ABSTRACT
Building Information Modelling (i.e., BIM) has been widely applied in civil engineering structures and infrastructures. Long-term performance of structures is of significance in whole life management, and BIM provides a useful tool to assess the durability of civil engineering structures at the design stage. Cracking is a significant durability problem in reinforced concrete structures as it destroys the integrity of the structures and causes premature failure. It is therefore desirable to predict the cracking of reinforced concrete structures and integrate the model in BIM platform so that better-informed decisions can be made for designers in terms of repairs and maintenance. In this paper, the Finite Element Method (FEM) and Artificial Neural Network (ANN) are combined to predict concrete cracking over time. The combined method is achieved in the BIM Application Programming Interface (API) to realise the whole life management. Moreover, maintenance strategies are developed which have an impact on structure bearing capacity and cost analysis. Meanwhile, optimised construction process decision could be made to allow designers and practising engineers to understand the serviceability and economic situation of the structures easily.
