A grammar-based framework for strut-and-tie modelling of reinforced concrete structures

Abstract

Strut-and-tie models offer a simplified design approach for reinforced concrete structures such as walls or beams and are particularly suitable for static or geometrical discontinuities. They guarantee designs that are safe based on the lower bound theorem of the theory of plasticity. Currently, their manual generation demands significant time and expertise to navigate the solution space for various configu rations with different objectives in mind. Automating the generation of strut-and-tie models has faced several challenges, with previous methods such as discrete layout optimisation or topology optimisation struggling to consider either (i) user adjustments, such as changes of nodal coordinates, or (ii) practical aspects of fabrication and constructability. In response, this work presents a novel grammar-based generative framework that imposes strict and constraining rules, tailored to strut-and-tie models. Unlike previous work, our framework incorporates engineering judgement directly into its rule set, thereby significantly reducing the design space. Fur thermore, the sequential application of rules allows for user intervention and thus human-computer in teraction in the sense of a design co-pilot. We demonstrate the effectiveness of this framework through its application to two use cases: a cantilevered beam with a point load at its end and a dapped-end beam with an opening and two acting loads. The truss structure is represented as a graph and the rules are applied akin to graph grammar. Compared to optimisation-based methods, the developed models are practical, consider the preference towards orthogonal and distributed reinforcement and are typically preferred by professional structural engineers. This marks a first step towards an AI-assisted, grammar based generative design approach for strut-and-tie models. The framework offers interpretability that closely mirrors the intuitive decision-making process employed by human engineers in the selection of suitable strut-and-tie models.