Application of artificial neural network model for forecast energy efficiency of the cryogenic liquefaction system in the meaning of sustainability. (21st July 2021)

• Record Type: Journal Article
• Authors: Altintas, Elif; Tolon, Mert; Karabuga, Arif; Utlu, Zafer
• Is Part Of: International journal of global warming. Volume 24:Number 3/4(2021)
• Page Start: 420
• Page End: 444
• Publication Date: 2021-07-21
• Subjects: sustainability -- sustainable engineering approach -- thermodynamic analysis -- cryogenic liquefaction system -- artificial neural networks -- ANNs; Global warming -- Periodicals; Global warming -- Statistics -- Periodicals; Global warming -- Economic aspects -- Periodicals; Climatic changes -- Periodicals; Climatic changes -- Economic aspects -- Periodicals; Climatic changes -- Environmental aspects -- Periodicals; 363.73874
• Languages: English
• ISSNs: 1758-2083

Abstract

Sustainable engineering approaches are a necessity for improving efficiency. For this reason, the artificial neural network (ANN) model is used to forecast different types of energy efficiency problems. In this paper, a comparison is made between a simple model based on ANN which gives meaningful findings in terms of thermodynamics and a model that is based on thermodynamic principles as auditing and predicting tool to forecast exergy efficiency of the system by applying different ANN architecture types with 441 data of experimental measurements obtained from liquefied nitrogen and analysed the Engineering Equation Solver (EES) program to make an exergy analysis.