Training based, moving digital filter method for real time heat flux function estimation

Farshad Kowsary; Morteza Mohammadzaheri; Saeed Irano

doi:10.1016/j.icheatmasstransfer.2006.08.013

Training based, moving digital filter method for real time heat flux function estimation

Farshad Kowsary^*, Morteza Mohammadzaheri, Saeed Irano

^*Corresponding author for this work

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

24 Citations (Scopus)

Abstract

In this paper the neural networks is utilized to estimate the "filter coefficients" needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations.

Original language	English
Pages (from-to)	1291-1298
Number of pages	8
Journal	International Communications in Heat and Mass Transfer
Volume	33
Issue number	10
DOIs	https://doi.org/10.1016/j.icheatmasstransfer.2006.08.013
Publication status	Published - Dec 2006
Externally published	Yes

Keywords

Artificial neural networks
Heat flux estimation
Inverse heat conduction

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Chemical Engineering(all)
Condensed Matter Physics

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10.1016/j.icheatmasstransfer.2006.08.013

Cite this

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abstract = "In this paper the neural networks is utilized to estimate the {"}filter coefficients{"} needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations.",

keywords = "Artificial neural networks, Heat flux estimation, Inverse heat conduction",

author = "Farshad Kowsary and Morteza Mohammadzaheri and Saeed Irano",

year = "2006",

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doi = "10.1016/j.icheatmasstransfer.2006.08.013",

language = "English",

volume = "33",

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journal = "International Communications in Heat and Mass Transfer",

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T1 - Training based, moving digital filter method for real time heat flux function estimation

AU - Kowsary, Farshad

AU - Mohammadzaheri, Morteza

AU - Irano, Saeed

PY - 2006/12

Y1 - 2006/12

N2 - In this paper the neural networks is utilized to estimate the "filter coefficients" needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations.

AB - In this paper the neural networks is utilized to estimate the "filter coefficients" needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations.

KW - Artificial neural networks

KW - Heat flux estimation

KW - Inverse heat conduction

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M3 - Article

AN - SCOPUS:33750834473

SN - 0735-1933

VL - 33

SP - 1291

EP - 1298

JO - International Communications in Heat and Mass Transfer

JF - International Communications in Heat and Mass Transfer

IS - 10

ER -

Training based, moving digital filter method for real time heat flux function estimation

Abstract

Keywords

ASJC Scopus subject areas

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