Jacket Type Offshore Platforms Research Articles

Damage detection in jacket-type offshore platforms via generalized flexibility matrix and optimal genetic algorithm (GFM-OGA)

Jacket-type offshore platforms are crucial infrastructure assets that can be damaged, disrupting operations and causing significant economic losses. To manage these risks, Structural Health Monitoring (SHM) is crucial in extending the lifespan of these structures. Recent years have seen the development of innovative vibration-based methods for SHM, which are based on the principle that changes in the dynamic model specifications of a structure indicate damage. The aim of this paper is to present an effective process for detecting structural damage through vibrational analysis and determining its location and severity. The proposed method uses vibrational characteristics of the structure, such as mass and stiffness, to deduce changes in its physical properties through monitoring with sensors. The methodology is formulated as an optimization problem where the target function is established based on the modal information of the structure in both intact and damaged states, and optimized subject to specific constraints. The solution to the optimization problem provides information on the location and severity of the damage. The methodology is demonstrated through a case study on a scaled model of a jacket-type offshore platform, showing its effectiveness in accurately identifying damage location and severity at varying levels of damage.

FOSM-based updated consecutive modal pushover procedure (FUCMP) for seismic uncertainty quantification of jacket offshore platforms

In this paper, the updated consecutive modal pushover (UCMP) procedure is implemented in the framework of the first-order-second-moment (FOSM) approach, called herein the FUCMP procedure, to propose a simplified and fast method in order to quantify the effects of epistemic (modeling) uncertainties in jacket type offshore platforms (JTOP). The UCMP procedure can take into consideration the progressive changes in the modal characteristics of structures together with the higher mode effects in predicting the seismic demands of JTOPs. The proposed FUCMP procedure is applied to a case study JTOP structure for the ductility level seismic performance evaluation considering the uncertainties in the material mechanical properties, mass and weight, and geotechnical properties. The sensitivity analysis on the seismic drift demands along the platform height to the variability in different random variables is also conducted. To this end, the results of the UCMP procedure for the modified platform models created by different uncertain variables are compared with those of the mean deterministic model. Moreover, the results of the FUCMP procedure are compared with those from the nonlinear response history (NRH) analysis conducted using a suite of far-field earthquake ground motions. These records are scaled to the design abnormal level earthquake (ALE) response spectrum. The results indicate that the FUCMP procedure is successful in predicting the standard deviation of the seismic demands considering various sources of uncertainty. Conceptually, the proposed procedure can be applied for the probabilistic seismic demand evaluation of the other structural systems.

Effect of earthquake directional uncertainty on the seismic response of jacket-type offshore platform

Effect of earthquake directional uncertainty on the seismic response of jacket-type offshore platform

Study on an Oscillating Water Column Wave Power Converter Installed in an Offshore Jacket Foundation for Wind-Turbine System Part II: Experimental Test on the Converting Efficiency

This study is an experimental study corresponding to an analytical study presented previously, where a scaled-down model was built and tested in a water tank by following the size and shape of the structure applied in the analytical study. In this study, a wave energy converter of an oscillating water column (OWC) system is integrated with the infrastructure of a jacket-type offshore platform applied to an offshore wind turbine system. The purpose is to conduct a combination system through the simultaneous utilization of both wind power and wave power so that sustainable energy can be maximized. During the analytical study’s analysis, the airflow response and the converting efficiency of wave energy from an OWC system integrated with an offshore template structural system were evaluated. By following the analytical study’s analysis, the performance of all the systems is tested, including the airflow velocity, pneumatic power, and the converting efficiency of the power from waves. The experimental data are analyzed and discussed in terms of the variations of the OWC system’s geometrical parameters. The parameters under consideration include the exhale orifice-area of airflow, gate-openings of inflow water, and the submerged chamber depth. It is found from the experimental results that, through the comparison between the experimental data and the analytical results, the results of the analytical study’s analysis are countable, and an open sea OWC system can be successfully applied to the template structure of offshore wind power infrastructure as a secondary generating system for the multi-purpose utilization of the structure.

