بررسی و مقایسه آزمایشها و مدلهای ریاضی انتشار گازهای سنگین
محورهای موضوعی :
آلودگی هوا
نرجس همتی علم
1
,
اسلام کاشی
2
,
راضیه حبیب پور
3
1 - دانشجوی دکتری، پژوهشکده فناوری های شیمیایی، سازمان پژوهشهای علمی و صنعتی ایران، تهران، ایران.
2 - استادیار مهندسی شیمی، پژوهشکده فناوری های شیمیایی، سازمان پژوهشهای علمی و صنعتی ایران، تهران، ایران. *(مسوول مکاتبات)
3 - استادیار شیمی فیزیک، پژوهشکده فناوری های شیمیایی، سازمان پژوهشهای علمی و صنعتی ایران، تهران، ایران.
تاریخ دریافت : 1395/08/22
تاریخ پذیرش : 1398/04/05
تاریخ انتشار : 1400/08/01
کلید واژه:
انتشار گاز سنگین,
CFD,
آزمایشهای انتشار گاز,
مدلهای انتشار گاز,
مدلهای اغتشاش,
چکیده مقاله :
زمینه و هدف :رهایش و پراکندگی ابر گازهای سمی و آتشگیر در جو یکی از حوادث حائز اهمیت در ایمنی فرآیندهاست. پیش بینی نحوه انتشار گازها پس از رهایش آن ها به عنوان یک حادثه خطر زا برای جمعیت های انسانی مجاور صنایع یا محیط زیست برای کاهش خسارات ناشی از آن دارای اهمیت ویژه ای می باشد. آنالیز ریسک معمولاً با نرم افزارهایی که بر پایه آزمایش های تجربی و روش های ریاضی استوارند، انجام می شوند.روش بررسی: برای به دست آوردن مدل ها و ارزیابی مدل های ارائه شده چندین آزمایش در تحقیقات مختلف انجام گرفته است. آزمایش های انجام یافته در زمینه انتشار گاز را می توان به دو دسته اصلی آزمایش های میدانی و آزمایش های در تونل باد تقسیم بندی کرد. از جمله آزمایش های میدانی مهم می توان به آزمایش های Kit Fox، Thorney Island ، Coyote اشاره کرد. آزمایش های گروه PREP، EMU از جمله آزمایش های صورت گرفته ی مهم در تونل باد می باشند. در بسیاری از موارد به دلیل آن که حادثه بیشتر در فضای باز رخ می دهد، بررسی انتشار گاز در فضای باز بدون حضور مانع و یا در حضور مانع به نمایندگی از ساختمان ها و تجهیزات فرآیندی انجام یافته است. در برخی از مطالعات نیز انتشار گاز در فضای بسته و ساختمان های بزرگ صورت گرفته است. در مدلسازی انتشار گاز، ابتدا مدل های ساده با عنوان مدل های جعبه ای، مدل های پلوم پایدار، مدل های انتگرالی و بعد مدل های پیشرفته تر مانند مدل های لاگرانژی و مدل های لاگرانژی گوسی ارائه شده است. در سال های اخیر نیز استفاده از روش های دینامیک سیالات محاسباتی مورد توجه است. مدل های LES، RANSوDNS از جمله مدل های بکار برده شده در روش CFD می باشند.یافته ها: گازها و سناریوهای رهایش گوناگونی در کارهای یاد شده مورد مطالعه قرار گرفته اند. از دیگر موارد تاثیر گذار بر انتشار گاز می توان به توپوگرافی محل رهایش و بستر انتشار گاز اشاره کرد که در آزمایش ها و شبیه سازی های عددی مورد بررسی قرار گرفته اند.بحث و نتیجه گیری: در زمان استفاده و استناد به آزمایش ها و مدلهای ارائه شده، تا حد ممکن بایستی شرایط سناریو با آزمایش و مدل نزدیک باشد. از این شرایط میتوان به نوع گاز، بستر انتشار گاز، نحوه برون ریزی و نشت گاز ( آنی یا پیوسته) و شرایط محیطی دیگر اشاره کرد.
