Scipediacontent: Scipediacontent moved page Draft Content 365639212 to Diaz et al 2021a

2021-03-11T16:43:34Z

Scipediacontent moved page Draft Content 365639212 to Diaz et al 2021a

Scipediacontent: Created page with "== Abstract == In this work, the application of an artificial neural network (ANN) is proposed to develop a predicting model for the holdup of a two-phase flow composed of wa..."

2021-03-11T16:43:31Z

Created page with "== Abstract == In this work, the application of an artificial neural network (ANN) is proposed to develop a predicting model for the holdup of a two-phase flow composed of wa..."

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== Abstract ==

In this work, the application of an artificial neural network (ANN) is proposed to develop a predicting model for the holdup of a two-phase flow composed of water and mineral oil in a horizontal pipe. For this, the surface velocities of each fluid and the differential pressure in the pipeline are used as input parameters of the multilayer artificial neural network with backpropagation, while the holdup of the fluids is used as the output parameter for the training. A set of 56 experimental data was obtained in the LabPetroCEPETRO-UNICAMP laboratory. The best performing results for the predictive model show a mean absolute error (AAPE) of 3.01% and a coefficient of determination 2 of 0.9964 using 15 neurons in the hidden layer of the network and the TanSig transfer function.

== Full document ==
<pdf>Media:Draft_Content_365639212p5989.pdf</pdf>

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Diaz et al 2021a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 365639212 to Diaz et al 2021a

Scipediacontent: Created page with "== Abstract == In this work, the application of an artificial neural network (ANN) is proposed to develop a predicting model for the holdup of a two-phase flow composed of wa..."