The shipping industry is an essential business factor of global trade, supporting the cargo movement in maritime shipping that is driving the world's economy. Therefore, sustainability and risk management need to improve the critical business approach toward sustainable business. This research aims to develop a sustainability risk model for shipping business management in Thailand. Structural equation modelling (SEM) is applied to create this model using the PLS method. The relationship and model findings are the sustainability risk for shipping management, three factors including Environmental, Societal, and Technological factors, a total of 10 indicators of sustainability risk that need to improve in 10 years, and the relationship of factors and indicators to confirm the shipping business sustainability. This model presents guideline concepts for the operation and implication planning for developing the sustainable shipping business and international standards. To operationalize the proposed framework, the indicators were defined as observable risk items and evaluated through a questionnaire-based assessment of shipping practitioners and managers in Thailand. PLS-SEM was used to examine measurement quality (reliability and validity) and to test the hypothesised effects among Environmental, Societal, and Technological factors. The validated model helps identify high-priority sustainability risks and supports decision-making for mitigation, capability development, and monitoring over the next decade.

Offshore support operations must balance safety and sustainability under highly variable sea conditions. Deterministic motion analyses can underestimate extreme vessel responses, leading to insufficient operational limits and increased environmental impact. We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height, peak period, added mass, and radiation damping are represented as fuzzy numbers. An α-cut decomposition yields interval bounds at each confidence level, and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper “vertex” systems. A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology. The heave response envelopes under calm (nominal α = 1: 0.73 m; full range at α = 0: 0.64–1.64 m) and severe (nominal 1.58 m; range 1.32–2.36 m) sea states reveal potential underestimations of 124 % and 49 %, respectively, when using only nominal values. By selecting an operational α-level (e.g., α* = 0.35 to cap heave ≤ 1.8 m), decision-makers can balance risk tolerance and conservatism. Sensitivity analysis identifies significant wave height as the dominant uncertainty driver. Computational trade-offs and adaptive α-sampling strategies are discussed. This work provides a self-contained, uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization. By embedding fuzzy uncertainty quantification into vessel dynamics, the methodology supports safer, more sustainable marine operations and can be extended to real-time sensor fusion, multi-vessel interactions, and frequency-dependent hydrodynamics.

In this study, an alternative modelling approach for absorbed hydrogen stress corrosion cracking (SCC) is proposed, with hydrogen-enhanced decohesion (HEDE) identified as the key failure mechanism. All analyses have been performed by utilising only ABAQUS standard elements, COH2D4T and CPE4T, already available within the software and without the need to develop external subroutines. The study also tends to highlight the criticality of implementing a correct Traction Separation Law (TSL) curve to simulate the hydrogen diffusion within the specimen and using the concept of dynamic hydrogen penetration by continuously updating the hydrogen concentration boundary conditions as the crack propagates. In conclusion, this study successfully demonstrated that standard software elements (COH2D4T and CPE4T) can effectively model physical problems and crack velocity propagation without custom subroutines. It emphasized that while the specific shape of the Traction-Separation Law (TSL) is less critical, its correct implementation is vital for simulating dynamic hydrogen coverage. Crucially, excluding this dynamic coverage—a common practice—risks significantly underestimating crack propagation speed. Although results incorporating dynamic coverage aligned well with experimental data, minor discrepancies are likely due to unmodeled factors like material property variations, hydrogen trapping, temperature, and granular microstructure, which are proposed for future research.

The global discussion surrounding Functionally Graded Materials (FGMs) highlights their unique and diverse micro-material properties that result from varying two or more materials in a strategic combination profile. These combinations produce distinct physical and chemical characteristics. Changes in these characteristics may occur continuously, referred to as a gradient function, or discontinuously as a stepwise function. The changes can appear within homogeneous or heterogeneous material geometries. The variation in material properties depends on the volume fraction index function. This variation can occur in 1D, 2D, or 3D, either in the thickness or length direction within a material model. The vacuum in the review study on mechanically toughened and thermally resistant Functionally Graded (FG) pipelines prompted the current review study. This study addresses the absence of an appropriate variational function for FG cylindrical pipelines. It proposes a gradation function pattern to improve pipeline structural performance. An appraisal based on relevant FGM literature was conducted to improve the temperature differentials in traditional composite materials and stress-related issues in carbon steel pipelines. The review identifies specific FGM property variations that reduce failures that are possible in conventional materials. Reviewed articles and evaluation procedures followed the 2020 PRISMA guidelines. Literature was obtained from Scopus, Connected Papers, and other reputable sources. The study also discusses potential FG pipelines for gas and green energy transportation. The reviewed literature establishes the context for this research and addresses the gap in 3D FG model variation functions involving multiple materials.

