On the optimization of experimental parameters in photopyroelectric investigation of thermal diffusivity of solids

Strzałkowski, K.; Dădârlat, D.; Streza, M.; Firszt, F.

doi:10.1016/j.tca.2015.06.027

Cited by 27 publications

(18 citation statements)

References 26 publications

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“…The thickness of the specimens was measured with a micrometer with an accuracy of 10 mm, which produces additional uncertainty of about 0.2e0.3%. The systematic error connected with the presence of coupling fluid in case of thermal diffusivity [18] and effusivity can be estimated as 3e4%. One can conclude that final uncertainty of the thermal conductivity value is of the order of 5e6%.…”

Section: Resultsmentioning

confidence: 99%

“…In modified setup the sample is stick to the sensor with ethylene glycol and some pushing force is applied to it. Thanks to that the influence of the thickness of the liquid on thermal diffusivity values has been reduced [17,18]. The modulation frequency of the excitation source was changed in the range 1e15 Hz and 5e45 Hz in case of back and front mode, respectively.…”

Section: Experimental Systemsmentioning

confidence: 99%

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Effect of lattice disorder on the thermal conductivity of ZnBeSe, ZnMgSe and ZnBeMgSe crystals

Strzałkowski

2015

Materials Chemistry and Physics

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Section: Resultsmentioning

confidence: 99%

Section: Experimental Systemsmentioning

confidence: 99%

Effect of lattice disorder on the thermal conductivity of ZnBeSe, ZnMgSe and ZnBeMgSe crystals

Strzałkowski

2015

Materials Chemistry and Physics

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“…It has also already been shown by several researchers how the presence of a coupling fluid can influence the results obtained with PPE technique [5][6][7][8]. It was demonstrated that even 1 µm layer of a coupling liquid can change the slope of the phase-root frequency graph, especially in case of highly conductive or thin samples [5,8]. It was also shown that thanks to some optimization procedures, this drawback could be minimized [8].…”

Section: Introductionmentioning

confidence: 91%

“…It was demonstrated that even 1 µm layer of a coupling liquid can change the slope of the phase-root frequency graph, especially in case of highly conductive or thin samples [5,8]. It was also shown that thanks to some optimization procedures, this drawback could be minimized [8].…”

Section: Introductionmentioning

confidence: 99%

Effect of the surface roughness on the measured thermal diffusivity of the ZnBeMnSe single-crystalline solids

et al. 2019

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In this work, the influence of the surface treatment of bulk samples of the single-crystals observed by means of the Atomic Force Microscopy on the measured thermal diffusivity of the material is presented and discussed. The mixed Zn 1 − x − y Be x Mn y Se crystals were grown from the melt by the modified high-pressure Bridgman method with different Be and Mn contents. The investigated specimens were first ground, then polished, chemically etched and finally annealed in zinc vapor. After each surface technological preparation the AFM images were taken and the thermal diffusivity of Zn 1 − x − y Be x Mn y Se compounds was determined by the photopyroelectric technique in the back configuration. The ground sample exhibited the highest roughness, whereas the annealed sample showed the lowest one. It has also been shown that the thermal diffusivity of the ground sample was significantly lower compared to the samples whose surface has been treated by other procedures. It was assumed that the measured thermal diffusivity had an effective value attained through the mediation of the thermal parameters of the bulk sample with those of the damaged surface layer. To analyze the results, a two-layer model proposed by J.J. Alvarado-Gil was employed. It turned out that the effective thermal diffusivity value depends much stronger on the conductivity of the system than on the diffusivity of the bulk.

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“…The tested material was the sample of a glassy carbon where these techniques were used to gain the thermal diffusivity of a sample. Experiments and numerical simulations were performed in order to evaluate the coupling fluid influence to the thermal diffusivity values by a photo-pyroelectric technique, assuming that the values of thermal diffusivity obtained by thermography were correct [13]. Another method that was applied for a material's thermal diffusivity determination was based on the Markov-Chain Monte Carlo method (MCMC) [14].…”

Section: Overview Of Thermal Properties Researchmentioning

confidence: 99%

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

Durdán¹,

Kačur²,

Laciak³

et al. 2019

Energies

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In annealing, steel coils should be heated and consequently cooled according to the technological prescription defined for the annealed type of steel. It is appropriate to develop the systems and methods for estimation of the steel coil inner temperature for that reason. The proposal for such a system of indirect measurement of inner temperature is described in this study. This system, in the form of the mathematical model, is developed based on the theory of heat transfer and needs thermophysical parameters as inputs. In many cases, the thermophysical properties are difficult to access or unknown for the specific composition of the material being processed. In this paper, two optimization methods were applied to estimate two thermophysical properties. The application of the iterative dynamic programming method is aimed to estimate optimal thermal diffusivity. The verification of this method was performed on 11 laboratory measurements. The algorithm of the gradient method was used for estimating thermal conductivity and was verified on seven operational measurements. Results show that the optimized values of thermophysical properties increased the accuracy of the steel coil inner temperature estimation in the locations nearer to the steal coil central axis.

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On the optimization of experimental parameters in photopyroelectric investigation of thermal diffusivity of solids

Cited by 27 publications

References 26 publications

Effect of lattice disorder on the thermal conductivity of ZnBeSe, ZnMgSe and ZnBeMgSe crystals

Effect of lattice disorder on the thermal conductivity of ZnBeSe, ZnMgSe and ZnBeMgSe crystals

Effect of the surface roughness on the measured thermal diffusivity of the ZnBeMnSe single-crystalline solids

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

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