Design and operation of large welded structural systems (e.g. ship and offshore structures) are challenging due to numerous fatigue-sensitive details, limited available budgets, uncertainties in fatigue damages, inspection & maintenance activities, etc. Traditionally, fatigue design and maintenance planning have been almost disconnected, which restricts coherent decision-making and optimum safety management. Structural design optimization, without quantitatively incorporating the effects of operational maintenance, can hardly result in a structural plan that is optimum in terms of life cycle costs. Also, if the design of a structure is not optimum, maintenance optimization alone cannot really yield a optimum maintenance plan. As operational inspections and maintenance are essential, there are merits to utilize their effects on structural design and meanwhile optimize them at the initial design stage when impacts of decisions are greater. This paper proposes a risk-based approach to holistic decision-making enveloping decisions and uncertainties affecting design, inspection and maintenance of fatigue-sensitive components. Decisions variables in structural scantling and operational maintenance are obtained holistically at the structural design stage by risk-based optimization, based on quantitative assessment of the effectiveness of both structural scantling and maintenance interventions. Optimum fatigue reliability level is also obtained, informed by the effects of uncertainties and failure consequences. The method captures combined benefits of structural scantling and operational maintenance to fatigue reliability and risk mitigation and achieves optimum resource utilization and life cycle cost reduction. Advantages of the proposed method have been demonstrated via a numerical example, in comparison to alternative methods.
Bibliografisk noteFunding Information:
The authors would like to express their gratitude to the European Union's Horizon 2020 research and innovation programme for their funding toward this project under the Marie Sklodowska-Curie grant agreement No. 642453 (http://trussitn.eu).
The authors would like to express their gratitude to the European Union’s Horizon 2020 research and innovation programme for their funding toward this project under the Marie Sklodowska-Curie grant agreement No. 642453 ( http://trussitn.eu ).
© 2020 Elsevier Ltd
- Decision analysis
- Integrity management
- Life cycle engineering
- Probabilistic optimization
- Risk analysis
- Risk-based inspection