Thermocouple response time estimation and temperature signal correction for an accurate heat flux calculation in inverse heat conduction problems

1995 ◽

Author(s):

Hans-Jürgen Reinhardt ◽

Dinh Nho Hao

Keyword(s):

Heat Flux ◽

Heat Conduction ◽

Numerical Methods ◽

Stationary Point ◽

Forthcoming Paper ◽

Inverse Heat Conduction ◽

Piecewise Constant ◽

Numerical Tests ◽

Inverse Heat Conduction Problems ◽

Special Case

Abstract In this contribution we propose new numerical methods for solving inverse heat conduction problems. The methods are constructed by considering the desired heat flux at the boundary as piecewise constant (in time) and then deriving an explicit expression for the solution of the equation for a stationary point of the minimizing functional. In a very special case the well-known Beck method is obtained. For the time being, numerical tests could not be included in this contribution but will be presented in a forthcoming paper.

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Applying Neural Networks to the Solution of the Inverse Heat Conduction Problem in a Gun Barrel

Journal of Pressure Vessel Technology ◽

10.1115/1.2937763 ◽

2008 ◽

Vol 130 (3) ◽

Cited By ~ 4

Author(s):

Y. Hwang ◽

S. Deng

Keyword(s):

Neural Network ◽

Heat Flux ◽

Heat Conduction ◽

Heat Conduction Problem ◽

Nonlinear Function ◽

Inverse Heat Conduction ◽

Unknown Parameters ◽

Acceptable Error ◽

Gun Barrel ◽

Inverse Heat Conduction Problems

The primary cause of gun barrel erosion is the heat generated by the shell as its travels along the barrel. Therefore, calculating the heat flux input to the gun bore is very important when investigating wear problems in the gun barrel and examining its thermomechanical properties. This paper employs the continuous-time analog Hopfield neural network (CHNN) to compute the temperature distribution in various forward heat conduction problems. An efficient technique is then proposed for the solution of inverse heat conduction problems using a three-layered backpropagation neural network (BPN). The weak generalization capacity of BPN networks when applied to the solution of nonlinear function approximations is improved by employing the Bayesian regularization algorithm. The CHNN scheme is used to calculate the temperature in a 155mm gun barrel and the trained BPN is then used to estimate the heat flux of the inner surface of the barrel. The results show that the proposed neural network analysis method successfully solves forward heat conduction problems and is capable of predicting the unknown parameters in inverse problems with an acceptable error.

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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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