Comparing the Markov Chain Model with the Eulerian and Lagrangian Models for Indoor Transient Particle Transport Simulations
Comparing the Markov Chain Model with the Eulerian and Lagrangian Models for Indoor Transient Particle Transport Simulations
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DOI：
10.1080/02786826.2015.1079587
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发表时间：
2015-10-03
影响因子：
5.2
通讯作者：
Chen, Qingyan
中科院分区：
文献类型：
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作者：
Chen, Chun;Liu, Wei;Chen, Qingyan
正确预测室内环境中的瞬时颗粒传输对于改善通风系统的设计和降低获得空气传染性疾病的风险至关重要。最近，基于马尔可夫链框架开发了一个新模型，以快速预测室内瞬态粒子传输。为了评估这一马尔可夫链模型，本研究将其与传统的欧拉和拉格朗日模型相比，就性能，计算成本和鲁棒性而言。该比较使用了四个粒子传输的情况，其中三个包括实验数据。马尔可夫链模型能够以与欧拉和拉格朗日模型相似的精度预测室内瞬时粒子传输。此外，当相同的时间步长（courant号码）
Correctly predicting transient particle transport in indoor environments is crucial to improving the design of ventilation systems and reducing the risk of acquiring airborne infectious diseases. Recently, a new model was developed on the basis of Markov chain frame for quickly predicting transient particle transport indoors. To evaluate this Markov chain model, this study compared it with the traditional Eulerian and Lagrangian models in terms of performance, computing cost, and robustness. Four cases of particle transport, three of which included experimental data, were used for this comparison. The Markov chain model was able to predict transient particle transport indoors with similar accuracy to the Eulerian and Lagrangian models. Furthermore, when the same time step size (Courant number