Literature DB >> 29489791

Toward real-time volumetric tomography for combustion diagnostics via dimension reduction.

Tao Yu, Hecong Liu, Jiaqi Zhang, Weiwei Cai, Fei Qi.   

Abstract

Volumetric tomography for combustion diagnostics is experiencing significant progress during the past few years due to its capability of imaging evolving turbulent flows. Such capability facilitates the understanding of the mechanisms behind complicated combustion phenomena such as lean blowout, acoustic oscillations, and formation of soot particles. However, these techniques are not flawless and suffer from high computational cost which prevents them from applications where real-time reconstructions and online monitoring are necessary. In this Letter, we propose a new reconstruction method that can effectively reduce the dimension of the inversion problem, which can then be solved with a minimum computational effort. This method and a classical iterative method were tested against each other using a proof-of-concept experiment in which endoscopic computed tomography of chemiluminescence (CTC) was implemented. The results show that the proposed method can dramatically reduce the computational time and, at the same time, maintain similar reconstruction accuracy, as opposed to the classical approach. Although this Letter was discussed under the context of CTC, it can be applied universally to other modalities of volumetric tomography such as volumetric laser-induced fluorescence.

Year:  2018        PMID: 29489791     DOI: 10.1364/OL.43.001107

Source DB:  PubMed          Journal:  Opt Lett        ISSN: 0146-9592            Impact factor:   3.776


  1 in total

1.  Gray wolf optimization-extreme learning machine approach for diabetic retinopathy detection.

Authors:  Musatafa Abbas Abbood Albadr; Masri Ayob; Sabrina Tiun; Fahad Taha Al-Dhief; Mohammad Kamrul Hasan
Journal:  Front Public Health       Date:  2022-08-01
  1 in total

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