Building performance simulation promises to reduce the future impact of buildings on the environment by helping architects predict the energy demand associated with different design options. We present a new method for simulating occupant behavior in buildings, a key phase in the prediction of energy use. Our method first inputs the recorded activities of actual building occupants, then randomly generates fictional schedules with similar behavioral patterns. The main contribution of this work is a mathematical technique in which an arbitrary set of factors can be used to select plausible activity types, durations, and numbers of participants during a simulation. A prototype model was implemented to test the method, and results obtained to date suggest that the generated occupant schedules are believable when compared both qualitatively and quantitatively to real occupant schedules.
Anticipating building-related complexities ensuing from occupants' behaviour is a major challenge in architectural design. Conventional building performance simulation tools model occupancy in a highly aggregated form, abstracting away the impact of dynamic spatial and social factors on occupant behaviour. To address this issue, we propose a multi-agent system that accounts for these aspects in process-driven facilities, such as hospitals. The approach involves modelling 'narratives', rule-based scripts that direct occupants' movement and shared activities. A scheduling mechanism employs Operations Research techniques to dynamically coordinate the narratives' execution. We demonstrate the method by simulating dayto-day operations in a typical hospital setting, involving scheduled procedures and unscheduled adaptations due to dynamic social and environmental conditions. The process involved collecting data using field observations and interviews with experts, modelling narratives, and simulating them to produce use scenarios that can be visualized and analysed by design stakeholders.
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