Author: Xavier Estrella

The practice of architecture and structural engineering has undergone a significant revolution over the last two decades due to the introduction of technological tools and computational methods to optimize, speed up, and standardize design procedures. Lately, the development of Artificial Intelligence (AI) methods has proven to be a game-changing paradigm for the architecture and structural engineering practice, helping to tackle complex problems with low resource requirements. However, the structural design of buildings remains a resource-intensive and time-consuming phase, requiring personnel highly experienced in building standards, structural methods, modelling software, and building economy. In this context, AI-powered tools capable of assisting the structural design of buildings at early stages have prominent potential to increase the competitiveness and performance of commercial design offices, aiming at reducing operational costs and yielding optimal designs in terms of structural utilization, space distribution, and construction schedule. In this context and in view of the promising market prospect, the iBuilt project aims to develop a novel AI-powered product for assisted building structural design, with the goal of providing practitioners and commercial design offices with a tool that allows (1) open structural and architecture exploration at early project phases, (2) code-compliant structural design during the building conception, and (3) structural/cost/emissions optimization at the project detailing phases. It is expected that the results of the iBuilt project will set the technical, scientific, and engineering foundations (as well as shortcomings and future challenges) for the upcoming development of a robust commercial AI-powered tool for assisted building design.

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