ISSN 1008-5548

CN 37-1316/TU

最新出版

基于气流组织数值模拟的电子工业洁净厂房通风方案

Ventilation scheme for electronic industrial cleanrooms based on numerical simulations of airflow patterns


郭二宝,蒋成鑫,张泽龙,朱星鑫,陈 琢,王 灿,王海涛

安徽建筑大学 环境与能源工程学院,安徽 合肥230601


引用格式:

郭二宝, 蒋成鑫, 张泽龙, 等. 基于气流组织数值模拟的电子工业洁净厂房通风方案[J]. 中国粉体技术, 2025, 31(6): 1-13.

GUO Erbao, JIANG Chengxin, ZHANG Zelong, et al. Ventilation scheme for electronic industrial cleanrooms based on numerical simulations of airflow patterns[J]. China Powder Science and Technology, 2025, 31(6): 1-13.

DOI:10.13732/j.issn.1008-5548.2025.06.016

收稿日期: 2024-08-27, 修回日期: 2025-05-15, 上线日期: 2025-06-14。

基金项目: 国家自然科学基金项目,编号: 42402038;安徽省教育厅质量工程项目,编号: 2023jyxm0419; 中国建设教育协会教育教学科研课题,编号: 2023062; 安徽建筑大学产学研项目,编号: HYB20240214; 安徽建筑大学教学研究项目,编号: 2023jy11;安徽省新时代育人质量工程项目(研究生教育),编号:2024lhpysfjd055,2024zyxwjxalk134。

第一作者简介: 郭二宝(1980—),男,副教授,博士,硕士生导师,研究方向为室内环境空气污染控制技术。E-mail: guoerbao_2006@sohu.com。

通信作者简介: 王海涛(1971—),男,教授,博士,硕士生导师,安徽省科技进步奖获得者,研究方向为环境污染物扩散与控制。E-mail: 263760999@qq.com。


摘要: 【目的】 为了营造符合ISO6级洁净度标准的电子工业洁净厂房并兼顾降低能源消耗,优化非单向流电子工业洁净厂房的通风方案。【方法】 采用由新风机组(make-up air unit,MAU)、风机过滤机组(fan filter unit,FFU)、干冷盘管(dry cooling coil,DCC)组成MAU-FFU-DCC通风系统,以计算流体力学(computational fluid dynamics,CFD)作为数值模拟工具模拟洁净厂房内的非单向流气流组织,在上方送风口、侧面回风口的方式下,分别采用不同的送风速度、单侧或双侧回风方式确定4种通风方案。建立洁净厂房的三维几何模型和数学模型,并进行模型的可靠性验证;通过分析不同通风方案条件下洁净厂房内非单向气流组织的温度场、压力场的分布特征以及有无上返气流现象,并以温度不均匀系数、热通风效率和空气龄作为评价指标,筛选出满足ISO6级洁净度标准的最优通风方案。【结果】4种通风方案均无上返气流现象,满足洁净厂房的温度和正压环境要求;方案S1、 S2、 S3、 S4的温度不均匀系数分别为0.012、 0.013、 0.026、 0.023,热通风效率分别为0.95、 0.96、 1.09、 1.13;双侧回风方案的热通风效率大于1,能量利用率更高,经济性良好;当送风速度分别为0.30、 0.35 m/s时,单侧回风方案S1、 S2的平均空气龄分别为75、 60 s,双侧回风方案S3、 S4的平均空气龄分别为60、 35 s;方案S2、 S3、 S4的平均空气龄满足规范要求,方案S3 比S4的送风量更小,更为节省能源。【结论】 送风速度较低时的双侧回风方案最佳,能够提供性价比高、洁净度满足国家标准的生产环境。

关键词: 电子工业洁净厂房; 气流组织; 数值模拟; 通风方案; 空气龄; 温度不均匀系数; 热通风效率

Abstract

Objective To build electronic industrial cleanrooms that comply with the ISO Class 6 cleanliness standards while reducing energyconsumption, this study focuses on optimizing non-unidirectional airflow ventilation schemes in electronic industrial cleanrooms.

Methods For the non-unidirectional airflow organization in a cleanroom utilizing a make-up air unit-fan filter unit-dry cooling coil (MAU-FFU-DCC) ventilation system, computational fluid dynamics (CFD) simulations were conducted to evaluate four ventilation schemes. These schemes varied in air supply velocities and return air configurations, such as single-side or double-side returns, all operating under an upper-supply and side-return airflow pattern. A three-dimensional geometric model and a mathematical model of the cleanroom were established, and their reliability was verified. A systematic evaluation was conducted on the distribution characteristics of temperature and pressure fields of non-unidirectional airflow organization and the potential occurrence of upward airflow recirculation across different ventilation schemes. Three performance indices, temperature inhomogeneity coefficient, thermal ventilation efficiency, and air age, were used to identify the optimal ventilation scheme that meets the ISO Class 6 cleanliness standards.

