Grammar-based generation of strut-and-tie models for designing reinforced concrete structures

Abstract

Reinforced concrete structures featuring discontinuity regions are complex to design and often susceptible to errors linked to numerical analysis methods. For such structural design problems, strut-and-tie models offer a simple, intuitive and safe design method based on the lower bound theorem of plasticity. Although intuitive, the derivation of strut-and-tie models requires nonnegligible effort and a certain degree of expertise to navigate the highdimensional design space. The automated generation of strut-and-tie models is nontrivial with existing optimisation-based methods, which struggle with accounting for fabrication aspects or incorporating user adaptations.

This paper presents a novel grammar-based approach for generating practical strut-and-tie models by representing them as graphs and constructing a graph grammar. It consists of rules customised to consider engineering judgement, significantly reducing the dimensionality of the design space. The sequential application of such rules allows for human-computer interaction and aids engineers in decision-making, while being kept in the loop. Parsing four common design examples from the literature demonstrates the efficacy of this approach. The developed designs are more practical compared with existing optimisation-based suggestions. This interpretable grammar-based approach closely follows the intuitive decision-making process of practising structural engineers, which could be adapted to support further structural engineering design tasks.