A second law analysis and entropy generation minimization of an absorption chiller

This paper presents performance analysis of absorption refrigeration system (ARS) using an entropy generation analysis. A numerical model predicts the performance of absorption cycle operating under transient conditions along with the entropy generation computation at assorted heat source temperatur...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Applied thermal engineering 2011-10, Vol.31 (14), p.2405-2413
Hauptverfasser: Myat, Aung, Thu, Kyaw, Kim, Young-Deuk, Chakraborty, A., Chun, Won Gee, Ng, Kim Choon
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper presents performance analysis of absorption refrigeration system (ARS) using an entropy generation analysis. A numerical model predicts the performance of absorption cycle operating under transient conditions along with the entropy generation computation at assorted heat source temperatures, and it captures also the dynamic changes of lithium bromide solution properties such as concentration, density, vapor pressure and overall heat transfer coefficients. An optimization tool, namely the genetic algorithm (GA), is used as to locate the system minima for all defined domain of heat source and cooling water temperatures. The analysis shows that minimization of entropy generation the in absorption cycle leads to the maximization of the COP. ► A distributed-parameter model to capture both transient and steady state processes in a co-generation plant has been successfully studied. ► The Entropy generation that employs the Gibbs’ Free energy approach is applied to capture the component entropy generation such as heat transfer, mass transfer and chemical potential losses. ► A specific entropy generation technique that locates the minimum entropy generation point at assorted heat source temperature. ► Global optimal point of the overall plant is captured by applying Genetics Algorithm (GA) optimization tool.
ISSN:1359-4311
DOI:10.1016/j.applthermaleng.2011.04.004