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addressing simulation challenges are derived from two disciplinary domains, each informed by its own respective fields of expertise:

1.  Meteorologists and climatologists have introduced constraining anthropogenic sources in prognostic weather and climate models to better understand urban heat islands as well as outdoor air quality and contaminant dispersion in cities.

2.  Building scientists have explored weather and climate forcing for airflow, energy, and contaminate simulations in and around buildings to understand building energy consumption, ventilation/infiltration, and contaminant dispersion.

The connection among all of these disparate fields of study is the universal system of transport equations solved numerically for appropriate temporal and spatial scales. The solution of transport equations typically includes mass and momentum equations to solve the airflow field, while the addition of partial differential equations to represent scalars, such as temperature and contaminant concentrations, or solid phase for particles are problem specific. The required computational power to directly solve these partial differential equations is enormous. For example, the fastest petaflops supercomputers allow up to approximately 1012 grid resolution that is only sufficient to solve simple indoor airflows in a single room, where a typical Reynolds number is 105. Directly solving an outdoor airflow problem is impossible, as Reynolds numbers are on the order of 107. Therefore, the required grid resolution for a simple outdoor airflow problem would be close to 1016. As a compromise, building simulations have to be based on accurate physical models that can be successfully implemented and solved with the available computational power.

For the past couple of decades, modeling of buildings was accomplished using several approximations that were quite important for understanding physical transport processes in and around buildings even as we were gaining access to unprecedented computational power. More recently, those models are being coupled in unifying simulation platforms, and novel methods for leveraging different models are being discovered. For example, multizone modeling (MZ), energy simulations (ES), and computational fluid dynamics (CFD) based on Reynoldsaveraged Navier-Stokes equations all have their strengths and weaknesses in modeling building transport processes. MZ can predict infiltration rates, bulk flow, and contaminant transport; ES can predict building energy consumption; while CFD can predict detailed airflow, temperature, and contaminant concentrations. For the same simulation domain of a single building, MZ typically requires seconds, ES takes minutes, and CFD needs hours to run a model on a personal computer. This is due to different levels of model complexity, which correspond to the level of details that each model provides. No matter how simple or complex, each of

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