Improving Facility Performance Prediction by Formalizing an Activity-Space-Performance Model

The design, construction, and operation of high-performing facilities depends on the ability of planners and designers to predict the future performance of a facility with reasonable accuracy and granularity, and tailor the performance to support the facility users' business and operational requirements and activities. However, today's design and engineering methods are not able to predict, document and communicate the performance of facilities with sufficient accuracy and granularity to allow the users to select the building design that works best for them. Thus, we develop a logical framework that enables planners and designers to connect users, their activities, and spaces to generate activity-space pairs. We then formalize the relationships between activity-space pairs and two performance metrics (i.e., space utilization and energy consumption) to provide space-level prediction of these metrics. Our model provides the rationale for tailoring functional performance by providing information of activity-space pairs and by shedding light on who this information affects other performance, such as space utilization and energy consumption.