Full Text:   <2929>

Summary:  <2191>

CLC number: TQ021.4

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2018-09-12

Cited: 0

Clicked: 4783

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jing-feng Li

https://orcid.org/0000-0002-5780-3192

Li-min Qiu

https://orcid.org/0000-0003-1943-8902

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2018 Vol.19 No.10 P.746-757

http://doi.org/10.1631/jzus.A1700632


A parametric sensitivity study by numerical simulations on plume dispersion of the exhaust from a cryogenic wind tunnel


Author(s):  Jing-feng Li, Kai Wang, Xiao-bin Zhang, Xia Zhou, Li-min Qiu

Affiliation(s):  Institute of Refrigeration and Cryogenics, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   Limin.Qiu@zju.edu.cn

Key Words:  Cryogenic wind tunnel, Plume dispersion, Computational fluid dynamics (CFD), Phase change


Jing-feng Li, Kai Wang, Xiao-bin Zhang, Xia Zhou, Li-min Qiu. A parametric sensitivity study by numerical simulations on plume dispersion of the exhaust from a cryogenic wind tunnel[J]. Journal of Zhejiang University Science A, 2018, 19(10): 746-757.

@article{title="A parametric sensitivity study by numerical simulations on plume dispersion of the exhaust from a cryogenic wind tunnel",
author="Jing-feng Li, Kai Wang, Xiao-bin Zhang, Xia Zhou, Li-min Qiu",
journal="Journal of Zhejiang University Science A",
volume="19",
number="10",
pages="746-757",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1700632"
}

%0 Journal Article
%T A parametric sensitivity study by numerical simulations on plume dispersion of the exhaust from a cryogenic wind tunnel
%A Jing-feng Li
%A Kai Wang
%A Xiao-bin Zhang
%A Xia Zhou
%A Li-min Qiu
%J Journal of Zhejiang University SCIENCE A
%V 19
%N 10
%P 746-757
%@ 1673-565X
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1700632

TY - JOUR
T1 - A parametric sensitivity study by numerical simulations on plume dispersion of the exhaust from a cryogenic wind tunnel
A1 - Jing-feng Li
A1 - Kai Wang
A1 - Xiao-bin Zhang
A1 - Xia Zhou
A1 - Li-min Qiu
J0 - Journal of Zhejiang University Science A
VL - 19
IS - 10
SP - 746
EP - 757
%@ 1673-565X
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1700632


Abstract: 
The low temperature plume exhausted from a cryogenic wind tunnel may sink down, posing a severe threat to public health and safety. Quantitative risk assessment of cryogenic plume flow behavior therefore plays an important role in the design and optimization of a cryogenic wind tunnel. A numerical model with a modified Hertz-Knudsen relation considering the phase change physics of the small quantity of water involved is applied to analyze the dispersion of the low temperature nitrogen plume exhausted from a 0.3 m cryogenic wind tunnel. The homogeneous multiphase flow is modeled using the single-fluid mixture model. A model validation is presented for the exhaust plume from the US National Transonic Facility (NTF). The predicted results are found to be better than those predicted by National Aeronautics and Space Administration (NASA)’s two-stage analytical model. The influences of the environmental wind speed, the environmental wind temperature, the relative humidity, and the exhaust flow rate, on low temperature nitrogen plume dispersion are obtained. In particular, the parametric sensitivities of different influence factors are analyzed. The environmental wind temperature and the exhaust flow rate of the nitrogen gas have greater impact on the temperature of the plume near the ground than do the environmental wind speed and the relative humidity. The exhaust flow rate of the nitrogen gas has greater impact on the oxygen concentration near the ground than does the environmental wind speed, while the environmental wind temperature and the relative humidity have negligible impacts. The results provide guidance on the operation and design improvement of a cryogenic gaseous nitrogen discharge system to avoid its potential hazards.

This is an interesting manuscript dealing with the plume dispersion of the exhaust from a cryogenic wind tunnel by numerical simulations. In this work, the influences of wind speed, wind temperature, relative humidity and exhaust flow rate on low temperature nitrogen plume dispersion are investigated, as well as their parametric sensitivities. This manuscript is significant with regard to offering useful information on the operation and design improvement of a cryogenic gaseous nitrogen discharge system to avoid the potential hazards.

基于数值模拟的低温风洞羽流扩散过程的参数敏感性分析

目的:低温风洞运行时大流量低温氮气被排放到大气环境中,对周围环境造成潜在的低温、缺氧危险.本文旨在研究羽流扩散过程中各变量(环境风速、环境风温度、相对湿度和排气出口流速)对羽流沉降的影响.
创新点:采用考虑相变的低温羽流扩散模型,通过数值模拟对影响羽流扩散的各参数进行敏感性分析.
方法:1. 基于Hertz-Knudsen关系修正,考虑空气中水的相变,构建低温羽流扩散的数值模型; 2. 对照美国National Transonic Facility的羽流扩散数据和NASA的二阶分析模型的计算结果,验证本文所采用的数值模型的准确性; 3. 利用数值模拟,比较不同排放条件下近地面的最低氧含量和最低温度,并对各变量进行敏感性分析.
结论:1. 考虑相变的羽流扩散数值模型,相比NASA的二阶分析模型拥有更好的准确性. 2. 对于0.3 m低温风洞的羽流扩散,高环境风速有利于羽流消散;高环境温度和高相对湿度能提升近地面的最低温度,但对近地面的最低氧含量影响甚微. 3. 当排气速度小于2 kg/s时,排气流速增大不利于羽流消散; 当羽流速度大于2 kg/s时,排气流速增大有利于羽流消散.

