Studies on structural monitoring of offshore jacket platforms
13 Jun 2001-Vol. 4317, pp 521-527
TL;DR: In this paper, a series of analytical and physical model studies conducted to develop an online monitoring system for offshore platforms was described, and the final outcome was a scheme for integrity monitoring of jacket type of fixed offshore platforms using vibration characteristics of the structure.
Abstract: The paper describes a series of analytical and physical model studies conducted to develop an online monitoring system for offshore platforms. An actual offshore jacket platform situated in a water depth of 88m was selected for the study. A detailed 3D finite element analysis of the platform involving free and forced vibration revealed that there were dynamic characteristics of the platform which could be used to identify the structural damages in the structure. Having established the feasibility of the method, further work was carried out on a physical model of the platform. Dynamic characteristics of the model were determined by spectral analysis of the response data, simulating various changes including compete and partial damages on individuals elements of the model. Simultaneously work was also initiated to apply the result of the physical model tests for interpreting the causes of the changes in the dynamic characteristics using ANN trained with the database created through experiments and analysis. The final outcome of these comprehensive studies was a scheme for integrity monitoring of jacket type of fixed offshore platforms using vibration characteristics of the structure.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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TL;DR: In this article, a bibliographical review of finite element methods applied to non-destructive evaluation of materials is given, which is a continuation of the same paper published in Modelling Simul.
Abstract: This paper gives a bibliographical review of the finite-element methods applied to the non-destructive evaluation of materials. It is a continuation of the same paper published in Modelling Simul. ...
38 citations
Dissertation•
10 Dec 2012
TL;DR: Using completely new environmental forces as input to ANN, the time history response of spar platform can be very accurately predicted and the ANN approach is very efficient and significantly reduces the time for predicting response time histories.
Abstract: Due to global energy demand, offshore industries are moving towards deep and ultra-deep waters for oil and gas exploration in ocean environment. Floating offshore structures such as spar platform is considered to be the most economic and suitable offshore structure in deep water regions. During oil and gas exploration, floating offshore structures may sometimes be affected by critical environmental forces. Quick decision must be taken either to continue or to stop production, on the basis of response prediction of offshore structures under forecasted environmental conditions. Finite Element Method (FEM) is an important technique to predict the response of offshore structures considering all nonlinearities. However, FEM is a highly time-consuming process for predicting the response of platforms and usually used as a final analysis tool. On the other hand, Artificial Neural Networks (ANN) can predict response in rapid mode. ANNs are also capable of providing efficient solutions to problems such as damage detection, time series prediction and control where formal analysis is highly complex.
This study presents nonlinear response prediction of spar platform for various environmental forces using ANN. The neural network has three layers, namely the input, output, and hidden layer. A hyperbolic tangent function is considered in the present study as an activation function. Environmental forces and structural parameters are used as inputs and FEM-based time history of spar platform responses are used as targets. Feed-forward neural networks with back-propagation algorithm are used to train the network. After training the network, the response of the spar platform is obtained promptly for newly selected environmental forces. The response obtained using ANN is validated by conventional FEM analysis. It has been observed that using completely new environmental forces as input to ANN, the time history response of spar platform can be very accurately predicted. Results show that the ANN approach is very efficient and significantly reduces the time for predicting response time histories.
6 citations
Cites methods from "Studies on structural monitoring of..."
...Banerji and Datta (1997); Idichandy and Mangal (2001) used ANN for monitoring the integrity of an offshore structure....
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