Structural System Parameter Estimation by Two-Stage Least Squares Method

Gersch, Will; Liu, Robert; Taoka, George T.

doi:10.1061/jmcea3.0002167

Cited by 11 publications

(1 citation statement)

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“…Besides AIC and BIC, model selection using dynamic data from some system is an active area of research for a long-time history in many fields such as civil and mechanical engineering (Gersch et al, 1976;Beck, 1978;Beck and Katafygiotis, 1998;Sanayei et al, 1999;Vanik et al, 2000). Beck and Yuen (2004) proposed a Bayesian approach based on their probabilities conditional on the response data, which finally provides a quantitative expression of a principle for selecting the most plausible class of modes.…”

Section: Application Of 3-dimensional Classical Copula Modelsmentioning

confidence: 99%

Long-term fatigue assessment of deepwater risers in time domain

Gao¹

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With the increasing demand for oil and gas, offshore industry moved offshore structures towards deeper waters and severe environmental conditions. Offshore structures are subjected to many environmental loads during their service life, such as waves, winds, currents and ice.Such environmental conditions are non-stationary processes. However, in common practice, it is always assumed that these environmental actions are statistically stationary for short-term sea state, typically for three hours. Riser system is one of the most critical offshore structure component and is exposed to a large number of sea states during its life span, especially in deep water environment. Therefore, only stationary analysis for the riser system is not sufficient, and a global dynamic analysis is indispensable to obtain its response due to the fluid-structure interactions. During the global dynamic analysis, extreme response and fatigue life are two important design concerns. Extreme response predictions can be obtained based on either shortterm or long-term approaches. However, fatigue predictions can only be based on long-term methods due to their accumulative characteristics.The main objective of this study is to investigate various existing methods for their accuracy, limitations and efficiency, and to develop advanced methods in calculating the long-term fatigue damage of deep-water risers as well as in constructing a suitable statistical model for ocean environmental random variables.The traditional way of solving long-term fatigue problem is using a wave scatter diagram. By lumping several sea states into a small number of bins, one sea state is selected as a representation of each block to ensure that the damage quantity yielded by this sea state is not lower than the original sea states. It is apparent that such block method has a lack of accuracy.Therefore, there is a need for a fast and precise method for long-term fatigue analysis especially in time domain. The first part of the author's research is to develop a new efficient approach for long-term riser fatigue analysis in time domain. This new approach allows one to simulate the wave amplitudes from a distribution different from the original one. Then, the results for many sea states can be obtained by simply altering the importance sampling weighting function.This proposed approach is enhanced by a succession of additional techniques to reduce the sampling variability. The study of this proposed new efficient approach is presented in Chapter 3. IIIThe stochastic nature of environmental loads such as wave and wind applied on the structure is quite complicated. In the random process related structural analysis, a suitable statistical environmental condition model is essential and should be carefully developed for the prediction of long-term performance of offshore structures. As a common practice, a conditional joint distribution model is used for the statistical environmental condition, which is popularly used in the industry. However, in such model, only a linear relati...

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