关键词:低温风洞;羽流扩散;计算流体动力学;相变

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]ANSYS, 2011. ANSYS FLUENT 14 User’s Guide Manual. ANSYS Inc., USA.

[2]Brown TC, Cederwall RT, Chan ST, et al., 1990. Falcon Series Data Report: 1987 LNG Vapor Barrier Verification Field Trials. Technical Report No. UCRL-CR-104316, Lawrence Livermore National Lab, Livermore, CA, USA.

[3]Bruce Jr WE, Fuller D, Igoe WB, 1984. National Transonic Facility shakedown test results and calibration plans. 13th Aerodynamic Testing Conference.

[4]Chan ST, Rodean HC, Ermak DL, 1982. Numerical simulations of atmospheric releases of heavy gases over variable terrain. In: de Wispelaere C (Ed.), Air Pollution Modeling and Its Application III. Springer, Boston, MA, USA, p.295-328.

[5]Ermak DL, Chapman R, Goldwire Jr HC, et al., 1989. Heavy Gas Dispersion Test Summary Report. Technical Report No. ESL-TR-88-22, Lawrence Livermore National Lab, Livermore, CA, USA.

[6]Goldwire Jr HC, Rodean HC, Cederwall RT, et al., 1983. Coyote Series Data Report. LLNL/NWC 1981 LNG Spill Tests Dispersion, Vapor Burn, and Rapid-phase-transition. Vol. 2. Appendices. Technical Report No. UCID-19953-Vol. 2, Lawrence Livermore National Lab, Livermore, CA, USA.

[7]Ivey Jr GW, 1979. Cryogenic gaseous nitrogen discharge system. NASA Conference on Cryogenic Technology, p.271-278.

[8]Kilgore RA, 1976. Design Features and Operational Characteristics of the Langley 0.3-meter Transonic Cryogenic Tunnel. Technical Report No. NASA-TN-D-8304, NASA Langley Research Center, Hampton, VA, USA.

[9]Kilgore RA, 1994. Cryogenic wind tunnels-a brief review. In: Kittel P (Ed.), Advances in Cryogenic Engineering. Springer, Boston, MA, USA, p.63-70.

[10]Kilgore RA, 2005. Evolution and development of cryogenic wind tunnels. 43rd AIAA Aerospace Sciences Meeting and Exhibit.

[11]Koopman RP, Baker J, Cederwall RT, et al., 1982. LLNL/ NWC 1980 LNG Spill Tests. Burro Series Data Report: The Appendices. Technical Report No. UCID-19075-Vol. 2, Lawrence Livermore National Lab, Livermore, CA, USA.

[12]Lassiter WS, 1987. Plume Dispersion of the Exhaust from a Cryogenic Wind Tunnel. Technical Report No. NASA-TM-89148, NASA Langley Research Center, Hampton, VA, USA.

[13]Luketa-Hanlin A, Koopman RP, Ermak DL, 2007. On the application of computational fluid dynamics codes for liquefied natural gas dispersion. Journal of Hazardous Materials, 140(3):504-517.

[14]Marek R, Straub J, 2001. Analysis of the evaporation coefficient and the condensation coefficient of water. International Journal of Heat and Mass Transfer, 44(1):39-53.

[15]McBride MA, Beeves AB, Vanderheyden MD, et al., 2001. Use of advanced techniques to model the dispersion of chlorine in complex terrain. Process Safety and Environmental Protection, 79(2):89-102.

[16]Mousavi J, Parvini M, 2016. A sensitivity analysis of parameters affecting the hydrogen release and dispersion using ANOVA method. International Journal of Hydrogen Energy, 41(9):5188-5201.

[17]NIST (National Institute of Standards and Technology), 2007. NIST Reference Fluid Thermodynamic and Transport Properties Database. NIST, USA.

[18]Ohba R, Kouchi A, Hara T, et al., 2004. Validation of heavy and light gas dispersion models for the safety analysis of LNG tank. Journal of Loss Prevention in the Process Industries, 17(5):325-337.

[19]Rubel GO, Gentry JW, 1984. Measurement of the kinetics of solution droplets in the presence of adsorbed monolayers: determination of water accommodation coefficients. The Journal of Physical Chemistry, 88(14):3142-3148.

[20]Sklavounos S, Rigas F, 2006. Simulation of Coyote series trials —part I: CFD estimation of non-isothermal LNG releases and comparison with box-model predictions. Chemical Engineering Science, 61(5):1434-1443.

[21]Smelt R, 1945. Power Economy in High Speed Wind Tunnels by Choice of Working Fluid and Temperature. Report No. Aero. 2081, Royal Aircraft Establishment, Farnborough, UK.

[22]Tauseef SM, Rashtchiian D, Abbasi SA, 2011. CFD-based simulation of dense gas dispersion in presence of obstacles. Journal of Loss Prevention in the Process Industries, 24(4):371-376.

[23]Zhang XB, Li JF, Zhu JK, et al., 2015. Computational fluid dynamics study on liquefied natural gas dispersion with phase change of water. International Journal of Heat and Mass Transfer, 91:347-354.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE