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    Social distancing enhanced automated optimal design of physical spaces in the wake of the COVID-19 pandemic

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    Publication date
    2021-05
    Author
    Ugail, Hassan
    Aggarwal, R.
    Iglesias, A.
    Howard, N.
    Campuzano, A.
    Suarez, P.
    Maqsood, M.
    Aadil, F.
    Mehmood, Irfan
    Gleghorn, S.
    Taif, K.
    Kadry, S.
    Muhammad, K.
    Show allShow less
    Keyword
    Automatic optimal design
    Computer aided design
    Physical spaces
    Covid-19
    Pandemic
    Social distancing measures
    Peer-Reviewed
    Yes
    Open Access status
    closedAccess
    
    Metadata
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    Abstract
    As the COVID-19 pandemic unfolds, manually enhanced ad-hoc solutions have helped the physical space designers and decision makers to cope with the dynamic nature of space planning. Due to the unpredictable nature by which the pandemic is unfolding, the standard operating procedures also change, and the protocols for physical interaction require continuous reconsideration. Consequently, the development of an appropriate technological solution to address the current challenge of reconfiguring common physical environments with prescribed physical distancing measures is much needed. To do this, we propose a design optimization methodology which takes the dimensions, as well as the constraints and other necessary requirements of a given physical space to yield optimal redesign solutions on the go. The methodology we propose here utilizes the solution to the well-known mathematical circle packing problem, which we define as a constrained mathematical optimization problem. The resulting optimization problem is solved subject to a given set of parameters and constraints – corresponding to the requirements on the social distancing criteria between people and the imposed constraints on the physical spaces such as the position of doors, windows, walkways and the variables related to the indoor airflow pattern. Thus, given the dimensions of a physical space and other essential requirements, the solution resulting from the automated optimization algorithm can suggest an optimal set of redesign solutions from which a user can pick the most feasible option. We demonstrate our automated optimal design methodology by way of a number of practical examples, and we discuss how this framework can be further taken forward as a design platform that can be implemented practically.
    URI
    http://hdl.handle.net/10454/18945
    Version
    No full-text in the repository
    Citation
    Ugail H, Aggarwal R, Iglesias A et al (2021) Social distancing enhanced automated optimal design of physical spaces in the wake of the COVID-19 pandemic. Sustainable Cities and Society. 68: 102791.
    Link to publisher’s version
    https://doi.org/10.1016/j.scs.2021.102791
    Type
    Article
    Collections
    Engineering and Informatics Publications

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