The adaptive reuse of historic masonry buildings presents a nuanced challenge, requiring a delicate balance between structural stability and preservation goals. This study introduces an innovative computational approach aimed at identifying modifications to shear wall layouts during the adaptive reuse process. The primary objective is to redefine structural wall arrangements to accommodate new openings and/or cuts in existing structural elements, offering designers flexibility in spatial arrangement modifications. Central to this approach is the utilization of a Genetic Algorithm, inspired by evolutionary principles, as a potent tool for deriving potential layout solutions that adhere to structural requirements while facilitating the incorporation of new openings. The strategy is defined aiming to maximize material reuse, minimize existing elements in the design, and minimize the building’s eccentricity. Design solutions are evaluated according to their compliance to these objective functions, respecting structural constraints in terms of compressive capacity, and shear and torsion effects. By systematically evolving potential solutions over multiple generations, the algorithm navigates the intricate design space to pinpoint areas within the original shear layout where material can be removed, all while respecting the unique constraints inherent to unreinforced masonry structures. The methodology’s validity is demonstrated through a case study situated in a UNESCO World Heritage Site, providing tangible evidence of the practical application and success of the genetic algorithm approach in real-world scenarios. The findings presented in this paper contribute to the convergence of structural engineering and architectural preservation, offering a systematic and efficient means of determining shear wall layouts for the adaptive reuse of unreinforced masonry buildings. The integration of genetic algorithms into the adaptive reuse process holds transformative potential, establishing a robust framework for sustainable urban development that honors and enhances the historical fabric of our built environment.
Learning Objectives:
Understand a process for identifying which structural elements can be removed during the adaptation process.
Describe the principles and application of Genetic Algorithms in the context of optimizing shear wall layouts for the adaptive reuse of historic masonry buildings.
Evaluate the effectiveness and practicality of integrating computational approaches into heritage-led reuse projects, considering factors such as structural stability, material reuse, and preservation of historical integrity.
Understand how computational tools can be used to effectively to explore design possibilities, generate potential solutions, and evaluate their alignment with structural requirements and preservation objectives in practical contexts.