A Near Real-Time Solution Approach for Surface Heat Flux Estimation in One Dimensional Inverse Heat Conduction Problems With Moving Boundary

ASME 2019 Heat Transfer Summer Conference ◽

10.1115/ht2019-3458 ◽

2019 ◽

Author(s):

Obinna Uyanna ◽

Hamidreza Najafi

Keyword(s):

Heat Flux ◽

Heat Conduction ◽

Real Time ◽

Surface Heat Flux ◽

Moving Boundary ◽

Surface Heat ◽

Inverse Heat Conduction ◽

Heat Flux Estimation ◽

Flux Estimation ◽

Inverse Heat Conduction Problems

Abstract Developing accurate and efficient solutions for inverse heat conduction problems allows advancements in the heat flux measurement techniques for many applications. In the present paper, a one-dimensional medium with a moving boundary is considered. It is assumed that two thermocouples are used to measure temperature at two locations within the medium while the front boundary is moving towards the back surface. Determining surface heat flux using measured temperature data is an inverse heat conduction problem. A filter based Tikhonov regularization method is used to develop a solution for this problem. Filter coefficients are calculated for various thicknesses of the medium. It is demonstrated that the filter coefficients can be interpolated to calculate the appropriate values for each thickness while it is continuously moving at a known rate. The use of filter method allows near real-time heat flux estimation. The developed solution is validated through several numerical test cases including a test case for a moving boundary in a medium modeled in COMSOL. It is shown that the proposed solution can effectively estimate the surface heat flux on the moving boundary in a near real-time fashion.

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Application of Artificial Neural Network As a Near-Real Time Technique for Solving Non-Linear Inverse Heat Conduction Problems in a One-Dimensional Medium With Moving Boundary

ASME 2020 Heat Transfer Summer Conference ◽

10.1115/ht2020-9054 ◽

2020 ◽

Author(s):

Hamidreza Najafi ◽

Obinna Uyanna ◽

Jian Zhang

Keyword(s):

Heat Flux ◽

Real Time ◽

Surface Heat Flux ◽

Moving Boundary ◽

Temperature Data ◽

Surface Heat ◽

Inverse Heat Conduction ◽

Heat Flux Estimation ◽

Flux Estimation ◽

Inverse Heat Conduction Problems

Abstract Developing accurate and stable solutions for inverse heat conduction problems (IHCPs) is crucial in many industrial applications where direct measurement of surface conditions, such as heat flux or temperature, is not possible in practice and temperature measurement from interior points can be obtained alternatively. IHCPs are mathematically ill-posed and therefore developing stable solutions for them is challenging. Application of intelligent algorithms for solving IHCPs has been successfully explored for several cases. In the present paper, the problem of near real-time surface heat flux estimation in a one-dimensional domain with temperature dependent material properties and moving boundary is considered. An artificial neural network (ANN) is developed to use the temperature measurement data from interior points for limited number of time steps as the inputs and calculate the surface heat flux and recession rate at the current time step as the output of the network. For this purpose, a multi-layer perceptron (MLP) network is selected, trained and tested using heat flux-temperature data that were evaluated via COMSOL Multiphysics for a 1D medium that is exposed to standard heat flux profiles on its surface (including triangular, parabolic and step function). A randomly generated heat flux profile is also applied to the surface of the medium and temperature distribution is calculated via COMSOL Multiphysics. The temperature data are then used as the inputs to the network and surface heat flux is evaluated under this condition to assess the capability of the developed ANN in surface heat flux estimation. The performance of the network when using different number of inputs (previous and future time steps from which temperature data are needed for surface heat flux estimation) as well as different network topology are explored in the presence of random measurement error. The results show that the developed approach allows accurate near real-time surface heat flux estimation in a 1-D medium with temperature dependent material properties and moving boundary. The solution of this problem can be further extended to be used in sensors for ablative thermal protection system in space vehicles.

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Particle Swarm Optimization-based algorithms for solving inverse heat conduction problems of estimating surface heat flux

International Journal of Heat and Mass Transfer ◽

10.1016/j.ijheatmasstransfer.2011.12.007 ◽

2012 ◽

Vol 55 (7-8) ◽

pp. 2062-2068 ◽

Cited By ~ 21

Author(s):

Fung-Bao Liu

Keyword(s):

Heat Flux ◽

Particle Swarm Optimization ◽

Heat Conduction ◽

Surface Heat Flux ◽

Particle Swarm ◽

Surface Heat ◽

Inverse Heat Conduction ◽

Swarm Optimization ◽

Inverse Heat Conduction Problems

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Two-probe calibration integral equation method for nonlinear inverse heat conduction problem of surface heat flux estimation

International Journal of Heat and Mass Transfer ◽

10.1016/j.ijheatmasstransfer.2017.12.072 ◽

2018 ◽

Vol 121 ◽

pp. 246-264 ◽

Cited By ~ 9

Author(s):

Hongchu Chen ◽

Jay I. Frankel ◽

Majid Keyhani

Keyword(s):

Heat Flux ◽

Surface Heat Flux ◽

Heat Conduction Problem ◽

Integral Equation Method ◽

Inverse Heat Conduction Problem ◽

Surface Heat ◽

Inverse Heat Conduction ◽

Heat Flux Estimation ◽

Flux Estimation ◽

Probe Calibration

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Application of Artificial Neural Network as a Near-Real Time Technique for Solving Non-Linear Inverse Heat Conduction Problems in a One-Dimensional Medium With Moving Boundary

10.1115/1.0001545v ◽

2021 ◽

Author(s):

Jian Zhang ◽

Obinna Uyanna ◽

Hamidreza Najafi

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Heat Conduction ◽

Real Time ◽

Moving Boundary ◽

Inverse Heat Conduction ◽

One Dimensional ◽

Non Linear ◽

Artificial Neural ◽

Inverse Heat Conduction Problems

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Finite Element Formulation for Two-Dimensional Inverse Heat Conduction Analysis

Journal of Heat Transfer ◽

10.1115/1.2911317 ◽

1992 ◽

Vol 114 (3) ◽

pp. 553-557 ◽

Cited By ~ 42

Author(s):

T. R. Hsu ◽

N. S. Sun ◽

G. G. Chen ◽

Z. L. Gong

Keyword(s):

Heat Flux ◽

Finite Element ◽

Heat Conduction ◽

Surface Heat Flux ◽

Surface Heat ◽

Element Formulation ◽

Two Dimensional ◽

Inverse Heat Conduction ◽

Discrete Point ◽

Element Algorithm

This paper presents a finite element algorithm for two-dimensional nonlinear inverse heat conduction analysis. The proposed method is capable of handling both unknown surface heat flux and unknown surface temperature of solids using temperature histories measured at a few discrete point. The proposed algorithms were used in the study of the thermofracture behavior of leaking pipelines with experimental verifications.

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