Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

Giampaolo D’Alessandro, Michele Potenza, Sandra Corasaniti, Stefano Sfarra, Paolo Coppa, Gianluigi Bovesecchi and Filippo de Monte ()
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Giampaolo D’Alessandro: Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila, Italy
Michele Potenza: Department of Industrial Engineering, University of Rome “Tor Vergata”, 00133 Rome, Italy
Sandra Corasaniti: Department of Industrial Engineering, University of Rome “Tor Vergata”, 00133 Rome, Italy
Stefano Sfarra: Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila, Italy
Paolo Coppa: Department of Industrial Engineering, University of Rome “Tor Vergata”, 00133 Rome, Italy
Gianluigi Bovesecchi: Department of Enterprise Engineering, University of Rome “Tor Vergata”, 00133 Rome, Italy
Filippo de Monte: Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila, Italy

Energies, 2022, vol. 15, issue 23, 1-29

Abstract: The present review describes the up-to-date state of the evaluation of thermophysical properties (TP) of materials with three different procedures: modeling (also including inverse problems), measurements and analytical methods (e.g., through computing from other properties). Methods to measure specific heat and thermal conductivity are described in detail. Thermal diffusivity and thermal effusivity are a combination of the previously cited properties, but also for these properties, specific measurement and calculation methods are reported. Experiments can be carried out in steady-state, transient, and pulse regimes. For modeling, special focus is given to the inverse methods and parameter estimation procedures, because through them it is possible to evaluate the thermophysical property, assuring the best practices and supplying the measurement uncertainty. It is also cited when the most common data processing algorithms are used, e.g., the Gauss–Newton and Levenberg–Marquardt least squares minimization algorithms, and how it is possible to retrieve values of TP from other data. Optimization criteria for designing the experiments are also mentioned.

Keywords: thermophysical properties; steady-state methods; transient methods; inverse techniques; optimal experiment design; thermal conductivity; specific heat; thermal diffusivity (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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