THERMAL SCIENCE

International Scientific Journal

Kun Wang

,

Bo Peng

,

Chunqiu Zhang

,

Chunqin Zhang

,

Yong Shi

,

Songtao Kong

,

Keqin Ding

RAPID RECONSTRUCTION OF TEMPERATURE FIELD OF COKE CHAMBER BASED ON POD-BP AND TIKHONOV METHOD

ABSTRACT
As the key equipment of delayed coking unit, the coking chamber generally uses the cycle heating and cooling process to produce products. Due to the large temperature rise and fall process of the cycle, the coke chamber runs under harsh thermal conditions for a long time, and the thermal stress generated by temperature fluctuation is one of the main reasons for the failure of the coke chamber structure. However, the working state of coking chamber is complex, and the traditional numerical method cannot realize timely monitoring, so it is of great practical significance to study the new method to realize timely monitoring. In this paper, POD-BP reduced order models under the second and third thermal boundary conditions are established by studying the coke chamber in the production process. The models are applied to the inversion of the spatial heat flux distribution and the calculation of the temperature field of the coke chamber, which greatly improves the calculation speed of the inversion. It has been proved that the proposed method has the advantages of good real-time performance, high precision, strong anti-interference ability and strong operability, which provides a detection method for the real-time reconstruction of temperature field and production state of coke chamber.
KEYWORDS
heat, POD-BP, Tikhonov, inverse, Reconstruction
PAPER SUBMITTED: 2022-10-17
PAPER REVISED: 2022-11-23
PAPER ACCEPTED: 2022-11-25
PUBLISHED ONLINE: 2023-01-07
DOI REFERENCE: https://doi.org/10.2298/TSCI221017216W
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2023, VOLUME 27, ISSUE Issue 5, PAGES [3513 - 3524]
REFERENCES
  1. Xia, Z. H., et al., Heat Transfer and Stress Analysis of Coke Drum for a Complete Operating Cycle, Journal of Pressure Vessel Technology, 132 (2010), 5
  2. Cohn, M., et al., Service Experience and Fitness-for-service in Power and Petroleum Processing, Proceedings, ASME Pressure Vessels and Piping Conference, American Society of Mechanical Engineers, Seattle, Wash., USA, 2000, Vol. 411
  3. Li, Q., et al., Prediction of Critical Properties and Boiling Point of Fluorine/Chlorine-Containing Refrigerants, International Journal of Refrigeration, 143 (2022), Nov., pp. 28-36
  4. Jie, Y. H., et al., Molecular Simulation of Thermal Energy Storage of Mixed CO2/IRMOF-1 Nanoparticle Nanofluid, International Journal of Heat and Mass Transfer, 125 (2018), Oct., pp. 1345-1348
  5. Ellis, P. J., et al., Tutorial: Delayed Coking Fundamentals, Proceedings, AICHE Spring National Meeting, New Orleans, La., USA, 1998
  6. Yang, F., et al., A Simplified Tikhonov Regularization Method for Determining the Heat Source, Applied Mathematical Modelling, 34 (2010), 11, pp. 3286-3299
  7. Beck, J. V., Inverse Heat Conduction, Ill-Posed Problems, A Wiley-Interscience Publication, New York, USA, 1985
  8. Huang, C. H., et al., An Inverse Geometry Problem in Identifying Irregular Boundary Configurations, International Journal of Heat and Mass Transfer, 40 (1997), 9, pp. 2045-2053
  9. Sladewski, et al., Optimization of Combustion Process in Coal-Fired Power Plant with Utilization of Acoustic System for in-Furnace Temperature Measurement, Applied Thermal Engineering, 123 (2017), Aug., pp. 711-720
  10. Jaremkiewicz, M., et al., Measuring Transient Temperature of the Medium in Power Engineering Machines and Installations, Applied Thermal Engineering, 29 (2009), 16, pp. 3374-3379
  11. Agnieszka, et al., Regularization of the Inverse Heat Conduction Problem by the Discrete Fourier Transform, Inverse Problems in Science and Engineering, 24 (2015), 2, pp. 195-212
  12. Tikhonov, A. N., On the Solution of Ill-Posed Problems and the Method of Regularization, Russian Academy of Sciences, Doklady Akademii Nauk, 151 (1963), 3
  13. Cheng, W., et al., A Regularization Method for Solving the Radially Symmetric Backward Heat Conduction Problem, Applied Mathematics Letters, 30 (2014), Apr., pp. 38-43
  14. Yang, F., et al., A Simplified Tikhonov Regularization Method for Determining the Heat Source, Applied Mathematical Modelling, 34 (2010), 11, pp. 3286-3299
  15. Xiong, X., et al., A Numerical Method for Identifying Heat Transfer Coefficient, Applied Mathematical Modelling, 34 (2010), 7, pp. 1930-1938
  16. Xiong, X., et al., A Tikhonov-Type Method for Solving a Multidimensional Inverse Heat source Problem in an Unbounded Domain, Journal of Computational and Applied Mathematics, 236 (2012), 7, pp. 1766-1774
  17. Cheng, W., et al., A Modified Tikhonov Regularization Method for a Spherically Symmetric 3-D Inverse Heat Conduction Problem, Mathematics and Computers in Simulation, 75 (2007), 3-4, pp. 97-112
  18. Alifanov, O. M., Inverse Heat Transfer Problems, Springer Science and Business Media, Berlin, Germany, 2012
  19. Aling, H., et al., Non-Linear Model Reduction for Simulation and Control of Rapid Thermal Processing, Proceedings, American Control Conference (Cat. No. 97CH36041), IEEE, Piscataway, N. J., USA, 1997, Vol. 4
  20. Alonso, D., et al., Robust Reduced Order Modelling of Heat Transfer in a Back Step Flow, International Journal of Heat and Mass Transfer, 52 (2009), 5-6, pp. 1149-1157
  21. Raghupathy, et al., Boundary-Condition-Independent Reduced-Order Modelling of Complex Electronic Packages by POD-Galerkin Methodology, IEEE Transactions on Components and Packaging Technologies, 33 (2010), 3, pp. 588-596
  22. Notghi, et al., Adaptive Reduced-Basis Generation for Reduced-Order Modelling for the Solution of Stochastic non-Destructive Evaluation Problems, Computer Methods in Applied Mechanics and Engineering, 310 (2016), Oct., pp. 172-188
  23. Mcculloch, W. S., et al., A Logical Calculus of the Ideas Immanent in Nervous Activity, The Bulletin of Mathematical Biophysics, 5 (1943), Dec., pp. 115-133
  24. Kim, H. T., et al., Application of the Finite Volume Method to the Radial Conduction Model of the CATHENA code, Annals of Nuclear Energy, 33 (2006), 10, pp. 924-931
  25. Li, J., et al., Brief Introduction of Back Propagation (BP) Neural Network Algorithm and Its Improvement, Springer, Heidelberg, Germany, 2012
  26. Jin, W., et al., The Improvements of BP Neural Network Learning Algorithm, WCC 2000-ICSP 2000, Proceedings, 5th International Conference on Signal Processing Proceedings, 16th World Computer Congress, IEEE, Piscataway, N. J., USA, 2000, Vol. 3
  27. Hansen, P. C., Analysis of Discrete Ill-Posed Problems by Means of the L-Curve, Siam Review, 34 (1992), 4, pp. 561-580
PDF VERSION [DOWNLOAD]
Rapid reconstruction of temperature field of coke chamber based on POD-BP and Tikhonov method

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence