- Volume 30 Issue 3
DOI QR Code
Fatigue Damage Estimation for Mooring lines of Spar Platform Using System Identification Method
시스템 식별법을 이용한 스파 플랫폼 계류라인의 피로 수명 예측
- Received : 2016.01.11
- Accepted : 2016.06.24
- Published : 2016.06.30
This paper presents a methodology through which the time series of the dynamic response of mooring line tension can be predicted without relying on a time-consuming nonlinear time-domain analysis. The mooring line tension for the target short-term sea states was predicted using a Hammerstein-Wiener model, a popular system identification scheme, based upon the pre-calculated motion-tension time history data for some selected short-term sea states that do not overlap with the targeted ones. The obtained mooring line tension was further processed, and a fatigue damage comparison was made between the predicted and calculated values. The results showed that the predicted time series of the mooring line tension matched the calculated one fairly well. Thus, it is expected that the methodology may be employed to enhance the efficiency of mooring line tension analysis.
Mooring tension;System identification;Fatigue life;Mooring line;Wave scatter diagram
- American Petroleum Institute (API), 2007. Recommended Practice for Planning Designing and Constructing Fixed Offshore Platforms - Working Stress Design. RP 2A-WSD.
- Ban, I.H., 2015. Prediction of Mooring Tension and Fatigue Damage of Mooring Line in Offshore Plant Based on System Identification. Master Dissertation. Inha University.
- Jeon, G.Y., 2014. A Study on Mooring System Design of Floating Offshore Wind Turbine in Jeju Offshore Area. Master Dissertation, Inha University.
- Kim, Y, 2014. Prediction of the Dynamic Response of a Slender Marine Structure under an Irregular Ocean Wave using the NARX-based Quadratic Volterra Series. Applied Ocean Research, 49, 42-56.
- Ko, S.H., 2012. Non-parametric System Identification. Institute of Control, Robotics and Systems, 19(1), 60-65.
- Mazaheri, S., Downie, M.J., 2010. Response-based Method for Determining the Extreme Behavior of Floating Offshore Platforms. Ocean Engineering, 32, 363-393.
- Pina, A.C., Monteiro, B.F., Albrecht, C.H., Lima, B.S.L.P., Jacob, B.P., 2014. ANN and Wavelet Network Meta-models for the Coupled Analysis of Floating Production Systems. Applied Ocean Research 48, 21-32. https://doi.org/10.1016/j.apor.2014.07.009
- Vazquez-Hernandez, A., Ellwanger, G., Sagrilo, L., 2011. Longterm Response Analysis of FPSO Mooring Systems. Applied Ocean Research 33, 375-383. https://doi.org/10.1016/j.apor.2011.05.003
- Yasseri, S.F., Bahai, H., Bazargan, H., Aminzadeh, A., 2010. Prediction of Safe Sea-state using Finite Element Method and Artificial Neural Network. Ocean Engineering 37, 200-207. https://doi.org/10.1016/j.oceaneng.2009.11.006