Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582532
Title: Automatic synthesis of architectural structures using an evo-devo approach to design
Author: Richards, Daniel
Awarding Body: Manchester Metropolitan University
Current Institution: Manchester Metropolitan University
Date of Award: 2013
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Abstract:
To address important global challenges regarding climate change and urbanisation, architects and engineers require new methods of designing efficient, performance- oriented structures. An emerging approach looks to nature for inspiration and seeks to utilise computation early within the design process to create bio-inspired, performance-driven structures. Indeed, natural structures are often much more complex and efficient than anything we can design by hand, thus the ability to harness nature's underlying processes in computation would provide significant advances for architectural design and contribute new territories for performance- oriented design. However, existing computational models are limited to addressing relatively simple design problems and have not yet been able to synthesise complex material structures as nature does. This research proposes a new and interdisciplinary trajectory for architectural design which focuses on computational processes of form generation that require minimal direct human guidance. Significantly, it is argued that such models could provide ways of dealing with complex design problems and thereby greatly extend existing approaches. Using a series of experiments, this research proposes, develops and interrogates a novel computational model which is inspired by principles gene regulation and evolutionary-developmental biology. The results contribute a novel method of automatically designing efficient material-based structures, from scratch, and demonstrate rich trajectories for further research in the emerging field of computational design synthesis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.582532  DOI: Not available
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