Items where Author is "Krishna, S."

Group by: Item Type | No Grouping
Number of items: 10.

Article

Maldar, N.R. and Yee, N.C. and Oguz, E. and Krishna, S. (2022) Performance investigation of a drag-based hydrokinetic turbine considering the effect of deflector, flow velocity, and blade shape. Ocean Engineering, 266.

Krishna, S. and Thonhauser, G. and Kumar, S. and Elmgerbi, A. and Ravi, K. (2022) Ultrasound velocity profiling technique for in-line rheological measurements: A prospective review. Measurement: Journal of the International Measurement Confederation, 205.

Krishna, S. and Thonhauser, G. and Kumar, S. and Elmgerbi, A. and Ravi, K. (2022) Ultrasound velocity profiling technique for in-line rheological measurements: A prospective review. Measurement: Journal of the International Measurement Confederation, 205.

Abdullah, A.H. and Ridha, S. and Mohshim, D.F. and Yusuf, M. and Kamyab, H. and Krishna, S. and Maoinser, M.A. (2022) A comprehensive review of nanoparticles: Effect on water-based drilling fluids and wellbore stability. Chemosphere, 308.

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Sophian, A. (2020) Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: A comprehensive review. Journal of Petroleum Science and Engineering, 195.

Krishna, S. and Ridha, S. and Vasant, P. (2020) Prediction of Bottom-Hole Pressure Differential During Tripping Operations Using Artificial Neural Networks (ANN). Lecture Notes in Networks and Systems, 118. pp. 379-388.

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Ofei, T.N. (2020) Simplified predictive model for downhole pressure surges during tripping operations using power law drilling fluids. Journal of Energy Resources Technology, Transactions of the ASME, 142 (12).

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Ofei, T.N. (2020) Simplified predictive model for downhole pressure surges during tripping operations using power law drilling fluids. Journal of Energy Resources Technology, Transactions of the ASME, 142 (12).

Conference or Workshop Item

Krishna, S. and Ridha, S. and Ilyas, S.U. and Campbell, S. and Bhan, U. and Bataee, M. (2021) Application of deep learning technique to predict downhole pressure differential in eccentric annulus of ultra-deep well. In: UNSPECIFIED.

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. (2020) New analytical approach for predicting surge/swab pressure gradient using mud clinging effect and frictional pressure losses: For yield power law fluid. In: UNSPECIFIED.

This list was generated on Tue Dec 24 00:39:19 2024 +08.