270
Views
8
CrossRef citations to date
0
Altmetric
Articles

Dilute gas-particle flow through thin and thick orifice: a computational study through two fluid model

&
Pages 711-725 | Received 10 Sep 2018, Accepted 03 Jan 2019, Published online: 29 Mar 2019
 

Abstract

The present work deals with the three-dimensional computational study of dilute gas-particle suspension through thin and thick orifice. The objective of the study is to predict the two phase pressure drop across an orifice for relatively higher solid loading but within the limit of dilute phase flow situation. The study involves the investigation of effect of five pertinent parameters namely area ratio, thickness of orifice, particle phase volume fraction, particle size, and particle phase density on the two phase pressure drop across orifice. The Eulerian–Eulerian model (Two fluid model) has been used for this purpose. The numerical procedure adopted in the present work has been validated with the experimental data for gas-particle flow through a horizontal sudden expansion pipe and good agreement has been revealed. The study reveals that the two phase pressure drop across orifice increases with increases in solid volume fraction and particle density, whereas it decreases with increase in particle diameter and area ratio of the pipe. Moreover, slight increase in pressure drop across orifice is observed with increase in thickness of orifice. Thus, higher pressure drop is observed for thick orifice as compared to thin orifice.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 438.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.