Search

Measurement errors, spatial incompleteness, and parameter uncertainties frequently lead to significant deviations between the estimated correction coefficients of structural model updating and their actual values. To address the limitations, a novel multi-objective evolutionary algorithm called MOEA-HiMs is proposed for structural model updating, which incorporates a hybrid initialization and multi-stage update strategy. Two main contributions are summarized: (a) the introduction of optimal point and elite set initialization to enhance population diversity, which is achieved through the use of Latin hypercube sampling and a regularization technique, respectively; (b) the division of the optimization process into multiple stages, where solutions are corrected to improve converging efficiency using an appropriate update strategy. Additionally, the elite set is selected through the execution of sensitivity classification using a novel mathematical sensitivity index. The effectiveness and robustness of the MOEA-HiMs are demonstrated by the numerical offshore jacket platform and an experimentally-scaled platform structure. Both numerical and experimental results prove that the novel proposed MOEA-HiMs is more effective and robust than the traditional MOEA when using limited information, even under heavy noise conditions. The algorithm can serve as preliminary methods for online structural model updating of offshore platforms. • An evolutionary algorithm that incorporates a hybrid initialization and multi-stage update strategy (MOEA-HiMs) is proposed. • A normalized sensitivity index is proposed and K-means clustering analysis is performed for sensitivity classification. • Numerical and experimental results demonstrate that the MOEA-HiMs is more effective and robust compared to the MOEA. • The MOEA-HiMs significantly enhances the precision and accuracy of the correction coefficients that have lower sensitivities. • The MOEA-HiMs effectively solves ill-conditioned problems in structural model updating that are caused by measured noises. [ABSTRACT FROM AUTHOR]

In structural engineering, offshore structures are undoubtedly among the most exposed to the effects of harsh environmental conditions. The external conditions of these semi-immersed systems involve complex combinations of wave and wind loads. The operating conditions are also unique because oil production platforms are subjected to repeated loading and unloading cycles of the extracted material, which continuously alter their mass. These characteristics make the definition of a structural health monitoring (SHM) protocol highly challenging but necessary to avoid environmental disasters. In this regard, this study discusses an SHM method that can be applied to offshore structures under realistic wave and wind loads. This approach combines anomaly detection, frequency domain decomposition, and a cointegration strategy. Two machine learning regression algorithms were tested to define a cointegration relationship: the support vector machine and the relevance vector machine. The effectiveness of the overall method was evaluated on time-domain signals generated from a finite-element model of a fixed steel platform, on which the Davenport and JONSWAP spectra were used to simulate wind and wave forces. The results show that this damage detection strategy is effective in supervising the health conditions in the analyzed scenario. • A Structural Health Monitoring (SHM) strategy is presented, based on Frequency Domain Decomposition and Cointegration. • Innovatively, the method is output-only, allowing its unrestricted use on-site and under normal operating conditions. • It can be applied directly to the time series as recorded from the structure's dynamic response. • Instead of the classic assumption of white Gaussian noise as input, realistic wind and wave forces are considered. • Different operating conditions and damage scenarios are numerically simulated and investigated. [ABSTRACT FROM AUTHOR]

Blow-outs occurred on offshore platform and associated fires have been recurrent during the previous few decades, and poses a potential safety hazard to humans, property and the surrounding environment. Although the real-time forecast based on deep learning have shown promise in the fields of fire modelling and hazardous area evaluations, jet fire spatio-temporal modelling has not yet undergone sufficient investigation in complex ocean engineering cases like offshore platforms. This research therefore proposes a deep learning-based framework for jet fire spatio-temporal probabilistic real-time forecast by developing the Hybrid-VB-ConvSTnn model, which integratesConvGRU and variational Bayesian inference. And the significant hyperparameters were locally optimized through sensitivity analysis and finally identified as Monte Carlo (MC) sampling number m = 100 and dropout probability p = 0.1. By performance comparison with different models, the Hybrid-VB-ConvSTnn model shows competitive spatio-temporal forecasting capabilities in terms of both real-time (Inference time = 0.83s) and accuracy (R 2 = 0.982). Moreover, the Hybrid-VB-ConvSTnn model could provide the additional uncertainty inferences based on the probability density of the Bernoulli distribution, which avoids the inherent shortcomings of "overconfidence" for traditional point-estimate models and lends credibility to flame boundary identification. The proposed framework could support the digital twin-based fire emergency management on offshore platforms by more comprehensive and robust risk evaluation. • Deep learning-based advanced approach framework for natural gas jet fire spatiotemporal probabilistic forecast is developed. • Uncertainty inference in flame boundary forecast can be determined with variational Bayesian inference. • Hyperparameters that determine model performance are locally optimized through sensitivity analysis. • Real-time forecast provides an alternative for digital twin model of jet fire accidents management on offshore platform. [ABSTRACT FROM AUTHOR]

