Development and multi-utility of an ANN model for an industrial gas turbine
M. Fast,
M. Assadi and
S. De
Applied Energy, 2009, vol. 86, issue 1, 9-17
Abstract:
Demonstration of different utilities for industrial use of an artificial neural network (ANN) model for a gas turbine has been reported in this paper. The ANN model was constructed with the multi-layer feed-forward network type and trained with operational data using back-propagation. The results showed that operational and performance parameters of the gas turbine, including identification of anti-icing mode, can be predicted with good accuracy for varying local ambient conditions. Different possible applications of this ANN model were also demonstrated. These include instantaneous gas turbine performance estimation through a graphical user interface and extrapolation beyond the range of training data.
Keywords: ANN; Gas; turbine; Modelling; Simulation (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306-2619(08)00072-X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:86:y:2009:i:1:p:9-17
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().