The growing utilization of the ocean as a renewable energy source drives the need for reliable maritime infrastructure. One major challenge for these structures is withstanding impulsive loads from extreme ocean waves, which requires materials with high strength and deformation resistance to maintain structural integrity. Metal Matrix Composite (MMC) is a promising material, yet studies on its behavior under impulsive loading remain limited. This study investigates the ultimate capacity of MMC sandwich structures using the Finite Element Method (FEM) through simulations with an Underwater Shock Loading Simulator (USLS). Validation against the results of He et al. confirms the accuracy of the simulation method. Results indicate that increasing flyer velocity from 135 to 195 m/s raises the maximum displacement from 5.83 mm to 10.7 mm. Increasing face sheet thickness from 0.4 to 1.8 mm reduces deformation from 4.95 to 3.09 mm, while increasing core thickness from 14 to 20 mm decreases deflection from 5.42 to 3.68 mm. Furthermore, the thickness ratio analysis indicates that the 1:10 configuration produces the smallest deformation (4.13 mm) and is more efficient because it provides higher stiffness with lower mass. These findings demonstrate that optimizing core and face sheet thickness significantly enhances structural resistance to deformation. The study concludes that a balanced thickness configuration is key to improving the structural performance of MMC sandwiches, supporting the design of stronger and more sustainable materials for maritime structures in extreme environments.

Interest in understanding the structural behavior of marine floating photovoltaic (FPV) systems has grown significantly over the last decade. Numerical models are the preferred approach for understanding FPV responses under environmental loads, but they require validation. Several methods are commonly used to validate numerical results, such as comparison with analytical, field data, and experimental data. The use of analytical approaches to validate numerical results can sometimes be inaccurate due to the complexity of the problems; nevertheless, field data is commonly restricted and frequently unavailable for numerical model validation. Thus, physical models play a crucial role in validating numerical results. This study focuses on the two-dimensional (2-D) modeling process and sensors development for an FPV system with taut mooring, aiming to investigate wave-structure interaction while considering hydroelastic effects. The model is developed in accordance with the Froude-Cauchy similitude law and is made from composite materials to capture structural stiffness. Structural motions, specifically heave and pitch, are measured using an Inertial Measurement Unit (IMU), while strain gauges measure structural stress and mooring tension. The sensors provide precise measurements for strain and pitch; however, heave, as a result of time-domain integration from acceleration, requires further validation. The motion responses of the model align with reference results.

The rapid transformation of Arctic maritime routes, driven by diminishing sea ice and shifting geopolitical conditions, presents both opportunities and challenges for global shipping. This study develops an integrated optimization framework for sustainable Arctic marine logistics, grounded in Agile Supply Chain Theory (ASCT), to address cost efficiency, environmental sustainability, and operational robustness under climate and policy uncertainty. A Mixed‐Integer Linear Programming (MILP) model was employed to optimize vessel routing across Arctic corridors, incorporating Energy Efficiency Operational Indicator (EEOI) and Carbon Intensity Indicator (CII) metrics directly into the objective function. Scenario analyses tested performance under varying climate conditions and policy constraints. The model was parameterized using vessel operational data from Arctic shipping logs, environmental datasets from ESA CryoSat‐2 and NSIDC, port accessibility records from Arctic port authorities, and economic data from Clarksons and the World Bank, ensuring realistic and replicable inputs for the analysis. Results demonstrate that ASCT‐based optimized routes achieved an average 14.8% reduction in operating costs, 12.3% reduction in CO₂ emissions, and an 11.6% improvement in EEOI, with the majority of voyages improving by at least one CII grade. Robustness analysis showed that optimized routes maintained up to 14.7 percentage points higher feasibility under severe ice scenarios and reduced cost volatility by 20–28% under carbon tax regimes. These findings confirm the value of embedding agility and resilience principles into Arctic shipping, aligning operational efficiency with International Maritime Organization (IMO) decarbonization objectives. The study extends ASCT into extreme maritime contexts, offering a replicable model for sustainable route planning in high‐risk logistics sectors.

