Grant: Alliance Grants

This project addresses the need for advanced structural engineering solutions to ensure building safety under severe wind conditions, a gap in current Canadian building codes. The objective is to develop a machine learning algorithm to predict wind behavior around various building shapes, including irregular ones, under different wind loads. Key milestones include extensive wind tunnel testing, creating an aerodynamic database, developing predictive models, and validating them. The deliverable is a subscription-based webpage offering these models, enhancing structural safety and resilience in urban environments. This project is a collaboration with i2R Systems, this partnership facilitates practical application of the project's outcomes, ensuring effective commercialization and broader adoption of advanced wind engineering solutions across Canada. The project will significantly benefit Canada by improving building codes and construction practices, enhancing public safety, and fostering innovation in the engineering industry. Economically, it will reduce the costs associated with wind tunnel testing and increase efficiency in building design, leading to faster project completions and higher quality constructions. Environmentally, it will promote sustainable urban development by optimizing building designs to withstand severe weather, reducing the need for repairs and lowering the overall environmental impact. Societally, it will ensure safer communities by improving the resilience of buildings to extreme winds, protecting lives and property.