Risk Assessment of Launching Airbags Using Functional Resonance Accident Model

‘Ship Launching Airbags’ can greatly increase the economic benefits of a new gravitational launching operation. Gravitational launching of a new ship with marine airbags takes into account the resistance force of rolling friction. However, a launching operation is a high-risk process, as it involves many risk factors. In this paper, Functional Resonance Accident Model (FRAM) was used systematically to identify potential risks and carry out the risk analysis of the ship launching operation. The human factor, technical factors, and organisational factors were identified based on the common performance conditions of FRAM. Functional performance changes, prevention, and hazard control barriers were evaluated to identify key operations. The results show that the ship launching operation is characterized by high collision, decreasing stability, and the need for the use of airbags

A new resilient risk management model for offshore wind turbine maintenance

The objective of this study is to implement the principles of Resilience Engineering (RE) for the maintenance management of Offshore Wind Turbine (OWT) systems by taking into account human and organizational factors. Resilience concepts are integrated into existing maintenance management elements and a resilient model is developed and applied to OWT in order to manage the maintenance related risks. The four main capabilities proposed by RE, i.e. responding, monitoring, anticipating and learning, are linked to a three level resilience system in order to prevent or mitigate OWT maintenance failures. The paper presents the applicability and effectiveness of RE in preventing accidents/incidents and system failures, and learning activities

Risk Analysis for Offshore Wind Turbines Using Aggregation Operators and VIKOR

In various engineering actions, potential hazards are reduced, calculated, or controlled using a variety of risk analysis methodologies. The FMEA, or Failure Mode and Effects Analysis, is a very efficient strategy that may be used in this situation. When evaluating safety concerns, failure modes\u27 likely causes and consequences are considered. Serious failures in the FMEA are identified using the Risk Priority Number (RPN). The RPN considers the effect of the probability of occurrence, probability of detection and severity by multiplying these three parameters. However, because of the formula\u27s various flaws, it is frequently criticized. In the current work, a hybrid approach using ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and geometric averaging of ordered weights (OWGA) as an aggregation operator is used to assess risk for offshore wind turbines. While the OWGA technique is used to provide weight to risk indices, the VIKOR method is used to assess the relevance of failure modes of offshore wind turbine components. The method\u27s final findings show it solves the issues with the traditional RPN technique and produces more logical outcomes

AN APPLICATION OF SOFT COMPUTING TECHNIQUES TO PREDICT DYNAMIC BEHAVIOUR OF MOORING SYSTEMS

A spread mooring system (SMS) allows a ship or a floating platform to moor the seafloor using multiple mooring lines at a restricted region with a fixed heading in harsh weather. These systems can be used for the operations of ships of different tonnage at different sea depths. The optimal design of these systems is a challenging engineering problem because of the effects of many design parameters and changing environmental conditions. Modern soft computing techniques allow difficult engineering problems to be solved easily and precisely and are becoming more and more popular. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as soft computation techniques have been chosen to estimate the hawser tensions and displacements of a spread mooring system. The attained results show both techniques can give consistent indicators for the modelling of dynamic systems. Although these techniques performed very well, the ANFIS model is relatively superior to the ANN technique, considering the accuracy of hawser tensions and displacements in terms of the relative errors and coefficient of correlation obtained for the ANN and ANFIS

Risk Tabanlı Deniz Ambulansı Tasarımı

Denizde, emniyeti en üst düzeye çıkarmak için risk faktörlerini modellemek ve risk tabanlı tasarım araçlarını kullanmak önemlidir. Emniyeti arttırmak ve müşteri taleplerini karşılamak için etkin risk modelleme teknikleri ve karar verme araçlarının geliştirilmesi ve uygulanması gerekmektedir. Bu çalışmada, mevcut bir deniz ambulans teknesi operasyon riskleri incelenmiş ve mevcut tekne risk tabanlı bir yaklaşımla yeniden tasarlanmıştır. Risk değerlendirmesi ve model tasarımında, Hata Türü ve Etki Analizi (FMEA) kullanılmış ve risk öncelik sayıları (RPNs) hesaplanmıştır. Bu çalışmadan elde edilen sonuçlar, deniz ambulans teknelerinin emniyetini arttırmaya ve potansiyel risklerin önlenmesine veya azaltılmasına katkıda bulunacaktır