Search Results (733)

Cryogenic industries handling liquid hydrogen and helium require rigorous safety verification. However, current standards (ASTM, ASME, ISO) are optimized for LNG at −163 °C and remain inadequate for extreme cryogenic conditions such as −253 °C. As the temperature decreases, materials experience ductile-to-brittle transition, raising the risk of sudden fracture in testing equipment. This study presents a fuzzy-integrated reliability framework that combines fault tree analysis (FTA) and Failure Modes, Effects, and Criticality Analysis (FMECA). The method converts qualitative expert judgments into quantitative risk indices for use in data-scarce conditions. When applied to a cryogenic impact testing apparatus, the framework produced a total failure probability of 1.52 × 10⁻³, about 7.5% lower than the deterministic FTA result (1.64 × 10⁻³). These results confirm the framework’s robustness and its potential use in cryogenic testing and hydrogen systems. Full article

Compared with other fossil energy sources, natural gas is characterized by compressibility, low energy density, high storage costs, and imbalanced usage. Natural gas pipeline supply systems possess unique attributes such as closed transportation and a highly integrated upstream, midstream, and downstream structure. Moreover, pipelines are almost the only economical means of onshore natural gas transportation. Given that the upstream of the pipeline features multi-entity and multi-channel supply including natural gas, coal-to-gas, and LNG vaporized gas, while the downstream presents a competitive landscape with multi-market and multi-user segments (e.g., urban residents, factories, power plants, and vehicles), there is an urgent social demand for non-discriminatory and fair opening of natural gas pipeline network infrastructure to third-party entities. However, after the fair opening of natural gas pipeline networks, the original “point-to-point” transaction model will be replaced by market-driven behaviors, making the verification and allocation of gas transmission capacity a key operational issue. Currently, neither pipeline operators nor government regulatory authorities have issued corresponding rules, regulations, or evaluation plans. To address this, this paper proposes a multi-dimensional quantitative evaluation model based on the Analytic Hierarchy Process (AHP), integrating both commercial and technical indicators. The model comprehensively considers six indicators: pipeline transportation fees, pipeline gas line pack, maximum gas storage capacity, pipeline pressure drop, energy consumption, and user satisfaction and constructs a quantitative evaluation system. Through the consistency check of the judgment matrix (CR = 0.06213 < 0.1), the weights of the respective indicators are determined as follows: 0.2584, 0.2054, 0.1419, 0.1166, 0.1419, and 0.1357. The specific score of each indicator is determined based on the deviation between each evaluation indicator and the theoretical optimal value under different gas volume allocation schemes. Combined with the weight proportion, the total score of each gas volume allocation scheme is finally calculated, thereby obtaining the recommended gas volume allocation scheme. The evaluation model was applied to a practical pipeline project. The evaluation results show that the AHP-based evaluation model can effectively quantify the advantages and disadvantages of different gas volume allocation schemes. Notably, the gas volume allocation scheme under normal operating conditions is not the optimal one; instead, it ranks last according to the scores, with a score 0.7 points lower than that of the optimal scheme. In addition, to facilitate rapid decision-making for gas volume allocation schemes, this paper designs a program using HTML and develops a gas volume allocation evaluation program with JavaScript based on the established model. This self-developed program has the function of automatically generating scheme scores once the proposed gas volume allocation for each station is input, providing a decision support tool for pipeline operators, shippers, and regulatory authorities. The evaluation model provides a theoretical and methodological basis for the dynamic optimization of natural gas pipeline gas volume allocation schemes under the fair opening model. It is expected to, on the one hand, provide a reference for transactions between pipeline network companies and shippers, and on the other hand, offer insights for regulatory authorities to further formulate detailed and fair gas transmission capacity transaction methods. Full article

Liquefied natural gas plays a crucial role in global energy transitions due to its high efficiency and low emissions, especially in long-distance transportation. However, the thermal management of LNG storage tanks remains a significant challenge due to temperature fluctuations, which impact both efficiency and safety. Traditional methods rely on thermodynamic models or computational fluid dynamics simulations but are computationally expensive and time-consuming. This study proposes a hybrid approach that integrates machine learning techniques with CFD data to predict temperature variations inside LNG storage tanks. Several ML models, including Random Forest, XGBoost, and deep learning-based models like CNN and TCN, were tested. Results indicate that CNN and TCN models offer the best performance in predicting temperature changes, showing superior accuracy and computational efficiency. This approach significantly enhances the real-time prediction capability, offering a promising solution for improving LNG tank thermal management, ensuring both operational safety and efficiency. Full article

