Comparison of added resistance methods using digital twin and full-scale data

Taskar, Bhushan; Andersen, Poul

doi:10.1016/j.oceaneng.2021.108710

Cited by 20 publications

(5 citation statements)

References 24 publications

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“…The goal of their DT is to advice on the cleaning scheduling of the ship, hence the twin predictions are read by a human rather than directly by the physical system, which means that their data flow is P → M → H according to our nomenclature. The same data flow was implemented in (Taskar and Andersen, 2021), where a physics-based model was used to predict the effect of the waves on the ship performance. Major et al (Major et al, 2021) andVanDerHorn et al (VanDerHorn et al, 2022) are among the few works that implemented a model update, i.e., Component 3: in the former, the conditions of vessel remote monitoring, vessel maneuvering under harsher weather and for moving the ship crane are considered by switching between different models, whereas in the latter the update of the model is implemented following an assessment of the vessel fatigue damage accumulation.…”

Section: Resultsmentioning

confidence: 99%

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Digital Twins for Marine Operations: A Brief Review on Their Implementation

Zocco¹,

Wang²,

Van³

2023

Preprint

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While the concept of a digital twin to support maritime operations is gaining attention for predictive maintenance, real-time monitoring, control, and overall process optimization, clarity on its implementation is missing in the literature. Therefore, in this review we show how different authors implemented their digital twins, discuss our findings, and finally give insights on future research directions.

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Section: Resultsmentioning

confidence: 99%

“…3 Ph. system Score (Vasanthan and Nguyen, 2021) Yes (physics) No (none) No Vessel 1 (Coraddu et al, 2019) Yes (statistics) No (P → M → H) No Ship 1.5 (Taskar and Andersen, 2021) Yes (physics) No (P → M → H) No Ship 1.5 (Kutzke et al, 2021) Yes (n.…”

Section: Workmentioning

confidence: 99%

Digital Twins for Marine Operations: A Brief Review on Their Implementation

Zocco¹,

Wang²,

Van³

2023

Preprint

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“…The first recommended practice on how to build and assure the quality of digital twins for the oil and gas industry was recently published by DNV [18]. In the shipping industry, a DT can model a ship and estimate important parameters for the ship performance-for instance, the added resistance in waves [25] and facilitation of monitoring and control capabilities [26]. In the wind energy sector, a DT can coordinate work of different actors and contribute to increasing sustainability of wind energy systems in a way that addresses complex, societal, spatial, and environmental issues [27].…”

Section: State Of the Artmentioning

confidence: 99%

Digital Twin for the Prediction of Extreme Loads on a Wave Energy Conversion System

2022

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Wave energy is a renewable energy source with the potential to contribute to the global electricity demand, but a remaining challenge is the survivability of the wave energy converters in harsh offshore conditions. To understand the system dynamics and improve the reliability, experimental and numerical studies are usually conducted. However, these processes are costly and time-consuming. A statistical model able to provide equivalent results is a promising approach. In this study, the digital twin of the CFD solution is developed and implemented for the prediction of the force in the mooring system of a point-absorber wave energy converter during extreme wave conditions. The results show that the digital twin can predict the mooring force with 90.36% average accuracy. Moreover, the digital twin needs only a few seconds to provide the solution, while the CFD code requires up to several days. By creating a digital analog of a wave energy converter and showing that it is able to predict the load in critical components during extreme wave conditions, this work constitutes an innovative approach in the wave energy field.

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“…The wind loads are estimated using Fujiwara's method (Fujiwara et al (2005)), as recommended by ITTC (2017), and the wave loads are estimated using Liu and Papanikolaou's method (Liu and Papanikolaou (2020)). Unlike DTU's method (Martinsen (2016), Taskar and Andersen (2021); used by Gupta et al (2021)), which provides added wave resistance estimates for mean wave heading from head seas to beam seas only, Liu and Papanikolaou's method (Liu and Papanikolaou (2020)), used here, provides the estimated added wave resistance for all the wave headings, including the following waves.…”

Section: Future Workmentioning

confidence: 99%