Editorial on Special Issue "Performance Prediction, Durability and Modelling of Concrete Materials and Structures".

Concrete is one of the construction industry's most essential and commonly used materials. The papers of Duan et al. [[4]] and Amin et al. [[5]] used the machine-learning technique to estimate the neutralization depth of concrete bridges and the compressive strength of rice-husk-ash-blended concrete, respectively. The authors proposed a new approach to test the performance of concrete during a sulfate attack under practical conditions, based on the residual tensile strength of concrete briquet specimens, according to ASTM C307. Of the papers featured in this issue, the prediction of modeling and concrete material parameters are discussed in [[1], [3], [5]], wherein advanced numerical simulations are used to model the permeability, compressive strength, porosity, neutralization depth, etc. [Extracted from the article]