Details

Autor(en) / Beteiligte

• Neves, Kennedy L. S.
• Dotta, Raul
• Malta, Edgard B.
• Gay Neto, Alfredo
• Franzini, Guilherme R.
• Bitencourt, Luís A. G.

Titel

A digital twin to predict failure probability of an FPSO hull based on corrosion models

Ist Teil von

• Journal of marine science and technology, 2023-12, Vol.28 (4), p.862-875

Ort / Verlag

Tokyo: Springer Japan

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Digital twins have been developed in the oil and gas industry to support a more precise risk assessment that enables performance improvement of offshore structures throughout their life span. Usually, a floating, production, storage and offloading (FPSO) unit is required to exploit oil fields in deep and ultra-deepwater with the postponement of the decommissioning stage, leading to increasing maintenance costs due to aging effects. This paper proposes an adaptive methodology for the development of a digital twin that performs automated numerical analysis via finite element model updating (FEMU) based on coupled systems of a high-fidelity FPSO hull model. The methodology employs a three-cargo tank length finite element (FE) model to receive data and automatically solve multiple numerical analyses. If during results checking any alert level is reached by any structural component, a more complex structural reliability method is applied to provide failure probability considering material strength statistical distribution. The application herein investigates the effects of corrosion, but other phenomena can be considered within the developed framework. A corrosion prediction model is used to create different hypotheses of degradation for bottom plates, while data provided from coupled systems are considered to investigate the effect of deterioration. The results demonstrate a consistent probability of failure when compared to the evolution of the predicted corrosion during service life.