Hydro-dynamic induced vibration is a major risk for offshore platform, which may cause fatigue damdage. The present work experimentally studies a smart isolation system for vibration mitigation of offshore platform utilizing magnetorheological elastomer (MRE). The principle of the proposed MRE-based smart isolation system is presented, in which a real-time decoupling between superstructure (deck) and the jacket structure is achieved by controlling MRE's horizontal stiffness. For a case study, a scaled simplified fixed offshore platform model is built. The prototype of MRE-based isolation system is manufactured and its field-induced dynamic performances are tested. A fuzzy logic controller is proposed for achieving real-time decoupling control. A wave tank testing for the offshore platform with MRE-based isolation system is conducted, in which wave loadings in different dynamic characteristics are considered (e.g., regular and random waves). The results show that the deck acceleration and its displacement, and isolation drift are greatly decreased by the controlled MRE isolation system. It is proven that the smart MRE-based isolation system is able to provide effectiveness vibration suppression for offshore platform structure over a wide range of wave loadings. • Innovation: It is the first experimental investigation on the vibration mitigation of fixed platform by MRE-based variable stiffness isolation system. • Highlight 1: An MRE-based isolation system for reducing wave-induced dynamic responses of fixed platform is numerically studied. • Highlight 2: The testing model of a platform with MRE isolator is developed, and the controllable stiffness of MRE isolator is tested. • Highlight 3: A fuzzy logic controller is proposed to control the performance of MRE isolation system. [ABSTRACT FROM AUTHOR]

Ice loading is the main controlling design load for offshore platforms in Bohai Bay. The ice-induced vibration of offshore platform can be monitored every winter. Both the freezing and drifting sea ice can damage an offshore platform causing structural damage, discomfort for workers, gas leakage and other problems. Two platform designs were studied aiming to reduce ice-induced vibration. One design is the offshore platform with concrete filled double-skin legs (JOP-CFDSL). The other design is the self-centering offshore platform with concrete filled double-skin legs (SRJOP-CFDSL). Both platforms were tested in laboratory experiments, and the data were used to prepare numerical simulations. The results showed that the ice-induced vibration of the two novel jacket platforms are all reduced under push loads, and the SRJOP-CFDSL have better control effect. The replacement of jacket offshore platform's steel circle hollow section legs with concrete filled double-skin legs can effectively improve the structural stiffness. And prestressed tendons were found to improve the platform's performance even further, helping it to reset after lateral impact. It should be noted that the prestressed tendon as an important bearing member, must do some anti-icing protection. Thus, the influence of ice force on the prestressed tendon isn't considered in this paper. • CFDST legs can effectively improve platform's stiffness. • JOP-CFDSL and SRJOP-CFDSL have good ability to resist ice-induced vibration. • SRJOP-CFDSL has great self-centering performance. • SHS improve the corrosion resistance of JOP-CFDSL and SRJOP-CFDSL. [ABSTRACT FROM AUTHOR]

Flammable gas dispersion and deflagration above sea resulting from subsea release have the possibility to cause an adverse impact on the operation safety of surface vessels. This paper presents a systematic simulation of gas dispersion and deflagration above sea from a subsea release using CFD-based approach, aiming to study the evolution process of accident scenario and assess its impact on surface vessels. A jack-up drilling platform is used as a case to discuss the impact of gas dispersion and deflagration. The uniqueness of this study is the integration of release, dispersion, and deflagration scenarios. The simulation includes the modelling of wind flow, gas dispersion and subsequent deflagration due to accidental ignition. The wind flow above sea surface is given using wind speed profile equation to generate steady wind field around offshore platform. Simulation of gas dispersion is conducted based on the generated wind field. The development of flammable gas cloud is predicted, and the dangerous area on offshore platform is assessed. Considering the appearance of ignition source, a deflagration simulation based on dispersion results is performed to predict the consequences including overpressure, high temperature, and heat radiation. Eventually, the damage criterion is utilized to evaluate their impact on offshore platform. [ABSTRACT FROM AUTHOR]

Floatover installation is an effective installation method for topsides of offshore platforms. The floatover operation is very sensitive to the ocean environment conditions, and the motions of the topside are required to be strictly limited within a certain level. The field monitoring is essential to support the installation. This paper presents a comprehensive introduction to the monitoring system developed by Shanghai Jiao Tong University for the jacket platform floatover installations. Four subsystems were designed for the purposes of environment monitoring, motions and position monitoring, deck support unit (DSU) separating monitoring and closed-circuit television (CCTV) monitoring, respectively. Besides, the integrated monitoring system (IMS) for data integration is also introduced. In addition, applications of the monitoring system with respect to a recently implemented floatover installation project in Malaysian waters is presented. The execution plan is introduced in details, and the implementation process for the monitoring system including validation, installation, tests and field operation is presented. Moreover, the field monitoring results are presented and discussed in brief. [ABSTRACT FROM AUTHOR]

Offshore structures are critical infrastructure in the field of ocean engineering, which may under the threat of earthquake shaking, especially when they are located in the high-risk seismic zones. This paper proposes using an innovative inerter-based damping isolation system (IDIS) for the seismic protection of offshore platforms. The concept of IDIS is firstly proposed by integrating the conventional bearings with inerter-based dampers (IDs). An analytical model of the system is established, and the corresponding equilibrium equations of motion are derived. Without loss of generality, the deck acceleration, displacement on the jacket cap, and isolating layer deformation are chosen as the performance objectives, and parametric analyses are performed to investigate the influences of the key parameters of IDIS on each performance objective. A performance-based multi-objective optimization framework is then developed for determining the optimal parameters of IDIS. The control effectiveness of IDIS is demonstrated in the frequency domain and compared to that of the traditional damping isolation system (DIS). Finally, case studies are performed to further investigate the performance of IDIS subjected to natural seabed ground motions. The results show that properly optimized IDIS is more effective than the conventional DIS in terms of not only the structural responses but also the deformation of the isolating layer. The proposed IDIS can be an attractive and effective alternative to the conventional DIS in the vibration control of offshore platforms. • Inerter-based damping isolation system (IDIS) is proposed for offshore platforms. • Performance-oriented multiple-objective optimization is formulated for IDIS. • Control effectiveness of IDIS is investigated in both frequency and time domains. [ABSTRACT FROM AUTHOR]

