Identification of Critical Factors Influencing Early Age Creep of High Strength Concrete Using Artificial Neural Networks

Ensuring precise estimation of creep characteristics is critical for the efficient design of structures prone to creep deformation.Creep is an indicator of permanent and gradual deformation that transpires within a material when it is continuously subjected to a burden for an extended duration.In addition to the temperature and duration of load application, the degree of creep in concrete is also affected by the material's inherent properties and the length of time it has been exposed to the load.The enduring consequences of creep might result in significant distortions that give rise to structural deficiencies inside the edifice.Multiple factors, including the concrete's mixing ratios and compressive strength, affect the initial hardening of the material.The data pertaining to the early creep behaviour of high-strength concrete were gathered from relevant literature sources for the purposes of this study.The research utilised artificial neural network methodology and relative importance analysis to ascertain the most influential parameters on the early creep behaviour of high-strength concrete.Understanding the components that contribute to creep is crucial in mitigating the detrimental effects of creep on concrete and concrete structures.