Modeling the free convection heat transfer in a partitioned cavity using ANFIS

被引：46
|
作者：
Rezaei, Ehsan [1 ]
Karami, Alimohammad [1 ]
Yousefi, Tooraj [2 ]
Mahmoudinezhad, Sajjad [3 ]
机构：
[1] Kermanshah Univ Technol, Dept Mech Engn, Kermanshah, Iran
[2] Razi Univ, Dept Mech Engn, Kermanshah, Iran
[3] Islamic Azad Univ, Dept Mech Engn, Gachsaran Branch, Gachsaran, Iran
来源：
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER | 2012年 / 39卷 / 03期
关键词：
Free convection; Heat transfer; Partitioned cavity; Modeling; ANFIS; NATURAL-CONVECTION; HOT-WALL; SQUARE CAVITY; THIN FIN; ENCLOSURE; BLIND;
D O I：
10.1016/j.icheatmasstransfer.2011.12.006
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is used to predict the free convection in a partitioned cavity consisting of an adiabatic partition. The main focus of the present paper is to consider the effects of partition angle and Rayleigh number variation on average heat transfer in the partitioned cavity. The training data for optimizing the ANFIS structure is obtained experimentally. For the best ANFIS structure obtained in this study, the mean relative errors of the train and test data were found to be 0.055% and 1.735% respectively, which shows that ANFIS can predict the experimental results precisely. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：470 / 475
页数：6
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