Nowadays, natural load excitation cannot detect all modal problems when testing vibration responses of offshore platforms. To overcome this issue, the present paper proposes a novel method to detect structural damages of offshore platforms based on grouping modal strain energy. This method divides the unit modal strain energy into axial tension-compression and bending. It may not only expand known modals and overcome the incomplete modal parameters under natural load excitation, but also could estimate the damage locations based on low-order modal parameters. The proposed method was verified by numerical simulations. Based on simulations on different damage conditions of a jacket offshore platform, damage locations could be determined accurately through comprehensive analysis of grouping modal strain energy distribution. [ABSTRACT FROM AUTHOR]

Natural gas explosion of offshore platform is prone to cause accidental disaster such as platform collapse and casualties etc. Real-time natural gas explosion consequence reconstruction is essential to support a quick accidental emergency response planning to prevent the accidental escalation to disaster. The widely-used CFD is computationally intensive and thereby has a significant delay. Machine/deep learning-based models offer a potential real-time alternative, which however are not able to quantify the uncertainty of spatial overpressure prediction. This study aims to propose a hybrid deep learning probability model to real-time predict spatial explosion overpressure of offshore platform by using sparsely-observed overpressures. In this hybrid model, Variational Bayesian inference is incorporated into deep learning backbone. Both natural gas explosion experimental and numerical modeling of offshore platform are conducted to construct the benchmark dataset. By using this benchmark dataset, sensitivity analysis of Monte Carlo sampling number N , drop probability p on model's performance is also conducted. The results demonstrated our model exhibits high accuracy with R 2 = 0.955 and real-time capability with inference time of 2.9s. Compared to the state-of-the-art model, the additional uncertainty estimation improves the accuracy and robustness of spatial overpressure prediction, which contributes to the reliable explosion accidental emergency decision-making. Overall, this study provides a reliable alternative for constructing digital twin emergency management system to effectively manage natural gas explosion risk of offshore platforms. • Deep learning probability model for real-time natural gas explosion prediction of offshore platforms. • Model correlates spatial explosion overpressure with sparsely-observed overpressures. • Uncertainty information ensures reliable guidance for emergency decision-makings. [ABSTRACT FROM AUTHOR]

The purpose of structural health monitoring (SHM) is to detect damage as early as possible. To this end, damage-sensitive features (DSFs) must be evaluated to achieve the objectives. Researchers have developed numerous features. However, some gaps remain in the literature for feature selection; thus, conducting research that collects, evaluates, and suggests suitable DSFs are deemed essential. Consequently, this article seeks to identify effective DSFs and damage diagnosis recommendations. Seven categories are examined for output-only DSFs: 1) statistical features, 2) spectral function features, 3) modal property-based features, 4) entropy-based features, 5) transmissibility function (TF), 6) time series models, and 7) vibration parameter features. The sensitivity of DSFs to noise is also investigated. Three types of offshore platforms subjected to ambient loads are modeled in SAP2000. For each model, nine damage scenarios with three types of damage (cross-section area, moment of inertia, and pinned connection) are considered. The results of this study include a comparison of the performance of categories and features, efficient features for identifying the damage occurrence, and efficient features for locating the damage in noise-free and noisy conditions. Finally, suggestions are made for effective damage diagnosis. • This research covers a significant gap in the SHM literature, particularly for offshore platforms. • A comprehensive analysis of seven categories of output-only damage-sensitive features (DSFs) for damage detection is presented. • Three types of damage are considered: reduction of the cross-section area, the moment of inertia, pinned connection with severity ranging from 5% to 50%, and ambient loads such as waves, currents, and winds. • Suggestions are made concerning sensitive and efficient DSFs for damage detection. In addition, the noise sensitivity of various categories and features for noise conditions is investigated. • Several recommendations and observations on damage diagnosis are presented. [ABSTRACT FROM AUTHOR]

Among offshore platform structures, multi-planar tubular joints are usually in the most dangerous positions and generate fatigue cracks the earliest. In this study, DX-joints were regarded as the research object, and finite element method was adopted to conduct systematic research on the fatigue properties of multi-planar tubular joint welds. Axial, in-plane bending moment, and out-of-plane bending moment loads were applied to explore the stress distribution along the weld path and the hotspot location under different load conditions. Results indicated that the hotspot stress (HSS) location of DX-joints changed with the variation in the combined stress ratio. Through HSS analysis, cracks were prefabricated at the hotspot location of DX-joints to analyze the change rule of the stress intensity factor (SIF). The influence of different loads, crack lengths, and crack depths on SIF was studied to estimate the growth trend of the weld crack and its dominance. The findings can provide theoretical guidance for fatigue damage and safety assessment of offshore platforms. [ABSTRACT FROM AUTHOR]

