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RISS 인기검색어
- 검색키워드
- 저자 : Vladimir Yakimov (검색결과 2 건)
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Fatigue assessment for FPSO hawsers
Yakimov Vladimir,Gaidai Oleg,Wang Fang,Xu Xiaosen,Niu Yuhao,Kelin Wang 대한조선학회 2023 International Journal of Naval Architecture and Oc Vol.15 No.-
Floating Production Storage and Offloading Unit (FPSO) is designed to produce, store and transport hydrocarbon products. FPSO's hawsers may be exposed to both extreme and fatigue loads during operations. Hence prediction of their fatigue life is important for operational safety. During some unloading operations, consistent hawser tensions could develop as a result of internal friction in nylon ropes, casing wear and accumulated fatigue damage. Methodology, suggested in this study, may be effectively employed at the vessel design phase, when optimizing vessel parameters, reducing potential FPSO hawser tension fatigue damage. This study aims to contribute to development of novel fatigue assessment approaches, in order to use limited available datasets more effectively. Stresses occurring within FPSO hawsers have been modelled, using actual in situ environmental conditions. Simulated continuous stress time series were used as input for the rainflow counting analysis; the cumulative fatigue damage was then evaluated. Note on experimental validation has been provided.
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Oleg Gaidai,Vladimir Yakimov,Fang Wang,Yu Cao 한국정밀공학회 2024 International Journal of Precision Engineering and Vol.25 No.5
Energy harvesting is a component of contemporary offshore and onshore green energy engineering. Rigorous experimental studies, as well as safety and reliability research, being essential for modern green energy design and engineering. In order to evaluate dynamic performance of galloping energy harvesters, this study utilized extensive wind-tunnel tests, performed under realistic in situ windspeed conditions. State of art Gaidai structural reliability approach has been presented, that is particularly well suitable for non-stationary imperfect or damaged multi-dimensional energy harvesting systems. This approach utilizes analog observations made during representative timelapse, producing quasi-ergodic system dynamic record. As shown in the current study, the recommended technique may be utilized to evaluate the risk of damage or failure in dynamic systems. Additionally, high-dimensionality, deterioration, and nonlinear cross-correlations between dynamic system's key components are challenging to handle for standard reliability approaches, dealing with nonstationary, multidimensional systems. The goal of this study was to benchmark novel Gaidai multivariate reliability approach that allows for effective processing of pertinent statistical data even from limited, multivariate non-stationary underlying dataset. Gaidai multivariate reliability approach attempts to assist designers in evaluating risks of failure and hazards for nonlinear multidimensional dynamic energy harvesting systems, when initial manufacturing imperfections being present.
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