﻿ 大型邮轮典型舱室气流分布及污染物传播数值模拟
 舰船科学技术  2022, Vol. 44 Issue (5): 37-44    DOI: 10.3404/j.issn.1672-7649.2022.05.008 PDF

1. 浙江国际海运职业技术学院，浙江 舟山 316021;
2. 中国船舶科学研究中心，江苏 无锡 214082

Numerical simulation of air distribution and pollutant transport in typical cabin of major cruise
TANG Jing1, SU Jing2, ZHUO Hong-ming1, LI Yun1, PANG Jun1
1. School of Shipbuilding, Zhejiang International Maritime College, Zhoushan 316021, China;
2. China Ship Scientific Research Center, Wuxi 214082, China
Abstract: This article carries out numerical simulation of air distribution and pollutant transport in typical four cabin of major cruise based on CFD by RNG k- $\varepsilon$ turbulence equation. It compares the advantages and disadvantages of cabin air flow performance of four typical air distribution form. And it studies the law of droplet propagation after a cough. The research shows that the airflow form of upper supply air and upper return air by diffuser has better airflow performance and ADPI is close to 90 percent. The displacement ventilation form from the bottom and supply air from the top has better energy utilization coefficient. People are the least likely to be infected by displacement ventilation and are most likely to be infected by mixing ventilation. The air distribution form has great influence on the concentration of head droplet of personnel in each position.The same side people has higher probability to be infected by mixing ventilation and negative pressure cabin ventilation. The other side people has higher probability to be infected by displacement ventilation. This study has practical significance for the cabin layout and ventilation system configuration of large cruise ships in the context of novel Coronavirus global pandemic.
Key words: CFD     air distribution performance     aeration mode     pollutant transport
0 引　言

1 计算方法及验证 1.1 计算方法

1.1.1 数学模型

 $\frac{\partial }{{\partial t}}\left( {\rho \varphi } \right) + \frac{\partial }{{\partial {x_j}}}\left( {\rho {u_j}\varphi } \right) = \frac{\partial }{{\partial {x_j}}}\left( {{\varGamma _\varphi }\frac{{\partial \varphi }}{{\partial {x_j}}}} \right) + {S_\varphi } 。$ (1)

1.1.2 求解假设条件

1.1.3 软件设置

1.2 计算方法验证

 图 1 房间物理模型 Fig. 1 Room physical model

 图 2 实验测量值与CFD计算值对比（圆圈表示实验测量值） Fig. 2 Comparison between experimental value and CFD value (circle indicates experimental value)
2 工况设置 2.1 几何模型

 图 3 几何模型示意图 Fig. 3 Schematic diagram of geometric model

 图 4 气流组织形式示意图 Fig. 4 Schematic diagram of air distribution

2.2 人员咳嗽边界条件

 图 5 人员1咳嗽的角度 Fig. 5 Angle of cough of person 1

 图 6 咳嗽的速度曲线 Fig. 6 Velocity curve of cough
3 气流组织评价指标

 $\Delta ET = \left( {{t_i} - {t_N}} \right) - 7.66\left( {{{\rm{u}}_{\rm{i}}} - 0.15} \right)。$ (2)

 $ADPI=\frac{-1.7\leqslant \Delta ET\leqslant +1.1的测点数}{总测点数}\times 100\text{%} 。$ (3)

 $\gamma = \frac{{\left( {{t_{{p}}} - {t_0}} \right)}}{{\left( {{t_{{n}}} - {t_0}} \right)}}。$ (4)

4 气流性能结果分析

4.1 主要参数结果分析

4.2 全局温度分布分析

 图 7 四种方案各截面温度分布（单位：K） Fig. 7 Temperature distribution at each section of the four schemes (unit: K)

 图 8 不同高度和水平位置测点温度对比 Fig. 8 Temperature comparison of measuring points at different heights and horizontal positions
5 污染物传播结果分析

 图 9 人员头部上方液滴的浓度（115s） Fig. 9 Concentration of droplets above the head of a person (115s)

 图 10 方案4不同时刻舱内液滴的传播情况（浓度5E-13） Fig. 10 Droplet propagation in The chamber at different times of Scheme 4 (concentration 5E-13)
6 结　语

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