کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
586383 | 878211 | 2013 | 6 صفحه PDF | دانلود رایگان |
• The aim is to improve accuracy of determination of explosion severity parameters.
• Two methods are presented: a statistical method and a method that corrects for differences of turbulence intensity.
• The statistical method considers all test results in determination of the parameters and calculates experimental error.
• The correction method allows to reduce discrepancies between results caused by difference in the turbulence intensity level.
• Both methods seems to give promising results.
Accurate determination of explosion severity parameters (pmax, (dp/dt)max, and KSt) is essential for dust explosion assessment, identification of mitigation strategy, and design of mitigation measure of proper capacity. The explosion severity parameters are determined according to standard methodology however variety of dust handled and operation circumstances may create practical challenge on the optimal test method and subsequent data interpretation. Two methods are presented: a statistical method, which considers all test results in determination of explosion severity parameters and a method that corrects the results for differences of turbulence intensity. The statistical method also calculates experimental error (uncertainty) that characterises the experimental spread, allows comparison to other dust samples and may define quality determination threshold. The correction method allows to reduce discrepancies between results from 1 m3 vessel and 20-l sphere caused by difference in the turbulence intensity level. Additionally new experimental test method for difficult to inject samples together with its analysis is described. Such method is a versatile tool for explosion interpretation in test cases where different dispersion nozzle is used (various turbulence level in the test chamber) because of either specific test requirements or being “difficult dust sample”.
Journal: Journal of Loss Prevention in the Process Industries - Volume 26, Issue 6, November 2013, Pages 1002–1007