چکیده انگلیسی:
Background and Objective: Release and dispersion of toxic and flammable gases in atmosphere is one of the most important incident in safety of the processes. Risk analysis with the aim of prevention from harm and damage usually carries out by software packages, which are based on the field experiments and mathematical models.Material and Methodology: In order to derive dispersion models and evaluate existing models, some different experiments are done. Experiments of the gas release and gas dispersion are in two categories, experiments which took place in wind tunnels and which are field experiments. Kit Fox, Thorney Island and coyote are some of the most famous field experiments. PERP group and EMU tests are major experiments in wind tunnels. In many of studies, gas dispersion was investigated in the open places in absence or presence of obstacles because most of the industrial accident happens in open places. Others are also taking place in indoors and large buildings. Early, simple models such as box models, steady state plume and integral models were proposed. Thereafter, group models like Lagrangian models and Lagrangian- Gaussian models were evinced. One of the other approach is using more complex and computational methods. Fluid dynamics methods are designed and developed for this purpose. The models of the heavy gas dispersion can be categorized to four major group. The first is simple and experimental models. intermediate and integral or shallow layer models include box models, steady state / general steady state plume models, one dimensional integral models is located in the next. The third group is advanced and lagrange models. The last and latest models are computational fluid dynamic models: RANS, LES and DNSFindings: Different gases, distinct release scenarios are studied in researches. As another effective parameter on the path of gas dispersion, topology of release location can be mentioned which is investigated in field experiments and simulations.Discussion and conclusions: in order to use and refer the field experiments and models as an evaluation, desired scenarios’ condition should be as close as possible to the models or experiments’ condition. These conditions could be such as type of gas, terrain and topology of release path, puff or plume release and other environment and physical conditions.
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Sklavounos and F. Rigas, "Validation of turbulence models in heavy gas dispersion over obstacles," Journal of Hazardous Materials, vol. 108, pp. 9-20, 2004.
Assael MJ, Kakosimos KE. Fires, explosions, and toxic gas dispersions: effects calculation and risk analysis: CRC Press; 2010.
Rigas F, Konstandinidou M, Centola P, Reggio G. Safety analysis and risk assessment in a new pesticide production line. Journal of Loss Prevention in the Process Industries. 2003;16(2):103-9.
Tauseef S, Rashtchian D, Abbasi S. CFD-based simulation of dense gas dispersion in presence of obstacles. Journal of Loss Prevention in the Process Industries. 2011;24(4):371-6.
Meroney RN. CFD modeling of dense gas cloud dispersion over irregular terrain. Journal of Wind Engineering and Industrial Aerodynamics. 2012;104:500-8.
Kashi E., Shahraki F., Rashtchian D, Mohebinia S., Investigation of gas dispersion and explosion in obstacle area with CFD analysis, Amirkabir 19(68)7. (In Persian)
Kashi E, Mirzaei F, Mirzaei F. Analysis of Chlorine Gas Incident Simulation and Dispersion Within a Complex and Populated Urban Area Via Computation Fluid Dynamics. Advances in Environmental Science and Technology. 2015;1(1):49-58.
Siddiqui M, Jayanti S, Swaminathan T. CFD analysis of dense gas dispersion in indoor environment for risk assessment and risk mitigation. Journal of hazardous materials. 2012;209:177-85.
Cocchi G. Modeling instantaneous heavy gas releases with FDS5. Fire Safety Journal. 2014;69:89-98.
Markiewicz M. A Review of Mathematical Models for the Atmospheric Dispersion of Heavy Gases. Part I. A Classification of Models. Ecological Chemistry and Engineering S. 2012;19(3):297-314.
Hanna S, Drivas P, Chang J. Guidelinesfor use of vapour cloud dispersion models. CCPS, AI Ch. E., New York; 1996.