Cointegration has been used to distinguish the changes in dynamic features of a structure caused by environmental variations from those related to structural damage. This paper describes the development of a novel low-rank filter to suppress the noise in damage-sensitive features and enhance the identifiability of cointegration. It has been confirmed that cointegration is highly dependent on the presence of a vector error-correction model composed of a rank-deficient long-run impact matrix Π. Therefore, the low-rank filter employs a low-rank matrix pencil A + B K C to reconstruct Π iteratively, where A is the noise-free counterpart of Π , and the matrix product BKC accounts for the influence of noise. By minimizing the Frobenius norm of the gain matrix K , the random noise in the damage-sensitive feature series can be suppressed while the cointegration relationship among the damage-sensitive features can be recovered. Comparison between the low-rank filter and two widely used denoising methods, i.e., wavelet and empirical mode decomposition, is performed with the numerical model of an offshore platform and an experimental lattice structure. Results indicate that the low-rank filter is more compatible with cointegration for simultaneously suppressing noise and revealing the damage state of the structures in the presence of environmental variations. • A low-rank filter is proposed to suppress the noise in damage-sensitive features. • A time series analysis method is proposed for damage detection under varying environmental conditions. • The low-rank filter is more compatible with cointegration than wavelet and EMD. • An experimental lattice structure confirms the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper the control problem for an offshore steel jacket platform subject to nonlinear wave-induced force is investigated by introducing several new types of adaptive sliding mode controllers. Three control schemes are presented to reduce the oscillation amplitudes of the offshore platform. The first scheme is named an adaptive output feedback integral sliding mode controller, which has a better performance in comparison with an integral sliding mode controller. By introducing an intentional time delay into the control channel, an adaptive output feedback integral sliding mode controller is proposed as the second scheme. This controller is called a delayed adaptive output feedback integral sliding mode controller. It shows a good performance in reduction of the internal oscillations and control force. In the third scheme, a combination of current states and delayed states is used in the sliding surface and control law. This control scheme is named a combinational delayed adaptive output feedback integral sliding mode controller. One advantage of this scheme is that it provides an appropriate response by increasing the time delay. According to the simulation results, the proposed control schemes can effectively improve the control performance of the offshore platform in comparison with several existing control schemes. [ABSTRACT FROM AUTHOR]

The chloride penetration in three different exposure zones (Atmospheric, Splash and Tidal) of an offshore concrete platform in the year 2000 and 2005 was analyzed. Chlorides profiles for different orientations of the analyzed structure were also obtained. The apparent diffusion coefficients and surface chloride contents of concrete specimens were determined by curve fitting of chloride profiles in chloride penetration models based in diffusion. Increase in the chlorides ingress with exposure time was verified and microclimatic factors such as exposure to wind and wetting and drying cycles were the main responsible for the behavior of obtained chloride profiles. [ABSTRACT FROM AUTHOR]

The present paper validates a recently developed cross model cross mode (CMCM) model updating method for an offshore platform structure by using experimental data. First, the CMCM model updating method, where a modal expansion technique is used to overcome the spatial incompleteness problem, is briefly summarized. One particularly novel development is that a simplified added-mass model of the surrounding water is proposed, and the updating coefficients are directly incorporated into the CMCM procedure. Next, a small-scale offshore platform is fabricated. Model tests are experimentally conducted for four cases, including two cases in air with and without deck mass and two cases in water under hammer and wave excitation. Finally, the first three orders of modal parameters are identified. The CMCM method in combination with the modal expansion technique is used to update the structural models. The results demonstrate that the present method is effective for the model updating of offshore platform structures with a minimal amount of lower-order, spatially incomplete experimental modal data. [ABSTRACT FROM AUTHOR]

The use of cathodic protection (CP) is a widely used practice to mitigate the corrosion of metals. In certain circumstances, stray-current induced corrosion can occur on a structure when it interacts with the CP system of another nearby structure. Due to the locality of the phenomenon, stray-current induced corrosion is one of the most severe types of corrosion. The boundary element method (BEM) is ideal for solving CP problems. In the present work, two accelerated BEM formulations are presented to treat direct current interference problems. The first formulation is more efficient in solving small and medium scale problems, while the second one is more suitable for large scale problems. Furthermore, the stray current induced corrosion in an offshore platform due to its interaction with a nearby moored oil tanker is studied utilizing the above methodologies. The obtained numerical results are extensively discussed, and interesting conclusions are outlined. • The ACA/BEM methodology is extended for the first time for solving large scale DC interference problems. • A new incremental methodology for solving DC interference problems is proposed. • Solution of a large-scale DC interference problem in an offshore platform due to a nearby oil tanker, using two different numerical formulations. [ABSTRACT FROM AUTHOR]

This paper is concerned with discrete feedforward and feedback optimal tracking control schemes for an offshore steel jacket platform subject to irregular wave force. By discretizing a dynamic model of the offshore steel jacket platform system, a discrete feedforward and feedback optimal tracking controller is developed first to attenuate the wave-induced vibration of the offshore platform. Then, for the case of the offshore platform with control delays, a discrete feedforward and feedback optimal tracking controller with memory is presented. The controllers can be designed by solving an algebraic Riccati equation and a Stein equation, respectively. It is found through simulation results that compared with the classic state feedback optimal tracking control schemes, the proposed control schemes are more efficient in attenuating the vibration of the offshore platform. In addition, compared with the feedforward and feedback optimal control schemes, the proposed control schemes require less control cost. [ABSTRACT FROM AUTHOR]

