This paper presents a different method for simultaneously estimating the thermal conductivity and the volumetric heat capacity of metallic samples. The contribution of this work consists in how it obtains the optimal conditions to produce such estimates. This method uses different intensities of heat flux in the same experiment, all in accordance with the analyses of the sensitivity coefficients. These analyses were performed along with an objective function to find both the best points to be analyzed and the best experimental configuration for estimating these properties. The method consists in positioning a uniform heat flux on the top surface and insulation on the bottom surface where a thermocouple is placed. The thermal properties were obtained by solving the heat diffusion equation for the one-dimensional model. The estimated values of the thermal properties for all materials present a difference lower than 2%, and an uncertainty analysis presented a result lower than 4% for all materials.

Thermal conductivity, λ, and volumetric heat capacity, ρcp, variables that depend on temperature were simultaneously estimated in a diverse technique applied to AISI 1045 and AISI 304 samples. Two distinctive intensities of heat flux were imposed to provide a more accurate simultaneous estimation in the same experiment. A constant heat flux was imposed on the upper surface of the sample while the temperature was measured on the opposite insulated surface. The sensitivity coefficients were analyzed to provide the thermal property estimation. The Broydon-Fletcher-Goldfarb-Shanno (BFGS) optimization technique was applied to minimize an objective function. The squared difference objective function of the numerical and experimental temperatures was defined considering the error generated by the contact resistance. The temperature was numerically calculated by using the finite difference method. In addition, the reliability of the results was assured by an uncertainty analysis. Results showing a difference lower than 7% were obtained for λ and ρcp, and the uncertainty values were above 5%.

This work aims to present a method for simultaneously estimating the thermal conductivity, k, and specific heat, c p , in samples of stainless steel 304 and cemented carbide by accounting the imperfect thermal contact at the heater-sample interface. A transient one-dimensional heat conduction model with constant thermal properties is used. The metallic sample is placed in the middle of a polyimide heater and a thermal insulator. A constant heat flux is applied on the specimen upside surface and a thermal insulation condition is maintained on the opposing surface, where a type T thermocouple measures the temperature response. Contact resistance is determined and accounted for as a reducing factor on heat flux. Instead of considering a lumped model, a microscopic approach of the contacting regions is used to describe both the surface roughness and the fluid gap. With the intention of guaranteeing simultaneous and reliable estimates for both thermal properties, sensitivity analysis is used to establish heat flux intensity, experiment duration, time step for data acquisition, and other characteristics of the experiments. To simultaneously achieve both thermal properties, the optimization method BFGS (Broyden-Fletcher-Goldfarb-Shanno) is employed to minimize a least-squares objective function comparing experientially measured and numerically calculated temperatures. The numerical solution for the transient conduction problem is determined with COMSOL, which solves the transient heat diffusion problem by discretizing it applying the finite element method (FEM). The linear system of equations is solved using the PARDISO solver and backward differentiation formula (BDF) method. Heat flux is estimated employing the sequential function specification method (SFSM) as a means of verifying the robustness of parameter estimation and experimental procedure. Moreover, uncertainty analysis is performed to confirm the quality of the results obtained. Finally, the uncertainty analysis outcomes and thermal properties estimated are compared with literature.

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