Havens J. Review of dense gas dispersion field experiments. Journal of loss prevention in the process industries. 1992;5(1):28-41.
Briggs G, Britter R, Hanna S, Havens J, Robins A, Snyder W. Dense gas vertical diffusion over rough surfaces: results of wind-tunnel studies. Atmospheric Environment. 2001;35(13):2265-84.
Hanna SR, Hansen OR, Dharmavaram S. FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations. Atmospheric Environment. 2004;38(28):4675-87.
Barad ML. Project PRAIRIE GRASS, a field program in diffusion. Volume II. DTIC Document, 1958.
Goldwire Jr H, Rodean H, Cederwall R, Kansa E, Koopman R, McClure J, et al. Coyote series data report LLNL/NWC 1981 LNG spill tests dispersion, vapor burn, and rapid-phase-transition. Volume 1.[7 experiments with liquefied natural gas, 2 with liquid methane, and one with liquid nitrogen]. Lawrence Livermore National Lab., CA (USA), 1983.
Sklavounos S, Rigas F. Simulation of Coyote series trials—Part I:: CFD estimation of non-isothermal LNG releases and comparison with box-model predictions. Chemical Engineering Science. 2006-61(5):1434-43.
McQuaid J. Objectives and design of the phase I heavy gas dispersion trials. Journal of Hazardous Materials. 1985;11:1-33.
Crabol B, Roux A, Lhomme V. Interpretation of the Thorney Island Phase I trials with the box model CIGALE2. Journal of hazardous materials. 1987;16:201-14.
Puttock J, Colenbrander G. Thorney Island data and dispersion modelling. Journal of Hazardous Materials. 1985;11:381-97.
Deaves D. 3-dimensional model predictions for the upwind building trial of Thorney Island Phase II. Journal of Hazardous Materials. 1985;11:341-6.
Hanna S, Chang J, Briggs G. Dense gas dispersion model modifications and evaluations using the Kit Fox Field Observations. Report P011F by Hanna Consultants. 1999;3911.
Hanna S, Steinberg K. Overview of Petroleum Environmental Research Forum (PERF) dense gas dispersion modeling project. Atmospheric Environment. 2001;35(13):2223-9.
Robins A, Castro I, Hayden P, Steggel N, Contini D, Heist D, et al. A wind tunnel study of dense gas dispersion in a stable boundary layer over a rough surface. Atmospheric Environment. 2001;35(13):2253-63.
Hall R. Evaluation of modelling uncertainty. CFD modelling of near-field atmospheric dispersion. Project EMU final report, European Commission Directorate–General XII Science. Research and Development Contract EV5V-CT94-0531, WS Atkins Consultants Ltd, Surrey. 1997.
26 Cowan IR, Castro IP, Robins AG. Numerical considerations for simulations of flow and dispersion around buildings. Journal of Wind Engineering and Industrial Aerodynamics. 1997;67:535-45.
Pramod Kumara A-AF. Performance Analysis of an Air Quality CFD Model in Complex Environments: Numerical Simulation and Experimental Validation with EMU Observations. Building and Environment. 2016.
Kashi E, Shahraki F, Rashtchian D, Behzadmehr A. Effects of vertical temperature gradient on heavy gas dispersion in build up area. Iranian Journal of Chemical Engineering. 2009;6(3):27.
Rigas F, Sklavounos S. Simulation of Coyote series trials—Part II: A computational approach to ignition and combustion of flammable vapor clouds. Chemical Engineering Science. 2006;61(5):1444-52.
Hanna SR, Chang JC. Use of the Kit Fox field data to analyze dense gas dispersion modeling issues. Atmospheric Environment. 2001;35(13):2231-42.
Koopman R, McRae T, Goldwire H. Results of recent large-scale NH 3 and N 2 O 4 dispersion experiments. 1984.