This study evaluates the thermodynamic performance of the following two CO₂ liquefaction processes for onboard carbon capture and storage (OCCS) on a 174,000 m³ LNG carrier: the Linde–Hampson and vapor compression refrigeration cycles. The cycles were designed based on realistic vessel operating conditions and compared using the specific energy consumption (SEC) as the primary performance indicator, alongside the coefficient of performance (COP). To enable a fair comparison of the two distinct cycles, a complementary COP metric was validated for the open-loop Linde–Hampson cycle by establishing a system-level definition of heat removal. The validity of this metric was confirmed by demonstrating that its optimal point (maximum COP) aligns with that of the primary metric (minimum SEC), ensuring thermodynamic consistency. The analysis reveals that the vapor compression cycle demonstrates superior performance, achieving an 8.35% higher COP and an 11.45% lower SEC than the Linde–Hampson cycle. This work provides a consistent methodology for the comparative assessment of open- and closed-loop liquefaction systems. Full article

Although liquefied natural gas (LNG) is already widely used as a marine fuel, its use on large cruise ships is a relatively new development. By the end of 2024, twenty-four LNG-fuelled cruise ships were in operation, each carrying several thousand passengers and making frequent port calls. These operational characteristics increase the potential risks compared to conventional cargo ships and require a rigorous safety assessment. In this study, the safety of LNG-fuelled cruise ships is assessed using the Formal Safety Assessment (FSA) framework prescribed by the International Maritime Organization (IMO). The assessment includes a hazard identification (HAZID), a risk analysis, an evaluation of risk control options, a cost–benefit analysis and recommendations for decision-making. Given the limited operational data on LNG-fuelled cruise ships, event trees are developed on the basis of LNG tanker incidents, adjusted to reflect passenger-related risks and cruise-specific operating conditions. A statistical overview of marine casualties involving cruise ships and LNG carriers of more than 20,000 GT over the last 35 years provides a further basis for the analysis. To ensure compliance, the study also analyses class requirements and regulatory frameworks, including risk assessments for ship design, bunker operations and emergency preparedness. These assessments, which are carried out at component, ship and process level, remain essential for safety validation and regulatory approval. The results provide a comprehensive framework for assessing LNG safety in the cruise sector by combining existing safety data, regulatory standards and probabilistic risk modelling. Recent work also confirms that event tree modelling identifies critical accident escalation pathways, particularly in scenarios involving passenger evacuation and port operations, which are under-researched in current practice. The results contribute to the wider debate on alternative fuels and support evidence-based decision-making by ship operators, regulators and industry stakeholders. Full article

Conducting a safety simulation assessment of gas release from the vent mast during the design stage holds significant importance for ship design and system operation safety on LNG-powered vessels. Based on a large-scale practical LNG-powered vessel, this paper employs the CFD method to carry out a safety assessment of the natural gas dispersion, and proposes an optimization design method to address the issue where the vent mast height of large-scale LNG-powered vessels fails to meet specifications. The influencing factors of gas dispersion are discussed. The simulation results indicate that the vent mast height, wind direction, and wind velocity significantly affect the gas dispersion behavior. A lower vent mast height results in a greater risk of flammable gas clouds accumulating on the deck surface. Hazards analysis of the 6 m vent mast condition with windless suggests that a cryogenic explosion hazard zone is formed on the deck centered around the mast position, with the maximum gas concentration reaching 30% and the minimum temperature below −55 °C. The gas cloud spreads along the wind direction, and the extension distance is positively correlated with wind speed. With the increase in wind velocity, the height and volume of flammable gas clouds decrease. When the wind speed is 15 m/s, the volume of the flammable gas cloud is less than half of that at 5 m/s and less than one-tenth of that at 0 m/s. Higher wind velocity can notably promote gas diffusion. Full article

