Time Series Simulations of Wide-Band Spectra for Fatigue Tests of Offshore Structures

1984 ◽  
Vol 106 (4) ◽  
pp. 466-470 ◽  
Author(s):  
N. K. Lin ◽  
W. H. Hartt
Keyword(s):  
Time Series ◽  
Fatigue Testing ◽  
Wide Band ◽  
Simulation Method ◽  
Offshore Structures ◽  
Fatigue Tests ◽  
Time Series Model ◽  
Long Time ◽  
Band Spectra ◽  
Time Series Simulation

A time-series simulation method, based on the principle of time series modeling for dynamic systems, is used to reproduce a wide-band stress history from a prescribed stress spectral model for fatigue testing of offshore structures. The optimization procedures and stability of the time series model for the prescribed spectrum are presented and discussed. The optimization procedures are developed on the basis of the Levison-Durbin algorithm, which usually produces a stable time series model if the order of the time series model is even. An example is presented to demonstrate the applicability of the proposed method to long-time, high-cycle fatigue testing.

scholarly journals Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
João P. R. Cortina ◽  
Fernando J. M. de Sousa ◽  
Luis V. S. Sagrilo
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Cross Sections ◽  
Computational Cost ◽  
Offshore Structures ◽  
Fatigue Analysis ◽  
Element Analysis ◽  
Long Time ◽  
Wave Induced ◽  
Hybrid Methodology

Time domain stochastic wave dynamic analyses of offshore structures are computationally expensive. Considering the wave-induced fatigue assessment for such structures, the combination of many environmental loading cases and the need of long time-series responses make the computational cost even more critical. In order to reduce the computational burden related to the wave-induced fatigue analysis of Steel Catenary Risers (SCRs), this work presents the application of a recently developed hybrid methodology that combines dynamic Finite Element Analysis (FEA) and Artificial Neural Networks (ANN). The methodology is named hybrid once it requires short time series of structure responses (obtained by FEA) and imposed motions (evaluated analytically) to train an ANN. Subsequently, the ANN is employed to predict the remaining response time series using the prescribed motions imposed at the top of the structure by the floater unit. In this particular work, the methodology is applied aiming to predict the tension and bending moments’ time series at structural elements located at the top region and at the touchdown zone (TDZ) of a metallic riser. With the predicted responses (tensions and moments), the stress time series are determined for eight points along the pipe cross sections, and stress cycles are identified using a Rainflow algorithm. Fatigue damage is then evaluated using SN curves and the Miner-Palmgren damage accumulation rule. The methodology is applied to a SCR connected to a semisubmersible platform in a water depth of 910 m. The obtained results are compared to those from a full FEA in order to evaluate the accuracy and computer efficiency of the hybrid methodology.

Response Statistics of Moored Offshore Structures

1995 ◽  
Vol 117 (3) ◽  
pp. 159-165 ◽  
Author(s):  
T. Kinoshita ◽  
S. Takase
Keyword(s):  
Experimental Data ◽  
Time Series ◽  
Extreme Values ◽  
Offshore Structures ◽  
Theoretical Estimation ◽  
Floating Structure ◽  
Correlation Parameter ◽  
Random Seas ◽  
Limited Length ◽  
Time Series Simulation

This paper discusses the prediction of extreme values for total first and second-order responses of a floating structure moored in random seas. It is hard to estimate the extreme values from time series simulation or experimental data of limited length. Several methods of theoretical estimation of the extreme values are examined. They are the SRSS formula introduced by Naess (1987, 1989), the modified SRSS with a correlation parameter, the SRSS with Naess (1987, 1989) corection factor, the approximate SRSS (Naess, 1989), and the formula proposed by authors previously. The results of those methods are compared, and it is confirmed that the last one is very promising.

Development of a Welding Sequence Optimized for the Fatigue Resistance of Tubular Joints With a Novel Representative Welded Sample

2018 ◽  
Author(s):  
Philippe Thibaux ◽  
Eric Van Pottelberg
Keyword(s):  
Fatigue Resistance ◽  
Fatigue Testing ◽  
Welding Process ◽  
Offshore Structures ◽  
Fatigue Tests ◽  
Complex Geometries ◽  
Tubular Joints ◽  
Welding Sequence ◽  
Welding Procedure ◽  
Welding Position

Tubular joints are complex geometries present in many offshore structures. Fatigue testing of tubular joints requires either downsizing of the dimensions of the joints or the use of a simplified geometry, to avoid prohibitive costs. For the development of a welding process optimized for the fatigue performance of tubular joints, one needs to use a representative sample: same material, same thickness, use of similar welding positions, same level of restraint as in a real structure, combined with the supplementary requirement of ease of manufacturing and testing. A novel geometry was developed to fulfil all these requirements. Then, different welds were produced using robot and manual welding in different positions. The fatigue tests proved to be very reproducible, and indicate a strong influence of the welding position on the fatigue resistance. For that reason, an optimized welding procedure and sequence was developed, in which the welds in the most fatigue sensitive locations are produced first in optimum condition, while the less sensitive parts are produced by subsequent welding in position.

Analysis and Probabilistic Modeling of the Unstationary Ice Loads Stochastic Process, Based on Experiments With Models of Offshore Structures

2015 ◽  
Author(s):  
Petr Zvyagin ◽  
Kirill Sazonov
Keyword(s):  
Stochastic Process ◽  
Time Series ◽  
Statistical Analysis ◽  
Probabilistic Modeling ◽  
Offshore Structures ◽  
Offshore Structure ◽  
Sample Mean ◽  
Ice Loads ◽  
Time Series Simulation ◽  
Fuzzy C Means Algorithm

Experiments with models of platforms and offshore structures with vertical and inclined panels, which were conducted at Krylov Research Center (St. Petersburg), demonstrated that sometimes ice loads time series registered in these experiments cannot be considered as stationary. At the same time until nowadays methods and algorithms of probabilistic modeling were mainly based on the assumption of ice loads time series stationarity. That is because the analysis and modeling for stationary stochastic process is easier than for those unstationary. In the paper the method for determining the presence of unstationarity in ice loads time series, based on statistical analysis, is described. This method employs sample mean normality. Fuzzy C-means algorithm is used to cluster autocorrelation vectors, which are built for different fragments of time series. In the paper ice loads time series, got in experiments in ice tank with offshore structure columns and basement models, are investigated on their unstationarity. The algorithm of unstationary ice loads time series simulation is offered.

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