Title of the research: A Framework for Façade Retrofitting Decision-Making to Decarbonize Buildings
under the supervision of Prof. Ursula Eicker, Prof. Carmela Cucuzzella and Prof. Hua Ge
Abstract: Façades are central to building decarbonization, yet façade knowledge remains fragmented across three disconnected domains: architectural theory, data modelling, and retrofit decision-making. This thesis addresses that gap through three integrated contributions. First, it develops a structured categorization of contemporary façades, a three-part architectural taxonomy (Utilitarian, Formal, Image) validated against 11 Canadian buildings, alongside a technical classification of five sustainable façade systems (Smart Skin, Kinetic, Vertical Greenery, Solar, Double-Skin). Second, it builds a Façade Data Model (FDM) in UML/Ecore, structuring 33 façade parameters into a simulation-ready, standards-aligned schema. Third, it synthesizes both into a five-stage, multi-criteria retrofit decision-making framework, demonstrated through energy simulations across 90 Montreal social-housing buildings. Results show retrofit effectiveness depends more on envelope compactness than glazing ratio alone. Together, these contributions bridge architecture and data science, offering a reusable pathway from façade categorization to data-driven retrofit decisions, while transparently identifying where further empirical validation is still needed.