Search Results (973)

Hydrogen permeation parameters of PA12 were obtained through high-pressure hydrogen permeation experiments conducted under various temperature and pressure conditions. The temperature-dependent mechanism governing the hydrogen permeation behavior of PA12 was further examined using dynamic mechanical analysis (DMA). A multi-field coupled numerical model was established and validated against the experimental results. Based on the validated numerical approach, the hydrogen permeation behavior of a type IV hydrogen storage vessel with local reinforcement was investigated. The results show that both temperature and pressure have a significant influence on the hydrogen permeation performance of PA12. When the temperature is below the glass transition temperature (Tg) of PA12 (48.34 °C), the diffusion coefficient remains low, whereas temperatures above the Tg led to a marked increase in the diffusion coefficient. In addition, the local reinforcement patch effectively prolongs the time required to reach steady-state permeation, reduces the hydrogen permeation flux before and after steady state, and enhances the overall resistance to hydrogen permeation of the type IV vessel. As the diffusion coefficient of the liner material increases, the hydrogen diffusion rate increases substantially, leading to greater hydrogen accumulation in the dome region and higher permeation levels both before and after steady state. These findings provide theoretical guidance and design references for optimizing the hydrogen-resistant performance of type IV hydrogen storage vessels. Full article

This study investigates the influence of ore particle shape on the wear behavior of ball mill liners using the Rocky-DEM software. A simulation model of a laboratory-scale ball mill was established to analyze the wear patterns of liners under three different ore particle shapes: polyhedron, ellipsoid, and sphere. The results indicate that while the overall motion patterns of the charge showed minor differences across particle shapes, significant variations were observed in flowability, with the polyhedral system exhibiting the lowest fluidity. Particle shape had a negligible impact on translational velocity but a substantial effect on rotational velocity. Regarding liner wear, the polyhedral system generated significantly higher wear compared to the spherical and ellipsoidal systems. The polyhedral system also exhibited the highest shear stress, identifying shear stress as the core factor dominating liner wear. The wear-time curves for individual liners in both radial and axial directions displayed a stepwise increase, suggesting that wear is primarily concentrated in the toe region. Full article

The Estimated Time of Arrival (ETA) of vessels is a vital operational indicator for voyage planning, fleet deployment, and resource allocation. However, most existing studies focus on short-distance liner services with fixed routes, while ETA prediction for long-distance tramp bulk carriers remains insufficiently accurate, often resulting in operational inefficiencies and charter party disputes. To fill this gap, this study proposes a data-driven stacking ensemble learning framework that integrates Light Gradient-Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) as base learners, combined with a Linear Regression meta-learner. This framework is specifically tailored to the unique complexities of tramp shipping, advancing beyond traditional single-model approaches by incorporating systematic feature engineering and model fusion. The study also introduces the construction of a comprehensive multi-dimensional AIS feature system, incorporating baseline, temporal, speed-related, course-related, static, and historical behavioral features, thereby enabling more nuanced and accurate ETA prediction. Using AIS trajectory data from bulk carrier voyages between Weipa (Australia) and Qingdao (China) in 2023, the framework leverages multi-feature fusion to enhance predictive performance. The results demonstrate that the stacking model achieves the highest accuracy, reducing the Mean Absolute Error (MAE) to 3.30 h—a 74.7% improvement over the historical averaging benchmark and an 11.3% reduction compared with the best individual model, XGBoost. Extensive performance evaluation and interpretability analysis confirm that the stacking ensemble provides stability and robustness. Feature importance analysis reveals that vessel speed, course stability, and remaining distance are the primary drivers of ETA prediction. Additionally, meta-learner weighting analysis shows that LightGBM offers a stable baseline, while systematic deviations in XGBoost predictions act as effective error-correction signals, highlighting the complementary strengths captured by the ensemble. The findings provide operational insights for maritime logistics and port management, offering significant benefits for port scheduling and maritime logistics management. Full article

