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Fuel Flexible Prediction Model for T100 Gas Turbine

Nyberg, Björn (2010) In ISRN LUTMDN/TMHP-10/5210--SE
Department of Energy Sciences
Abstract
To be able to predict the behaviour of the things around us is valuable asset, whether it is the stock prices
or the train arrival, a chance to know before it is happening is always beneficial. The computer has taken
the prediction of behaviour to a higher level. From reading tea leaves in a cup, to really look into large
amounts of data and with previous answers find a good approximation to what will happen.
This report will explain how such operation can be done. It will describe a program designed for an
electrical power generating gas turbine. With a large number of nested equations, which represents the
components in this machine, a prediction of what will happen when the circumstances decline from its
ideal conditions, is... (More)
To be able to predict the behaviour of the things around us is valuable asset, whether it is the stock prices
or the train arrival, a chance to know before it is happening is always beneficial. The computer has taken
the prediction of behaviour to a higher level. From reading tea leaves in a cup, to really look into large
amounts of data and with previous answers find a good approximation to what will happen.
This report will explain how such operation can be done. It will describe a program designed for an
electrical power generating gas turbine. With a large number of nested equations, which represents the
components in this machine, a prediction of what will happen when the circumstances decline from its
ideal conditions, is found. This feature is of great importance when understanding why such complex
machine acts as it does.
When making an advanced simulation program like this, the focus cannot only be on getting a good
approximation. If no one can run the program or understand the results, it has been done for nothing.
Words as “user friendly” and “robust” might sound like clichés, but they cannot be over emphasised.
The way of completing this master thesis has gone through three phases; finding the right answers, making
it stable and making it understandable. (Less)
Please use this url to cite or link to this publication:
author
Nyberg, Björn
supervisor
organization
year
type
H1 - Master's Degree (One Year)
subject
keywords
generating electrical power gas turbine simulation
publication/series
ISRN LUTMDN/TMHP-10/5210--SE
language
English
id
2541208
date added to LUP
2012-05-16 13:32:33
date last changed
2012-05-16 13:32:33
@misc{2541208,
  abstract     = {To be able to predict the behaviour of the things around us is valuable asset, whether it is the stock prices
or the train arrival, a chance to know before it is happening is always beneficial. The computer has taken
the prediction of behaviour to a higher level. From reading tea leaves in a cup, to really look into large
amounts of data and with previous answers find a good approximation to what will happen.
This report will explain how such operation can be done. It will describe a program designed for an
electrical power generating gas turbine. With a large number of nested equations, which represents the
components in this machine, a prediction of what will happen when the circumstances decline from its
ideal conditions, is found. This feature is of great importance when understanding why such complex
machine acts as it does.
When making an advanced simulation program like this, the focus cannot only be on getting a good
approximation. If no one can run the program or understand the results, it has been done for nothing.
Words as “user friendly” and “robust” might sound like clichés, but they cannot be over emphasised.
The way of completing this master thesis has gone through three phases; finding the right answers, making
it stable and making it understandable.},
  author       = {Nyberg, Björn},
  keyword      = {generating electrical power gas turbine simulation},
  language     = {eng},
  note         = {Student Paper},
  series       = {ISRN LUTMDN/TMHP-10/5210--SE},
  title        = {Fuel Flexible Prediction Model for T100 Gas Turbine},
  year         = {2010},
}