Skip navigation

Finite-element modeling of electrostatic sensors for the flow measurement of particles in pneumatic pipelines

Finite-element modeling of electrostatic sensors for the flow measurement of particles in pneumatic pipelines

Krabicka, Jan and Yan, Yong (2009) Finite-element modeling of electrostatic sensors for the flow measurement of particles in pneumatic pipelines. IEEE Transactions on Instrumentation and Measurement, 58 (8). pp. 2730-2736. ISSN 0018-9456 (doi:10.1109/TIM.2009.2016288)

Full text not available from this repository.

Abstract

Electrostatic sensors are used in certain industries for the flow measurement of pneumatically conveyed solids. However, despite various advances that have been made in recent years, relatively little information is known about the exact nature of the electrostatic charge induced onto the sensor electrode due to moving particles, which is dependent on electrode geometry, particle distribution, and particle velocity. This paper presents a novel approach to the study of the charge induced onto electrostatic sensors based on fitting a Lorentzian curve to the results of a finite-element model of the electrostatic sensor and pipeline. The modeling method is validated by comparing the modeling results of a nonintrusive circular electrode with an established analytical solution. The modeling results are used for in-depth analysis and informed design of a particular sensor configuration.

Item Type: Article
Additional Information: [1] Date of Publication : 24 April 2009. Date of Current Version : 07 July 2009. Issue Date : August 2009.
Uncontrolled Keywords: electrode, electrostatic sensors, finite-element modeling (FEM), flow measurement, pneumatic conveying, pulverized fuel, two-phase flow
Subjects: Q Science > QA Mathematics
T Technology > TP Chemical technology
Pre-2014 Departments: School of Engineering
School of Engineering > Department of Computer & Communications Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:17
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/6816

Actions (login required)

View Item View Item