The layout of gas detector is an important factor affecting whether hazardous gas can be detected successfully. However, existing standards only put forward general requirements, and the practical application effect is not satisfying. In this paper, three p-median optimization models with different objectives have been proposed, including the minimal cumulative detection time model (MCDT), the minimal cumulative leakage concentration model (MCLC), and the minimal cumulative individual risk model (MCIR). To achieve the balance of computation cost and optimization accuracy, the complete accident scenario set (CASS) has been filtered according to the cumulative probability of all scenarios and further more reduced by the K-means cluster analysis. Since some small leakage which could not reach lower explosion limit (LEL) results in limited risk, a scenario screening has been carried out to take out these scenarios. The gas detector layout optimization of an offshore platform has been carried out as a case study. After that, the results have been contrasted, which demonstrates that these models can effectively improve the detection efficiency and each has its own advantages. MCDT model can provide the fastest detection speed which means it suites the situations that require more time to conduct emergency response and evacuation. MCLC model pays more attention to the overall risk of the region. On the other hand, considering the individual risk as the primary focus, MCIR model is more suitable for toxic gas leakage and poisoning situations. • Build a complete accident scenario set (CASS) which contains all potential accident scenarios. • Reduce the computation cost through cumulative probability screening and K-means cluster analysis. • An offshore platform is adopted as a case study. The leakage consequences are simulated by Fluent software. • Lower explosion limit (LEL) screening is adopted to retain the scenarios which has higher risk potential. • Three SP layout optimization models with different objectives are proposed and compared. [ABSTRACT FROM AUTHOR]

The advances observed in the offshore-renewable industry include the recent development of a deep draft paired column semisubmersible platform developed for application on dry trees in Gulf of Mexico (GoM). These developments led to the recent innovation of the Paired Column Semisubmersible by Jun Zou of Houston Offshore Engineering. This paper presents a detailed investigation on the mooring line analysis for two different configurations on the hull of a Paired Column Semisubmersible (PCSemi). The numerical research of the PCSemi platform coupled with mooring lines was conducted, and the model was validated. Two different mooring configurations were investigated: Chain-Polyester-Chain (CPC) and Polyester-Polyester (PP) configurations, with dynamic coupling in frequency domain (FD) and time domain (TD) using ANSYS AQWA and Orcaflex. A comparative study of the mooring lines is also investigated in 2,438 m water depth at GoM, using 16 mooring lines with catenary mooring design. Results of this study gives the natural period of floating PCSemi's heave motion ranged from 21s to 22s. Also, the effect of a damaged mooring line increased the tension in other mooring lines. Lastly, the CPC configuration has a smaller amplitude for wave-frequency platform motions compared to the PP mooring configuration from the depicted PCSemi global performance. [Display omitted] • Mooring design of a paired-column semi-submersible (PCSemi) was investigated under catenary designs. • Two configurations were investigated: Chain-Polyester-Chain (CPC) and Polyester-Polyester (PP) configurations. • Modelling technique adopted for the mooring analysis is well presented. • Mooring lines attached to the fairleads of the PCSemi are presented for different design configurations. • Hydrodynamic loading effects on the PCSemi were conducted for low frequency and wave frequency motions. [ABSTRACT FROM AUTHOR]

When fire occurs in an offshore platform, evacuation plays a vital role in safeguarding the evacuees' lives. How to efficiently evacuate to minimize the loss of life is a dynamic problem, requiring a continuing research effort with changing technologies. In this research, a dynamic optimisation model is proposed to determine the optimized evacuation route in the fire scenarios of offshore platforms. Firstly, the road network model of an offshore platform is built in a Geographic Information System (GIS) environment based on the data from a real drilling platform. Secondly, drilling platform fires are simulated using Fire Dynamics Simulation (FDS), and then the fire simulation data is input into the proposed road network model. Thirdly, the traditional Ant Colony Optimisation (ACO) Algorithm is improved by considering the influence of fire on evacuation to study the impact of high temperature, smoke and toxic gases on evacuation. Next, the improved route optimisation algorithm and a road network model of the offshore platform are integrated to formulate a dynamic route optimisation model for evacuation in fire scenarios. Finally, a case study is conducted to demonstrate the model on a drilling platform of Nan Hai in China. The results reveal that the equipment area around the fire source on the lower deck is mostly affected by the smoke. It is validated that the proposed model can be used to optimize the evacuation route to guide evacuees avoid the hazardous area according to the dynamic spread of smoke. This study can provide fast real-time guidance for the trapped evacuees during the evacuation process on offshore platforms by considering the influence of fire on evacuation. • The road network model of an offshore platform is built in a GIS environment. • Drilling platform fires are simulated by FDS, and then the fire data is input into the proposed road network model. • The traditional Ant Colony Algorithm is improved by considering the influence of fire on evacuation. • The improved route optimisation algorithm and the road network model are integrated to propose the dynamic route optimisation model for evacuation in the fire scenarios of offshore platforms. • The scientific novelty is that the proposed dynamic route optimisation model can visualize the real time impact of dynamic fires on evacuation route and optimize the evacuation route. [ABSTRACT FROM AUTHOR]