Evaluating frequency domain methods for fatigue analysis of fixed jacket type offshore platform

Fatigue damage in offshore platforms is a major issue since they are exposed to periodic wave loads. Frequency domain methods of fatigue damage calculation are more efficient than time domain method, but they usually provide inaccurate and conservative results. Several alternatives have been developed to modify the results of frequency domain methods. In this paper, accuracy of these methods for application to fatigue analysis of tubular joints of fixed offshore platforms is evaluated by studying a typical platform in the Persian Gulf, considering various sea states and structural dynamic characteristics. The results are compared with those of time domain analysis using rainflow count method. They show that the frequency domain methods generally present conservative results, when the bandwidth parameter of stress spectrum is greater than 0.7. It is also found that the slope of S-N curve has a significant impact on the results. Furthermore, among the existing methods, Dirlik and Tovo-Benasciutti ones while being conservative, provide relatively most accurate results for fatigue life of tubular joints.

Damage detection of offshore platforms using dispersion analysis in Hilbert–Huang transform

A novel approach to damage detection based on dispersion analysis and signal processing methods is described. The proposed method was used on a scaled experimental model of a jacket-type offshore platform. A forced vibration test was conducted on the platform to acquire the acceleration signals. The frequency spectrum of the first intrinsic mode function of the recorded signals was obtained by the Hilbert transform (HT); it was found that damage engendered dispersion in the extracted frequencies. A novel damage index, capable of accurate damage detection and based on the Mahalanobis distance dispersion of the HT frequency spectrum was thus developed. The results of this work show that the proposed index can determine the location and severity of damage with acceptable accuracy.

Experimental investigation of decomposition of signal energy for damage detection of jacket type offshore platforms

ABSTRACT Steel jacket-type offshore platforms are operating in extreme environmental conditions and are prone to various damages. Thus, using structural health monitoring techniques prevents irreparable damages, long-term out of services, and losses. Several methods, such as physical and data-driven models-based, are presented for damage detection. In this paper, the experimental response of a prototype model with various damage scenarios has been measured. The prototype was excited using an eccentric-mass actuator, and dynamic responses were applied to identify damage locations using the decomposition of the signal energy approach. This approach could overcome the weaknesses of other energy methods. These methods don't demonstrate the location and intensity of damages when a wide range of damages exists in the structure. However, the DSE approach can predict all damages in a prototype with reasonable accuracy. Therefore, the DSE method can be proposed as an acceptable method for structural health monitoring for steel jacket-type offshore platforms.

Deep learning methods for damage detection of jacket-type offshore platforms

Recently, big data and machine learning based damage detection methods to support risk management of offshore facilities have received great attention, compared to traditional modal parameters-based methods. This paper illustrates the application of deep learning methods in damage detection of offshore platforms using measured vibration response of the structures subjected to random excitations. The numerical example of a jacket-type offshore platform under random wave excitation is applied to verify the applicability of convolutional neural network (CNN), long short-term memory (LSTM) networks, and CNN-LSTM method. The comparison of the three approaches are conducted in terms of accuracy and efficiency of damage localization and severity estimation for the simulated damage cases. In addition, the random decrement technique (RDT) for data preprocessing is used to improve the capability of damage detection of the three deep learning methods in noisy conditions. Moreover, the proposed RDT combined with the deep learning methods are applied to laboratory tests of a jacket platform model under random loading produced by a shaking table. Minor and major damages at different locations are discussed. Results show that the proposed combination method has an outstanding performance in structural damage detection even in noisy conditions, and also has great potential application in industrial process safety and operational risk management.

A Novel Risk Evaluation Procedure Using a Kriging-Based Surrogate Modeling for Offshore Structures

An innovative reliability estimation procedure for Jacket-type offshore platforms is proposed. The information on risk is extracted using multiple deterministic analyses using advanced mathematical theories resulting in compounding beneficial effects. The platforms are modeled by finite elements. Nonlinearity and major sources of uncertainty are incorporated. The wave loading model is realistically developed to satisfy the underlying physics. It is applied in three-dimension in time domain incorporating the uncertainties in the parameters. Implicit performance functions are expressed explicitly using several advanced factorial schemes and significantly improved response surface method. The efficiency and accuracy of the method are improved using a comprehensively improved Kriging-based surrogate modeling technique. The risk is evaluated for the serviceability and strength limit state functions for a jacket-type offshore platform using about two hundred nonlinear finite element analyses. The procedure was verified using simulation techniques. The concept can be considered an alternative to the conventional random vibration techniques and the standard Monte Carlo simulation procedure.

