Energy Performance and LCA-driven Computational Design Methodology for Integrating Modular Construction in Adaptation of Concrete Residential Towers in Cold Climates

Adaptation of dated residential towers is an urgent issue due to aging housing infrastructure and growing demand for affordable housing. Computational design methodologies have the potential for facilitating optimized design strategies driven by improved energy performance and reduced life-cycle carbon emissions. Modular Construction (MC) can also increase efficiencies in the design and implementation of building adaptation projects and minimize construction waste. The application of MC in the adaptation of existing buildings is gaining interest with improvements to MC technologies and processes, as well as large-scale adoption. There are currently no frameworks for the integration of MC in the adaptation of complex buildings driven by energy performance and Life Cycle Analysis (LCA). To address this gap, a framework is developed for integrating computational design methodologies and design optimization using energy use and LCA for improving overall building adaptation processes. The building adaptation of Ken Soble Tower in Hamilton, Ontario, is used for the functional demonstration. A set of extension modules are considered, and various adaptation scenarios that conform to set design constraints are evaluated for energy use and LCA. The results of this study prove the practicality of using computational design methodologies for the integration of MC in the adaptation of concrete residential towers and can promote the efficiency of improving existing residential infrastructure.