Recent advances in 3D flame tomography

Yong Yan, Tian Qiu, Gang Lu, Md Moinul Hossain, Guillermo Gilabert

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

11 Citations (Scopus)

Abstract

To reduce greenhouse gas emissions from fossil fuel fired power plants a range of new combustion technologies are being developed or refined, including oxy­fuel combustion, co­firing biomass with coal and fluidized bed combustion. Flame characteristics under such combustion conditions are expected to be different from those in normal air fired combustion processes. Quantified flame characteristics such as temperature distribution, oscillation frequency, and ignition volume play an important part in the optimized design and operation of the environmentally friendly power generation systems. However, it is challenging to obtain such flame characteristics particularly through a three­ dimensional (3D), non­intrusive means. Various 3D tomography methods have been proposed to visualize and characterize combustion flames. These include passive optical tomography, laser based tomography, and electrical tomography. This paper identifies the challenges in 3D flame tomography and reviews the existing techniques for quantitative characterization of combustion flames. Future trends in 3D flame tomography for applications in the power generation industry are discussed.

Original languageEnglish
Title of host publication6th World Congress in Industrial Process Tomography
Pages1530-1539
Number of pages10
Publication statusPublished - 1 Jan 2010
Event6th World Congress in Industrial Process Tomography - Beijing, United Kingdom
Duration: 6 Sep 20109 Sep 2010

Conference

Conference6th World Congress in Industrial Process Tomography
CountryUnited Kingdom
CityBeijing
Period6/09/109/09/10

Keywords

  • biomass
  • combustion
  • flame
  • fossil fuel
  • imaging
  • power generation
  • tomography

Fingerprint Dive into the research topics of 'Recent advances in 3D flame tomography'. Together they form a unique fingerprint.

Cite this