Seed dormancy and germination is regulated by internal hormones and exogenous environment cues. Ethylene is one of the hormones that break seed dormancy and induce seed germination. Our previous study showed that N-degron pathway gene, proteolysis6 (PRT6) was involved in dormancy release by ethylene, the defection of which exhibiting ethylene-insensitivity in Arabidopsis thaliana. In the present study, through screening an ethyl methyl sulfonate-mutagenized (EMS) population of prt6−1, we isolated a recessive mutant that acted as a suppressor of prt6 that rescued its insensitivity to ethylene as well as a phenotype of shorter silique length. Further bulk segregant analysis on F2 population identified a premature termination located in the third exon of LONGIFOLIA1 (LNG1), previously reported in the regulation of longitudinal cell elongation. Mutation of LNG1 in prt6−1 background by CRISPR-Cas9 confirmed that LNG1 was epistatic to PRT6 in seed responsiveness to ethylene. Our finding proposed the pleiotropic effect of LNG1 in seed dormancy breakage by ethylene via PRT6, providing novel functional component at the downstream of the coordinated PRT6 and ethylene signaling pathway. Full article

The article addresses the issue of liquefied natural gas (LNG) distribution as a marine fuel, analyzing both ecological and economic aspects in the context of the Baltic Sea basin. The authors emphasize that LNG plays an increasingly significant role in the global energy balance, and its application in maritime transport is crucial for implementing sustainable development policies and advancing the energy transition. From an ecological perspective, LNG offers a substantial reduction in harmful emissions compared with conventional marine fuels such as marine diesel oil (MDO) and heavy fuel oil (HFO). In particular, the use of LNG results in lower emissions of carbon dioxide (CO₂), sulfur oxides (SO_x), nitrogen oxides (NO_x), and particulate matter (PM). The reduction in these pollutants is essential not only for improving air quality in port and coastal areas but also for mitigating global environmental impacts, including climate change. On the economic side, the article focuses on the cost structure of LNG distribution, highlighting that its price dynamics are subject to significant fluctuations. These variations are driven by geopolitical developments, crude oil price volatility, environmental regulations, and the expansion of bunkering infrastructure. From an economic perspective, LNG prices show significant volatility depending on the year and market conditions. Between 2018 and 2023, LNG prices ranged from approximately 450 to 530 USD/ton, at times exceeding the cost of HFO (400–550 USD/ton) but in some years remaining cheaper. In comparison, MDO prices were consistently the highest, increasing over the analyzed period from 600 USD/ton to over 720 USD/ton. This variability results from geopolitical factors, supply and demand dynamics, and environmental regulations, which highlight the strategic importance of LNG as a transitional fuel in shipping. The purpose of this study is to examine the role of LNG as an alternative fuel for shipping in the Baltic Sea, with particular emphasis on the scale of vessel emissions and the key factors influencing its distribution costs. Full article

Climate change has exacerbated the need for transitional shifts within high-impact sectors, notably maritime transport, which facilitates nearly 90% of global trade. In response, the International Maritime Organization (IMO) has implemented stricter environmental regulations under MARPOL Annex VI, which includes, among other things, the designation of Emission Control Areas (ECAs) and Particularly Sensitive Sea Areas (PSSAs). These regulatory instruments have prompted the uptake of new technologies, such as scrubbers, LNG propulsion, and low-sulfur fuels to mitigate emissions in these zones. However, emerging evidence has raised environmental concerns about these solutions which may offset their intended climate benefits. This study investigates the hypothesis that ECAs and PSSAs act as catalysts for maritime environmental advancements through a systematic mapping of 76 peer-reviewed articles. Drawing on data from Scopus and Web of Science, the study analyzes trends in technological advances, publication timelines, geographic research distribution, and the increasing role of decision-support tools for regulatory compliance. Findings show increased academic outputs particularly in China, North America, and Europe, and suggest that achieving effective emissions reduction requires globally harmonized policies, bridging research practice gaps, and targeted financial support to ensure sustainable outcomes throughout the sector. The study suggests that for ECAs and PSSAs to deliver truly sustainable outcomes, global regulation must be supported by empirical performance assessments, environmental safeguards for compliance technologies, and targeted support for developing maritime regions. Full article

