密闭室内近壁热源上方颗粒物浓度预测模型

Study on the Prediction Model of Particle Concentrations above Near-wall Heat Sources in Sealed Indoor Environments

有效预测近壁热源上方的颗粒物浓度,有助于利用热羽流贴附效应改善悬浮颗粒状况及减少有害沉积。为此,采用Grimm 1.109系列粉尘监测器对近壁热源上方的PM10、PM2.5和PM1质量浓度进行了24 h实验监测,并利用实验数据对既有颗粒物浓度预测模型进行修正,建立了密闭室内近壁热源上方颗粒物无因次浓度预测模型。研究结果表明所建立的模型能较好地预测密闭室内近壁热源上方PM10、PM2.5和PM1的无因次浓度。

The valid prediction of the particle concentrations above near-wall heat sources contributes to controlling the suspended particles by thermal plumes and reducing the harmful particle deposition. Therefore, the mass concentrations of PM10、PM2.5 and PM1 above near-wall heat sources were measured continuously for 24 hours. The existing prediction model of the particle concentrations was amended by using the experimental data. Then the prediction model of the particle dimensionless concentrations above near-wall heat sources in sealed indoor environments was established. The results indicate that this model can well predict the dimensionless concentrations of PM10、PM2.5 and PM1 above near-wall heat sources in sealed indoor environments.