An updated consecutive modal pushover (UCMP) procedure for estimating the ductility level earthquake design demands of jacket offshore platforms

According to API- RP-2EQ/ISO 19901-2:2004(E), the static pushover method is allowed to be utilized for the abnormal level earthquake (ALE) design check of jacket type offshore platforms (JTOP) under the effects of earthquake ground motions. Therefore, the pushover method can be employed to check the ductility adequacy of JTOP structures under ALE (the ductility level earthquake in the previous versions of the API). In this paper, two modifications to the consecutive modal pushover (CMP) procedure are proposed in order to take into account the progressive changes in the dynamic characteristics of JTOP structures as well as the effects of higher modes on the seismic demands of JTOPs. The first modified procedure is called the updated consecutive modal procedure (UCMP), in which the load pattern for the second mode is updated at the beginning of the second stage of the CMP procedure based on the inelastic state of the structure at the end of the first stage. The UCMP procedure conceptually introduces a great advantage over the current enhanced pushover procedures as it considers the change of the dynamic characteristics in the applied load pattern, while it maintains the non-adaptive nature of the CMP method. The second modified procedure, that is called the adaptive-alfa consecutive modal pushover (ACMP) procedure, is proposed to define the displacement increments for the two-stage UCMP procedure based on the instantaneous effective modal participating mass ratio (α). The proposed methods are applied to two case study JTOP models, and the predicted seismic demands are compared with those from the benchmark nonlinear time history (NTH) analyses. A suite of earthquake records, selected based on the ductility level response spectrum, is used for the NTH analysis. The results show that notable improvements are achieved by the UCMP method in estimating the seismic demands of the lower braced stories of the jacket, where the effects of higher modes are expected to be more significant. Therefore, it is recommended to utilize the UCMP method when a trade-off between the accuracy of the pushover analysis and its simplicity is of interest. Moreover, the ACMP method produces an excellent prediction of the seismic demands at the lower stories of the jacket, and provides satisfactory estimations at the foundation part. Consequently, this method is proposed as a rigorous one to be utilized in the design phase of the fixed offshore platforms for the ductility level earthquake check.

Seismic response analysis of fixed jacket-type offshore structures based on power spectrum density Driven input

ABSTRACT Offshore platforms in seismically active areas should be properly designed to survive within the face of intense earthquakes without a global structural collapse. This paper scrutinizes the seismic performance of a newly designed and established jacket type offshore platform based on the API-RP2A normalized response spectra during seismic events. A finite element model is developed from a typical jacket type offshore platform taking into the effect of the interaction among structure, pile, and soil components. The seismic responses of jacket type offshore platforms subjected to random earthquake excitations are evaluated by means of the power spectral density (PSD) analysis. Dynamic characteristics, the response function, output PSD and transfer functions for various elements of the platform are discussed. The spectrum compatible PSD is directly used to estimate the peak structural responses and determine the dynamic response of offshore jacket platforms that meet the required level of engineering practice for preliminary design.

A damage detection procedure using two major signal processing techniques with the artificial neural network on a scaled jacket offshore platform

With the help of Structural Health Monitoring (SHM) methods, it is possible to identify the occurrence of damage at its early stages and prevent fatality and financial damages. Great advances in signal processing methods in combination with Machine learning tools have led to better achieve this goal. In the present paper, the two major techniques, that is, Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) are combined with Artificial Neural Network (ANN) through processing raw acceleration responses measured on a scaled jacket type offshore platform which was constructed and tested as a benchmark structure at K.N. Toosi University of Technology. In this way, ANN was trained by the signals obtained from EMD and DWT for three different conditions of the jacket platform to determine the relative damage severity. The envelope of the obtained signal’s energy (ENV) as an appropriate damage index was used to determine the damage location. The results of the application of this procedure on the case study indicated that DWT, compared to EMD, is a more reliable signal processing method in damage detection due to better noise reduction.

