Simulation of the Stochastic Wave Loads Using a Physical Modeling Approach

Abstract:

In analyzing stochastic dynamic systems, analysis of the system uncertainty due to randomness in the loads plays a crucial role. Typically time series of the stochastic loads are simulated using traditional random phase method. This approach combined with fast Fourier transform algorithm makes an efficient way of simulating realizations of the stochastic load processes. However it requires many random variables, i.e. in the order of magnitude of 1000, to be included in the load model. Unfortunately having too many random variables in the problem makes considerable difficulties in analyzing system reliability or its uncertainty. Moreover applicability of the probability density evolution method on engineering problems faces critical difficulties when the system embeds too many random variables. Hence it is useful to devise a method which can make realization of the stochastic load processes with low, say less than 20, number of random variables. In this article we introduce an approach, so-called "physical modeling of stochastic processes", and show its applicability for simulation of the wave surface elevation.

• Periodical: Key Engineering Materials (Volumes 569-570)
• Pages: 571-578
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.569-570.571
• Online since: July 2013
• Authors: W.F. Liu, M.T. Sichani, S.R.K. Nielsen, Y.B. Peng, J.B. Chen, J. Li
• Keywords: Monte Carlo, PDEM, Physical Modeling, Wave Loads

References

[1] J. Li, J. Chen, Stochastic Dynamics of Structures, 1st Edition, Wiley, (2009).

[2] J. Falnes, Ocean waves and oscillating systems: linear interactions including wave-energy extraction, Cambridge University Press, (2002).

DOI: 10.1017/cbo9780511754630

[3] K. Hasselmann, et al., Measurements of Wind Wave Growth and Swell Decay During the Joint North Sea Project (JONSWAP), Erganzungsheft zur Deutschen Hydrograph. Z., Reihe A, No. 12, Hamburg, (1973).

[4] I. Svendsen, I. Jonsson, Hydrodynamics of Coastal Regions, Den Private Ingeniørfond, Technical University of Denmark, (1980).

[5] J. Li, Y. Peng, Q. Yan, Modeling and simulation of fluctuating wind speeds using evolutionary phase spectrum, Probabilistic Engineering Mechanics 32 (0) (2013) 48 - 55.

DOI: 10.1016/j.probengmech.2013.01.001

[6] Y. K. Lin, G. Cai, Probabilistic Structural Dynamics, McGraw-Hill, (2004).