Symmetry plays a key role in the study of stress and strain analysis of spherical tanks, as described in detail in the main text. The inherent geometric symmetry of a spherical tank–being uniform in all directions from its center–allows for significant simplification of finite element models. This radial symmetry means that the stress and strain fields under uniform internal pressure are also symmetrical, reducing the computational domain to a small, representative portion of the tank rather than the entire structure. By using these symmetry principles, the study not only ensures the accuracy of its predictions but also achieves a high degree of computational efficiency, making complex engineering problems easier and more accessible. The application of symmetry, therefore, is not just a theoretical concept but a practical tool that underlies the methodology and success of this analysis. This study investigates the mechanical behavior of a spherical tank subjected to internal fluid pressure, utilizing the finite element method (FEM) as a primary analytical tool. Spherical tanks are widely used for the storage of various fluids, including liquefied natural gas (LNG), compressed gases, and water. Their design is critical to ensure structural integrity and safety. This research aims to provide a comprehensive stress and strain analysis of a typical spherical tank, focusing on the hoop and meridian stresses, and their distribution across the tank’s geometry. A 3D finite element model of a spherical tank will be developed using commercial FEA software. The model will incorporate realistic material properties (e.g., steel alloy) and boundary conditions that simulate the support structure and internal fluid pressure. The analysis will consider both linear elastic and potentially non-linear material responses to explore the tank’s behavior under various operational and overpressure scenarios. The primary objectives of this study are as follows: (1) determine the maximum principal stresses and strains within the tank wall, (2) analyze the stress concentration at critical points, such as support connections and nozzle penetrations, and (3) validate the FEM results against classical analytical solutions for thin-walled spherical pressure vessels. The findings will provide valuable insights into the structural performance of these tanks, highlighting potential areas of concern and offering a robust numerical approach for design optimization and safety assessment. This research demonstrates the power and utility of FEM in engineering design, offering a more detailed and accurate analysis than traditional analytical methods. Full article

To enhance the energy efficiency of liquefied natural gas (LNG) terminals, this study developed a full-process dynamic simulation model using Aspen HYSYS (hereinafter referred to as HYSYS) to accurately replicate the time-varying energy consumption characteristics of key processes, including unloading, tank boil-off gas (BOG) management, recondensation, and vaporization for send-out. Through dynamic analysis of the impact of different operating conditions on the energy consumption of critical equipment, methane content and compressor outlet pressure were identified as sensitive factors, and multivariable interaction effects were quantified. Combining the Particle Swarm Optimization (PSO) algorithm to optimize equipment operating parameters and incorporating constraints such as equipment start-stop frequency and flare emissions, process improvements were achieved, including intelligent pre-cooling during unloading, multi-mode vaporization coupling, and model predictive control for storage tanks. Safety response logic under extreme conditions was also enhanced. Field validation results show that the optimized system reduces total energy consumption by 18.5%, with a relative error between simulated and field data of ≤13%. Daily equipment start-stop cycles decreased from five to two times, and flare emissions were reduced from 25 kg/h to 12 kg/h. Within a 95% confidence interval, the total energy consumption prediction fluctuated by ±4.2%, demonstrating good model stability. This study provides reliable technical support for energy-efficient operation of LNG terminals. The proposed multivariable interaction analysis and safety control strategies under extreme conditions further enhance the engineering applicability of the optimization framework. Full article

Recognition of flanges on LNG (“Liquefied Natural Gas”) vessels and distance determination are key prerequisites for automated docking of an unloading arm, and in complex environments, flange detection faces challenges such as low accuracy and large distance measurement errors. Therefore, an improved lightweight high-precision approach based on YOLOv8s that integrates the C2f_Ghost module, a CBAM, and Concat_BiFPN was proposed. In addition, a monocular ranging algorithm based on pixel width and coordinate transformation was introduced to estimate the 3D coordinates of a flange. Specifically, the original Bottleneck in the C2f module was replaced by the Ghost module, which combines dynamic convolution and dynamic depth-separable convolution to enhance feature representation while reducing model complexity. A CBAM was introduced in the middle layer of the backbone module to improve the model’s focus on key features with minimal parameter increases, and Concat_BiFPN was used in the neck to facilitate cross-scale feature fusion. To ensure the reproducibility of the experiments, this study primarily employed a fixed random seed (0), and experimental validation analysis was conducted on a flange dataset. The results show that for the improved model, mAP@0.5 reached 97.5% and mAP@0.5:0.95 reached 82.3% with a parameter size of 9.34 M, representing improvements in accuracy of 0.6% and 13.4%, respectively, and a reduction in the parameter size of 16.2% compared with the original YOLOv8s. The average ranging errors of the X-axis, Y-axis, and Z-axis were 2.43%, 2.77%, and 0.71%, respectively. Therefore, the combination of the two algorithms significantly improves the detection and ranging accuracy of flanges in complex environments. Full article