This study established an empirical structural equation model to examine whether the adoption of green shipping practices (GSPs) will influence customer satisfaction and customer retention in the container shipping industry from the perspective of freight forwarders, while accounting for the effectiveness of marketing activities. Through questionnaire survey, 114 responding data were collected from freight forwarders in the Taiwan area. The main results discovered are as follows: (1) adoption of GSPs was found to positively influence companies’ environmental performance in terms of perceived green capability (PGC); (2) the most significant finding in this study is the irrelevance of PGC to both CS and CR from the perspective of freight forwarders. In addition, after discussing the managerial implications, this study examined whether adopting GSPs to improve the environmental and productivity performance of liner carriers remains an ongoing debate and if it warrants a further investigation. Full article

In this study, using global liner shipping schedules, UNCTAD’s Port Liner Shipping Connectivity Index and Liner Shipping Bilateral Connectivity Index, together with bilateral trade-value data for 2022–2024, we construct a multilayer weighted port-to-port network that explicitly embeds port-level cargo-handling and service organisation capabilities, as well as demand-side routing pressure, into node and edge weights. Building on this network, we apply CONCOR-based structural-equivalence analysis to delineate functionally homogeneous port clusters, and adopt a structural role identification framework that combines multi-indicator connectivity metrics with Rank-Sum Ratio–entropy weighting and Probit-based binning to classify ports into high-efficiency core, bridge-control, and free-form bridge roles, thereby tracing the reconfiguration of cluster-level functional structures before and after the Red Sea crisis. Empirically, the clustering identifies four persistent communities—the Intertropical Maritime Hub Corridor (IMHC), Pacific Rim Mega-Port Agglomeration (PRMPA), Southern Commodity Export Gateway (SCEG), and Euro-Asian Intermodal Chokepoints (EAIC)—and reveals a marked spatial and functional reorganisation between 2022 and 2024. IMHC expands from 96 to 113 ports and SCEG from 33 to 56, whereas EAIC contracts from 27 to 10 nodes as gateway functions are reallocated across clusters, and the combined share of bridge-control and free-form bridge ports increases from 9.6% to 15.5% of all nodes, demonstrating a thicker functional backbone under rerouting pressures. Spatially, IMHC extends from a Mediterranean-centred configuration into tropical, trans-equatorial routes; PRMPA consolidates its role as the densest trans-Pacific belt; SCEG evolves from a commodity-based export gateway into a cross-regional Southern Hemisphere hub; and EAIC reorients from an Atlantic-dominated structure towards Eurasian corridors and emerging bypass routes. Functionally, Singapore, Rotterdam, and Shanghai remain dominant high-efficiency cores, while several Mediterranean and Red Sea ports (e.g., Jeddah, Alexandria) lose centrality as East and Southeast Asian nodes gain prominence; bridge-control functions are increasingly taken up by European and East Asian hubs (e.g., Antwerp, Hamburg, Busan, Kobe), acting as secondary transshipment buffers; and free-form bridge ports such as Manila, Haiphong, and Genoa strengthen their roles as elastic connectors that enhance intra-cluster cohesion and provide redundancy for inter-cluster rerouting. Overall, these patterns show that resilience under the Red Sea crisis is expressed through the cluster-level rebalancing of core–control–bridge roles, suggesting that port managers should prioritise parallel gateways, short-sea and coastal buffers, and sea–land intermodality within clusters when designing capacity expansion, hinterland access, and rerouting strategies. Full article

This work presents an analytical homogenization model developed to predict the tensile and bending behavior of double-wall corrugated cardboard. The proposed approach replaces the complex three-dimensional geometry, composed of five paper layers, with an equivalent two-dimensional homogenized plate. Based on lamination theory and enhanced by sandwich structure theory, the model accurately captures the orthotropic behavior of the material. To achieve this objective, three configurations of double-wall corrugated cardboard were investigated: KRAFT LINER (KL), DUOSAICA (DS), and AUSTRO LINER (AL). A comprehensive experimental characterization campaign was conducted, including physical analyses (density measurement, SEM imaging, and XRD analysis) and mechanical testing (tensile tests), to determine the input parameters required for the homogenization process. The proposed model significantly reduces geometric complexity and computational cost while maintaining excellent predictive accuracy. Validation was performed by comparing the results of a 3D finite element model (ANSYS-19.2) with those obtained from the homogenized H-2D model. The differences between both approaches remained systematically below 2%, confirming the ability of the H-2D model to accurately reproduce the axial and flexural stiffnesses of double-wall corrugated cardboard. The methodology provides a reliable and efficient framework specifically dedicated to the mechanical analysis and optimization of corrugated cardboard structures used in packaging applications. Full article

