# Accident Risk Analysis of Gas Tankers in Maritime Transport Using an Integrated Fuzzy Approach
## 1 Introduction  
Gas Carrier Tankers (GCTs), which play a critical role in the global energy supply chain as energy demand increases, are specially designed maritime vessels. They ensure the safe and efficient transport of gas products such as Liquefied Natural Gas (LNG) and Liquefied Petroleum Gas (LPG) under low temperature or low-pressure conditions, offering significant advantages in terms of efficiency and energy density in global energy logistics. The International Maritime Organization (IMO) plays a central role in formulating and enforcing international standards for the maritime transport of LNG and LPG. Among these, the International Gas Carrier Code (IGC Code) is a critical regulatory framework that prescribes detailed safety and design criteria for ships used in the transport of liquefied gases [1]. However, the inherently hazardous nature of these substances requires stringent operational standards and continuous risk monitoring [2]. By their very nature, gas tanker operations present several safety and environmental hazards, including fire and explosion, structural failure, and toxic gas emissions [3]. The complexity of these operations requiresa multidisciplinary safety assessment that considers not only technological and procedural factors but also human and environmental elements [1; 4]. Considering the pivotal function of gas carrier operations, it is imperative to employ state-of-the-art methodologies for managing associated risks. While traditional safety protocols remain important, they frequently fail to consider the complex and evolving nature of maritime operations [5]. Consequently, there is an increasing necessity for data-driven risk evaluation techniques, including hybrid models, to assess and mitigate potential hazards more effectively [6]. Given the increasing intricacy of operations involving gas carriers and the limitations of conventional safety measures, there is a compelling need to adopt more advanced risk management models [1]. These models offer a more profound understanding of how diverse risks interact, thereby enabling enhanced anticipation and mitigation of emergent threats. Moreover, the integration of such techniques has been demonstrated to facilitate the identification of both immediate dangers and underlying systemic issues that have the potential to result in major accidents [7]. A forward-thinking approach is imperative for the protection of personnel and vessels, as well as for the safeguarding of the environment. This is particularly crucial in the context of the ongoing increase in global demand for energy [5]. It is vital to acknowledge the pressing necessity for a comprehensive risk management framework, as evidenced by several high-profile accidents involving GCTs. Notable incidents include the explosion of the M/T SYN ZANIA at PETKIM Terminal and the Kerch Strait incident involving the Maestro and Candy vessels. These incidents, frequently precipitated by technical malfunctions such as hose failures or ignition source malfunctions, underscore the vulnerability of gas tanker operations to both operational faults and systemic oversights [8]. Moreover, the risk landscape is further exacerbated by factors such as corrosion-induced degradation, inadequate safety systems, and failure to comply with international maritime safety protocols [4]. The consequences of such accidents are not limited to economic loss and human casualties but also encompass significant environmental impacts [9; 10]. The uncontrolled release of liquefied gases into the atmosphere can result in significant environmental concerns, including atmospheric pollution, and pose a threat to the health of port personnel and nearby populations [11; 12]. Furthermore, in confined and poorly ventilated areas, the flammable and toxic nature of these gases significantly increases the risk of catastrophic events, such as Boiling Liquid Expanding Vapor Explosions (BLEVE) and Unconfined Vapor Cloud Explosions (UVCE) [1; 13; 14].