Dust explosions have been the cause of serious industrial accidents for several years, including industries in a wide variety of sectors, from metalworking to pharmaceuticals. It is good practice to distinguish between metallic and organic powders, because of the different phenomenology with which they are burned. In accordance with the latest Chemical Safety Board (CSB) investigations about dust explosions in the United States, three out of four have involved metal dust (iron, titanium, zirconium and aluminium); such explosions have also occurred in Europe, Japan and China. Many chemical plants make use of metal powders for their exceptional mechanical, optical and catalytic properties; for example, they are employed in the production of plastics, rubber, paints, coatings, inks, pesticides, detergents and even drugs. The plants that use, process and store them are all subject to the risk of explosion. The severity of these explosions can be characterized from experimental parameters such as the maximum explosion pressure (Pmax), the maximum rate of pressure rise ((dP/dt))max and the deflagration index KSt, which are employed to predict the consequences of a dust explosion for a given scenario. Among these indexes, the deflagration index plays a fundamental role, since it is used for the design of deflagration nozzles aimed to protect industrial equipment and silos from internal dust explosions. Nowadays, the estimation of KSt is carried out through a series of experimental tests, conducted mainly within a standard sphere of 20 liters but, unfortunately, this type of experimentation is rather expensive and time-consuming, especially when considering that different particle sizes correspond to different explosion characteristics. An experimental investigation of all the different particle sizes would be advisable but difficult to achieve. In fact, it has been proved by previous studies that the characterization of the deflagration index can be affected by the particle size distribution polydispersity. The purpose of this work is to develop a mathematical model able to predict the KSt value of metal powders as a function of chemical-physical data and the particle size distribution (D50 has been used as global information). The model structure is based on the writing and resolution of the material and energy balance equations on the single particles, estimating the contribution of oxygen diffusion, which in the case of metal powders greatly depends on tortuosity and porosity. The results were well compared with the experimental data, providing the basis for the development of more detailed models.
Le esplosioni da polveri sono da diversi anni causa di gravi incidenti industriali. In accordo con le ultime indagini condotte dalla Chemical Safety Board (CSB) sulle esplosioni da polveri negli Stati Uniti, tre su quattro hanno interessato polveri metalliche (ferro, titanio, zirconio e alluminio); esplosioni di questo tipo si sono verificate anche in Europa, Giappone e Cina. Molte industrie chimiche impiegano polveri metalliche per le loro straordinarie proprietà meccaniche, ottiche e catalitiche; per esempio, sono impiegate nella produzione di plastiche, gomma, vernici, rivestimenti, inchiostri, pesticidi, detergenti e anche farmaci. Gli impianti che le utilizzano, trattano e immagazzinano sono tutti soggetti al rischio di esplosione. La pericolosità di queste esplosioni può essere determinata attraverso parametri sperimentali quali la massima pressione di esplosione (Pmax), la massima velocità di aumento della pressione ((dP/dt)max) e l’indice di deflagrazione (KSt), che vengono utilizzati per prevederne le conseguenze in uno specifico contesto. Tra gli indici sopra citati uno dei più rilevanti, è l’indice di deflagrazione la cui determinazione, oggigiorno, avviene attraverso una serie di test sperimentali condotti principalmente all’interno di un dispositivo costituito da una sfera standard da 20 litri. Purtroppo, questo tipo di sperimentazione richiede ingenti risorse sia in termini di tempo che di denaro, soprattutto se si considera il fatto che a granulometrie diverse corrispondono caratteristiche di esplosività diverse. Un’indagine sperimentale di tutte le diverse granulometrie sarebbe opportuna ma difficilmente realizzabile. È stato, infatti, dimostrato da precedenti studi che la caratterizzazione del KSt può essere influenzata dalla polidispersità della distribuzione delle dimensioni delle particelle. L’obiettivo del presente lavoro è quello di sviluppare un modello matematico che possa prevedere il valore del KSt delle polveri metalliche in funzione di dati chimico-fisici e della distribuzione granulometrica (è stato utilizzato il D50 come informazione globale). La struttura del modello si basa sulla scrittura e risoluzione delle equazioni di bilancio materiale ed energetico sulle singole particelle, stimando il contributo della diffusione di ossigeno, che nel caso delle polveri metalliche dipende molto da tortuosità e porosità. I risultati hanno fornito un buon confronto con i dati sperimentali, ponendo le basi per lo sviluppo di modelli più dettagliati.
A mathematical model for the prediction of the KST for metallic dusts as a function of the particle size distribution
SEBASTIO, FRANCESCA
2018/2019
Abstract
Dust explosions have been the cause of serious industrial accidents for several years, including industries in a wide variety of sectors, from metalworking to pharmaceuticals. It is good practice to distinguish between metallic and organic powders, because of the different phenomenology with which they are burned. In accordance with the latest Chemical Safety Board (CSB) investigations about dust explosions in the United States, three out of four have involved metal dust (iron, titanium, zirconium and aluminium); such explosions have also occurred in Europe, Japan and China. Many chemical plants make use of metal powders for their exceptional mechanical, optical and catalytic properties; for example, they are employed in the production of plastics, rubber, paints, coatings, inks, pesticides, detergents and even drugs. The plants that use, process and store them are all subject to the risk of explosion. The severity of these explosions can be characterized from experimental parameters such as the maximum explosion pressure (Pmax), the maximum rate of pressure rise ((dP/dt))max and the deflagration index KSt, which are employed to predict the consequences of a dust explosion for a given scenario. Among these indexes, the deflagration index plays a fundamental role, since it is used for the design of deflagration nozzles aimed to protect industrial equipment and silos from internal dust explosions. Nowadays, the estimation of KSt is carried out through a series of experimental tests, conducted mainly within a standard sphere of 20 liters but, unfortunately, this type of experimentation is rather expensive and time-consuming, especially when considering that different particle sizes correspond to different explosion characteristics. An experimental investigation of all the different particle sizes would be advisable but difficult to achieve. In fact, it has been proved by previous studies that the characterization of the deflagration index can be affected by the particle size distribution polydispersity. The purpose of this work is to develop a mathematical model able to predict the KSt value of metal powders as a function of chemical-physical data and the particle size distribution (D50 has been used as global information). The model structure is based on the writing and resolution of the material and energy balance equations on the single particles, estimating the contribution of oxygen diffusion, which in the case of metal powders greatly depends on tortuosity and porosity. The results were well compared with the experimental data, providing the basis for the development of more detailed models.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/151336