All Outputs (2)

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..

Simulation of rectangular fluidised bed with Geldart D particles. (2014)
Conference Proceeding
TANDON, M.P. and KARNIK, A.U. 2014. Simulation of rectangular fluidised bed with Geldart D particles. In Proceedings of the 10th International computational fluid dynamics in the oil and gas, metallurgical and process industries conference (CFD 2014), 17-19 June 2014, Trondheim, Norway. Trondheim: SINFEF [online], pages 509-516. Available from: https://www.sintef.no/globalassets/project/cdf2014/docs/official_proceedings_cfd2014-redusert-filstr.pdf

In this study, simulations are carried out using the Euler-Euler granular model in STAR-CCM+ for a gas-solid flow in a rectangular bubbling fluidized bed. The problem studied was announced as Small Scale Challenge Problem (SSCP-I) in 2013. Experiment... Read More about Simulation of rectangular fluidised bed with Geldart D particles..