Correctly predicting contaminant transport in enclosed environments is crucial for improving interior layouts to reduce infection risks. Using the measured airflow field as input to predict the contaminant transport may overcome the challenges of measuring complex boundary conditions and inaccurate turbulence modeling in the existing methods. Therefore, this study numerically explored the feasibility of predicting contaminant transport from the measured airflow field. A stand-alone Markov chain solver was developed so that the calculations need not rely on commercial software. Airflow information from CFD simulation results, including the three-dimensional velocity components and turbulence kinetic energy, was used as surrogate for experimental measurement based on the spatial resolution of ultrasonic anemometers. Three cases were used to assess the feasibility of the proposed method, and the calculation results were compared with the benchmark calculated by the commercial CFD software. The results show that, when the airflow was simple, such as that in an isothermal ventilated chamber, the stand-alone Markov chain solver based on the measured airflow field predicted the trend of contaminant transport and peak concentrations reasonably well. However, for complex airflow, such as that in non-isothermal chambers with heat sources or occupants, the solver can reasonably predict only the general trend of contaminant transport.

正确预测封闭环境中的污染物传输对于改善室内布局以降低感染风险至关重要。使用测得的气流场作为输入来预测污染物传输，可以克服现有方法中测量复杂边界条件和不准确湍流建模的挑战。因此，本研究从数值上探讨了从实测气流场预测污染物迁移的可行性。开发了一个独立的马尔可夫链求解器，​​因此计算不需要依赖商业软件。来自 CFD 模拟结果的气流信息，包括三维速度分量和湍流动能，被用作基于超声波风速计空间分辨率的实验测量的替代。通过三个案例来评估所提出方法的可行性，并将计算结果与商业CFD软件计算的基准进行比较。结果表明，当气流很简单时，例如在等温通风室中，基于实测气流场的独立马尔可夫链求解器可以较好地预测污染物迁移趋势和峰值浓度。然而，对于复杂的气流，例如在具有热源或居住者的非等温室中的气流，求解器只能合理地预测污染物传输的总体趋势。例如，在等温通风室中，基于测量气流场的独立马尔可夫链求解器可以合理地预测污染物迁移趋势和峰值浓度。然而，对于复杂的气流，例如在具有热源或居住者的非等温室中的气流，求解器只能合理地预测污染物传输的总体趋势。例如，在等温通风室中，基于测量气流场的独立马尔可夫链求解器可以合理地预测污染物迁移趋势和峰值浓度。然而，对于复杂的气流，例如在具有热源或居住者的非等温室中的气流，求解器只能合理地预测污染物传输的总体趋势。