Ghanta, K. C.

National Institute of Technology, Durgapur, India

A support vector classification method for regime identification of slurry transport in pipelines

Ghanta, K. C., Lahiri, S. K., National Institute of Technology

Statistical analysis showed the proposed solution has an average misclassification error of only 1.5%

Computational fluid dynamics simulation of solid–liquid slurry flow

Ghanta, K. C., Lahiri, S. K., National Institute of Technology

The resulting model's predictions showed reasonably good agreement with the experimental data

Genetic algorithm tuning improves artificial neural network models

Ghanta, K. C., Lahiri, S. K., National Institute of Technology

The technique is illustrated by predicting hold-up of slurry flow in pipelines

Minimize power consumption in slurry transport

Ghanta, K. C., Lahiri, S. K., National Institute of Technology

Accurately predict critical velocity