کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
586030 1453267 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Effect of inert species on the laminar burning velocity of hydrogen and ethylene
ترجمه فارسی عنوان
اثر گونه های بی اثر بر روی سرعت سوختن آرام هیدروژن و اتیلن
کلمات کلیدی
سرعت سوختن آرام ؛ انفجار ابر بخار؛ پیش بینی بار انفجار؛ هیدروژن، اتیلن؛ احداث تأسیسات
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بهداشت و امنیت شیمی
چکیده انگلیسی


• CO2 is more effective at decreasing the LBV of a fuel-inert mixture than N2 due to its lower thermal diffusivity.
• Of all the simplified prediction methods evaluated, the Spalding method was applicable to the widest range of data.
• Le Chatelier's rule cannot predict the effect of inert species. A simple average cannot distinguish between different inerts.
• When applying the Spalding method to fuel-inert mixtures with inert fractions greater than 30%, caution should be exercised.

The maximum laminar burning velocity (LBV) of a fuel-air mixture is an important input parameter to vapor cloud explosion (VCE) blast load prediction methods. In particular, the LBV value has a significant impact on the predicted blast loads for high reactivity fuels with the propensity to undergo a deflagration-to-detonation transition (DDT). Published data are available for the maximum LBV of many pure fuel-air mixtures. However, little test data are available for mixtures of fuels, particularly for mixtures of fuels and inert species. Such mixtures are common in the petroleum refining and chemical processing industries. It is therefore of interest to be able to calculate the maximum LBV of a fuel/inert mixture based on the mixture composition and maximum LBV of each component.This paper presents measured test data for the maximum LBV of H2/inert and C2H4/inert mixtures, with both nitrogen and carbon dioxide as the inert species. The LBV values were determined using a constant-volume vessel and the pressure rise method. This paper also provides a comparison of the measured LBV values with simplified LBV prediction methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Loss Prevention in the Process Industries - Volume 41, May 2016, Pages 376–381
نویسندگان
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