Forkhead box protein O1 (Foxo1) is an insulin-suppressed transcription factor that governs multiple biological processes, including cell proliferation, apoptosis, autophagy, mitochondrial function, and energy metabolism. Over the past 25 years, Foxo1 has evolved from a liner insulin effector to a pleiotropic integrator of systemic metabolic stress during obesity and aging. Foxo1 integrates hormonal signals with energy balance and plays a central role in glucose and lipid metabolism, organ homeostasis, and immune responses. Given its pleiotropic functions, therapeutic targeting of Foxo1 pathway will require a nuanced, context-specific approach. Here, we reviewed key advances in Foxo1 studies over the past 25 years, including multi-hormonal control of Foxo1 activity, Foxo1-mediated inter-organ crosstalk, immune modulation, and contributions to aging-associated pathologies. Understanding the regulation of Foxo1 and its pleiotropic function across multiple tissues will advance insight into the pathogenesis of metabolic diseases and promote the translation potential of Foxo1 signaling manipulation for the treatment of metabolic disorders, including insulin resistance and type 2 diabetes. Full article

This work advances a 6G-ready, micro-granular SDN fabric that unifies high-performance edge data planes with intent-driven, multi-domain orchestration and cloud offloading. First, edge and cell-site whiteboxes are upgraded with Smart Network Interface Cards and embedded AI accelerators, enabling line-rate processing of data flows and on-box learning/inference directly in the data plane. This pushes functions such as traffic classification, telemetry, and anomaly mitigation to the point of ingress, reducing latency and backhaul load. Second, an SDN controller, i.e., ETSI TeraFlowSDN, is extended to deliver multi-domain SDN orchestration with native lifecycle management (LCM) for whitebox Network Operating Systems—covering onboarding, configuration-drift control, rolling upgrades/rollbacks, and policy-guarded compliance—so operators can reliably manage heterogeneous edge fleets at scale. Third, the SDN controller incorporates a new NFV-O client that seamlessly offloads network services—such as ML pipelines or NOS components—to telco clouds via an NFV orchestrator (e.g., ETSI Open Source MANO), enabling elastic placement and scale-out across the edge–cloud continuum. Together, these contributions deliver an open, programmable platform that couples in-situ acceleration with closed-loop, intent-based orchestration and elastic cloud resources, targeting demonstrable gains in end-to-end latency, throughput, operational agility, and energy efficiency for emerging 6G services. Full article

In this article, electrodeposited Ni-Al₂O₃ coatings were fabricated on the surface of a cylinder liner to enhance its corrosion resistance. The effect of current density on the surface morphology, phase structure, and corrosion resistance of the Ni-Al₂O₃ coatings was investigated using a scanning electron microscope (SEM), X-ray diffraction (XRD) instrument, and electrochemical workstation, respectively. The observed results show that a dense, flat morphology emerged on the surface of the Ni-Al₂O₃ coatings prepared under a current density of 3.5 A/dm². Furthermore, among three Ni-Al₂O₃ coatings, the Al content of the one prepared under a current density of 3.5 A/dm² was the highest, with a value of 5.4 wt.%. XRD patterns demonstrated that the average nickel grain size of the Ni-Al₂O₃ coatings prepared at 3.5 A/dm² was only 251.6 nm, which was obviously smaller than those deposited under current densities of 2.5 A/dm² and 4.5 A/dm². Meanwhile, the adhesion strength of the Ni-Al₂O₃ coatings prepared under a current density of 3.5 A/dm² was the largest, with a value of 40.9 N. Polarization curves indicated the corrosion potential of the Ni-Al₂O₃ coatings prepared under a current density of 3.5 A/dm² was the highest, with a value of −0.42 V, while the corrosion current density of the coatings fabricated under a current density of 3.5 A/dm² was the lowest, with a value of 2.17 × 10⁻⁷ A/cm². In addition, the corrosive mass loss of Ni-Al₂O₃ coatings manufactured at 3.5 A/dm² was only 2.8 mg, illustrating excellent corrosion resistance. This study could enhance the service life and corrosion resistance of cylinder liners in internal combustion engines. Full article

