An experimental and straightforward approach to simultaneously estimate temperature-dependent thermophysical properties of metallic materials

Ramos, Nícolas Pinheiro; Antunes, Mariana de Melo; Silva, Sandro Metrevelle Marcondes de Lima e

doi:10.1016/j.ijthermalsci.2021.106960

Cited by 10 publications

(9 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, for magnetic materials, it was analysed whether the magnetic parameters, that is, magnetic permeability, and the related electrical parameters, that is, resistivity, can significantly affect the accuracy of the estimation of the thermal diffusivity by dependence Energies 2024, 17, 887 6 of 19 (6) in the system from Figure 2a. The study was carried out in accordance with the classic one-factor-at-a-time (OFAT) approach, that is, examining the impact of each parameter separately.…”

Section: Using the Impulse Methods To Estimate The Thermal Diffusivit...mentioning

confidence: 99%

“…On the other hand, growing technological requirements increasingly lead to the need for precise, reliable information about the properties of the processed material, which leads to the need to verify them in situ. The importance of the problem raised is confirmed by numerous publications [2][3][4][5][6][7][8][9][10][11], in which the issue of the possibly simplest and quickest way to determine material properties is considered, preferably several at once using one measurement station. The cited literature examples mainly concern attempts to determine thermal properties, that is, thermal diffusivity and volumetric heat capacity.…”

Section: Introductionmentioning

confidence: 99%

“…In the frequently used contact methods of providing thermal forcing, there are also significant problems with eliminating the influence of thermal resistances on connections [5]. In recent years, there has been promising information [6,7] about measurement techniques, allowing for the simultaneous determination of the temperature characteristics of specific heat and the specific thermal conductivity of metal samples with an accuracy of several percent. However, these techniques are based on the use of a resistive contact heat source, which makes them less useful in the case of higher temperatures encountered in metal processing thermal processes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Inductive Method for Comprehensive Estimation of Temperature-Dependent Electrical and Thermal Properties of Conductive Ferromagnetic Materials

Zgraja

2024

Energies

View full text Add to dashboard Cite

Reliable information about the properties of the processed materials has a significant impact on the effects of their processing. In induction heating processes, this also applies to information about the influence of temperature T on these properties. These are both thermal and electro-magnetic properties. Based on previous studies, a comprehensive experimental method is presented for estimating the temperature characteristics of thermal diffusivity, volumetric heat capacity and resistivity on one measurement station, with particular attention to ferromagnetic materials. The estimation process is carried out on an induction heating stand using forcing signals from an inverter generator. In a computer-controlled cycle that changes the base temperature level, basic measurements of thermal and electrical properties are carried out on a material sample in the form of a cylindrical disk. They are the results of the analysis of the temperature and electromagnetic responses of a material sample to short- and long-term step pulses of a sinusoidal excitation signal with a frequency of approximately 40 kHz. The presented estimation method can be treated as a final method or a preliminary procedure for radically narrowing the variability in decision variables inthe optimization process of simultaneous determination of the sought material characteristics.

show abstract

Section: Using the Impulse Methods To Estimate The Thermal Diffusivit...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Inductive Method for Comprehensive Estimation of Temperature-Dependent Electrical and Thermal Properties of Conductive Ferromagnetic Materials

Zgraja

2024

Energies

View full text Add to dashboard Cite

show abstract

“…Embedded thermocouple wires need that some filler material to be introduced into a milled hole, which causes a discontinuity effect [51]. In this context, only the bottom surface can be explored to collect temperature data with wire thermocouples in the 1D thermal model [33,36,43]. Thus, data from the 1D experiment was measured at the bottom surface, i.e., at location x=L.…”

Section: Experimental Aspectsmentioning

confidence: 99%

“…These approaches require experiments or numerical simulations, where the sample is subjected to different initial conditions. Researchers have fitted lines to sparse-point estimates using whole temperature domain data and a modified version of the Levenberg-Marquardt method [43]. This dispersion arises from the 1D thermal model used, leading to problems related to low thermal sensitivity when experimentally investigating metals.…”

Section: Introductionmentioning

confidence: 99%

Complementary transient thermal models and metaheuristics to simultaneously identify linearly temperature-dependent thermal properties of austenitic stainless steels

Ramos¹,

Antunes²,

Silva³

2022

Phys. Scr.

Self Cite

View full text Add to dashboard Cite

This paper presents an experimental approach for simultaneously identifying the temperature-dependent thermal conductivity (k) and specific heat (cp) of 304 austenitic stainless steel (ASS) using complementary transient experiments and metaheuristics. Inverse thermal analysis was based on two heat conducting solids with different geometries. In estimation problems in general, one seeks to obtain as much sensitive data as possible using as few sensors as possible. Single thermocouple data were collected for each thermal model. An objective function fitting these complementary measurements to the corresponding numerical temperatures was minimized using the Lichtenberg algorithm. This metaheuristic algorithm takes advantage of more sensitive information provided by using complementary data, enabling for an accurate inverse solution, even when dealing with wide search ranges. The proposed technique provides a cost-effective and robust property estimation from tests conducted at room temperature. Single-step estimation occurred throughout the whole temperature domain to determine the parameters for linear functions representing the temperature dependence of k and cp. The obtained lines agreed well with curves from the literature. The 95% confidence bounds for the parameters of interest indicated deviations below ± 8.5%. Error analysis considering numerical and experimental processes showed an uncertainty close to ± 3%, applied to all estimated parameters.

show abstract

Effects of tempering temperature on temperature-dependent thermal properties of 1045 steel

Ramos

Antunes²,

Silva³

et al. 2023

J Mater Sci

View full text Add to dashboard Cite

An experimental and straightforward approach to simultaneously estimate temperature-dependent thermophysical properties of metallic materials

Cited by 10 publications

References 45 publications

An Inductive Method for Comprehensive Estimation of Temperature-Dependent Electrical and Thermal Properties of Conductive Ferromagnetic Materials

An Inductive Method for Comprehensive Estimation of Temperature-Dependent Electrical and Thermal Properties of Conductive Ferromagnetic Materials

Complementary transient thermal models and metaheuristics to simultaneously identify linearly temperature-dependent thermal properties of austenitic stainless steels

Effects of tempering temperature on temperature-dependent thermal properties of 1045 steel

Contact Info

Product

Resources

About