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Optimizing the Control Process of a
designed Natural Gas Pipeline
Using Neural Network
By: Engr. Edgar Caburatan Carrillo II
Master of Science in Mechanical Engineering
De La Salle University Manila, Philippines
2013 (24 October) Kazakhstan's giant Kashagan oil field closed
opportunity lost: 160,000 barrels/day*$100/barrel=$ 16,000,000/day x P 40= P 640,000,000/day
Leak lost: 10% leakage: P 64,000,000/day if operational
2013 (8 October) Explosion of a natural gas pipeline near
2013 (20 August) Explosion of a natural gas pipeline near Kiowa
southwest of Oklahoma City
2011 Nairobi pipeline fire kills approximately 100 people and
2004: A major natural gas pipeline exploded in Ghislenghien,
Belgium near Ath (50 kilometres southwest of Brussels), killing
24 people and leaving 122 wounded, some critically on July 30,
In natural gas pipeline, leaks may took place and hard to
detect using visual inspection .
A Neural network system that detect the leakage.
1. Determine the leakage detection capability using neural
In computer science and related fields, artificial neural
networks are computational models inspired by animals'
central nervous systems (in particular the brain) that are
capable of machine learning and pattern recognition. They
are usually presented as systems of interconnected
"neurons" that can compute values from inputs by feeding
information through the network.
This neural network system is design to help automate the
detecting of leaks of natural gas pipeline. Creation of a
pipeline system under management and optimizing the
system will sure save cost for companies at the same time
minimizing the environmental impacts.
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This presentation talks about the design of natural gas pipelines in its controls using neural networks.