The barrier performance of containment liners against heavy metals and other contaminants is a critical element in ensuring environmental safety. However, the high concentration of multivalent cations in landfill leachate raises concerns about the effectiveness of conventional barriers (e.g., sodium bentonite). To address concerns regarding the high permeability and elevated heavy metal concentrations in effluents from sodium bentonite (Na-B) barriers, this study proposes the use of new complex-modified sorbent bentonite—specifically treated with disodium ethylenediaminetetraacetate (EDTA-2Na) and sodium tripolyphosphate (STPP). Batch adsorption and flexible-wall permeability tests in extreme synthetic leachate demonstrate that the complex-modified sodium bentonite not only maintains low permeability but also enhances contaminant adsorption capacity of barriers. When modified with 2% EDTA-2Na and 4% STPP (by mass), the maximum Zn(II) adsorption capacity of bentonite was measured at 43.22 and 48.22 μg/g, respectively. These values correspond to enhancements by a factor of 1.99 and 2.32 compared to the unmodified Na-B. Simultaneously, the hydraulic conductivity met the permeability requirements for engineering barrier systems (k < 1 × 10⁻⁷ cm/s) throughout the tested range of confining pressures. Microscopic analyses confirmed the successful incorporation of functional groups into bentonite by both EDTA-2Na and STPP. STPP-induced electrostatic repulsion, promoting ordered particle stacking and dense structure formation. EDTA-2Na physically filled pores to block ion migration pathways while electrochemically counteracting double-layer compression under high ionic strength. This effective strategy resolves the long-standing trade-off between permeability and adsorption capacity in conventional bentonite, providing a theoretical basis for designing barrier materials in complex contaminated sites. Full article

The combustor liner of the modern aero-engine operates under extreme thermal loads with limited coolant supply, necessarily making efficient cooling approaches important. Impingement–effusion double-wall cooling integrates impingement, convection, and film cooling, but most studies testing this approach have been conducted at atmospheric pressure, limiting the application of the technology in real engines. This work experimentally and numerically evaluates the cooling performance of baseline and optimized configurations, focusing on the effects of pressure drop, initial cooling filmand operating pressure under atmospheric and elevated pressures up to 0.3 MPa. The results show that increasing the pressure drop enhances cooling effectiveness, which can be attributed to enhanced jet momentum and cooling film coverage, though benefits diminish when the pressure drop further increases to over 4%. Introducing initial film cooling extends upstream protection, improves downstream uniformity, and stabilizes overall effectiveness across varying pressure drops. Elevated operating pressure further enhances the cooling effectiveness of impingement–effusion cooling, as higher coolant density promotes stronger impingement and more coherent cooling film formation. The simulations confirm that pressure-induced density effects dominate the cooling process, whereas blowing-ratio-based similarity fails to capture these dependencies. The results highlight the limitations of atmospheric evaluations and provide physical insights for designing efficient combustor liners under realistic pressure conditions. Full article

The non-uniformity of the inlet velocity profile (referred to as inlet distortion) in a gas turbine combustor critically influences the outlet temperature distribution, which is a key factor for the operational safety and durability of the turbine blades. To investigate the influence of inlet velocity distortion on the outlet temperature distribution factor (OTDF) and the hot streak evolution in a combustor, scaled-adaptive simulations (SAS) and experiments were conducted at an inlet temperature of 400 K, an inlet total pressure of 0.20 MPa, and a fuel–air ratio (FAR) of 0.018. RP-3 aviation kerosene was used as fuel for this investigation. The results show that in the primary zone, the heat release rate is quite low in the counter-current region, while it is very high in the co-current region. In the area downstream of the primary zone, intense heat release mainly takes place near the primary and dilution jets. The substantial penetration of the jets results in a relatively low FAR at the mid-height part of the liner, while the FAR is relatively high near the wall leading to the formation of hot streaks. Critically, experimental data demonstrate that the defined inlet distortions substantially increase the OTDF by 40 percentage points (from approximately 10% to 50%), highlighting a significant challenge for combustor design. This work provides validated insight into the linkage between inflow distortions and critical thermal loads, which is essential for developing more robust combustion systems. Full article

