MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM

This report discusses the research done on the chosen topic, which is Modeling of Primary Reformer Tube Metal Temperature (TMT) using LS-SVM. The objective of the project is to develop a modelthat can predict the temperature of the reformer tubes. The scope of the study focused on the modeling of th...

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Main Author: YAP , WI SON
Format: Final Year Project
Language:English
Published: UniversitiTeknologi PETRONAS 2012
Subjects:
Online Access:http://utpedia.utp.edu.my/4041/1/Yap_Wi_Son_-_FYP_final_report.pdf
http://utpedia.utp.edu.my/4041/
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spelling my-utp-utpedia.40412017-01-25T09:41:06Z http://utpedia.utp.edu.my/4041/ MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM YAP , WI SON TK Electrical engineering. Electronics Nuclear engineering This report discusses the research done on the chosen topic, which is Modeling of Primary Reformer Tube Metal Temperature (TMT) using LS-SVM. The objective of the project is to develop a modelthat can predict the temperature of the reformer tubes. The scope of the study focused on the modeling of the primary reformer TMT of PETRONAS Ammonia hydrocarbons such as natural gas into its constituents which are carbon dioxide, carbon monoxide and hydrogen. Pressurized feed (300barg) of hydrocarbon and steam is fed into the reformer tubes and heated by the burners at about 800-1000°C to facilitate the hydrocarbon conversion. The temperature of the tubes is an important parameter to determine the life-time of the tubes. Operating the reformer beyond the TMT design limits can cause premature failures on the tubes which lead to production losses and higher downtime. Based on the literature survey, it shows that the mathematical modeling and simulation approaches are used to determine the behavior of the reformer tubes. For this project, empirical model developed by integrating the process variable will be used to predict the reformer tubes temperature. Empirical model is developed based on real-time data obtained from PASB plant. LS-SVM is used in developing the model and Back Propagation Neural Network is used to develop a model that serves as the benchmark for this project. UniversitiTeknologi PETRONAS 2012-05 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/4041/1/Yap_Wi_Son_-_FYP_final_report.pdf YAP , WI SON (2012) MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM. UniversitiTeknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
YAP , WI SON
MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
description This report discusses the research done on the chosen topic, which is Modeling of Primary Reformer Tube Metal Temperature (TMT) using LS-SVM. The objective of the project is to develop a modelthat can predict the temperature of the reformer tubes. The scope of the study focused on the modeling of the primary reformer TMT of PETRONAS Ammonia hydrocarbons such as natural gas into its constituents which are carbon dioxide, carbon monoxide and hydrogen. Pressurized feed (300barg) of hydrocarbon and steam is fed into the reformer tubes and heated by the burners at about 800-1000°C to facilitate the hydrocarbon conversion. The temperature of the tubes is an important parameter to determine the life-time of the tubes. Operating the reformer beyond the TMT design limits can cause premature failures on the tubes which lead to production losses and higher downtime. Based on the literature survey, it shows that the mathematical modeling and simulation approaches are used to determine the behavior of the reformer tubes. For this project, empirical model developed by integrating the process variable will be used to predict the reformer tubes temperature. Empirical model is developed based on real-time data obtained from PASB plant. LS-SVM is used in developing the model and Back Propagation Neural Network is used to develop a model that serves as the benchmark for this project.
format Final Year Project
author YAP , WI SON
author_facet YAP , WI SON
author_sort YAP , WI SON
title MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
title_short MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
title_full MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
title_fullStr MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
title_full_unstemmed MODELING OF PRIMARY REFORMER TUBE METAL TEMPERATURE (TMT) USING LS-SVM
title_sort modeling of primary reformer tube metal temperature (tmt) using ls-svm
publisher UniversitiTeknologi PETRONAS
publishDate 2012
url http://utpedia.utp.edu.my/4041/1/Yap_Wi_Son_-_FYP_final_report.pdf
http://utpedia.utp.edu.my/4041/
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score 13.160551