Ichard M, Hansen OR, Melheim J, GexCon A. 6.2 Release of pressurized liquefied gases: simulations of the desert tortoise test series with the CFD model FLACS 2010.
Mack A, Spruijt M. CFD Dispersion Investigation of CO2 Worst Case Scenarios Including Terrain and Release Effects. Energy Procedia. 2014;51:363-72.
Nielsen M, Ott S, Jørgensen HE, Bengtsson R, Nyrén K, Winter S, et al. Field experiments with dispersion of pressure liquefied ammonia. Journal of hazardous materials. 1997;56(1):59-105.
McRae T, Cederwall R, Goldwire Jr H, Hipple D, Johnson G, Koopman R, et al. Eagle series data report: 1983 nitrogen tetroxide spills. Lawrence Livermore National Lab., CA (USA), 1984.
Havens J, Spicer T. LNG vapor cloud exclusion zones for spills into impoundments. Process safety progress. 2005;24(3):181-6.
König-Langlo G, Schatzmann M. Wind tunnel modeling of heavy gas dispersion. Atmospheric Environment Part A General Topics. 1991; 25(7):1189-98.
Meroney RN, Leitl BM, Rafailidis S, Schatzmann M. Wind-tunnel and numerical modeling of flow and dispersion about several building shapes. Journal of Wind Engineering and Industrial Aerodynamics. 1999; 81(1):333-45.
Hall D, Waters R, Marsland G. Repeat variability in instantaneously released heavy gas clouds-some wind tunnel model experiments1991.
Pitblado R, Baik J, Hughes G, Ferro C, Shaw S. Consequences of liquefied natural gas marine incidents. Process safety progress. 2005;24(2):108-14.
Luketa-Hanlin A. A review of large-scale LNG spills: experiments and modeling. Journal of Hazardous Materials. 2006;132(2):119-40.
Qi R. Liquefied Natural Gas (LNG) Vapor Dispersion Modeling with Computational Fluid Dynamics Codes: Texas A&M University; 2011.
Sun B, Utikar RP, Pareek VK, Guo K. Computational fluid dynamics analysis of liquefied natural gas dispersion for risk assessment strategies. Journal of Loss Prevention in the Process Industries. 2013;26(1):117-28.
Zhang X, Li J, Zhu J, Qiu L. Computational fluid dynamics study on liquefied natural gas dispersion with phase change of water. International Journal of Heat and Mass Transfer. 2015;91:347-54.
Lisbona D, McGillivray A, Saw JL, Gant S, Bilio M, Wardman M. Risk assessment methodology for high-pressure CO2 pipelines incorporating topography. Process Safety and Environmental Protection. 2014; 92(1): 27-35.
Xing J, Liu Z, Huang P, Feng C, Zhou Y, Sun R, et al. CFD validation of scaling rules for reduced-scale field releases of carbon dioxide. Applied Energy. 2014;115:525-30.
Liu B, Liu X, Lu C, Godbole A, Michal G, Tieu AK. Computational fluid dynamics simulation of carbon dioxide dispersion in a complex environment. Journal of Loss Prevention in the Process Industries. 2016;40:419-32.
Liu X, Godbole A, Lu C, Michal G, Venton P. Source strength and dispersion of CO2 releases from high-pressure pipelines: CFD model using real gas equation of state. Applied Energy. 2014;126:56-68.
Bouet R, Duplantier S, Salvi O. Ammonia large scale atmospheric dispersion experiments in industrial configurations. Journal of loss prevention in the process industries. 2005;18(4):512-9.
Scenna NJ, Santa Cruz AS. Road risk analysis due to the transportation of chlorine in Rosario city. Reliability Engineering & System Safety. 2005;90(1):83-90.
Robins A, Hall R, Cowan I, Bartzis J, Albergel A. Evaluating modelling uncertainty in CFD predictions of building affected dispersion. International Journal of Environment and Pollution. 2000;14(1-6):52-64.
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