This paper presents a two-stage stochastic programming model for the joint optimization of fleet deployment and sailing speed in liner shipping under fuel price volatility and carbon tax uncertainty. The integrated framework addresses strategic fleet planning by determining optimal fleet composition in the first stage, while the second stage optimizes operational decisions, including vessel assignment to routes and sailing speeds on individual voyage legs, after observing stochastic parameter realizations. The model incorporates nonlinear fuel consumption functions that are approximated using piecewise linearization techniques, with the resulting formulation being solved using the Sample Average Approximation (SAA) method. To enhance computational tractability, we employ big-M methods to linearize mixed-integer terms and introduce auxiliary variables to handle nonlinear relationships in both the objective function and constraints. The proposed model provides shipping companies with a comprehensive decision-support tool that effectively captures the complex interdependencies between long-term strategic fleet planning and short-term operational speed optimization. Numerical experiments demonstrate the model’s effectiveness in generating optimal solutions that balance economic objectives with environmental considerations under uncertain market conditions, highlighting its practical value for resilient shipping operations in volatile fuel and carbon pricing environments. Full article

The rapid growth of the hydrogen industry, driven by global decarbonization efforts, has intensified the need for safe and large-capacity storage systems. Although hydrogen is one of the most abundant elements on Earth, its storage remains technically challenging due to its chemical reactivity and stringent containment requirements. Previous research has primarily emphasized the material-level behavior of polymer liners, composites, and metal alloys because chemical compatibility plays a critical role in aboveground high-pressure tanks. However, for underground storage systems, long-term structural stability is governed not only by material performance but also by the geo-mechanical behavior of deep rock masses. This study proposes a seismic design approach for Lined Rock Caverns (LRCs), a deep underground storage concept capable of sustaining high internal pressure. The method incorporates ground-induced deformation and evaluates the additional influence of internal pressure on lining behavior. Numerical analyses demonstrate that internal pressure has a significant stabilizing effect on the structural response by reducing ovalization and suppressing nonlinear deformation mechanisms. The results highlight that internal pressure is not a secondary load but a key design parameter that must be integrated into the seismic evaluation of LRC-based hydrogen storage facilities. Full article

Inland LNG-fuelled liner shipping is emerging as a significant trend, yet limited refueling infrastructure presents operational challenges. The complexity of inland navigation requires frequent speed adjustments to meet scheduled arrivals, which directly affects fuel consumption and refueling strategies. Additionally, imbalances in domestic and foreign trade container flows further increase operating costs for liner shipping companies. Given estimated weekly demands, considering navigational restrictions such as water depth and bridge clearance, as well as streamflow velocity, port time windows, empty container repositioning, port selection, speed adjustment, and uncertain fuel consumption, two novel models based on empty container arc variables and node variables are formulated, aiming to maximize voyage profit. These models are extended from divisible demand to indivisible demand cases. The explicit expression for the maximum fuel consumption under the worst-case speed deviation is derived, and an external linear approximation algorithm is proposed to linearize the nonlinear models while controlling approximation errors. Furthermore, the NP-hardness of the problem, the strict equivalence of the two modeling approaches, and the solution properties are proved. A case study of LNG-fuelled liner shipping on the Yangtze River shows the following: (1) for divisible demand, both models achieve optimal solutions within seconds, while for indivisible demand, the node-variable model outperforms the arc-variable model; (2) tactical strategies should be flexibly adjusted based on seasonal water depth, fuel prices, carbon taxes, speed deviations, and expected lock passage times; and (3) increasing fuel prices and carbon taxes generally reduce port calls and sailing speeds, suggesting that stricter fuel price and carbon tax policies can support the transition to green shipping. This study provides both theoretical guidance and managerial insights, supporting shipping companies in optimizing operations and promoting the development of sustainable inland shipping. Full article