This repository features the development of a neural network model to measure gas-liquid flowrate for high-resolution experimental data. The paper describing the outcome from the BNN project is available at arXiv:2003.08182 [physics.flu-dyn].

The root contains:

• models: Pre-trained Keras models
• samples: Experimental data samples
• src: Source code for the BNN project
• videos: Videos for visualizing layer activation
• requirements.txt: Dependency requirements

If you use this work for your own research, please cite as:

A. J. Dave, A. Manera, “Inference of Gas-liquid Flowrate using Neural Networks,” arXiv:2003.08182 [physics.flu-dyn], 2020.

If you have any questions, comments, or suggestions feel free to email me!