Improved partial inerting MIE test method for combustible dusts and its CFD validation
Graphical abstract
Introduction
Dust explosions have been a major safety concern in powder manufacturing and handling facilities, sometimes resulting in catastrophic loss of life and property (Bartnecht, 1989; Cashdollar and Hertzberg, 1986; Eckhoff, 2003; Yuan et al., 2015; Bagaria et al., 2017). Despite recurring dust explosion incidents, there is still a lack of general awareness of dust hazards (Amyotte, 2014). Dust explosion risk assessments require several critical parameters, the MIE (minimum ignition energy) being one of them. MIE is the smallest amount of energy required to ignite a dust cloud at a given temperature and pressure, and it helps quantify the ignition probability of the dust. To minimize the risk of dust explosion, inerting of combustible dust processes is one of the techniques used in industries (Eckhoff, 2003; Hoppe and Jaeger, 2005). Generally, with respect to inerting, industry tends to follow an all-or-nothing approach. However, complete inerting (100% nitrogen atmosphere) of industrial processes can be more hazardous than partial inerting and more expensive. Additionally, the notion that it is the only option is a common misconception (Amyotte, 2013, 2014).
Partial inerting can be used as an intermediate inerting technique where rather than complete oxygen removal, the oxygen levels are reduced such that the MIE of the dust is significantly raised, thereby substantially reducing the probability of ignition (Eckhoff, 2004). Hoppe and Jaeger (2005) have used the term partial inerting and discussed its implementation on an industrial scale. Some of the many advantages of partial inerting are cost effectiveness, improved safety, improved product quality for products requiring oxygen, and reduced explosion vent area (Eckhoff, 2004, 2009).
Several partial inerting studies have experimentally investigated the effect of oxygen content on MIE for various dusts (Ackroyd et al., 2011; Choi et al., 2015; Glor and Schwenzfeuer, 1996; Glarner, 1984). The change in the dust Minimum Ignition Energy (MIE) with changing oxygen content is also known as the MIE-O2 relationship of the dust. The nature of the MIE-O2 relationship is dependent on the type of dust (see Fig. 1). As seen from Fig. 1, the variability in the oxygen content of the gas composition used for MIE testing and the precise oxygen content at which the MIE measurement is conducted become an important factor.
In certain cases, MIE testing can be very expensive due to limited availability of dusts or not feasible due to limited and discrete range of MIE testing devices. In such cases, consistently collected and accurate data sets for determining the MIE-oxygen relationship are necessary for predicting the dust MIE at any desired oxygen concentration without the need for actual testing. In their previous work, Chaudhari and Mashuga (2017) have conducted partial inerting MIE testing by implementing a test method in a modified MIKE3 minimum ignition energy apparatus. Additionally, Han et al. (2018) have extended this test method and utilized the same modified MIKE3 apparatus for hybrid combustible dust-flammable gas systems which resulted in more conservative (lower) MIE measurements than those reported in literature. This work uses the same modified MIKE3 device to further develop and refine the fundamental understanding of the test method for partial inerting MIE testing. The goal of this work is to examine the purge time required to produce partial inerting MIE measurements at known oxygen concentrations. In addition, an ANSYS Fluent CFD model was developed to help guide the experimental efforts and provide a validation of the modifications and method used. The CFD simulation of the purge flow is an important step as it allows for an estimated purge time required at any oxygen concentration, ensuring that the desired oxygen content is achieved in the Hartmann tube with minimal consumption of specialty gases. In addition, the experimentally verified CFD model in this work would assist in extending this experimental test method (including purge time) to other combustible dust gas systems such as hybrid systems (flammable gas-air-combustible dust mixtures). This improved test method has further been utilized to experimentally determine the partial inerting MIE-O2 behavior of three combustible dusts (Anthraquinone, Lycopodium clavatum, Calcium Stearate).
Section snippets
Materials
In order to capture the MIE–oxygen behavior of different dust types, Lycopodium clavatum, Calcium Stearate and Anthraquinone were tested in this study. Lycopodium clavatum is a naturally occurring plant spore and has been used by researchers as a reference material due to its dispersibility, flowability, combustibility, and monodispersity. Its naturally occurring monodisperse size distribution (narrow range of particle size distribution) results in consistent explosion characteristics (Amyotte
Effect of purge time on oxygen concentration
The decrease in the oxygen concentration in the Hartmann tube during purging was monitored using an oxygen sensor at points 1, 2 and 3 in the tube shown in Fig. 7. Experimentally, the time required to reach the desired oxygen concentration of 12.03% was observed to be 39 ± 3 s. Thus, the experimental measurements (Fig. 7) confirm that the purge time of ∼ 21 s used previously (Chaudhari and Mashuga, 2017) is not sufficient and can result in higher oxygen concentrations than desired.
An average of
Conclusions
In this work, Hartmann tube purging was conducted prior to partial inerting MIE experimentation. The purge time required was determined experimentally and simulated using CFD. For consistency in literature and to facilitate easy comparison amongst different studies, it is recommended that partial inerting studies employ pre-purging and mention the purge flow rate and time along with other relevant testing parameters. Based on this study, for 12–21 volume % oxygen the minimum purge time was
Acknowledgement
The authors would like to acknowledge the support and resources of the Texas A&M High Performance Research Computing facility (https://hprc.tamu.edu). The authors would like to recognize the undergraduate students Ethan Licon and Benjamin Hall at Texas A&M University for their assistance and inputs in this work.
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