Results and Discussion In the four ventilation schemes (S1, S2, S3, and S4), the average temperatures in the cleanroom were recorded as 22.04 ℃, 21.95 ℃, 21.98 ℃, and 21.80 ℃, respectively, all of which met the regulatory requirements for temperature. All four ventilation systems maintained a positive pressure environment. Compared to schemes S2 and S4 with an air supply velocity of 0.35 m/s, S1 and S3 with an air supply velocity of 0.30 m/s had lower air supply volumes and lower airflow pressure in the airflow patterns. Under the same supply velocities, no significant difference in pressure distribution was observed between the single-side return and double-side return configurations within the cleanroom. In single-side return schemes, eddies formed due to airflow collisions with walls on the non-outlet side, whereas in double-side return systems, the air was smoothly exhausted from both sides, reducing eddy phenomena. The average airflow deflection angles measured for S1, S2, S3, and S4 were 82.4°, 83.5°, 82.1°, and 83.2° respectively, all of which were below 90°. This indicated there was no upward return airflow in any of these schemes, thus meeting the cleanroom standards. The temperature non-uniformity coefficients for S1 S2, S3, and S4 were calculated as 0.012, 0.013, 0.026, and 0.023, respectively, suggesting relatively uniform temperature distributions within the cleanroom. The thermal ventilation efficiency for these schemes reached 0.95, 0.96, 1.09, and 1.13, respectively. For the single-side return schemes, the efficiency was below 1, showing that the outlet temperatures were lower than those in the working zone. This resulted in insufficient heat exchange and energy waste. Conversely, in the double-side return schemes, the efficiency exceeded 1.0, with outlet temperatures higher than those in the working zone. This suggested more waste heat was absorbed before exhaust, leading to higher energy utilization efficiency and better economic viability. When the air supply velocities were 0.30 m/s and 0.35 m/s, the mean air ages for the single-side return schemes (S1 and S2) were 75 s and 60 s, respectively, while those for the double-side return schemes (S3 and S4) were 60 s and  35 s, respectively. The mean air ages in S2, S3, and S4 met the regulatory standards and decreased with increasing air supply velocity. Notably,S3 required less air supply than S4, offering greater energy savings. Overall, the double-side return scheme with an air supply velocity of 0.3 m/s was found to be optimal. It delivered a cost-effective production environment that satisfied national cleanliness standards.

Conclusion All four ventilation schemes demonstrate no upward airflow phenomena and meet the temperature and positive pressure requirements of the cleanroom. Among them, the double-side return scheme with an air supply velocity of 0.3 m/s is the most optimal one. It has a smaller air supply volume, conserves energy, and provides a cost-effective production environment that adheres to national cleanliness standards.

Keywords: electronic industrial cleanroom; airflow organization; numerical simulation; ventilation scheme; air age; temperature inhomogeneity coefficient; thermal ventilation efficiency


参考文献(References)

[1]赵福云, 文雅冰, 黄志荣, 等. 电子洁净室气流特性分布及颗粒物扩散数值模拟[J]. 湖南工业大学学报, 2023, 37(3): 14-20.

ZHAO F Y, WEN Y B, HUANG Z R, et al. A numerical simulation of airflow characteristics distribution and particle diffusion in electronic cleanrooms[J]. Journal of Hunan University of Technology, 2023, 37(3): 14-20.

[2]刘瓅, 刘远卓, 刘东, 等. 非单向流洁净室颗粒物浓度影响因素的正交模拟研究[J]. 洁净与空调技术, 2019(2): 9-15.

LIU L, LIU Y Z, LIU D, et al. Orthogonal numerical simulation on influencing factors of particle concentration in non-directional flow cleanroom[J]. Contamination Control & Air-conditioning Technology, 2019(2): 9-15.

[3]梁书奎, 刘禹, 邵晓亮, 等. 电子洁净厂房不同FFU风量下颗粒分布特征研究[J]. 建筑节能, 2022, 50(1): 96-101.

LIANG S K, LIU Y, SHAO X L, et al. Particle distribution characteristics of electronic industry clean room with different FFU air volume[J]. Building Energy Efficiency, 2022, 50(1): 96-101.

[4]宋业浩. 某洁净厂房气流组织的流场研究[D]. 邯郸: 河北工程大学, 2020.

SONG Y H. Study on the flow field of air distribution in a clean workshop[D]. Handan: Hebei University of Engineering, 2020.

[5]MARINOVA G I, BITRI A K. Challenges and opportunities for semiconductor and electronic design automation industry in post-Covid-19 years[J]. IOP Conference Series: Materials Science and Engineering, 2021, 1208(1): 012036.

[6]LI H K, HE H Y, SHAN J F, et al. Innovation efficiency of semiconductor industry in China: a new framework based on generalized three-stage DEA analysis[J]. Socio-economic Planning Sciences, 2019, 66: 136-148.

[7]栾鹍. 大跨度电子洁净室气流组织和污染物扩散研究[D]. 上海: 东华大学, 2023.

LUAN K. A study on airflow organization and pollutant diffusion in large-span electronic cleanroom[D]. Shanghai: Donghua University, 2023.

