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Lookup NU author(s): Professor Ehsan Mesbahi
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This paper presents a novel approach for fuel spray atomisation studies, i.e. to model the process of spray atomisation with Artificial Neural Networks (ANNs). An attempt was made to compare the accuracy and simplicity of ANN methodology with conventional mathematical regression techniques. Consequently, two functional relationships are provided and their predictions for spray penetration and spray angles are presented. It is concluded that ANN models can provide more accurate and simple mathematical functions to represent input and output data obtained from non-combustion bomb tests.
Author(s): Zhou PL, Mesbahi E
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 23rd CIMAC Congress on Combustion Engine Technology for Ship Propulsion, Power Generation, Rail Traction
Year of Conference: 2001
Number of Volumes: 4
Publisher: CIMAC Central Secretariat
