从一个房间到另一个房间的空气流动可以通过考虑空气的整体流动的网络流模型来近似。这种模型可以预测区域间的空气分布，但不能预测区域内的气流状况。另一方面，如果充分注意边界条件、初始条件和网格定义的说明，计算流体力学可用于以高精度预测室内空气流动。这两种建模技术都支持污染物迁移和行为预测模型。 为了克服个别技术的缺点，这两种方法在一个集成的建模框架内结合起来。除CFD外，预测污染物浓度的方法还使用了三种溶液程序。其中包括污染物分布和传输方程（稀疏线性系统）的建立和求解，气流方程（非线性系统）的建立和求解，以及建筑热方程（稀疏非线性系统）的建立和求解- 线性系统）。本文提出了一种集成这些方法的方法，以便准确预测室内和室内空气流动和污染物分布。单位:SICitation:ASHRAE Transactions，第114卷，pt。2008年1月1日，纽约

The flow of air from one room to another may be approximated by network flow models which consider the bulk flow of air. Such models can predict inter-zone air distributions but cannot predict intra-zone air flow conditions. Computational fluid dynamics, on the other hand, can be used to predict intraroom air flows with a high degree of accuracy provided sufficient care is taken in specification of boundary conditions, initial conditions and grid definition. Contaminant transport and behavior prediction models are supported by both modeling techniques. To overcome shortcomings of the individual techniques, both methods are combined within an integrated modeling framework. The methodology for prediction of contaminant concentration uses three solution procedures in addition to CFD. These involve the setting up and solution of contaminant distribution and transport equations (a sparse linear system), the setting up and solution of air flow equations (a non-linear system) and the setting up and solution of building thermal equations (a sparse non-linear system). This paper presents a method to integrate these approaches in order to accurately predict both inter- and intra-room air flows and contaminant distributions.Units: SI