Description
The optimisation of civil infrastructures maintenance and management is a challenging task, disseminated of open issues requiring the synergic development of effective structural health monitoring systems and reliable models to be addressed. Relevant to concrete structures, models cannot disregard the multi-physics nature of the problem: moisture and heat transport phenomena in uncracked and cracked conditions, the ingress of aggressive agents and the ensuing chemical reactions - that the latter may trigger - heavily affect the mechanical performance. Most of the mentioned processes happen at a scale typically smaller than the structural one. Then, it is also necessary to perform multiscale analysis, capable of adapting structural models upon the insights resulting from lower scale analyses.
In the last decade, the Multiphysics-Lattice Discrete Particle Model (M-LDPM) has been successfully adopted to model a wide range of phenomena in civil engineering involving concrete structural members: ageing, environment-induced degradation, shrinkage, creep, and usage of advanced construction materials. Furthermore, the discrete nature of the model has shown the capability of predicting the cracking patterns accurately. However, such comprehensive and accurate model simulates the material at the mesoscale, and computational and theoretical burdens pave the path towards the exploitation of the insights resulting from lower scale modelling at the structural level.
In this work a review of the state-of-the-art concepts that allow upscaling micro- and mesoscale mechanical and multiphysics models is presented to explore alternatives for the formulation of computationally efficient macroscale models that leverage on the predictive quality of M-LDPM, in capturing and predicting the material constitutive behaviour, and the computational affordability that features the classical Finite Element Method for the structural analysis of complex systems. Finally, a preliminary proposal for the model upscaling is presented.
