A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A variance reduction technique for long-term fatigue analysis of offshore structures using Monte Carlo simulation
Highlights New efficient approach for long-term fatigue analysis of offshore structures. Approach uses control variates to reduce variability of Monte Carlo simulation. No prior simulations needed; control function constructed from Monte Carlo data. Simulation process is unaltered, damage from multiple locations can be evaluated. Fatigue damage estimated is unbiased, and sampling variability can be quantified.
Abstract Long-term fatigue assessment of an offshore structure is a challenging practical problem. An offshore structure is exposed to fluctuating sea conditions, thus the fatigue analysis needs to account for many different wave heights and periods. Because each sea state entails a full dynamic analysis, the total computational effort can be formidable, particularly for time domain analysis. Recently, researchers have proposed various strategies for efficient estimation of the long-term mean damage, but these methods all have drawbacks, such as the predicted damage is approximate without means to quantify the error, and the simulation procedure is customized for a particular stress location. This paper outlines a new approach based on using control variates to enhance the efficiency of Monte Carlo simulation. The proposed approach has the advantage of being a post-processing scheme that does not alter the dynamic simulation procedure, enabling the damage of multiple locations to be evaluated from the same simulation results. The predicted mean damage is unbiased and the sampling error can be quantified. In addition, the approach supports both time domain and frequency domain analysis. Case studies of a floating production system demonstrate that the proposed approach provides a substantial speedup in computational time. The actual performance varies with factors such as sample size and model complexity.
A variance reduction technique for long-term fatigue analysis of offshore structures using Monte Carlo simulation
Highlights New efficient approach for long-term fatigue analysis of offshore structures. Approach uses control variates to reduce variability of Monte Carlo simulation. No prior simulations needed; control function constructed from Monte Carlo data. Simulation process is unaltered, damage from multiple locations can be evaluated. Fatigue damage estimated is unbiased, and sampling variability can be quantified.
Abstract Long-term fatigue assessment of an offshore structure is a challenging practical problem. An offshore structure is exposed to fluctuating sea conditions, thus the fatigue analysis needs to account for many different wave heights and periods. Because each sea state entails a full dynamic analysis, the total computational effort can be formidable, particularly for time domain analysis. Recently, researchers have proposed various strategies for efficient estimation of the long-term mean damage, but these methods all have drawbacks, such as the predicted damage is approximate without means to quantify the error, and the simulation procedure is customized for a particular stress location. This paper outlines a new approach based on using control variates to enhance the efficiency of Monte Carlo simulation. The proposed approach has the advantage of being a post-processing scheme that does not alter the dynamic simulation procedure, enabling the damage of multiple locations to be evaluated from the same simulation results. The predicted mean damage is unbiased and the sampling error can be quantified. In addition, the approach supports both time domain and frequency domain analysis. Case studies of a floating production system demonstrate that the proposed approach provides a substantial speedup in computational time. The actual performance varies with factors such as sample size and model complexity.
A variance reduction technique for long-term fatigue analysis of offshore structures using Monte Carlo simulation
Low, Ying Min (author)
Engineering Structures ; 128 ; 283-295
2016-09-22
13 pages
Article (Journal)
Electronic Resource
English
Variance reduction in Monte Carlo simulation of dynamic systems
| British Library Conference Proceedings | 2000
Stochastic long-term reliability of water distribution networks using Monte Carlo simulation
| Taylor & Francis Verlag | 2022
Monte Carlo simulation of weldment fatigue strength
| Elsevier | 1989