| Enhancing offshore process safety by selecting fatigue critical piping locations for inspection using Fuzzy-AHP based approach A Keprate, RMC Ratnayake Process Safety and Environmental Protection 102 (2016), 71-84, 2016 | 57 | 2016 |
| Adaptive Gaussian process regression as an alternative to FEM for prediction of stress intensity factor to assess fatigue degradation in offshore pipeline A Keprate, RMC Ratnayake, S Sankararaman International Journal of Pressure Vessels and Piping, 2017 | 37 | 2017 |
| Minimizing hydrocarbon release from offshore piping by performing probabilistic fatigue life assessment A Keprate, RMC Ratnayake, S Sankararaman Process Safety and Environmental Protection 106, 34-51, 2017 | 30 | 2017 |
| Probability of detection as a metric for quantifying NDE capability: the state of the art A Keprate, RMC Ratnayake J. Pipeline Eng 14 (3), 199-209, 2015 | 30 | 2015 |
| Fatigue and fracture degradation inspection of offshore structures and mechanical items: the state of the art A Keprate, RMC Ratnayake International Conference on Offshore Mechanics and Arctic Engineering 56505 …, 2015 | 27 | 2015 |
| Using gradient boosting regressor to predict stress intensity factor of a crack propagating in small bore piping A Keprate, RMC Ratnayake 2017 IEEE International Conference on Industrial Engineering and Engineering …, 2017 | 23 | 2017 |
| Comparison of various surrogate models to predict stress intensity factor of a crack propagating in offshore piping A Keprate, RM Chandima Ratnayake, S Sankararaman Journal of Offshore Mechanics and Arctic Engineering 139 (6), 2017 | 17 | 2017 |
| Use of AHP for risk based fatigue degradation inspection analysis of topside piping on offshore production and process facilities A Keprate, RMC Ratnayake 2015 IEEE International Conference on Industrial Engineering and Engineering …, 2015 | 15 | 2015 |
| Handling Uncertainty in Remnant Fatigue Life Assessment of Offshore Process Pipework A Keprate, RMC Ratnayake ASME 2016 Internactional Mechanical Engineering Conference and Exposition, 2016 | 13 | 2016 |
| COMPARING DIFFERENT METAMODELLING APPROACHES TO PREDICT STRESS INTENSITY FACTOR OF A SEMI-ELLIPTIC CRACK A Keprate, S Sankararaman, RMC Ratnayake OMAE 2017, 2017 | 12 | 2017 |
| Determining the Degree of Fuzziness for Fuzzy- AHP Methodology used for Identifying Fatigue Critical Piping Locations for Inspection A Keprate, RMC Ratnayake IEEE International Conference on Intelligent Engineering Systems,, 165-170, 2016 | 12 | 2016 |
| Probability of Detection: History, Development and Future A Keprate Pipeline Technology Journal 8 (2), 41-45, 2016 | 12 | 2016 |
| Selecting Fatigue Critical Inspection Location of Offshore Topside Piping Using Fuzzy-AHP Framework A Keprate, RMC Ratnayake IEEE 14th International Symposium on Applied Machine Intelligence and …, 2016 | 12 | 2016 |
| A Surrogate Model for Predicting Stress Intensity Factor: An Application to Oil and Gas Industry A Keprate, RMC Ratnayake, S Sankararaman International Conference on Offshore Mechanics and Arctic Engineering 57687 …, 2017 | 10 | 2017 |
| Experimental validation of the adaptive Gaussian process regression model used for prediction of stress intensity factor as an alternative to finite element method A Keprate, RM Chandima Ratnayake, S Sankararaman Journal of Offshore Mechanics and Arctic Engineering 141 (2), 2019 | 9 | 2019 |
| Impact of passive heave compensator on offshore lifting A Keprate Journal of Shipping and Ocean Engineering 5 (4), 166-80, 2015 | 9 | 2015 |
| Combining computational fluid dynamics and gradient boosting regressor for predicting force distribution on horizontal axis wind turbine N Bagalkot, A Keprate, R Orderløkken Vibration 4 (1), 248-262, 2021 | 8 | 2021 |
| Appraisal of riser concepts for FPSO in Deepwater A Keprate University of Stavanger, Norway, 2014 | 8 | 2014 |
| Data Mining for Estimating Fatigue Strength Based on Composition and Process Parameters A Keprate, RMC Ratnayake ASME 2019 38th International Conference on Ocean, Offshore and Arctic …, 2019 | 7 | 2019 |
| Predicting remaining fatigue life of topside piping using deep learning S Chatterjee, A Keprate 2021 International Conference on Applied Artificial Intelligence (ICAPAI), 1-6, 2021 | 5 | 2021 |
R.M. Chandima RatnayakeProfessor, University of StavangerVerified email at uis.no
