베이지안 추론을 이용한 VLOC 모형선 구조응답의 확률론적 시계열 예측
Probabilistic Time Series Forecast of VLOC Model Using Bayesian Inference
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초록
This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.
Abstract
This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.
참고문헌 (10)
- Det Norske Veritas(DNV), "Fatigue assessment of ship structures. Classification Notes, No.30.7", DNV, ~ (2003)
- Israelsen, B.W., "Generalized laguerre reduction of the volterra kernel for practical identification of nonlinear dynamic systems", Alche Spring Meeting and Global Congress on Process Safety (2014)
- Iwan, W. D., "On the dynamic response of continuous systems including model uncertainty", Journal of Applied Mechanics, 60(2), pp.484~490 (1993)
- Katafygiotis, L. S., "A probabilistic approach to structural model updating", Soil Dynamics and Earthquake Engineering, 17, pp.495~507 (1998)
- 김유일, "On the second order effect of the springing response of large blunt ship", International Journal of Naval Architecture and Ocean Engineering, 7(5), pp.873~887 (2015), 대한조선학회
- Schetzen, M., "The Volterra and Wiener Theoryies of Nonlinear Systems" (1980), Wiley-Interscience Publication
- Sedehi, O., "Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions", Mechanical Systems and Signal Processing, 123, pp.648~673 (2019)
- Son, J. H., "Parametric estimation of volterra kernel for the dynamic response of an offshore structure using Laguerre polynomials", Journal of Offshore Mechanics and Arctic Engineering, 142(6), pp.061701~ (2020)
- Stevens, N. T., "Bayesian probability of agreement for comparing the similarity of response surfaces", Journal of Quality Technology, 52(1), pp.67~80 (2020)
- Xu L., "Probabilistic load forecasting for buildings considering weather forecasting uncertainty and uncertain peak load", Applied Energy, 237, pp.180~195 (2019)