Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration

<p dir="ltr">Combustible dust explosion properties, like Minimum Explosible Concentration (MEC) and Minimum Ignition Energy (or Temperature), have a strong dependency on the particle surface area to mass ratio which varies with the particle size distribution. Unfortunately, the compa...

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Main Author: Asma Abousrafa (17991313) (author)
Other Authors: Tomasz Olewski (17346835) (author), Luc Véchot (17991316) (author)
Published: 2024
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author Asma Abousrafa (17991313)
author2 Tomasz Olewski (17346835)
Luc Véchot (17991316)
author2_role author
author
author_facet Asma Abousrafa (17991313)
Tomasz Olewski (17346835)
Luc Véchot (17991316)
author_role author
dc.creator.none.fl_str_mv Asma Abousrafa (17991313)
Tomasz Olewski (17346835)
Luc Véchot (17991316)
dc.date.none.fl_str_mv 2024-02-20T09:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.jlp.2024.105269
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Use_of_a_two-parameter_Weibull_distribution_for_the_description_of_the_particle_size_effect_on_dust_minimum_explosible_concentration/25248991
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Chemical engineering
Materials engineering
Particle size distribution
Weibull parameters
Minimum explosible concentration
MEC
Sulfur
Dust
dc.title.none.fl_str_mv Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Combustible dust explosion properties, like Minimum Explosible Concentration (MEC) and Minimum Ignition Energy (or Temperature), have a strong dependency on the particle surface area to mass ratio which varies with the particle size distribution. Unfortunately, the comparison of the dust explosion properties reported in the literature for a given dust material is often difficult because of the lack of description of the particle size distribution which is usually limited only to scattered information about the median (<i>d</i><sub><em>50</em></sub>), mean, or one, two, or maximum three percentiles (e.g., <i>d</i><sub><em>10</em></sub>, <i>d</i><sub><em>50</em></sub>, and <i>d</i><sub><em>90</em></sub>). This approach often gives conflicted conclusions or observations of no trend with measured independent parameters. It seems that a different approach is necessary to comprehensively describe the dependency of dust explosion properties on the particle size distribution. Such improvement could be achieved using a continuous probability distribution of which an example is a two-parameter normal distribution. However, the normal probability density function can only represent a symmetrical bell-shaped distribution which does not apply to the dust particle size analysis that often results in a skewed bell-shaped histogram. This study explored the use of a two-parameter (shape and scale) Weibull probability density function to describe a particle size distribution. A series of experimental data on the Minimum Explosible Concentration (MEC) of sulfur and polyethylene dust samples for which the particle distribution is measured were used to estimate the Weibull's scale and shape parameters. Two- and three-dimensional plots were generated to demonstrate the correlations of these parameters with MEC. The results show that as the scale and shape parameters increase, the MEC increases with higher dependence on the scale parameter (<i>b</i>). This is consistent with the initial conclusion where the MEC increases with increasing particle size. The paper discusses the advantages of using such an approach to describe the effect of particle size distribution on dust explosion properties but also shows that using only a median or mean of a particle size distribution to describe MEC may be misleading, especially if a sample represented by <i>d</i><sub><em>50</em></sub> as a coarse distribution contains a long tail of fine particles.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Loss Prevention in the Process Industries<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jlp.2024.105269" target="_blank">https://dx.doi.org/10.1016/j.jlp.2024.105269</a></p>
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identifier_str_mv 10.1016/j.jlp.2024.105269
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/25248991
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spelling Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentrationAsma Abousrafa (17991313)Tomasz Olewski (17346835)Luc Véchot (17991316)EngineeringChemical engineeringMaterials engineeringParticle size distributionWeibull parametersMinimum explosible concentrationMECSulfurDust<p dir="ltr">Combustible dust explosion properties, like Minimum Explosible Concentration (MEC) and Minimum Ignition Energy (or Temperature), have a strong dependency on the particle surface area to mass ratio which varies with the particle size distribution. Unfortunately, the comparison of the dust explosion properties reported in the literature for a given dust material is often difficult because of the lack of description of the particle size distribution which is usually limited only to scattered information about the median (<i>d</i><sub><em>50</em></sub>), mean, or one, two, or maximum three percentiles (e.g., <i>d</i><sub><em>10</em></sub>, <i>d</i><sub><em>50</em></sub>, and <i>d</i><sub><em>90</em></sub>). This approach often gives conflicted conclusions or observations of no trend with measured independent parameters. It seems that a different approach is necessary to comprehensively describe the dependency of dust explosion properties on the particle size distribution. Such improvement could be achieved using a continuous probability distribution of which an example is a two-parameter normal distribution. However, the normal probability density function can only represent a symmetrical bell-shaped distribution which does not apply to the dust particle size analysis that often results in a skewed bell-shaped histogram. This study explored the use of a two-parameter (shape and scale) Weibull probability density function to describe a particle size distribution. A series of experimental data on the Minimum Explosible Concentration (MEC) of sulfur and polyethylene dust samples for which the particle distribution is measured were used to estimate the Weibull's scale and shape parameters. Two- and three-dimensional plots were generated to demonstrate the correlations of these parameters with MEC. The results show that as the scale and shape parameters increase, the MEC increases with higher dependence on the scale parameter (<i>b</i>). This is consistent with the initial conclusion where the MEC increases with increasing particle size. The paper discusses the advantages of using such an approach to describe the effect of particle size distribution on dust explosion properties but also shows that using only a median or mean of a particle size distribution to describe MEC may be misleading, especially if a sample represented by <i>d</i><sub><em>50</em></sub> as a coarse distribution contains a long tail of fine particles.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Loss Prevention in the Process Industries<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jlp.2024.105269" target="_blank">https://dx.doi.org/10.1016/j.jlp.2024.105269</a></p>2024-02-20T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.jlp.2024.105269https://figshare.com/articles/journal_contribution/Use_of_a_two-parameter_Weibull_distribution_for_the_description_of_the_particle_size_effect_on_dust_minimum_explosible_concentration/25248991CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252489912024-02-20T09:00:00Z
spellingShingle Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
Asma Abousrafa (17991313)
Engineering
Chemical engineering
Materials engineering
Particle size distribution
Weibull parameters
Minimum explosible concentration
MEC
Sulfur
Dust
status_str publishedVersion
title Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
title_full Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
title_fullStr Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
title_full_unstemmed Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
title_short Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
title_sort Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration
topic Engineering
Chemical engineering
Materials engineering
Particle size distribution
Weibull parameters
Minimum explosible concentration
MEC
Sulfur
Dust