Predicting the capability-polar-plots for dynamic positioning systems for offshore platforms using artificial neural networks

As the capability of polar plots becomes better understood, improved dynamic positioning (DP) systems are possible as the control algorithms greatly depend on the accuracy of the aerodynamic and hydrodynamic models. The measurements and estimation of the environmental disturbances have an important role in the optimal design and selection of a DP system for offshore platforms. The main objective of this work is to present a new method of predicting the Capability-Polar-Plots for offshore platforms using the combination of the artificial neural networks (NNs) and the capability polar plots program (CPPP). The estimated results from a case study for a scientific drilling vessel are presented. A trained artificial NN is designed in this work and is able to predict the maximum wind speed at which the DP thrusters are able to maintain the offshore platform in a station-keeping mode in the field site. This prediction for the maximum wind speed will be a helpful tool for DP operators in managing station-keeping for offshore platforms in an emergency situation where the automation of the DP systems is disabled. It is obvious from the obtained results that the developed technique has potential for the estimation of the capability-polar-plots for offshore platforms. This tool would be suitable for DP operators to predict the maximum wind speed and direction in a very short period of time.     

Structural monitoring of offshore platforms using impulse and relaxation response

Monitoring offshore platforms, long span bridges, high rise buildings, TV towers and other similar structures is essential for ensuring their safety in service. Continuous monitoring assumes even greater significance in the case of offshore platforms, which are highly susceptible to damage due to the corrosive environment and the continuous action of waves. Also, since a major part of the structure is under water and covered by marine growth, even a trained diver cannot easily detect damage in the structure. In the present work, vibration criterion is adopted for structural monitoring of jacket platforms. Artificial excitation of these structures is not always practicable and ambient excitation due to wind and waves may not be sufficient for collecting the required vibration data. Alternate methods can be adopted for the same purpose, for example, the application of an impact or a sudden relaxation of an applied force for exciting the structure. For jacket platforms, impact can be applied by gently pushing the structure at the fender while relaxation can be accomplished by pulling the structure and then suddenly releasing it using a tug or a supply vessel in both cases. The present study is an experimental investigation on a laboratory model of a jacket platform, for exploring the feasibility of adapting vibration responses due to impulse and relaxation, for structural monitoring. Effects of damage in six members of the platform as well as changes in deck masses were studied. A finite element model of the structure was used to analyze all the cases for comparison of the results as well as system identification. A data acquisition and analysis procedure for obtaining the response signatures of the platform due to the impulse and relaxation procedure was also developed for possible adoption in on-line monitoring of offshore platforms. From the study, it has been concluded that both impulse and relaxation responses are useful tools for monitoring offshore jacket platforms. The present work forms the basis for the development of an automated, on-line monitoring system for offshore platforms, using neural networks.     

Experiment Verification of Damage Detection for Offshore Platforms by Neural Networks

1 .Introduction Large civil engineering structures are exposed to various external loads such as earthquakes ,winds ,traffic and wave loads during their lifetime . The structures may become deteriorated and de-graded withtime in an unexpected way, which m…     

Neural adaptive robust control of underactuated marine surface vehicles with input saturation

This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications.     

Wind and wave induced behaviour of offshore guyed tower platforms

Offshore guyed tower platforms belong to the group of compliant offshore platforms which are most suited for deep water exploration. The basic feature of compliant offshore platforms is that they are designed to move with the waves, in at least some degrees-of-freedom. As far as excitation of wave frequencies is concerned, the system opposes wave forces by inertial effects. The offshore guyed tower derives its stability against lateral movement from its mooring system.In this study, the response of offshore guyed towers to random forces generated by wind and wave is investigated. The exposed portion of the tower is subjected to the action of turbulent wind, while the submerged portion is acted upon by random wave forces. The analysis includes the nonlinearities due to the Morison equation of drag force, the variable submergence effect due to waves, the instantaneous position of the tower and force excursion relation of the mooring lines. A parametric study is conducted to investigate the behaviour of the tower under waves, and the combined effect of wind and wave forces.     

