The bending mechanics of dynamic subsea electrical cables are strongly influenced by the frictional shear interactions that exist between the armour wires and surrounding materials. In some cases the armour wires are clad with bitumen filler material so that the shear mechanics of bitumen are important to the overall bending mechanics of the cable. In this work the shear mechanics of bitumen are studied. Pull-out tests on bitumen-clad armour wires were conducted in-situ on a stub of a dynamic subsea electrical test cable. Test temperatures ranged from 0°C to room temperature and shear velocities ranged from 0.1mm/min to 40mm/min. A thermally activated model of the bitumen shear interaction, incorporating temperature, speed and displacement dependence was proposed and implemented into a finite element code. The testing and modelling was then extended to incorporate the effects of cyclic loading. The bitumen response was highly sensitive to test temperature, applied velocity and cyclic loading with the shear strength varying by approximately two orders of magnitude over the range of conditions studied. The experimental results and model predictions indicate that the shear mechanics of cables containing bitumen clad armour wires differ from the shear mechanics of cables that do not. The bending stiffness displays a velocity and temperature dependence and relaxation of cable stresses is expected during holding events. Because of this, it is recommended that modelling of bitumen clad armour wires be conducted using a suitable bitumen interaction model and not a classic friction model.
Skip Nav Destination
ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering
May 31–June 5, 2015
St. John’s, Newfoundland, Canada
Conference Sponsors:
- Ocean, Offshore and Arctic Engineering Division
ISBN:
978-0-7918-5651-2
PROCEEDINGS PAPER
Bitumen Shear Mechanics in a Dynamic Subsea Electrical Cable
Jonathan Mullins,
Jonathan Mullins
ABB Corporate Research, Västerås, Sweden
Search for other works by this author on:
Daniel Morin,
Daniel Morin
ABB Corporate Research, Västerås, Sweden
Search for other works by this author on:
Andreas Tyrberg,
Andreas Tyrberg
ABB High Voltage Cables, Karlskrona, Sweden
Search for other works by this author on:
Claes Sonesson,
Claes Sonesson
ABB High Voltage Cables, Karlskrona, Sweden
Search for other works by this author on:
Johan Ekh
Johan Ekh
ABB Corporate Research, Västerås, Sweden
Search for other works by this author on:
Jonathan Mullins
ABB Corporate Research, Västerås, Sweden
Daniel Morin
ABB Corporate Research, Västerås, Sweden
Andreas Tyrberg
ABB High Voltage Cables, Karlskrona, Sweden
Claes Sonesson
ABB High Voltage Cables, Karlskrona, Sweden
Johan Ekh
ABB Corporate Research, Västerås, Sweden
Paper No:
OMAE2015-41110, V05AT04A026; 8 pages
Published Online:
October 21, 2015
Citation
Mullins, J, Morin, D, Tyrberg, A, Sonesson, C, & Ekh, J. "Bitumen Shear Mechanics in a Dynamic Subsea Electrical Cable." Proceedings of the ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. Volume 5A: Pipeline and Riser Technology. St. John’s, Newfoundland, Canada. May 31–June 5, 2015. V05AT04A026. ASME. https://doi.org/10.1115/OMAE2015-41110
Download citation file:
30
Views
Related Proceedings Papers
Related Articles
Rheological Modeling of Complex Flow Behavior of Bitumen-Solvent Mixtures and Implication for Flow in a Porous Medium
J. Energy Resour. Technol (July,2022)
Semi-Analytical Proxy for Vapex Process Modeling in Heterogeneous Reservoirs
J. Energy Resour. Technol (September,2014)
A Mathematical Model for Frictional Elastic-Plastic Sphere-on-Flat Contacts at Sliding Incipient
J. Appl. Mech (January,2007)
Related Chapters
Pipeline Integrity and Security
Continuing and Changing Priorities of the ASME Boiler & Pressure Vessel Codes and Standards
Data Tabulations
Structural Shear Joints: Analyses, Properties and Design for Repeat Loading
Natural Selection of Asphalt Mix Stiffness Predictive Models with Genetic Programming
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20