Experimental determination of thermal conductivity and diffusivity using a partially heated surface method without heat flux transducer

Figures & data

Figure 1. Thermal model scheme.

Figure 2. Frequency-domain block diagram 2.

Figure 3. Dynamic thermal model system.

Figure 4. Calculation of cross-correlation of G_H.

Figure 5. Scheme of the sample/heater assembly: (a) frontal view; (b) superior view.

Figure 6. The vacuum chamber (a) with sample/heater assembly in detail (b).

Figure 7. Typical signal power generated by an on/off resistive heater element.

Figure 8. Temperature evoltution for AISI304 sample.

Figure 9. Output Y(t) given by difference of temperature evolution for AISI304 sample.

Figure 10. Estimated dimensionless heat flux, Ф(t), α_ref = 10⁻⁶ m² s⁻¹, using k = 1.0 W mK⁻¹.

Figure 11. Relation between phase factor and frequency.

Figure 12. Estimated values of k for AISI 304.

Table 1. Statistical data of the average value estimated of k, 21 experiments, confidence interval of 97.5%.

k (W mK^−1)	σ (W mK^−1)	k (W mK^−1) 11
14.99 ± 0.17	0.407	14.90

Figure 13. Estimated heat flux, φ.

Figure 14. Estimated values of α for AISI 304.

Table 2. Statistical data of the average value of α, 21 experiments, confidence interval of 97.5%.

α × 10^6 (m^2 s^−1)	σ × 10^6 (m^2 s^−1)	α × 10^6 (m^2 s^−1), 11
3.77 ± 0.029	0.0689	3.82

Figure 15. Experimental and estimated temperature evolution.

Figure 16. Error temperature between estimated temperature and experimental temperature T_e,1 − T₁.

Figure 17. Scheme of the experimental apparatus designed to identify the convection and radiation heat transfer loss from the sample into the chamber.

Figure 18. Comparison between the measured and estimated heat flux.

Figure 19. Measured and estimated heat flux residues.

Blum, JW, and Marquardt, W, 1997. An optimal solution to inverse heat conduction problems based on frequency-domain interpretation and observers, Numer. Heat Tr. B: Fund. 32 (1997), p. 453.

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