Mihiran Galagedarage Don
Postdoctoral Researcher
Department of Energy and Mechanical Engineering
Full researcher profile
https://research.aalto.fi/...
Sähköposti
[email protected]
Postiosoite
Puumiehenkuja 3
02150 Espoo
Finland
Puhelinnumero
+358504701144
Osaamisalueet
Materials, Bond Graph, Digital Twins, Condition Monitoring, 216 Materials engineering, 214 Mechanical engineering, Mechanical engineering and manufacturing technology, Metals
Tutkimusryhmät
- Materials to Products, Postdoctoral Researcher
Julkaisut
A Digital Twin Development Framework for an Electrical Submersible Pump (ESP)
Mihiran Galagedarage Don, Sampath Liyanarachchi, Thumeera R. Wanasinghe
2024
Archives of Advanced Engineering Science
A Digital Twinning Methodology for Vibration Prediction and Fatigue Life Prognosis of Vertical Oil Well Drillstrings
Mihiran Galagedarage Don, Geoff Rideout
2023
IEEE Access
Fatigue life prognosis of an oil well drill string using cascaded dynamic models
Mihiran Galagedarage Don, Geoff Rideout
2023
Applications in Engineering Science
An experimentally-verified approach for enhancing fluid drag force simulation in vertical oilwell drill strings
Mihiran Galagedarage Don, Geoff Rideout
2022
MATHEMATICAL AND COMPUTER MODELLING OF DYNAMICAL SYSTEMS
Chapter Four - Industry 4.0 based process data analytics platform
Thumeera R. Wanasinghe, Mihiran Galagedarage Don, Rajeevan Arunthavanathan, Raymond G. Gosine
2022
Methods to Assess and Manage Process Safety in Digitalized Process System
FATIGUE FAILURE PROGNOSIS OF AN OIL WELL DRILL STRING USING A LUMPED SEGMENT BOND GRAPH MODEL AND FINITE ELEMENT METHOD
Mihiran Galagedarage Don, Geoff Rideout
2021
International conference on Bond Graph Modeling and Simulation, ICBGM 2021
Auxiliary codes for fault prognosis of Tennessee Eastman process using a hybrid model (CPL1.0)
Mihiran Galagedarage Don, Faisal Khan
2019
SoftwareX
Dynamic process fault detection and diagnosis based on a combined approach of hidden Markov and Bayesian network model
M. Galagedarage Don, F. Khan
2019
Chemical Engineering Science
Process fault prognosis using hidden Markov model-bayesian networks hybrid model
M. Galagedarage Don, F. Khan
2019
Industrial and Engineering Chemistry Research
