Search Results (50,108)

The Strait of Messina poses unique challenges for small vessels due to strong currents and complex wave conditions, which critically affect structural integrity and operational safety. This study proposes an integrated methodology that combines seakeeping analysis, a comparison with classification society rules, and fatigue life assessment within a unified and computationally efficient framework. A panel-based approach was used to compute vessel motions and vertical bending moments at different speeds and wave directions. Hydrodynamic loads derived from Response Amplitude Operators (RAOs) were compared with regulatory limits and applied to fatigue analysis. A further innovative aspect is the use of high-resolution bathymetric data from the Strait of Messina, enabling a realistic representation of local currents and sea states and providing a more accurate assessment than studies based on idealized conditions. The results show that forward speed amplifies bending moments, reducing safe wave heights from 2 m at rest to about 0.5 m at 16 knots. Fatigue analysis indicates that aluminum hulls are highly vulnerable to 2–3 m waves, while steel and titanium show no significant damage. The proposed workflow is transferable to other vessel types and supports safer design and operation. The case study of the Strait of Messina, the busiest and most challenging maritime corridor in Italy, confirms the validity and practical importance of the approach. By combining hydrodynamic and structural analyses into a single workflow, this study establishes the foundation for predictive maintenance and real-time structural health monitoring, with significant implications for navigation safety in complex sea environments. Full article

Intelligent ventilation systems can optimize airflow regulation to enhance mining safety and reduce energy consumption, driving green development in mineral resource extraction. This paper systematically elaborates on the overall architecture, cutting-edge advances, and core technologies of current intelligent mining ventilation. Building upon this foundation, a comprehensive intelligent mine ventilation solution encompassing the entire process of ventilation design, optimization, and operation is constructed based on a five-layer architecture, integrating key technologies such as intelligent sensing, real-time solving, airflow regulation, and remote control, providing an overarching framework for smart mine ventilation development. To address the computational efficiency bottleneck of traditional methods, an improved loop-solving method based on minimal independent closed loops is realized, achieving near real-time analysis of ventilation networks. Furthermore, a multi-level airflow regulation strategy is realized, including the methods of optimization control based on mixed integer linear programming and equipment-driven demand-based regulation, effectively resolving the challenges of calculating nonlinear programming models. Case studies indicate that the intelligent ventilation system significantly enhances mine safety and efficiency, leading to approximately 10–20% energy saving, a 40–60% quicker emergency response, and an average increase of about 20% in the utilization of fresh air at working faces through its remote and real-time control capabilities. Full article

In this study, we investigate a shielded capacitive power transfer (S-CPT) system that employs cast iron road covers as transmission electrodes for both dynamic and static charging of electric vehicles. Coupling capacitance was evaluated from S-parameters using copper, aluminum, ductile cast iron, structural steel, and carbon steel electrodes, with additional comparisons of ductile iron surface conditions (casting, machining, electrocoating). In a four-plate S-CPT system operating at 13.56 MHz, capacitance decreased with electrode spacing, yet ductile cast iron reached ~70 pF at 2 mm, demonstrating a performance comparable to that of copper and aluminum despite having higher resistivity and permeability. Power transmission experiments using a Ø330 mm cast iron cover meeting road load standards achieved 58% efficiency at 100 W, maintained around 40% efficiency at power levels above 200 W, and retained 45% efficiency under 200 mm lateral displacement, confirming robust dynamic performance. Simulations showed that shield electrodes enhance grounding, stabilize potential, and reduce return-path impedance. Finite element analysis confirmed that the ductile cast iron electrodes can withstand a 25-ton design load. The proposed S-CPT concept integrates an existing cast iron infrastructure with thin aluminum receiving plates, enabling high efficiency, mechanical durability, EMI mitigation, and reduced installation costs, offering a cost-effective approach to urban wireless charging. Full article

