro glass tubes were employed to provide a self-healing system. These micro-tubes were filled with epoxy resin/anhydride hardener as a healing agent. When the structure is subjected to loading conditions, some damages or micro-cracks are created. In this situation, the micro glass tubes will rupture and the healing agent flows in the damage area, leading to the elimination of the defects over a time span. The aim of this study is to find out the appropriate self-healing material volume fraction and healing time to obtain an efficient healing. For this purpose, glass micro-tubes containing various healing agent loadings of 0.75, 1.65 and 2.5 vol.% were incorporated in epoxy-carbon fibers composites and the tensile behavior of the specimens were assessed during different time span from defect creation. The highest tensile strength recovery of 89% was observed for the specimen with 1.65 vol.% healing agent. Also the results show presence of micro tube decrease the fracture strain and over the time span fracture strain recovered.

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The occurrence of damage is considered as an unavoidable fact in fibrous polymers. For this reason, the self-healing systems could extend the service life time of materials by implementing the concept of autonomous or induced repair. In the present study, a self-healing E-glass fibers/epoxy composite based on micro-vascular channels has been designed and fabricated. The specimens were fabricated via the hand lay-up route, while the fabrication of micro-vascular channels was conducted through the removing of solid preforms. Due to the lack of previous studies about the utilization of anhydride resin-hardener system with lower viscosity and also their controllable miscibility in comparison to the amine systems, in the present work, these materials were selected as healing agent for repairing the primary defects created in the structure. For this purpose, mico vascular channels containing two various parts of epoxy resin and anhydride hardener (2, 3.2, and 3.7 Vol.% with respect to the matrix part) were incorporated in the structure of composites. The flexural behavior of the specimens was assessed during the different time span (0, 4, 8 and 11 days) from the primary damage creation. After the defect creation in the structure, the healing agents present in the micro vascular channels are flow into the defects and after the combining with catalysis dispersed in the matrix, local polymerization process and restoring of properties are started. According to the obtained results in this research, the highest flexural strength recovery of 46% was observed for the specimen with 3.2% healing agent after 8 days.

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In this research work, the self-healing behavior of epoxy matrix composite which reinforced by hollow glass fibers as self-healing container was investigated. For doing this, in first step, the hollow glass fibers were filled with the epoxy resin and hardener by creating a partial vacuum. Then, the filled hollow glass fibers with different percent of 1, 3 and 5 vol.% were embedded in the epoxy matrix. In the next step, by applying press, the destruction was created in these composites. Then, these destructed composites were healed at ambient temperature at different times of 2, 4, 7 and 14 days. Then, for accessing to the optimum healing time and percentage of hollow fibers in composite, the flexural test was applied in these composites. In the final step, the mechanical properties of composite with the optimum healing time and percentage of reinforcement were evaluated via tensile, flexural and impact exams. The obtained results show that the optimum percentage of hollow fibers and time for healing process are 3 vol.% and 7 days. Also, the healing efficiency of composite in optimum conditions (3 vol.% hollow fibers and 7 days healing time) at tensile, flexural and impact exams were approximately 77, 54 and 92 % respectively.

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Abstract:
Concrete is the most widely made construction material in the structural engineering world. Advantages such as high compressive strength, availability of raw materials, and low preparation cost make concrete one of the most important used construction materials. Under harsh environmental conditions, aggressive agents such as sulfates and chlorides penetrate the concrete through these cracks to damage the concrete. While concrete cracks are not only expensive to repair, they are often hard to detect as well. It is now identified that the strength of concrete alone is not sufficient, the degree of harshness of the environmental condition to which concrete is exposed over its entire life is very important. Self-healing concrete is a type of concrete that has the ability to repair itself without the need for an external agent during cracking. Concrete containing microorganisms has self-healing properties. The self-healing agent contains a specific concentration of bacteria with a nutrient in the concrete that produces calcium carbonate while the water and environmental conditions are suitable for the concrete. In this research, four different specimens of concrete have been made. Concrete containing microorganisms is made in two different concentrations of bacterium bacillus pasteurization (10⁷,10⁹ cells/ml) and calcium lactate nutrients and is compared with concrete containing silica fume, concrete containing latex and control concrete. In all four specimens, the same mix design was used with a water/cement ratio of 0.48 and containing silica fume, latex polymer, and calcium lactate, which replaced cement in different percentages. Specimens were subjected to compressive, flexural, and tensile strength tests at 7 and 28 days of operation, and the results were compared. The results showed that the best performance among all specimens for concrete containing silica fume and self-repair agent (bacteria and brain material) increased compressive strength and reduced tensile and flexural strengths compared to the controlled specimens. The use of a self-healing agent in concrete increases the compressive strength of concrete, but this increase is not as great as the increase in silica fume. Bacteria with a higher concentration have a negative effect on the compressive strength of concrete so that more use of bacteria in concrete increases the compressive strength to such an extent that it even reduces the compressive strength compared to the concrete strength of the control specimens. The self-healing agent reduces the flexural and tensile strength of concrete, as opposed to silica fume but they are better than latex and produce better results.

