Simultaneous estimations of temperaturedependent thermal conductivity and heat capacity

Chen, Han Taw; Lin, Jae Yuh

doi:10.1016/s0017-9310(97)00260-3

Cited by 29 publications

(9 citation statements)

References 12 publications

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“…In this work, the thermal conductivity is assumed to be constant or a linear function of temperature. Chen and Lin (1998) used a hybrid numerical algorithm of the Laplace transform technique and the control‐volume method to simultaneously estimate the temperature‐dependent thermal conductivity and heat capacity from temperature measurements inside the material. But, the functional forms of the thermal conductivity and heat capacity were unknown a priori.…”

Section: Introductionmentioning

confidence: 99%

A transient inverse problem in simultaneous estimation of TDTP based on MEGA

Ranjbar

Famouri

Imani

2010

International Journal of Numerical Methods for Heat &Amp; Fluid Flow

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PurposeThe main aim of this paper is to utilize the different forms of functions for the numerical solution of the two‐dimensional (2‐D) inverse heat conduction problem with temperature‐dependent thermo‐physical properties (TDTPs).Design/methodology/approachThe proposed numerical technique is based on the modified elitist genetic algorithm (MEGA) combined with finite different method (FDM) to simultaneously estimate temperature‐dependent thermal conductivity and heat capacity. In this paper, simulated (noisy and filtered) temperatures are used instead of experimental data. The estimated temperatures are obtained from the direct numerical solution (FDM) of the 2‐D conductive model by using an estimate for the unknown TDTPs and MEGA is used to minimize a least squares objective function containing estimated and simulated (noisy and filtered) temperatures.FindingsThe accuracy of the MEGA is assessed by comparing the estimated and the pre‐selected TDTPs. The results show that the measurement errors do not considerably affect the accuracy of the estimates. In other words, the proposed method provides a practical and confident prediction in simultaneously estimating the temperature‐dependent heat capacity and thermal conductivity. From the results, it is found that the RMS error between estimated and simulated temperatures is smaller for linear simulation and also we found this form convenient for parameters estimations.Research limitations/implicationsFuture approaches should find the optimal design of case study and then apply the proposed method to achieve the best results.Originality/valueApplications of the results presented in this paper can be of value in practical applications in parameter estimation even with one sensor temperature history.

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Section: Introductionmentioning

confidence: 99%

A transient inverse problem in simultaneous estimation of TDTP based on MEGA

Ranjbar

Famouri

Imani

2010

International Journal of Numerical Methods for Heat &Amp; Fluid Flow

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“…Most of the studies assumed that the thermal conductivity is only a function of the temperature [3,[5][6][7][8]. Also, some of the investigations assumed that the thermal conductivity is only a function of the spatial coordinates [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…The previous methods of IHCP to estimate the thermal conductivity mainly based on the iterative optimization technique [3,8,9]. The unknown thermal conductivity was found through minimizing the difference between calculated and measured temperature at specific points of the medium.…”

Section: Introductionmentioning

confidence: 99%

Inverse determination of thermal conductivity using semi-discretization method

Chang

2009

Applied Mathematical Modelling

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a b s t r a c tIn this work a semi-discretization method is presented for the inverse determination of spatially-and temperature-dependent thermal conductivity in a one-dimensional heat conduction domain without internal temperature measurements. The temperature distribution is approximated as a polynomial function of position using boundary data. The derivatives of temperature in the differential heat conduction equation are taken derivative of the approximated temperature function, and the derivative of thermal conductivity is obtained by finite difference technique. The heat conduction equation is then converted into a system of discretized linear equations. The unknown thermal conductivity is estimated by directly solving the linear equations. The numerical procedures do not require prior information of functional form of thermal conductivity. The close agreement between estimated results and exact solutions of the illustrated examples shows the applicability of the proposed method in estimating spatially-and temperature-dependent thermal conductivity in inverse heat conduction problem.

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“…They are in general conceived to be applied on samples with simple geometry: slab (Chen & Lin, 1998;Huang & Jan-Yuan, 1995;Jurkowski, Jarny, & Delaunay, 1997;Oladipo, Wichman, & Beck, 1999;Woodbury & Boohaker, 1996;Yang, 1998), cylinder (Ladevie, Fudym, & Batsale, 2000), or parallelepiped . Usually in the literature, inverse methods are applied only in simulation studies (Chen & Lin, 1998;Huang & Chin, 2000;Huang & JanYuan, 1995;Jurkowski, Jarny, & Delaunay, 1992;Kim, Kim, & Kim, 2002;Lesnic, Elliott, & Ingham, 1996;Sawaf, Ozisik, & Jarny, 1995;Woodbury & Boohaker, 1996;Yang, 1998;Yang, 1999). The few applications on real products concern bentonite/crushed rock mixtures (Engelhardt & Finsterle, 2003), fusing structures Nomenclature a, b, c, d polynomial coefficients, optimization variables a w water activity D mass diffusivity (m À2 s À1 ) C p specific heat (J kg À1 K À1 ) h heat transfer convection coefficient (W m 2 K À1 ) J criterion function (K 2 ) k mass transfer convection coefficient (s m À1 ) L w latent heat of water vaporization (J kg À1 ) m mass (kg) n normal to the surface, towards outside p water loss (kg) P vapor pressure (Pa) RH relative humidity…”

Section: Introductionmentioning

confidence: 99%

Estimation of thermal conductivity of sandwich bread using an inverse method

Monteau¹

2008

Journal of Food Engineering

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Simultaneous estimations of temperaturedependent thermal conductivity and heat capacity

Cited by 29 publications

References 12 publications

A transient inverse problem in simultaneous estimation of TDTP based on MEGA

A transient inverse problem in simultaneous estimation of TDTP based on MEGA

Inverse determination of thermal conductivity using semi-discretization method

Estimation of thermal conductivity of sandwich bread using an inverse method

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