Abstract: In the offshore industry there are two possible materials for the construction of the hull of any structure: steel and concrete. Steel is being widely used in the shipbuilding industry for merchant ships, warships, etc. Materials such as aluminium, glass reinforced plastic (GRP) or timber are also used in small units with lengths lower than 100m and with less adverse conditions than in the offshore industry. Nevertheless, some ships/barges have been built of concrete in the past, but these have been rather isolated cases and have not changed the industry practice. During the First and Second World War concrete was used due to the scarcity of other materials, so the series of barges by Alfred A. Yee were a rare exception. Other floating structures were also made in concrete, but they are almost anecdotal. However, the behaviour of these concrete structures, especially in terms of maintenance, has been excellent. Therefore, the fact that concrete has not had an adequate reception so far in shipbuilding does not mean that it will not be the material best suited to the offshore industry in the future. The extra displacement and associated fuel costs in concrete ships have been found to be prohibitive in the past. However the loss of mobility in a concrete hull compared to a steel hull can be perfectly offset by the advantages offered by concrete, as the shipping and offshore industry now have very different priorities. One of the main differences in these priorities is the importance of maintenance and resistance to fatigue, precisely the areas where concrete performs the better. Ships can easily be dry-docked for maintenance and repair, while in the offshore platforms these works have to be done in situ, so maintenance and fatigue are crucial to them. Besides these aspects, concrete has other advantages, according to a number of findings in several studies. This supports the fact that in recent years concrete offshore units have been built proving that in certain cases the benefits of steel are inferior to those of concrete. Concrete gravity base platforms type Condeep have been building since the first unit became operational in 1976, together with a few floating platforms, that have geometry similar to those made of steel (barges, semi-submersibles and TLP type platforms). Offshore LNG terminals and offshore industrial plants utilise emerging concepts in concrete that are lasting for years. The life of these barges can be designed for up to 200 years, such as the floating Nkossa barge, so they can be a good alternative to the construction of these facilities on land, thus avoiding landfills on the coast that degrade the already punished coastline of industrialized countries. The challenge is precisely to optimize their capital costs to compete for an offshore installation against a shore facility. The environment will undoubtedly benefit from this great challenge that lies ahead in the XXI century. [Copyright &y& Elsevier]

To accurately predict the crack growth trend of marine structures, this paper proposes a fatigue crack growth prediction method for offshore platforms based on digital twin. First, a digital twin model for offshore platforms is established, and the key technical procedures required for each part of the model are given. Subsequently, to implement consistency maintenance between the virtual model and the physical entity during the digital twin usage, a finite element surrogate model approach based on Gaussian process is performed, which integrates with the crack growth consistency maintenance strategy using dynamic Bayesian network. Finally, according to service condition characteristics of the offshore platform, a crack growth experiment under mixed-mode multi-step loading is designed to verify the effectiveness of the proposed method. The results show that the method not only reduces the influence of uncertain factors on crack growth prediction under complex loads, but also achieves accurate of crack growth through dynamic tracking. • A digital twin five-dimensional model for offshore platform is proposed. • Summarized the key technical methods for building digital twin model. • A fatigue crack growth prediction method based on digital twin is proposed. • A fatigue crack growth experiment under mixed-mode multi-step loading was designed according to the marine environment. • The proposed method can achieve dynamic following and accurate prediction of fatigue crack growth. [ABSTRACT FROM AUTHOR]

Lectotype optimization of offshore platforms is of particular importance in the concept design process. Lectotype optimization involves multiple objectives with uncertainty and so is a problem of multiple attribute decision making. To date, there have been few published works on this topic in the context of offshore engineering. This paper develops a framework and methodology for evaluation of offshore platform alternatives, where a fuzzy optimum model is proposed to integrate the influence of each objective in the criteria set, and a new weight-assessing method is developed to mimic the decision maker’s experience and preference based on complementary pairwise comparisons. A case study shows that the new framework and methodology is scientific, reasonable and easy to use in practice. [Copyright &y& Elsevier]

Multi-purpose offshore structures are very complex systems to be designed as many different requirements have to be taken into account simultaneously. Experimental tests on scaled models can be very useful to verify structural behavior and to validate numerical models. The definition of the scale can play a key role in performing tests as high scales, closer to full-scale, are generally related to more reliable results. The present paper concerns the design of a wind turbine model for a large-scale model of a Multi-purpose offshore Platform developed within the EU project H2020 Blue Growth Farm. This project aims at developing an offshore farm, based on a modular floating structure that integrates wave energy converters and a wind turbine with aquaculture. The scale model of the complete structure will be deployed at the Natural Ocean Engineering Laboratory (NOEL). The paper will focus on the strategies adopted to scale 1:15 the DTU 10 MW wind turbine in order to represent both the main aeroelastic features and all the functionalities of a real machine. The complete design of the machine and its control will be also provided. • The present work was developed within the EU H2020 project 'The Blue Growth Farm'. • The aim of the project is the design of a multi-purpose platform for offshore applications, equipped with a wind turbine. • A large outdoor scaled model of a wind turbine is completely designed. • Typical scaling procedure were adopted to obtain an aeroelastic model for a natural laboratory. • The outdoor scaled model was verified from structural and mechatronic point of view. • Control strategies for the outdoor scaled model were provided. [ABSTRACT FROM AUTHOR]

