热羽流与置换通风作用下油雾颗粒预测模型

王非; 孟钦鹏; 翁文兵; 耿宇; 王昕

doi:10.7638/kqdlxxb-2023.0048

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热羽流与置换通风作用下油雾颗粒预测模型

研究论文 | 更新时间：2026-05-28

- 热羽流与置换通风作用下油雾颗粒预测模型
- Prediction model of oil mist particles under the effects of heat plume and displacement ventilation
- 空气动力学学报 2024年42卷第3期页码：119-128
- 作者机构：
  
  上海理工大学环境与建筑学院,上海,200093
- 作者简介：
  
  王非*（1982—），男，博士，实验师，研究方向：建筑设备自动控制技术. E-mail：wangfei@usst.edu.cn
- 基金信息：
  
  国家自然科学基金面上项目（52278116）;机械工业联合会重点实验室创新平台项目（2019SA-10-07）
- DOI：10.7638/kqdlxxb-2023.0048
  中图分类号： TU83;X831
- 纸质出版：2024
- 稿件说明：
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王非, 孟钦鹏, 翁文兵, 等. 热羽流与置换通风作用下油雾颗粒预测模型[J]. 空气动力学学报, 2024, 42(3): 119−128.

WANG Fei, MENG Qinpeng, WENG Wenbing, et al. Prediction model of oil mist particles under the effects of heat plume and displacement ventilation[J]. 2024, 42(3): 119-128.
王非, 孟钦鹏, 翁文兵, 等. 热羽流与置换通风作用下油雾颗粒预测模型[J]. 空气动力学学报, 2024, 42(3): 119−128. DOI： 10.7638/kqdlxxb-2023.0048

WANG Fei, MENG Qinpeng, WENG Wenbing, et al. Prediction model of oil mist particles under the effects of heat plume and displacement ventilation[J]. 2024, 42(3): 119-128. DOI： 10.7638/kqdlxxb-2023.0048.

摘要

高大空间机械厂房采用置换通风系统时，存在竖直方向油雾颗粒浓度分布不均匀的现象。这种现象会影响以降低室内颗粒浓度为目的的需求通风量。为了快速预测竖向油雾颗粒浓度分布，采用区域模型建模方法，考虑壁面流区、热羽流区和主流区等主要区域，基于质量平衡与能量平衡方程，建立了竖向油雾颗粒浓度分布预测模型；同时在实验舱内进行了实验验证，模型计算结果与实验结果趋势相符，最大相对误差不大于20%，表明该模型能够基本满足工程要求；以5种颗粒散发率工况为例进行节能分析，发现引入预测模型后计算得到的置换通风系统需求通风量可比传统变风量系统通风设计方法计算的减少18.83%～44.41%。该预测模型能较为准确地预测高大厂房中置换通风时竖向不同高度的油雾颗粒浓度，可应用于需要快速预测竖向颗粒平均浓度的场景。

Abstract

The vertical inhomogeneous particle concentration in a large-space machining workshop with a displacement ventilation system will increase the required ventilation volume for indoor particle concentration reduction. The present work presents a particle concentration prediction model using a zonal modeling method that can rapidly predict the vertical particle concentration distribution for the energy-saving performance analysis of the ventilation system. The model

which takes the wall heat plume zone

heat source heat plume zone

and main airflow zone into account

can obtain the inter-regional airflow based on the energy balance and continuity equations and predict the zonal particle concentration based on the mass balance equations using particle emission rates and inter-regional airflow. A validation experiment conducted in a scaled chamber demonstrates that the relative error of the prediction model is less than 20%

it shows that the model can basically meet the engineering requirements. Further study of the prediction model by a case study under five particle emission conditions showed that the required air volume supply can be reduced by 18.83% to 44.41% compared to the traditional method used on variable air volume system. Overall

the prediction model can accurately and rapidly predict the vertical particle concentration distribution in large-space machining workshops under displacement ventilation

showing promising prospects in optimizing the performance of the ventilation system.

关键词

Keywords

references

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