Preview

Industrial laboratory. Diagnostics of materials

Advanced search
Open Access Open Access  Restricted Access Subscription Access

Determining of the thermophysical properties of materials with indirect control of the temperature of the medium bordering the wall

https://doi.org/10.26896/1028-6861-2025-91-1-30-43

Abstract

Temperature control of a medium bounded by walls without direct placement of sensors in it is important to ensure efficient operation of many devices and process units (heat treatment devices, engines, reactors, etc.). However, development of a monitoring method with a wide scope of application requires automation of determination of thermophysical properties of wall and medium materials without specialized tests, which is difficult due to the individual specifics of each object. The paper presents the results of determining the thermophysical properties of materials during indirect monitoring of the temperature of the medium bordering the wall. We investigated the difficulties arising in the automation of determining the properties of materials during adaptation of models of complex heat exchange between the medium and the wall with partially uncertain properties. We used simplified heat exchange models making it possible to present the model signals as increments relative to the initial moment for the time period and to reduce the effect of the mismatch between the functional form of the model and the object on the indirect monitoring results. The parameters unknown during model adaptation were determined based on retrospective data of a limited time domain. It is shown that the model can be used to monitor a generalized estimate of the temperature of the medium near the point of temperature monitoring in the wall with subsequent prediction of the consequences of varying the temperature of the isolated medium. The efficiency of the proposed approach is demonstrated using a case study of heating fireclay bricks. The results obtained can be used in developing universal temperature control methods applicable to various objects.

About the Authors

M. Yu. Ryabchikov
Nosov Magnitogorsk State Technical University
Russian Federation

Mikhail Yu. Ryabchikov

38, prosp. Lenina, Magnitogorsk, 455000



E. S. Ryabchikova
Nosov Magnitogorsk State Technical University
Russian Federation

Elena S. Ryabchikova

38, prosp. Lenina, Magnitogorsk, 455000



E. G. Neshporenko
Nosov Magnitogorsk State Technical University
Russian Federation

Evgeniy G. Neshporenko

38, prosp. Lenina, Magnitogorsk, 455000



T. G. Sukhonosova
Nosov Magnitogorsk State Technical University
Russian Federation

Tatyana G. Sukhonosova

38, prosp. Lenina, Magnitogorsk, 455000



E. I. Vasilyeva
Nosov Magnitogorsk State Technical University
Russian Federation

Elena I. Vasilyeva

38, prosp. Lenina, Magnitogorsk, 455000



References

1. Pobedria B. E., Kravchuk A. S., Arizpe P. A. Identification of the coefficients in a non-stationary heat conductivity equation / Vuchislitelnaya mekhanika sploshnukh sred. 2008. Vol. 1. N 4. P. 78 – 87 [in Russian].

2. Jinfei Wang, Orest Kochan, Krzysztof Przystupa, Jun Su. Information-measuring System to Study the Thermocouple with Controlled Temperature Field / Measurement science review. 2019. Vol. 19. N 4. P. 161 – 169. DOI: 10.2478/msr-2019-0022

3. Petukhova V. V., Ogorodnikova O. M. Modeling of the thermophysical properties of molding materials by solving the inverse heat conductivity problem / Industr. Lab. Mater. Diagn. Vol. 90. N 1. P. 42 – 49 [in Russian]. DOI: 10.26896/1028-6861-2024-90-1-42-49

4. Ogorodnikova O. M., Martynenko S. V. Computational and experimental adjustment of the databases for computer simulation of cast technologies / Industr. Lab. Mater. Diagn. Vol. 81. N 10. P. 40 – 43 [in Russian].

5. Mordasov S. A., Negulyaeva A. P., Chernyshov V. N. Control of the thermophysical characteristics of building materials by the adaptive method using microwave heating / Industr. Lab. Mater. Diagn. Vol. 86. N 2. P. 30 – 36 [in Russian]. DOI: 10.26896/1028-6861-2020-86-2-30-36

6. Ping Xiong, Jian Deng, Tao Lu, Qi Lu, Yu Liu, Yong Zhang. A sequential conjugate gradient method to estimate heat flux for nonlinear inverse heat conduction problem / Annals of Nuclear Energy. 2020. Vol. 149. 107798. DOI: 10.1016/j.anucene.2020.107798

7. Parsunkin B. N., Andreev S. M., Bondareva A. R., Akhmetov U. B. Continuous temperature control of liquid steel in technological units of metallurgical production / Vestnik YuUrGU. 2018. Vol. 18. N 3. P. 33 – 41 [in Russian]. DOI: 10.14529/met180304

8. Lu T., Liu B., Jiang P., Zhang Y., Li H. A two-dimensional inverse heat conduction problem in estimating the fluid temperature in a pipeline / Applied Thermal Engineering. 2010. Vol. 30. N 13. P. 1574 – 1579. DOI: 10.1016/j.applthermaleng.2010.03.011

