Despite cement’s superior performance and inexpensive cost compared to other industrial materials, crack development remains a persistent problem in concrete. Given the comparatively low tensile strength, when cracks emerge, a pathway is created for gas and water to enter the cementitious matrix, resulting in steel reinforcement corrosion which compromises the durability of concrete. Superabsorbent hydrogels have been developed as a novel material for enhancing the characteristics of cementitious materials in which they have been demonstrated to decrease autogenous shrinkage and encourage self-healing. This study will detail the design and application of polyelectrolyte hydrogel particles as internal curing agents in concrete and provide new findings on relevant hydrogel–ion interactions. When hydrogel particles are mixed into concrete, they generate their stored water to fuel the curing reaction that results in less cracking and shrinkage, thereby prolonging the service life of the concrete. The interaction of hydrogels with cementitious materials is addressed in this study; the effect of hydrogels on the characteristics and self-healing of cementitious materials was also studied. Incorporating hydrogel particles into cement decreased mixture shrinkage while increasing the production of particular inorganic phases within the vacuum region formerly supplied by the swollen particle. In addition, considering the control paste, cement pastes containing hydrogels exhibited less autogenous shrinkage. The influence of hydrogels on autogenous shrinkage was found to be chemically dependent; the hydrogel with a delayed desorption rate displayed significantly low shrinkage in cement paste.
Effect of microstructure on the formability of the stainless sheet metals is a major concern for engineers in sheet industries. In the case of austenitic steels, existence of strain-induced martensite ($${\alpha }^{^{\prime}}$$ α ′ -martensite) in their micro structure causes considerable hardening and formability reduction. In the present study, we aim to evaluate the formability of AISI 316 steels with different intensities of martensite via experimental and artificial intelligence methods. In the first step, AISI 316 grade steels with 2 mm initial thicknesses are annealed and cold rolled to various thicknesses. Subsequently, the relative area of strain-induced martensite are measured using metallography tests. Formability of the rolled sheets are determined using hemisphere punch test to obtain forming limit diagrams (FLDs). The data obtained from experiments were further utilized to train and validate an artificial neural fuzzy interfere system (ANFIS). After training the ANFIS, predicted major strains by the neural network are compared to a new set experimental results. The results indicate that cold rolling has unfavorable effects on the formability of this type of stainless steels while significantly strengthens the sheets. Moreover, the ANFIS exhibits satisfactory results in comparison to the experimental measurements.
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