Risk Analysis And Simulation Study On The PSV Under The Action Of Dropped Objects

Dropped objects from offshore cranes are of great risks to offshore platforms,oil and gas equipment,supply ships,etc.In case of serious consequences of Dropped objects accident,it will lead to ship damage,oil and gas equipment damage and leakage,even fire and explosion,resulting in huge economic losses and casualties.Platform supply vessel(PSV)is an important means of transportation for the development of marine resources,and also an important transportation guarantee for marine production.With the implementation of a new round of marine fuel oil emission standards,the number of new PSV ships powered by clean fuels such as LNG has increased significantly,and the safety of PSV under the risk of dropped objects cannot be ignored.The environment of offshore operation is complex,and many factors affect the dropped objects,which have great randomness and uncertainty.The existing statistical data for offshore dropped objects is less,and the historical data is lack of timeliness,which is difficult to meet the requirements of PSV falling object risk analysis.The traditional qualitative risk analysis has great limitations,and the quantitative analysis of dropped object risk needs further study.The traditional qualitative risk analysis has great limitations,which need to be further quantified.In this paper,the finite element model of the PSV deck impacted by dropped objects is established by the large-scale finite element analysis software ANSYS/LS-DYNA.The dynamic response process of dropped riser impacting PSV deck under the influence of different impact angles,falling height,weight,and other parameters is simulated,and the falling object collision damage database is established.Then,a BP(backpropagation neural network model for the impact damage prediction of dropped objects is established based on the simulation experiment data.Considering the defects and applicability of the traditional BP network model,the particle swarm optimization(PSO)algorithm is adopted to optimize the BP neural network model and improve the accuracy of damage prediction.Impact damage analysis is the premise of all impact consequence assessment,and the risk level is usually determined by the failure probability of structure.To evaluate the impact damage risk of PSV falling objects effectively,the Monte Carlo simulation(MCS)Matlab program is compiled to complete the random sampling of the impact scene of dropped objects.Combined with the BP-PSO damage prediction model,a PSV impact damage risk analysis method(MCS-BP-PSO)under the action of dropped objects is proposed.Finally,the failure probability of dropped object collision is obtained and the risk level is determined.The risk analysis of dropped objects of PSV provides a reference for the safety management and design of new PSV ships powered by clean fuels such as LNG.It can reduce the potential safety hazards to a large extent and ensure the safety and smooth development of offshore production.