A data-driven method for optimal control of ship motions for safe crew transfer to offshore wind turbines

Due to uncertainties and random behavior of sea loads, presenting an accurate hydrodynamic analysis for motion control of offshore ships is a big challenge. This paper aims to propose a novel method for motion control of a crew transfer vessel (CTV) in order to ensure safe crew transfer to an offshore wind turbine (OWT). For this purpose, we propose a novel neural network observer-based optimal control (NOPC) scheme to tackle unknown dynamics and disturbances, nonlinear effects, and non-symmetric control input saturation constraints. Accordingly, the neural network (NN) structure addresses the Hamilton-Jacobi-Bellman (HJB) equation and forms an optimal control signal remaining in the saturation bounds. The Lyapunov theory guarantees the Ultimately Uniformly Boundedness (UUB) of all signals of the closed-loop system. The high performance of the presented method is demonstrated in regular waves with high frequency in comparison with the previous studies. It is worth mentioning that there are not any limitations to implement the adopted strategy for other offshore applications.     

海洋平台磁流变阻尼器半主动控制研究

基于现代最优控制理论建立海洋平台磁流变 (MR)半主动控制系统的数学模型 ,采用白噪声过程通过滤波器来近似随机波浪力谱。以典型导管架平台为算例 ,对磁流变阻尼器进行了参数设计。分析了 MR阻尼器对海洋平台振动控制的有效性 ,仿真结果表明 ,采用磁流变阻尼器对海洋平台进行半主动控制能够有效的减小平台的动态响应。     

随机波浪荷载作用下海洋平台的前馈-反馈振动控制研究

该文研究线性前馈 -反馈控制策略对海洋平台振动控制的有效性。线性前馈 -反馈控制只有当输入荷载为白噪声过程时 ,所实施的控制才是最优的 ,因此该文采用一白噪声过程通过滤波器来近似随机波浪力谱 ,并将海洋平台 -主动控制系统的动力学方程转化为符合随机最优控制要求的增广状态空间表达形式。依据设计目标中对安全性以及经济性的权衡 ,通过使二次型控制目标函数最小化 ,推导出了随机最优控制力的计算方法 ,从而实现了最优控制的目的。在频率域上分析了海洋平台受控后的振动响应 ,结合典型的海洋天然气生产平台算例 ,将前馈 -反馈控制与反馈控制、TMD控制加以比较 ,总结了前馈 -反馈控制的特点及其优越性     

The application of the self-tuning neural network PID controller on the ship roll reduction in random waves

In this paper, we present a mathematical model including seakeeping and maneuvering characteristics to analyze the roll reduction for a ship traveling with the stabilizer fin in random waves. The self-tuning PID controller based on the neural network theory is applied to adjust optimal stabilizer fin angles to reduce the ship roll motion in waves. Two multilayer neural networks, including the system identification neural network (NN1) and the parameter self-tuning neural network (NN2), are adopted in the study. The present control technique can save the time for searching the optimal PID gains in any sea states. The simulation results show that the present developed self-tuning PID control scheme based on the neural network theory is indeed quite practical and sufficient for the ship roll reduction in the realistic sea.     

基于深度学习的随船波浪测量技术研究

深海极端波浪环境为浮式海洋平台作业时最为关键的海洋动力环境之一。在其作用下,深海浮式平台的运动、气隙以及结构响应等均为近年来的研究热点。然而,在深海环境中,入射波浪环境往往通过X波段雷达进行测量,仅能获得波浪的短时统计值,极大限制了实海域浮动平台动力响应的研究。目前,尚无成熟的方法能够对海洋浮式平台所处海域的入射波时序进行实时测量。针对深远海半潜式平台的波浪时序随船测量问题,结合平台气隙响应与运动响应数据建立基于深层神经网络的波浪非线性解耦模型,准确估计辐射、绕射波浪以及其非线性成分对时序波浪场的影响。研究显示,基于深度神经网络的波浪时序测量技术可以实现从气隙响应到入射波信息的反推,利用该方法计算得到的波浪时序具有较高的精度。     

