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The Fusion Model of Catalytic Combustion and Thermal Conductivity

Bin Lin1, Zhengyu Li2,*, Dong Wen2, Jianchao Liu2, Shan Yang3, Yong Zhou2, Chao Lu4, Qian Qiu4,5
1 Sichuan Normal University, Chengdu, 610066, China
2 School of Computer Science, Southwest Petroleum University, Chengdu, 610500, China
3 Jackson State University, Jackson, 39217, MS, USA
4 Key Laboratory on Aero-Engine Altitude Simulation Technology, Sichuan Gas Turbine Establishment, AECC, Mianyang, 621000, China
5 School of Power and Energy, Northwestern Polytechnical University, Xi’an, 710072, China
* Corresponding Author: Zhengyu Li. Email:

Computers, Materials & Continua 2023, 74(1), 1509-1521. https://doi.org/10.32604/cmc.2023.032557

Received 22 May 2022; Accepted 29 June 2022; Issue published 22 September 2022

Abstract

The further development of catalytic elements has been plagued by activation and binary problems. The automatic shift model that has emerged in recent years helps components achieve full range. However, the detection data still remains unstable in the shift area (7%~13%). This paper proposes a Catalytic Combustion and Thermal Conductivity (CCTC) model for the specified range, which can be explained from two aspects based on the existing methods. On the one hand, it uses iterative location search to process heterogeneous data, judges the prediction position of data points, and then gives weight evaluation. On the other hand, it corrects the abnormal points, determines the abnormal points in the horizontal direction, and gives the replacement value through the data of adjacent points. The experimental results show that the CCTC model reduces the sum of variance from 17 of the automatic shift model to 13, and the comparison of experimental variance is reduced by 23%. In the full-scale real-time data, the experimental variance of CCTC model and automatic shift model is reduced by 18%. In conclusion, CCTC is a cross section stability framework for full-scale methane measurement, in which the specified heterogeneous combination and anomaly point correction methods improve the stability.

Keywords

Catalytic combustion; thermal conductivity; activation problem; binary problem; data fusion

Cite This Article

B. Lin, Z. Li, D. Wen, J. Liu, S. Yang et al., "The fusion model of catalytic combustion and thermal conductivity," Computers, Materials & Continua, vol. 74, no.1, pp. 1509–1521, 2023.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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