9. Lu T., Liu B., Jiang P. Inverse estimation of the inner wall temperature fluctuations in a pipe elbow / Applied Thermal Engineering. 2011. Vol. 31. N 11 – 12. P. 1976 – 1982. DOI: 10.1016/j.applthermaleng.2011.03.002

10. Liuwei Cheng, Fengquan Zhong, Hongbin Gu, Xinyu Zhang. Application of conjugate gradient method for estimation of the wall heat flux of a supersonic combustor / International Journal of Heat and Mass Transfer. 2016. Vol. 96. P. 249 – 255. DOI: 10.1016/j.ijheatmasstransfer.2016.01.036

11. Liu Linhua, Tan Heping, Yu Qizheng. Inverse radiation problem of temperature field in three-dimensional rectangular furnaces / International Communications in Heat and Mass Transfer. 1999. Vol. 26. N 2. P. 239 – 248.

12. Ling Shen, Zhaohui Jiang, Weihua Gui, Chunhua Yang, Yalin Wang, Bei Sun. Modelling of Inner Surface Temperature Field of Blast Furnace Wall Based on Inverse Heat Conduction Problems / IFAC-Papers On-Line. 2019. Vol. 52. N 14. DOI: 10.1016/j.ifacol.2019.09.167

13. Ryabchikov M. Yu., Ryabchikova E. S., Shmanev D. E., Kokorin I. D. Strip cooling control for flexible production of galvanized flat steel / Steel in Translation. 2021. Vol. 51. N 7. P. 446 – 455. DOI: 10.17073/0368-0797-2021-7-519-529

14. Ryabchikov M. Yu., Ryabchikova E. S. Models for predictive thermal control in steel heat treatment using the continuous HD galvanizing units / Izvestiya vuzov. 2023. N 12(765). P. 80 – 96 [in Russian]. DOI: 10.18698/0536-1044-2023-12-80-96

15. Hongwu Fana, Bingxi Lib, Lidan Yangb, Ruzhu Wanga. Simultaneous estimation of the temperature and heat rate distributions within the combustion region by a new inverse radiation analysis / Journal of Quantitative Spectroscopy & Radiative Transfer. 2002. Vol. 74. P. 75 – 83. DOI: 10.1016/S0022-4073(01)00253-9

16. Farzan H., Hosseini Sarvari S., Mansouri S. Inverse boundary design of a radiative smelting furnace with ablative phase change phenomena / Applied Thermal Engineering. 2016. Vol. 98. P. 1140 – 1149. DOI: 10.1016/j.applthermaleng.2016.01.029

17. Mirko Gamba, Hakan Ertürk, Ofodike A. Ezekoye, John R. Howell. Modeling of a radiative RTP-type furnace through an inverse design: mathematical model and experimental results / Proceedings of ASME International Mechanical Engineering Congress & Exposition. — New Orleans, 2002. P. 237 – 246. DOI: 10.1115/IMECE2002-33844

18. Horsman A. P., Daun K. J. Design Optimization of a Two-Stage Porous Radiant Burner through Response Surface Modeling / Numerical Heat Transfer. Part A. Applications: An International Journal of Computation and Methodology. 2011. Vol. 60. N 9. P. 727 – 745. DOI: 10.1080/10407782.2011.627782

19. Larissa D. Lemos, Rogerio Brittes, Francis H. R. França. Application of inverse analysis to determine the geometric configuration of filament heaters for uniform heating / International Journal of Thermal Sciences. 2016. Vol. 105. P. 1 – 12. DOI: 10.1016/j.ijthermalsci.2016.02.015

20. Rahul Yadav, Swapnil Tripathi, Shailendra Asati, Malay K. Das. A combined neural network and simulated annealing based inverse technique to optimize the heat source control parameters in heat treatment furnaces / Inverse Problems in Science and Engineering. 2020. Vol. 28. N 9. P. 1265 – 1286. DOI: 10.1080/17415977.2020.1719087

21. Bayat N., Mehraban S., Sarvari S. Inverse boundary design of a radiant furnace with diffuse-spectral design surface / International Communications in Heat and Mass Transfer. 2010. Vol. 37. P. 103 – 110. DOI: 10.1016/j.icheatmasstransfer.2009.07.005

22. Leila Darvishvand, Babak Kamkari, Farshad Kowsary. Optimal design approach for heating irregularshaped objects in three-dimensional radiant furnaces using a hybrid genetic algorithm-artificial neural network method / Engineering Optimization. 2017. Vol. 50. N 6. P. 1 – 19. DOI: 10.1080/0305215X.2017.1323889

23. Martín E., Meis M., Mourenza C., Rivas D., Varas F. Fast solution of direct and inverse design problems concerning furnace operation conditions in steel industry / Applied Thermal Engineering. 2012. Vol. 47. P. 41 – 53. DOI: 10.1016/j.applthermaleng.2012.03.012

24. Hakan Erturk, Mirko Gamba, Ofodike A. Ezekoye, John R. Howell. Validation of inverse boundary condition design in a thermometry test bed / Journal of Quantitative Spectroscopy & Radiative Transfer. 2008. Vol. 109. P. 317 – 326. DOI: 10.1016/j.jqsrt.2007.08.029

25. Gulin A. I., Amirov A. R. Review of modern methods for measuring gas temperature in the combustion chamber of a gas turbine engine / Trends in the development of science and education. 2020. N 68-3. P. 72 – 76 [in Russian]. DOI: 10.18411/lj-12-2020-114

26. Rene Pinnau. Analysis of optimal boundary control for radiative heat transfer modeled by the SP1-system / Commun. Math. Sci. 2007. Vol. 5. N 4. P. 951 – 969.

27. Ryabchikov M. Yu., Ryabchikova E. S., Novak V. S. Hybrid Model for Metal Temperature Control during Hot Dip Galvanizing of Steel Strip / Mekhatron. Avtomat. Upravl. 2023. Vol. 24. N 8. P. 421 – 432 [in Russian]. DOI: 10.17587/mau.24.421-432

28. Ryabchikov M. Yu., Ryabchikova E. S. Model for predictive control of the temperature of the zinc melt in the bath during continuous hot-dip galvanizing of steel strip / Problems of ferrous metallurgy and materials science. 2024. N 1. P. 64 – 73 [in Russian]. DOI: 10.54826/19979258_2024_1_13

29. Kuznetsova A. E., Skvortsova M. P., Stefanyk E. V. The inverse problem solution of heat conduction for the initial conditions identification of the boundary value problem / Vestn. SGTU. 2014. Vol. 43. N 3. P. 155 – 162 [in Russian].

30. Diligenskaya A. N. Solution of the retrospective inverse heat conduction problem with parametric optimization / Teplofiz. Vysok. Temper. 2018. Vol. 56. N 3. P. 382 – 388 [in Russian]. DOI: 10.7868/S0040364418030110

31. Yaparova N. M., Gavrilova T. P. Numerical method for predicting temperature using the Volterra equation / Marchukov Scientific Readings. 2019. P. 570 – 574 [in Russian]. DOI: 10.24411/9999-016A-2019-10090

32. Bing Bai, Wenbin Yang, Xinhua Qi, Qingfeng Che, Quan Zhou, Weimin Sun, Shuang Chen. Experimental study of thermocouple temperature measurement based on coherent anti-Stokes Raman spectroscopy / AIP Advances. 2023. Vol. 13. 115216. DOI: 10.1063/5.0176359

33. Dariusz Michalski, Kinga Strąk, Magdalena Piasecka. Comparison of two surface temperature measurement using thermocouples and infrared camera / EFM16 — Experimental Fluid Mechanics. 2017. Vol. 143.02075. DOI: 10.1051/epjconf/201714302075

34. Tobias Krille, Rico Poser, Markus Diel, Jens von Wolfersdorf. Conduction and Inertia Correction for Transient Thermocouple Measurements. Part II: Experimental Validation and Application / XXV Biennial Symposium on Measuring Techniques in Turbomachinery (MTT 2020). — EDP Sciences, 2022. Vol. 345.01003. DOI: 10.1051/e3sconf/202234501003

35. Richard Skifton, Joe Palmer, Alex Hashemian. Optimized High-Temperature Irradiation-Resistant Thermocouple for Fast-Response Measurements / ANIMMA 2021 — Advancements in Nuclear Instrumentation Measurement Methods and their Applications. 2021. Vol. 253.06004. DOI: 10.1051/epjconf/202125306004

36. Raymond Litteaur. In Situ Verification Techniques for Multipoint Thermocouples in Pressure Vessels / Technical Report. 2018. DOI: 10.13140/RG.2.2.20703.30885

37. Poroshina E. Priority 2030: Scientists have invented smart temperature sensors for metallurgy and mechanical engineering. https://www.susu.ru/ru/news/2023/04/29/prioritet-2030-uchenye-izobreli-umnye-datchiki-temperatury-dlya-metallurgii-i (accessed 21.05.2024) [in Russian].

38. Kowsary F., Behbahaninia A., Pourshaghaghy A. Transient heat flux function estimation utilizing the variable metric method / International Communications in Heat and Mass Transfer. 2006. Vol. 33. P. 800 – 810. DOI: 10.1016/j.icheatmasstransfer.2006.02.008


Review

For citations:


Ryabchikov M.Yu., Ryabchikova E.S., Neshporenko E.G., Sukhonosova T.G., Vasilyeva E.I. Determining of the thermophysical properties of materials with indirect control of the temperature of the medium bordering the wall. Industrial laboratory. Diagnostics of materials. 2025;91(1):30-43. (In Russ.) https://doi.org/10.26896/1028-6861-2025-91-1-30-43

Views: 144


ISSN 1028-6861 (Print)
ISSN 2588-0187 (Online)