Distorted polyester lines for model testing of offshore moored platforms

Model tests of floating offshore platforms replace the mooring lines by inextensible cables connected to steel springs with a linear restoring capability. With the help of fundamental investigation on the similarity laws, the present work shows that the use of very thin polyester lines in model scaling is feasible and may allow a better physical representation of the full-scale polyester lines. The proposal is to use polyester lines with length distortion in order to keep the similar restoring capability and therefore, the same non-linear behavior would also be present during the tests. The work describes the application of these ideas in a model test of an Floating Production Storage and Offloading (FPSO) submitted to regular and random waves. The tests include both the linear spring lines and the distorted equivalent polyester lines, holding the FPSO model, submitted transversally to the same waves.     

Ocean wave forecasting using recurrent neural networks

The tremendous increase in offshore operational activities demands improved wave forecasting techniques. With the knowledge of accurate wave conditions, it is possible to carry out the marine activities such as offshore drilling, naval operations, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off Marmugao, west coast of India are used for this study. Here, the recurrent neural network of 3, 6 and 12 hourly wave forecasting yields the correlation coefficients of 0.95, 0.90 and 0.87, respectively. This shows that the wave forecasting using recurrent neural network yields better results than the previous neural network application.     

A Global Refiability Assessment Method on Aging Offshore Platforms with Corrosion and Cracks

Corrosion and fatigue cracks are major threats to the structural integrity of aging offshore platforms.For the rational estimation of the safety levels of aging platforms,a global reliability assessment approach for aging offshore platforms with corrosion and fatigue cracks is presented in this paper.The base shear capacity is taken as the global ultimate strength of the offshore plaffoms,it is modeled as a random process that decreases with time in the presence of corrosion and fatigue crack propagation.And the corrosion and fatigue crack growth rates in the main members and key joints are modeled as random variables.A simulation method of the extreme wave loads which are applied to the structures of offshore platforms is proposed too.Furthermore,the statistics of global base shear capacity and extreme wave loads are obtained by Monte Carlo simulation method.On the basis of the limit state equation of global failure mode,the instantaneous reliability and time dependent reliability assessment methods are both presented in this paper.Finally the instantaueous reliability index and time dependent failure probability of a jacket platform are estimated with different ages in the demonstration example.     

Semi-Active TLCD Control of Fixed Offshore Platforms Using Artifical Neural Networks

1 .Introductionanyoffshoreplatformshavebeenbuiltwiththedevelopmentofoceanengineering .However ,mostoffshorearelocatedinseismicregionsandtheplatformsareeasilytobeseriouslydamagedbyearthquakes.Hence ,theanti earthquakedesignhasalwaysbeenamajorpartofresearchonoffshoreplatforms.Theinclusionofvibrationabsorbersintheoffshoreplatformcanbeanattractivemethodofmitigatingseismicresponses .Vibrationabsorberscanbecategorizedintoactiveandpassive .Thetunedmassdamper (TMD)(FujinoandAbe ,1 993) ,eitherpassi…     

A Global Reliability Assessment Method on Aging Offshore Platforms with Corrosion and Cracks

Corrosion and fatigue cracks are major threats to the structural integrity of aging offshore platforms. For the rational estimation of the safety levels of aging platforms, a global reliability assessment approach for aging offshore platforms with corrosion and fatigue cracks is presented in this paper. The base shear capacity is taken as the global ultimate strength of the offshore platforms. It is modeled as a random process that decreases with time in the presence of corrosion and fatigue crack propagati...     

考虑流固耦合时的海洋平台结构非线性动力分析

采用非线性的Morison方程,建立了考虑流固耦合时的海洋平台非线性动力方程及其时程分析方法.以一固定式导管架平台为算例,计算了考虑流固耦合时的海洋平台浪致振动响应,比较了考虑流固耦合和不考虑流固耦合时海洋平台动力响应的差异.算例表明：在较大的波浪条件下,不考虑流固耦合时的计算结果明显小于考虑流固耦合时的计算结果,因此,偏于不安全.分析认为,在极端海况条件下,考虑流固耦合的分析方法更符合实际情况.     

