Optimal operation conditions for a single-stage heat transformer by means of an artificial neural network inverse

被引：24

作者：

Colorado, D. ^{[2
]}

Hernandez, J. A. ^{[2
]}

Rivera, W. ^{[1
]}

Martinez, H. ^{[1
]}

Juarez, D. ^{[2
]}

机构：

[1] Univ Nacl Autonoma Mexico, CIE, Temixco 62580, Morelos, Mexico

[2] UAEM, Ctr Invest Ingn & Ciencias Aplicadas CIICAp, Cuernavaca 62209, Morelos, Mexico

来源：

APPLIED ENERGY | 2011年 / 88卷 / 04期

关键词：

Exergy analysis; Heat transformers; Optimization; Artificial neural networks; Irreversibility; WATER-PURIFICATION PROCESS; THERMODYNAMIC PROPERTIES; EXERGY ANALYSIS; ENERGY; PERFORMANCE; BROMIDE; OPTIMIZATION; PREDICTION;

D O I：

10.1016/j.apenergy.2010.10.006

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Analysis based on first and second law of thermodynamics together with direct and artificial neural networks inverse (ANNi) have been used to develop a methodology to decrease the total irreversibility of an experimental single-stage heat transformer. With the proposed methodology it is possible to calculate the optimal input parameters that should be used in order to operate the heat transformer with the lower irreversibilities. Mathematical validation of ANNi was carried out together with the comparison between the total cycle irreversibility (I-cycle) obtained thermodynamically and the I-cycle determined by using the ANNi. The results showed a mean discrepancy of 0.9% of the I-cycle values. The proposed new methodology can be very useful to control on-line the performance of a single-state heat transformer obtaining lower I-cycle values. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：1281 / 1290

页数：10

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