Motivated by soial and environmental reasons, water scarcity has become a global top agenda item. Egypt is one of the countries suffering from an acute shortage of freshwater. A promising novel and efficient solution to overcome Egypt's freshwater shortage, especially in remote coastal areas far from the national grid of freshwater and electricity, is a mobile floating desalination plant (FDP) powered by offshore renewable energy. The proposed new FDP concept powered by an offshore wind turbine needs a special floating platform to provide enough buoyancy to support the weight of the desalination plant and to restrain the six degrees of freedom motions within an acceptable operational limit for a wind turbine. Based on hydrodynamics, the main objective of this study is to select the suitable offshore platform that can meet the novel FDP concept operation's requirements at a specific deployment location in Egypt. Determining the safe natural frequencies zone necessitates taking into account the new FDP concept operation constraints and the Egyptian environmental loads to select platform far from the dynamic amplifications responses in the structure. Numerical modelling results show that the cylindrical platform with a heave plate configuration demonstrated the best dynamic and static performance for Egypt. • A novel mobile Floating Desalination Plant (FDP) is proposed for Egypt. • FPD is powered by offshore renewable energy. • The most suitable offshore platform is selected by performing numerical analysis. • The cylindrical platform with heave plate configuration demonstrated the best performance. [ABSTRACT FROM AUTHOR]

A neural network-based fuzzy controller is proposed to attenuate the irregular wave-induced vibration of a steel-jacket offshore platform. Firstly, the offshore platform is modeled as a system with time-varying control delay under random wave forces. Secondly, disturbance rejection measures are taken in designing an optimal controller containing delayed states. Thirdly, neural networks are adopted to observe and restore the controlled system, in order to learn the delayed control law using instant state. Finally, fuzzy models are constructed for reducing the complexity in data collecting and neural network training. Trained with sample data from fuzzy models, the neuro-fuzzy observation system is able to reconstruct the control system, and the generalized neural network-based controller works efficiently in different delayed cases. It achieves better vibration-attenuating performance under uncertain control delay and random waves, when compared to existed optimal control laws and fuzzy controllers without neural networks. The main contributions of this paper are: 1) obtaining a neural network-based observer in state approximation; 2) designing a neural network-based controller based on fuzzy rules to cope with random control delay. • We design neural network observers to appropriate the system states containing uncertainty. • We propose fuzzy rules in model approximation to deal with time-varying control delay. • We develop observer-based controllers, using the neuro-fuzzy observation system to reconstruct the control system by extracting neural networks out of the designed controllers [ABSTRACT FROM AUTHOR]

For the vibration of long-served offshore platforms induced by working equipment, it is very difficult to determine the relevant parameters such as structural stiffness, mass and exciting loads accurately. In order to determine the parameters reasonably, a comprehensive vibration testing was carried out to learn the general vibrating features on the offshore platform by a total of 51 measured points distributed on different decks of a 15-year platform. The measurement showed that the induced vibration covers multiple modes with a range of frequencies because of the complexity of the platform structure. Therefore we introduced average amplitude of vibrating displacement at each measurement point to define its vibrating strength. With the measured results of the vibration, a finite element model of the platform with explicit solution was set up to simulate the vibration of the platform. The natural frequencies and average amplitudes at different locations were set as the target values to determine the unknown mass and exciting load in an updating procedure. The results of the modified model have a good agreement with the target values, which indicated that the modified model is reliable and the updating method for determining unknown parameters in a complex structure is feasible. • Carry out comprehensive in-situ measurementand simulation of vibration response on along-served offshore platform. • Determine the vibration source of a complicatedstructure in a complex environment based onin-situ vibration response. • Propose a new updating method for FE model toderive the unknown structural parameters and the excited load for the long-serviced offshoreplatform. [ABSTRACT FROM AUTHOR]

The study of evacuation on offshore platforms under fire is significant but has received little attention by previous researchers. The evacuation process from offshore platforms under three distinct visibilities (>10 m, 1 m–10 m, <1 m) is investigated by a group of experiments and questionnaires with 120 participants. The group evacuation activities of the participants regarding the evacuation time, movement speed, typical behavior and route choice were recorded and studied by 48 cameras and wristbands with Bluetooth positioning function. We ignited smoke bombs often used in the fire drill to generate the smoke, which had a little irritating smell but is safe for people. We investigated the speed in running mode and walking fast mode, and the speed of participants with walking fast without smoke we obtained fits well with the data that IMO recommend. In addition, we found the speed of participants does not always decrease in the smoke environment, sometimes it increases when people are well aware of the surroundings. Finally, we study the relationship between personnel characteristics and evacuation behavior with the help of hypothesis testing. The study will be helpful to the guidelines of IMO to be revised in the future and develop efficient evacuation strategy to guide the evacuation under fire in offshore platforms. • A full-scale evacuation experiment was carried out in a real platform in winter in China. • Smoke evacuation performance of the platform with three different visibilities was assessed by experiments and questionnaires. • The relationship between personnel characteristics and evacuation behavior is studied with quantitative analysis. [ABSTRACT FROM AUTHOR]

