Blucher Design Proceedings 2017
DOI: 10.5151/sigradi2017-059
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CONVIS: A tool enabling uninterrupted operation during refurbishments of complex buildings

Abstract: Clash Detection refers to the identification of geometrical overlaps within a Building Information Model (BIM). This paper seeks to extend the notion of overlapping to activities: Given a construction site within a building, we seek to find clashes between construction activities and occupant routines. Such a situation is often encountered in the context of refurbishments of complex buildings operating 24/7 (e.g. airports, train stations, hospitals, prisons). By finding the influence radii of adverse effects r… Show more

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Cited by 2 publications
(2 citation statements)
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“…This contribution is a continuation of previous work [1] in identifying clashes between regular operation and construction activities. It builds on a three-dimensional cellular automaton representing the built environment, in which we spatially embed…”
Section: Introductionmentioning
confidence: 63%
“…This contribution is a continuation of previous work [1] in identifying clashes between regular operation and construction activities. It builds on a three-dimensional cellular automaton representing the built environment, in which we spatially embed…”
Section: Introductionmentioning
confidence: 63%
“…In our work, we have reformulated this problem into a simplified model in which we can describe refurbishments as a sequence of operations acting on interior walls (create/delete) and thereby also on rooms (merge/split/enlarge/shrink) which we are also able to relocate. The succession of operations mimics a project plan for a refurbishment project, where the order of activities is equally important to their implementation (Coraglia and Wurzer 2017). Apart from being able to enter operations in our tool 'Refurb' , we also check whether all required installations and previous qualities still present, so that the "feeling" is more or less the same in the new or modified space.…”
Section: Introductionmentioning
confidence: 99%