### Abstract

Original language | English |
---|---|

Pages (from-to) | 1177-1189 |

Number of pages | 13 |

Journal | Inverse Problems |

Volume | 13 |

Issue number | 5 |

DOIs | |

Publication status | Published - 1997 |

MoE publication type | A1 Journal article-refereed |

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### Cite this

*Inverse Problems*,

*13*(5), 1177-1189. https://doi.org/10.1088/0266-5611/13/5/005

}

*Inverse Problems*, vol. 13, no. 5, pp. 1177-1189. https://doi.org/10.1088/0266-5611/13/5/005

**Gas temperature mapping using impedance tomography.** / Baroudi, Djebar; Somersalo, Erkki.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Gas temperature mapping using impedance tomography

AU - Baroudi, Djebar

AU - Somersalo, Erkki

PY - 1997

Y1 - 1997

N2 - This paper discusses a novel technique of estimating gas temperatures based on impedance tomography. More specifically, assume that we have a gas funnel (e.g. doorway, window, chimney) equipped with a mesh of thin electrically conducting filaments. Furthermore, assume that the thermal and thermoelectric properties of the conducting material are known. The temperature mapping method is based on changes of the resistivity of the filaments by the changes in temperature. The inverse problem is closely related to the standard tomography problem. Due to the severe underdetermination of the problem, common inversion techniques used in computerized tomography cannot be employed here. The problem is, therefore, recast in a form of a Bayesian parameter estimation problem. Markov chain Monte Carlo methods (MCMC) are applied for exploring the posterior distribution.

AB - This paper discusses a novel technique of estimating gas temperatures based on impedance tomography. More specifically, assume that we have a gas funnel (e.g. doorway, window, chimney) equipped with a mesh of thin electrically conducting filaments. Furthermore, assume that the thermal and thermoelectric properties of the conducting material are known. The temperature mapping method is based on changes of the resistivity of the filaments by the changes in temperature. The inverse problem is closely related to the standard tomography problem. Due to the severe underdetermination of the problem, common inversion techniques used in computerized tomography cannot be employed here. The problem is, therefore, recast in a form of a Bayesian parameter estimation problem. Markov chain Monte Carlo methods (MCMC) are applied for exploring the posterior distribution.

U2 - 10.1088/0266-5611/13/5/005

DO - 10.1088/0266-5611/13/5/005

M3 - Article

VL - 13

SP - 1177

EP - 1189

JO - Inverse Problems

JF - Inverse Problems

SN - 0266-5611

IS - 5

ER -