Increasing water demand in remote coastal areas in Egypt has shifted attention to the role of floating desalination plants to alleviate water shortages. A novel mobile floating desalination plant is proposed for Ras Ghareb city in Egypt. The compatibility between floater natural periods and the energy excitation range of waves in deployment area can lead to resonance responses. Therefore, understanding the motions behaviour among waves of such floaters at a particular location is important for its safety, performance and operation. The goal of the present study is to investigate the suitability of proposed concept for Egyptian environment conditions by characterising the behaviour of the plant motion responses during its entire deployment conditions. Based on full scale design of the proposed plant, experimental study over a range of wave heights and frequencies was performed in the present study using a 1:100 scale model test. In order to identify the plant natural frequency and damping ratio, free decay and swinging tests were performed for different load conditions. Different wave heights were tested during the experiments in order to investigate the effect of wave height on the heave and pitch responses at plant natural frequencies. The experimental test results were compared with numerical results from frequency domain program HydroD implemented in Sesam DNV GL software package. Results show that heave and pitch motion responses give the closest agreement between the measurements and numerical predictions over the whole range of wave periods except the peak spike. The proposed cylindrical FDP is compared against a conventional ship FPSO concept widely used for offshore freshwater production and it was concluded that new cylindrical FDP shows better motion responses compared to conventional ship FPSO concept in same wave bands in Egypt. • A novel mobile floating desalination plant is proposed for Egypt. • Experimental study over a range of wave heights and frequencies was performed. • Free decay and swinging tests were performed for different load conditions. • The effect of wave height on the heave and pitch responses at plant natural frequencies was investigated. [ABSTRACT FROM AUTHOR]

Blowout is a catastrophic accident in offshore drilling operations, and it poses a serious threat to the operational safety of an offshore platform. This paper uses a computational fluid dynamics (CFD) model to simulate an offshore platform blowout accident and to assess its impact on the assets and personnel. It integrates the dispersion of flammable gas with the subsequent deflagration due to the accidental ignition. The dispersion behavior of blowout gas with wind is predicted and the hazardous area generated on an offshore platform is assessed. Also, the effect of well productivity on the blowout gas dispersion is examined. Subsequently, the deflagration scenario due to ignition of flammable gas is simulated to predict the deflagration loads including overpressure, high temperature and heat radiation. Eventually, the impact of blowout gas deflagration on offshore platform and personnel is assessed. The hazardous area generated by blowout gas dispersion is mainly distributed on the drill floor. The increase of well productivity can cause an increase of the hazardous area. The minimum radius to ensure the safety under deflagration overpressure is 30.63 m. The present work could help in conducting a prior risk assessment and tomake an emergency response plan. • A methodology to more accurately assess offshore platform blowout is proposed. • Blowout gas dispersion with wind is integrated with the subsequent deflagration. • Hazardous area on offshore platform due to blowout gas dispersion is predicted. • Impact of blowout gas deflagration on assets and personnel is assessed. [ABSTRACT FROM AUTHOR]

In the paper, we study the problem of vibration control for offshore platform in nonideal network environment under wave and current forces based on the modified transformation. We consider the wave and current synchronously and give a dynamical system for the outside loads. The problem of time delay, packet dropouts and disordering due to nonideal network are taken into account. In the networked control model, two buffers output the received packets according to time stamps and upper bound of time delay. Based on a transformation, we reduce the time delay system into an equivalent delay-free system. Taking the nonideal network communication conditions into account, we design a modified transformation based on the past time data, wave and current loads, and received packets through network at current time. The networked controller is presented to depress the vibration of structure in nonideal network communication environment based on the modified transformation. An algorithm is given to simplify the computation of control law by recurrence. The system stability under presented networked controller is analyzed based on Lyapunov functional. Through the simulation results and comparison with other networked controllers, we can see that the presented controller can reduce the oscillation of offshore platform effectively. • An external system of wave and current forces is constructed that has wider applications compared with wave force only. • Present a modified system transformation that takes nonideal network conditions into account. • Introduce the current output of buffer through network and the past time control and outloads into networked controller. An approach for updating controller is provided to reduce the computation time. [ABSTRACT FROM AUTHOR]

In offshore platforms, effective gas detection system is an essential layer of protection for preventing potential gas release accident from turning to fire and explosion disasters. However, according to statistics the actual efficiency of gas detection systems is still unsatisfactory. In this work, a stochastic programming (SP) approach is proposed to arrange gas detectors in optimal places. Combined with meteorological data and the hydrocarbon releases (HCR) database, the equipment leakage scenarios are envisaged. The computational fluid dynamics (CFD) commercial code Ansys-Fluent is used to simulate selected scenarios and predict the consequences. With the objective of minimizing the cumulative risk of gas leakage scenarios, a stochastic mixed-integer linear programming formulation based on p-median value theorem is proposed. Then particle swarm optimization (PSO) algorithm is used to solve the optimization model. The gas detector placement optimization on an oil drilling production platform (DPP) is also carried out as a case example. This methodology can be used in the design phase of offshore platform and can hopefully enhance the performance of the gas detection system. • A stochastic programming approach is proposed for the optimization of gas detectors' placement in offshore platform. •An effective technique combining the offshore hydrocarbon releases database is provided to scientifically identify potential leakage scenarios and improve risk characterization. •The complete accident scenario set (CASS) is constructed by considering the leakage sources and wind fields to enhance the performance of the gas detection system. •This methodology can be used in the design phase of offshore platform, giving the high efficiency detector layout scheme on the basis of satisfying the standards and achieving optimal risk control effect of the gas detection system. [ABSTRACT FROM AUTHOR]