A multi-mode N2 (MN2) pushover procedure for ductility level seismic performance evaluation of jacket type offshore platforms

The static pushover analysis can be employed to check the adequate ductility of jacket type offshore platforms (JTOPs) under the abnormal level earthquake (ALE) in the design phase. The conventional pushover analysis suffers from different inherent limitations such as disregarding the higher mode effects. In this paper, it is intended to develop an advanced pushover procedure for the seismic design of JTOPs. To this end, a multi-mode N2 (MN2) pushover procedure is proposed that modifies the SRSS modal combination rule in the extended N2 procedure. The proposed procedure utilizes several modes of vibration to increase the accuracy of the method. The presented procedure is applied to two case study JTOP structures for the ductility level seismic performance evaluation. The seismic demands obtained by the MN2 procedure is compared with the average results of the benchmark nonlinear response history (NRH) analyses conducted using a suite of far-field ground motion records scaled to the ALE design response spectrum. The results of a statistical study show that there is a strong correlation between the spectral values of the records at the shorter periods of JTOPs and the responses of the foundation and the lower braced story levels of the jacket, which emphasize the important effects of the higher modes on the seismic demands of JTOPs if considering soil-pile-structure interaction. The utilized formulation for the modal combination is shown to improve the accuracy of the MN2 method at the pile foundation and at the lower braced story levels of the jacket. Moreover, the seismic drift demands predicted by the proposed MN2 method are in excellent agreement with the benchmark NRH results along the height of the platforms. Considering the simplicity and ease of application, this method can be utilized as a useful tool for checking the design ductility level earthquake.

Improved Modal Strain Energy Decomposition Method for damage detection of offshore platforms using data of sensors above the water level

Offshore structures usually are implemented in harsh environmental conditions which make the structures disposed to different failures. Negligible failures may lead to catastrophic ones. To prevent potential catastrophic failure, development of robust damage detection methods for offshore structures is necessary. Damages change structure's dynamic characteristics. Among different dynamic characteristics, modal frequencies and mode shapes are utilized more often. Due to various problems regarding damage detection methods for offshore structures such as sensor installation and data acquisition in water, damage detection methods using limited sensors seems very vital. In this paper, a novel method called Improved Modal Strain Energy Decomposition Method (IMSEDM) is developed to detect structural damage of jacket-type offshore platforms using a limited number of sensors just above the water. The proposed method has two main contributions. The first is simultaneous use of both modal frequencies and mode shapes which make damage detection more accurate. The second is decomposition of modal strain energy into axial and bending. IMSEDM locates damaged elements by considering the impacts of the damage on axial and bending modal strain energy. The method is evaluated using an experimental jacket type offshore platform. The results confirm that IMSEDM can effectively detect damages with incomplete data.

One-dimensional convolutional neural network for damage detection of jacket-type offshore platforms

Vibration-based damage detection techniques play an important role in health monitoring of offshore structures. This study explores the possibility to use the one-dimensional convolutional neural network (CNN) to extract the damage sensitive features automatically from the raw strain response data of a structure under a certain excitation without requiring any hand-crafted feature extraction. The validity of the proposed method is verified by using a numerical simulation of a jacket-type offshore platform under a regular and a random wave excitations in different directions, respectively. The damage localization and damage severity identification are conducted with considering several damage cases including different damage locations and the effect of noise. The data preprocessing procedure based on convolution and deconvolution for noisy data is proposed to enhance the capability of feature extraction and noise immunity of CNN. Furthermore, the experimental studies of a jacket-type offshore platform model subjected to a sinusoidal excitation, a white noise excitation and an impulse excitation are respectively investigated to check the applicability of the method, in which the major damage and minor damage on single and multiple locations are involved. Results indicate this approach has an excellent performance on structural damage detection.

Reliability estimation of jacket type offshore platforms against seismic and wave loadings applied in time domain

ABSTRACT A novel approach is proposed for the reliability estimation of jacket-type offshore platforms excited by dynamic loadings (wave and seismic) applied in time domain. The information on risk is extracted with the help of multiple finite element-based deterministic analyses. This feature is expected to be attractive to practitioners for routine applications without advanced expertise in the risk-based design concept. It will also be of interest to researchers since the proposed concept innovatively integrates several advanced mathematical concepts, including the extensively modified response surface method, advanced factorial design schemes, Kriging, and other techniques producing compounding beneficial effects. For verification, an operating platform is excited by multiple time histories of wave and seismic loadings generated using current design guidelines. The probabilities of failure of the platform are estimated for both the strength and serviceability performance functions using about 200 deterministic analyses. The results are successfully verified using 10,000 Monte Carlo simulations.

