Direct estimation of transient temperature field of heat transfer system based on mapping characteristics fuzzy clustering. (July 2022)

• Record Type: Journal Article
• Authors: Chen, Zehong; Wang, Guangjun; Chen, Hong; Sun, Shuangcheng
• Is Part Of: International journal of heat and mass transfer. Volume 190(2022)
• Publication Date: 2022-07
• Subjects: Temperature field -- Direct estimation -- Mapping eigenvector -- Model space reduction -- Fuzzy clustering; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2022.122787
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: For transient heat transfer system, a mapping relationship representation from input information to temperature field is proposed. A direct temperature field estimation method is developed based on mapping characteristics fuzzy clustering (MCFC). The method does not rely on specific system inputs and can realize real-time reconstruction of temperature field. Effectiveness and adaptability of the developed method is respectively verified. Abstract: In many engineering fields involving heat transfer process, real-time estimation of temperature fields is a fundamental task with significantly practical requirements. In this paper, a direct estimation method for retrieving the transient temperature field is developed based on mapping characteristics fuzzy clustering (MCFC). Mapping eigenvectors of the heat transfer system are determined by the heat transfer equations without specific system input information. According to the fuzzy clustering of the mapping eigenvectors, a temperature field predictive model space is reduced to cover the mapping relationship of the temperature field by finite representative spatial points, and to establish a fuzzy membership relationship between the mapping characteristics of the representative spatial points and that of the temperature field. The temperature field is estimated in real-time by synthesizing the temperature measurements of the representative spatial points. For the proposed method, the effectiveness as well as the adaptability is analyzed and verified by the achieved results on the preheating process of a steel casting mold. Furthermore, comparisons between the present method and other methods are conducted.