Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. (2022)
Conference Proceeding
ADEGBOYE, M.A., KARNIK, A., FUNG, W.-K. and PRABHU, R. 2022. Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. In Proceedings of the 9th International conference on soft computing and machine intelligence 2022 (ISCMI 2022), 26-27 November 2022, Toronto, Candada. Piscataway: IEEE [online], pages 129-134. Available from: https://doi.org/10.1109/iscmi56532.2022.10068436

Pipelines are often subject to leakage due to ageing, corrosion, and weld defects, and it is difficult to avoid as the sources of leakages are diverse. Several studies have demonstrated the applicability of the machine learning model for the timely p... Read More about Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation..

CFD modelling and prototype testing of a vertical axis wind turbines in planetary cluster formation. (2021)
Journal Article
DURKACZ, J., ISLAM, S., CHAN, R., FONG, E., GILLIES, H., KARNIK, A. and MULLAN, T. 2021. CFD modelling and prototype testing of a vertical axis wind turbines in planetary cluster formation. Energy reports [online], 7(Supplement 3): 6th International conference on advances on clean energy research 2021 (ICACER 2021), 15-17 April 2021, [virtual conference], pages 119-126. Available from: https://doi.org/10.1016/j.egyr.2021.06.019

This study aims to improve the applicability of Vertical Axis Wind Turbines (VAWTs) by investigating their feasibility in a novel planetary cluster configuration by observing its effect on efficiency and overall power density. Computational Fluid Dyn... Read More about CFD modelling and prototype testing of a vertical axis wind turbines in planetary cluster formation..