Estimating Design Loads with Environmental Contour Approach Using Copulas for an Offshore Jacket Platform

Jacket-type offshore platforms are widely used for oil, gas field, and energy development in shallow water. The design of a jacket structure is highly dependent on target environmental variables. This study focuses on a strategy to estimate design loads for offshore jacket structures based on an environmental contour approach. In addition to the popular conditional distribution model, various classes of bivariate copulas are adopted to construct joint distributions of environmental variables. Analytical formulations of environmental contours based on various models are presented and discussed in this study. The design loads are examined by dynamic response analysis of jacket platform. Results suggest that the conditional model is not recommended for use in estimating design loads in sampling locations due to poor fitting results. Independent copula produces conservative design loads and the extreme response obtained using the conditional model are smaller than those determined by copulas. The suitability of a model for contour construction varies with the origin of wave data. This study provides a reference for the design load estimation of jacket structures and offers an alternative procedure to determine the design criteria for offshore structures.

Quantitative collision risk assessment of a fixed-type offshore platform with an offshore supply vessel

Offshore installations are designed to withstand against potential collisions from offshore supply vessels (OSV). Quantitative risk assessment (QRA) provides an overall picture of expected collision frequencies and consequences for the design life of a platform and subsequently estimates the damage repair cost. However, the main challenge of the QRA study is how well various uncertainties are implemented into the model. This study aimed to introduce and demonstrate an advanced and efficient QRA model for the collision between an OSV and a jacket type offshore platform. A set of fifty collision scenarios were selected using probabilistic sampling techniques, and vessel motion analyses were performed to determine collision load characteristics. Extensive nonlinear structural crashworthiness analyses were conducted using advanced computational modelling techniques, and the repair cost of the damaged brace and column members were calculated. Probability exceedance diagrams were established for different consequence parameters, and asset risks were calculated. A comparison study of the design values of damage parameters and repair costs were carried out in association with the NORSOK and HSE risk acceptance criteria. A sensitivity study was carried out to study the effects of various collision load parameters on the structural consequences. The methods and insights developed in this study could be applied to both new and existing offshore platforms and practically useful for the platform owners to aid in their decision-making process towards the risk-based safety analysis of offshore platforms.

Evolved predictive vibration control for offshore platforms based on the Lyapunov stability criterion

ABSTRACT The objective is to propose a networked control system (NCS) predictive vibration controller capable of handling the inevitable random disturbances for steel jacket-type offshore platforms under irregular wave forces. We present a model of a networked control system with two buffers. The model is then applied for the vibration control of offshore platforms. The buffers are designed to solve the control problems using a novel derivation of the Lyapunov stability criterion based on the previously received packets of time. The evolved bat algorithm is utilized to simplify the computation of the control law and reduce the amount of storage required, for a methodology which physically realizable and easy to complete. The method is applied in an example for a steel jacket-type offshore platform and the findings show that the network based predictive vibration controller can efficiently compensate for random big delays, large packet dropouts and disordering. The improvement of the presented predictive controller means that it can significantly decrease oscillation of the offshore platform while simultaneously keeping the required control force on an ideal small scale.

Computational models for the structural crashworthiness analysis of a fixed-type offshore platform in collisions with an offshore supply vessel

The aim of this paper was to develop practical modelling techniques for the structural crashworthiness analysis in collisions between a fixed-type offshore platform and an offshore supply vessel (OSV). The computational models used nonlinear finite element method involving large deformations (strains) of both vessel and offshore platform, dynamic effects of material (e.g., strain rate and dynamic fracture strain), and the influence of surrounding waters. The applicability of the modelling techniques was demonstrated with an applied example to collisions between an OSV and a jacket-type offshore platform, where a sensitivity analysis was carried out for different collision parameters (e.g., collision velocities and impact locations). It is concluded that the computational models can ultimately be employed for quantitative risk assessment of fixed-type offshore structures collided with an OSV, which requires to perform the structural crashworthiness analysis. • Computational models for the crashworthiness in collisions between a fixed-type offshore platform and an OSV are developed. • The computational models use nonlinear finite element method. • Large deformations of target structures, dynamic effects of material, and the influence of surrounding waters are studied. • Applicability of modelling techniques is demonstrated for collisions between an OSV and a jacket-type offshore platform. • A sensitivity analysis is carried out with varying collision parameters (e.g.,velocities and impact locations).