Finite element modelling of cracking behaviour of reinforced concrete tensile members using a phase field approach

Abstract

Modelling the cracking behaviour of reinforced concrete (RC) elements remains a major challenge due to the inherent heterogeneity of concrete and the complex interaction with steel reinforcement. Existing finite element (FE) approaches are restricted to simplified 2D representations, depend on predefined crack paths, or do not incorporate the material heterogeneity of RC in three dimensions. This study presents a 3D FE framework in Abaqus to model the cracking behaviour of RC tie elements, combining a phase field formulation with stochastic random fields (RF) to represent spatial variability in tensile strength and fracture toughness. Parametric studies demonstrate the influence of key modelling parameters, including the phase field length scale, solution scheme, and correlation length of the RF. The numerical results are validated against experimental data from RC tie tests in the literature, and demonstrate good agreement in the global load–displacement response and localised crack patterns. The study shows that the proposed approach is a robust predictive tool able to capture the uncertainty arising from local material heterogeneity, and can simulate diverse crack initiation and propagation scenarios in RC

The authors acknowledge the support provided by the Spanish Ministry of Science, Innovation and Universities (MICIU/AEI) through the project PID2023-150934NB-C32/MICIU/AEI/10.13039/501100011033/FEDER, UE; M.B. acknowledges the support provided by the Agency for Management of University and Research Grants (AGAUR) Generalitat de Catalunya resolution REU/551/2022 for the support grants for university departments and research units aimed at the recruitment of pre-doctoral research staff in training in Catalonia (FI-SDUR 2022) ref. BDNS 612831; L.C. acknowledges the grant RYC2021-032171-I funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR ”. Open Access funding provided thanks to the CRUE-CSIC agreement with Elsevier.