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Integration of chaos theory and mathematical models in building simulation: Part I: Literature review

Clements-Croome, D. , Lu, X. and Viljanen, M. (2010) Integration of chaos theory and mathematical models in building simulation: Part I: Literature review. Automation in Construction, 19 (4). pp. 447-451. ISSN 0926-5805

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To link to this item DOI: 10.1016/j.autcon.2010.01.002


Current mathematical models in building research have been limited in most studies to linear dynamics systems. A literature review of past studies investigating chaos theory approaches in building simulation models suggests that as a basis chaos model is valid and can handle the increasingly complexity of building systems that have dynamic interactions among all the distributed and hierarchical systems on the one hand, and the environment and occupants on the other. The review also identifies the paucity of literature and the need for a suitable methodology of linking chaos theory to mathematical models in building design and management studies. This study is broadly divided into two parts and presented in two companion papers. Part (I) reviews the current state of the chaos theory models as a starting point for establishing theories that can be effectively applied to building simulation models. Part (II) develops conceptual frameworks that approach current model methodologies from the theoretical perspective provided by chaos theory, with a focus on the key concepts and their potential to help to better understand the nonlinear dynamic nature of built environment systems. Case studies are also presented which demonstrate the potential usefulness of chaos theory driven models in a wide variety of leading areas of building research. This study distills the fundamental properties and the most relevant characteristics of chaos theory essential to building simulation scientists, initiates a dialogue and builds bridges between scientists and engineers, and stimulates future research about a wide range of issues on building environmental systems.

Item Type:Article
Divisions:Science > School of the Built Environment
ID Code:18268
Publisher:Elsevier Science

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