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Today, the use of self-healing concretes has attracted the attention of various researchers. In this paper, the effect of Bacillus subtilis bacteria with different concentrations were used for evaluation on concrete containing zeolite.The mentioned bacteria were produced in the laboratory and added to the concrete mixing plan. In order to evaluate the effect of Bacillus subtilis bacteria on specimen with zeolite, resistance and durability tests including compressive strength, ultrasonic, water penetration test and water absorption tests were performed on the specimen at different ages. Also, using scanning electron microscope (SEM) and optical microscope, the self-healing of concrete was evaluated. The results of the compressive strength test showed that the specimen containing zeolite with a concentration of 2.8×10⁸ cells/ml increased the compressive strength by 16.76% and the specimen without zeolite increased the compressive strength by 13.51%. Also, the presence of Bacillus subtilis bacteria in the mixing design led to a 15% decrease in water absorption of specimens without zeolite and 30% of specimens with zeolite. Based on the results of the experiments, the most suitable concentration, for the simultaneous improvement of the resistance parameters and durability among the different concentrations of Bacillus subtilis bacteria, is suggested to be 2.8 x 10⁸.

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Improving the self-healing performance of warm mix asphalt depends on several factors and parameters that are highly interdependent and have significant complexity. In this study, the self-healing performance of warm mix asphalt was investigated using artificial intelligence and artificial neural network of multi-layer perceptron and radial base with two hidden layers. To conduct this study, two additives Sasobit and Zycotherm were used. The three-point bending test was performed at two temperatures of 25 and -16 degrees Celsius and with two crack lengths of 10 and 20 mm, and the fracture toughness, fracture energy and critical load indices were determined for each of the states. Asphalt samples were subjected to induction heating at two frequencies of 87 and 88 kHz and three induction times of 60, 90 and 120 seconds. The results of sensitivity analysis in two artificial neural network models showed that in the MLP network, the fracture toughness parameter had the greatest impact on the output. It was also observed that the test temperature parameter had the highest sensitivity coefficient in the RBF network. The results showed that in the perceptron neural network with two layers in the test section, the root mean square error (RMSE) values increased from 10.46 in the first model to 4.27 in the fourth model. The results of the basic radial artificial neural network showed that the addition of input parameters reduced the root mean square error (RMSE) value of the test section from 10.56 to 4.35. The results of MLP and RBF network estimation have shown that the addition of input variables to the model has increased NS in all three parts of test, train and validation. In this way, in the MLP network, the value of NS in the test section has reached from 0.45 to 0.90 and the estimation accuracy has doubled. In the RBF network, similarly to MLP, with the addition of the NS parameter, the NS value has increased from 0.44 to 0.90. Also, the results of this study showed that in both types of MLP and RBF networks, the value of R² in the second group was higher than the first group in all test, train and validation sections. In general, the results of this study showed that the artificial neural network has appropriate performance and accuracy due to the nature of learning and the ability to train from the previous laboratory results in estimating the self-healing ability and modeling the complex relationship of the influential input variables, and the use of the proposed intelligent model by reducing the of experiments and cost can be effective in evaluating the self-healing behavior of warm mix asphalt.