Wave-induced vibration control of offshore jacket platforms through SMA dampers

Since permanent wave-induced vibrations of offshore jacket platforms reduce the service life of the jacket structure and deck equipment and increase the fatigue failure of the welded connections, this research has used SMA (shape memory alloy) dampers to control the jacket platform oscillations. Superelasticity, high durability, and energy dissipation capability make SMA elements good nominees for the design of vibration control devices. In this research, to model the force-displacement hysteretic behavior of SMA elements their idealized multi-linear constitutive model has been implemented and the time history responses of vibration equations have been evaluated by direct integration method. To analyze the SMA damper effects on the vibration suppression of the jacket platforms, a 90 (m) high jacket located 80 (m) deep in water has been selected as a case study. Numerical results have shown that optimized SMA dampers with constant-geometry SMA bars will improve the dynamic behavior of the jacket platform under the action of an extreme regular wave. However, under the action of two irregular waves, SMA dampers with varying-geometry SMA bars will cause significant reduction in the dynamic responses of the jacket platform. The power spectral density function of the deck displacements have shown that the previously mentioned SMA dampers avoid resonance by shifting the natural frequencies of the jacket structure away from the excitation frequencies.     

Prediction of breaking waves with neural networks

The height of a wave at the time of its breaking, as well as the depth of water in which it breaks, are the two basic parameters that are required as input in design exercises involving wave breaking. Currently the designers obtain these values with the help of graphical procedures and empirical equations. An alternative to this in the form of a neural network is presented in this paper. The networks were trained by combining the existing deterministic relations with a random component. The trained network was validated with the help of fresh laboratory observations. The validation results confirmed usefulness of the neural network approach for this application. The predicted breaking height and water depth were more accurate than those obtained traditionally through empirical schemes. Introduction of a random component in network training was found to yield better forecasts in some validation cases.     

Parametric Resonance Analyses for Spar Platform in Irregular Waves

The parametric instability of a spar platform in irregular waves is analyzed. Parametric resonance is a phenomenon that may occur when a mechanical system parameter varies over time. When it occurs, a spar platform will have excessive pitch motion and may capsize. Therefore, avoiding parametric resonance is an important design requirement. The traditional methodology includes only a prediction of the Mathieu stability with harmonic excitation in regular waves. However, real sea conditions are irregular, and it has been observed that parametric resonance also occurs in non-harmonic excitations. Thus, it is imperative to predict the parametric resonance of a spar platform in irregular waves. A Hill equation is derived in this work, which can be used to analyze the parametric resonance under multi-frequency excitations. The derived Hill equation for predicting the instability of a spar can include non-harmonic excitation and random phases. The stability charts for multi-frequency excitation in irregular waves are given and compared with that for single frequency excitation in regular waves. Simulations of the pitch dynamic responses are carried out to check the stability. Three-dimensional stability charts with various damping coefficients for irregular waves are also investigated. The results show that the stability property in irregular waves has notable differences compared with that in case of regular waves. In addition, using the Hill equation to obtain the stability chart is an effective method to predict the parametric instability of spar platforms. Moreover, some suggestions for designing spar platforms to avoid parametric resonance are presented, such as increasing the damping coefficient, using an appropriate RAO and increasing the metacentric height.     

Feedback and Feedforward Optimal Control for Offshore Jacket Platforms

The optimal control is investigated for linear systems affected by external harmonic disturbance and applied to vibration control systems of offshore steel jacket platforms. The wave-induced force is the dominant load that offshore structures are subjected to, and it can be taken as harmonic excitation for the system. The iineafized Morison equation is employed to estimate the wave loading. The main result concerns the existence and design of a realizable optimal regulator, which is proposed to damp the forced oscillation in an optimal fashion. For demonstration of the effectiveness of the control scheme, the platform performance is investigated for different wave states. The simulations axe based on the tuned mass damper (TMD) and the active mass damper (AMD) control devices. It is demonstrated that the control scheme is useful in reducing the displacement response of jacket-type offshore platforms.