In recent decades, architects have turned to computer simulation with the hope of designing more functional, sustainable, and compelling buildings. In such efforts, it is important to regard buildings not merely as static structures, but rather as complex dynamic systems driven by highly stochastic elements including the weather and human behavior. In this chapter, we describe how simulation has impacted architectural design research and practice. A multitude of simulation tools have been developed to model specific aspects of a building such as thermodynamics, daylight, plug loads, crowd behavior, and structural integrity under internal and external loads. Yet numerous challenges remain. For example, although many factors influencing buildings are interdependent, they are often analyzed in isolation due to the development cost associated with integrating solvers. A systems approach combining visual programming with state-of-the-art modeling and simulation techniques may help architects and building scientists combine their expertise to produce integrated complex systems models supporting emerging paradigms such as generative design.
While traditional programming practices have produced a wide range of relatively independent simulation methods, predictive models of extremely complex natural and artificial systems will require a more scalable, more collaborative approach to modeling. This project strives for software that will help researchers develop, debug, document, share, and integrate simulation code.
Buildings are the largest consumers of energy responsible for 48% of all Green House Gas (GHG) emissions. Due to the complexity and multidisciplinary aspects of architectural design, construction, urban design, and building occupant behavior, simulation has gained attention as a means of addressing this enormous challenge. The idea is to model a building’s many interacting subsystems, including its occupants, electrical equipment, and indoor and outdoor climate. With simulation results in hand, an architect is better able to predict the energy demand associated with various designs, and choose from among the more sustainable options.