[8]李异, 马建平, 魏朝晖. 热风送风温差对室内环境的影响[J]. 节能技术, 2014, 32(5): 427-429, 433.

LI Y, MA J P, WEI Z H. Impact of heating supply air difference on indoor environment[J]. Energy Conservation Technology, 2014, 32(5): 427-429, 433.

[9]刘存, 胥娟, 耿诗洋, 等. 高大空间分层空调单侧送风方式下气流组织优化研究[J]. 制冷, 2020, 39(3): 59-63.

LIU C, XU J, GENG S Y, et al. Study on the optimization of air distribution of stratified air conditioning in large space[J]. Refrigeration, 2020, 39(3): 59-63.

[10]JURAEVA M, SONG D J, RYU K J. An optimum design study of the yarn-channel shape of the air-interlacing nozzle by analysis of fluid flow[J]. Textile Research Journal, 2012, 82(5): 474-483.

[11]孙照燕. SPF鸡场生物洁净室流场数值模拟研究[D]. 哈尔滨: 哈尔滨工业大学, 2007.

SUN Z Y. Numerical simulation of flow field in biological clean room of SPF chicken farm[D]. Harbin: Harbin Institute of Technology, 2007.

[12]赵福云, 王云鹤, 杨国彪. 洁净手术室空态气流组织模拟[J]. 武汉大学学报(工学版), 2020, 53(11): 986-994.

ZHAO F Y, WANG Y H, YANG G B. Numerical simulation of airflow in an empty and clean operating room[J]. Engineering Journal of Wuhan University, 2020, 53(11): 986-994.

[13]HAGHSHENAS-KASHANI S, SAJADI B. Evaluation of thermal comfort, IAQ and energy consumption in an impinging jet ventilation (IJV) system with/without ceiling exhaust[J]. Journal of Building Engineering, 2018, 18: 142-153.

[14]ROHDIN P, MOSHFEGH B. Numerical predictions of indoor climate in large industrial premises:a comparison between different k-ε models supported by field measurements[J]. Building and Environment, 2007, 42(11): 3872-3882.

[15]MA Z Y, LIU X H, ZHANG T. Measurement and optimization on the energy consumption of fans in semiconductor cleanrooms[J]. Building and Environment, 2021, 197: 107842.

[16]伊伟奇, 李浩, 李超, 等. ISO 6级洁净室换气次数确定方法的实验研究[J]. 建筑节能(中英文), 2023, 51(4): 71-76.

YI W Q, LI H, LI C, et al. Experimental study on the method of determining air change rate in a ISO 6 cleanroom[J]. Building Energy Efficiency, 2023, 51(4): 71-76.

[17]中华人民共和国住房和城乡建设部. 洁净厂房设计规范: GB 50073—2013[S]. 北京: 中国计划出版社, 2013.

Ministry of Housing and Urban-Rural Development of the People’s Republic of China. Code for design of clean room: GB 50073—2013[S]. Beijing: China Planning Press, 2013.

[18]陈龙. 候车大厅不同送风方式的热舒适性数值模拟研究[D]. 武汉: 华中科技大学, 2011.

CHEN L. Numerical simulation study on thermal comfort of different air supply modes in waiting hall[D]. Wuhan: Huazhong University of Science and Technology, 2011.

[19]王丽莎. 大空间气流组织方式数值模拟研究[D]. 北京: 华北电力大学, 2018.

WANG L S. Numerical simulation of air distribution in large space[D]. Beijing: North China Electric Power University, 2018.

[20]姚奕合. 周期性送风条件下ISO6级电子乱流洁净室排污性能增益研究[D]. 株洲: 湖南工业大学, 2024.

YAO Y H. Study on gain of sewage discharge performance of ISO6 electronic turbulence clean room under periodic air supply condition[D]. Zhuzhou: Hunan University of Technology, 2024.

[21]CHEN T S, CAO S J. Numerical study on the integrated effects of supplied air velocity and exhaust velocity on particles removal for industrial buildings[J]. Energy and Built Environment, 2021, 2(4): 380-391.

[22]HEINZ S, PEINKE J, STOEVESANDT B. Cutting-edge turbulence simulation methods for wind energy and aerospace problems[J]. Fluids, 2021, 6(8): 288.

[23]XU L L, BAI X S, JIA M, et al. Experimental and modeling study of liquid fuel injection and combustion in diesel engines with a common rail injection system[J]. Applied Energy, 2018, 230: 287-304.

[24]LIU Q, NIE W, HUA Y, et al. Research on tunnel ventilation systems: dust diffusion and pollution behaviour by air curtains based on CFD technology and field measurement[J]. Building and Environment, 2019, 147: 444-460.

[25]ZHANG Z, CHEN Q. Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms[J]. Atmospheric Environment, 2006, 40(18): 3396-3408.

[26]韩罡. ISO6级电子洁净室核心区气流组织数值研究[D]. 镇江: 江苏科技大学, 2023.

HAN G. Airflow organization in the core area of an ISO class 6 electronics cleanroom numerical studies[D]. Zhenjiang: Jiangsu University of Science and Technology, 2023.