Key areas such as marine resource exploration, real-time monitoring of ecological environments, and national defense security systems urgently require reliable underwater information transmission capabilities as a foundation. Underwater acoustic communication (UAC), leveraging its unique advantages as the most effective method for long-range data transfer in aquatic environments, has become an indispensable enabling technology for supporting these core applications. This review systematically examines recent advancements in UAC technology and their critical role in enabling modern marine initiatives. The analysis covers key developments in both non-coherent and coherent communication systems, including single-carrier and multi-carrier modulation schemes such as OFDM. It highlights their respective advantages in terms of robustness and high-data-rate transmission. The significant impact of challenging underwater channel characteristics, notably severe multipath fading, time-varying Doppler shifts, limited bandwidth, and environmental noise, is discussed alongside corresponding mitigation strategies. Furthermore, the integration of machine learning for sophisticated channel estimation, adaptive equalization, and intelligent system optimization is explored as a promising frontier. Emerging technologies like spread-spectrum, full-duplex, and covert UAC are also evaluated for their potential in specialized and high-stakes applications. The paper concludes by identifying persistent challenges, including regulatory constraints, physical-layer security issues, interoperability across platforms, and energy efficiency demands. Finally, it outlines future research directions aimed at developing more intelligent, secure, and efficient next-generation underwater networks.

Offshore logistics operations must continuously balance safety, fuel efficiency, and emissions reduction while navigating under uncertain and highly variable sea states. To address this challenge, we present an α-cut interval framework in which environmental uncertainties, specifically wave height and wind speed, are modeled as fuzzy numbers. Their corresponding α-level intervals are systematically propagated through a discrete vessel dynamics model, focusing on surge and heave responses. This procedure generates families of nested motion envelopes that tighten monotonically with increasing α, thereby producing deterministic yet progressively refined safety bounds without relying on full probabilistic distributions. A case study off the Karnataka coast is used to demonstrate the approach for a 20 km offshore supply voyage. Route planning constrained by α-envelopes ensures adherence to vessel structural and stability limits while enabling optimized transit speed. Comparative evaluation indicates that, relative to standard interval analysis, α-cut propagation substantially reduces over-conservatism, while against Monte Carlo-based envelopes it achieves similar coverage with significantly lower computational effort. Sensitivity analyses further quantify the influence of α-grid resolution, membership-function design, and hydrodynamic coupling coefficients on envelope width, fuel use, and emissions. In the tested scenario, higher α levels allow up to ~15% reduction in worst-case energy consumption and nearly 10% reduction in CO₂ emissions, all while preserving safety margins. Overall, the proposed framework is transparent, computationally efficient, and easily integrable into digital-twin-enabled operational workflows, providing a practical and sustainable decision-support tool for adaptive offshore logistics planning.

This study evaluates the effectiveness of integrating local wisdom with the use of Alat Pemecah, Peredam Ombak, dan Sedimen Traps (APPOSTRAPS) or Breakers, Wave Dampers, and Sediment Traps in empowering coastal communities in Karawang, Indonesia, as a strategic response to climate change, coastal erosion, and sustainable ecotourism development. The research aims to assess the combined impact of APPOSTRAPS technology and the Jaga Alam Melalui Pemberdayaan Masyarakat Pesisir (JAM PASIR) or Protecting Nature Through Coastal Community Empowerment program in reducing coastal abrasion, restoring mangrove ecosystems, and fostering sustainable livelihoods. A mixed methods approach was applied, combining quantitative analysis of coastline changes using Geographic Information System (GIS) with Landsat and Sentinel-2 imagery (2022–2024), field surveys using differential GPS (±2 m accuracy), and qualitative methods including 150 interviews, 18 months of participant observation, and community documentation. Results show a coastline extension of about 400 m (±15 m), increased ecotourism revenue from IDR 11.25 million per month in 2019 to IDR 90 million in 2024, women’s participation rising from 12% to 68%, and livelihood diversification reaching 110% of the target with 98 families involved. APPOSTRAPS, a patented breakwater and sediment trap made from repurposed tires, combined with the JAM PASIR program covering mangrove-based ecotourism, MSMEs for fishermen’s wives, waste management, and the Masyarakat Sadar Lingkungan and Bencana (MASDARLINA) or Environmentally and Disaster Aware Society system, effectively mitigates erosion and supports economic growth. The study concludes that integrating indigenous knowledge and technology strengthens community resilience and provides a replicable model for sustainable coastal adaptation.