In the present paper, a quantitative assessment of the effect of alternative fuel (LNG, LPG-B, LPG-P and MeOH) implementation in internal combustion engines in bulk carrier vessels on environmental compliance is presented. A fleet comprising 40 vessels across the Handymax, Panamax and Supramax classes is examined. By using LNG, the total fleet achieves environmental compliance up to 2030, with 52.5% of the fleet potentially achieving a minor superior energy ranking, while the EU ETS costs can be reduced by up to 24% compared to the case of burning conventional fuels. LPG-B and LPG-P demonstrated moderate improvements in the compliance period, with 50% to 87.5% and 52.5% to 97.5% surviving up to 2030, respectively. Reductions in the EU ETS costs were similar for these two fuels, with the reductions ranging from 3.3% to 12.1% for LPG-B and from 4.1% to 15.2% for LPG-P. Among all fuels, methanol showed the least improvement in extending the compliance period, with 52.5% to 67.5% of the fleet reaching 2030 with inferior to moderate CII ranks. The EU ETS cost reductions were low, ranging from 2.7% to 10%, with substantial fuel cost increases from 29.9% to 107%. The present study aims to assist ship owners/operators by providing a decision-support tool for bulk carrier alternative fuel pathways. Finally, it provides insights into the marine industry and shipping market regarding the future of the bulk carrier fleet in the context of decarbonization. Full article

The adoption of low-carbon fuels in maritime propulsion requires operational autonomy, material suitability, and compliance with safety standards, making liquid fuels like LNG and LH₂ the most viable options. LNG is widely used for reducing GHG, NOx, and SOx emissions, while LH₂, though new to the maritime sector, leverages aerospace experience. This paper explores the operational requirements and challenges of LH₂ cryogenic handling systems using LNG practices as a reference. Key comparisons are made between LNG and LH₂ supply systems, focusing on cryogenic materials, hydrogen embrittlement, and structural integrity under maritime conditions. Most maritime-approved materials are suitable for cryogenic use, and hydrogen embrittlement is less critical at cryogenic temperatures due to reduced atomic mobility. Risk assessments suggest LH₂’s safety record stems from limited operational data rather than superior inherent safety. The paper also addresses crucial safety and regulatory considerations for both fuels, underscoring the need for strict adherence to standards to ensure the safe and compliant integration of LH₂ in the maritime industry. Full article

Levonorgestrel (LNG), a synthetic progestin widely used in pharmaceuticals, is increasingly recognized as an emerging aquatic contaminant capable of exerting adverse biological effects beyond endocrine disruption. Acting in a xenobiotic-like manner, LNG may perturb redox homeostasis and induce oxidative stress in non-target species. To elucidate these mechanisms, this study integrates experimental toxicology with supervised machine learning to characterize tissue-specific and dose–time related oxidative responses in adult Zebrafish (Danio rerio). Fish were exposed to two environmentally relevant concentrations of LNG (0.312 µg/L; LNG-L and 6.24 µg/L; LNG-H) and a solvent control (LNG-C) for 24, 48, and 96 h in triplicate static bioassays. Redox biomarkers—superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and malondialdehyde (MDA)—were quantified in liver and muscle tissues. LNG-H exposure elicited a time-dependent increase in SOD activity, variable CAT responses, and a marked elevation in hepatic GPx, with sustained MDA levels indicating persistent lipid peroxidation. Five classification algorithms (Logistic Regression, Multilayer Perceptron, Gradient-Boosted Trees, Decision Tree and Random Forest) were trained to discriminate exposure outcomes based on biomarker profiles; GBT yielded the highest performance (96.17% accuracy), identifying hepatic GPx as the most informative feature (AUC = 0.922). Regression modeling via Extreme Gradient Boosting (XGBoost) further corroborated the dose- and time-dependent predictability of GPx responses (R² = 0.922, MAE = 0.019). These findings underscore hepatic GPx as a sentinel biomarker of LNG-induced oxidative stress and demonstrate the predictive utility of machinelearning-enhanced toxicological frameworks in detecting and modeling sublethal contaminant effects with high temporal resolution in aquatic systems. Full article