Inverse approach for estimating boundary properties in a transient fin problem

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Date

2018

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Springer

Abstract

A solution methodology is proposed for an inverse estimation of boundary conditions from the knowledge of transient temperature data. A forward model based on prevalent time-dependent heat conduction fin equation is solved using a fully implicit finite volume method. First, the inverse model is formulated and accomplished for time-invariant heat flux at the fin base, and later extended to transient heat flux, base temperature and average heat transfer coefficient. Secondly, the Nusselt number is then replaced with Rayleigh number in the forward model to realistically estimate the base temperature, which varies with respect to time, based on in-house transient fin heat transfer experiments. This scenario further corroborates the validation of the proposed inverse approach. The experimental set-up consists of a mild steel 250×150×6mm3 fin mounted centrally on an aluminium base 250×150×8mm3 plate. The base is attached to an electrical heater and insulated with glass-wool to prevent heat loss to surroundings. Five calibrated K-type thermocouples are used to measure temperature along the fin. The functional form of the unknown parameters is not known beforehand; sensitivity studies are performed to determine suitability of the estimation and location of sensors for the inverse approach. Conjugate gradient method with adjoint equation is chosen as the inverse technique and the study is performed as a numerical optimization; subsequently, the estimates show satisfactory results. © 2018, Indian Academy of Sciences.

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Keywords

Conjugate gradient method, Estimation, Finite volume method, Fins (heat exchange), Heat conduction, Heat flux, Heating, Numerical methods, Optimization, Thermocouples, Average heat transfers, Inverse, K-type thermocouples, Numerical optimizations, sensitivity, Solution methodology, Time-dependent heat conduction, Transient temperature, Inverse problems

Citation

Sadhana - Academy Proceedings in Engineering Sciences, 2018, 43, 7, pp. -

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