The successful establishment of battery electric vehicles (BEVs) is strongly linked to criteria such as cost and range. In particular, the need for air conditioning strains battery capacities and limits the availability of BEVs. Thermal energy storage systems (TESs) open up alternative paths for heat and cold supply with excellent scalability and cost efficiency. Previous TES concepts have largely focused on heat during cold seasons, but storage-based air conditioning systems for all seasons are still missing. To fill this gap, a concept based on a Brayton cycle allowing heat and cold supply and, simultaneously, an output of electrical energy at times when no air conditioning is needed was investigated. Central thermal components include water-based cold storage and electrically heated, high-temperature, solid-medium storage, both with innovative TPMS structures and flexible operation managements. With transient simulation studies a system was identified with effective storage densities of up to 100 Wh/kg, reaching a constant heat and cold supply of 5 kW and 2.5 kW, respectively, over 41 min. In addition, the underlying cycle allows an electrical output of up to 1.7 kW during times of inactive air conditioning requirements. Compared to a reference system designed only for winter operation, the moderately lower storage densities are compensated by proportionately longer discharging times. By combining a compact and dynamic Brayton cycle with a TES in BEVs, a storage-based air conditioning system with high utilization potential and high operational flexibility was developed. In addition to further optimizations, the knowledge for TES solutions can also be transferred to today’s air conditioning systems, extending the solution space for storage-supported thermomanagement options in BEVs. Full article

This study evaluated the antibacterial efficacy and growth-promoting potential of Moringa oleifera and Thymus vulgaris methanolic extracts in broiler chickens challenged with Escherichia coli O78. In vitro antibacterial screening using agar well diffusion and disc diffusion assays revealed that ciprofloxacin exhibited the strongest inhibitory effect, followed by tetracycline and enrofloxacin, whereas among plant extracts, T. vulgaris was more effective than M. oleifera. The optimal combination (M100T150; 100 mg M. oleifera + 150 mg T. vulgaris) produced the largest inhibition zones against E. coli strains. For the in vivo trial, 540 Ross-308 broiler chicks were distributed into six treatment groups in a completely randomized design and reared for 42 days. Parameters assessed included growth performance, carcass traits, gut pH, ileal microbial counts, and intestinal histomorphology. Results showed that E. coli challenge significantly reduced feed intake, weight gain, carcass yield, and villus integrity while increasing FCR and E. coli counts (p < 0.05). Addition of plant extracts, particularly M100T150, significantly improved weight gain, FCR, Broiler Performance Efficiency Factor (BPEF), and Broiler Farm Economy Index (BFEI) compared to the positive control (p < 0.05). Extracts reduced duodenal and jejunal pH (p < 0.001), suppressed E. coli counts (p = 0.003), and enhanced Lactobacillus populations (p = 0.0004). Histological analysis revealed that extract-supplemented groups had greater villus height and surface area with shallower crypts than the positive control, indicating restoration of gut integrity. These findings suggest that methanolic extracts of M. oleifera and T. vulgaris, particularly in combination, can serve as natural alternatives to antibiotics in broiler production under pathogenic challenge. Full article

To address the challenges of weight redundancy, low material utilization, and excessive performance margins in the design of electric cable-hauling machines, this study proposes a novel multi-objective optimization framework. The framework integrates Latin hypercube experimental design, Kriging surrogate modeling, a Non-dominated Sorting Genetic Algorithm III (NSGA-III), and a coupled TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach. A high-fidelity finite element model based on extreme operating conditions was established to simulate the performance of the electric towing winch. The Kriging model was employed to replace time-consuming finite element calculations, significantly improving computational efficiency. The NSGA-III algorithm was then utilized to search for the Pareto front, identifying a set of optimal solutions that balance multiple design objectives. Finally, the TOPSIS method was applied to select the most preferable solution from the Pareto front. The results demonstrate a 7.32% reduction in the overall mass of the towing winch, a 7.34% increase in the safety factor, and a 4.57% reduction in maximum structural deformation under extreme operating conditions. These findings validate the effectiveness of the proposed Kriging-NSGA-III-TOPSIS strategy for lightweight design of ship deck winch machinery. Full article

Efficient recycling of polyamide 6 (PA6) requires selective depolymerization routes that recover monomers under moderate conditions. This study investigates microwave-assisted acid hydrolysis of four PA6 waste streams, two oligomer-rich residues (WS-13, WS-24), an industrial fiber (C-fiber), and a commercial resin (C-resin) to elucidate degradation kinetics, activation energies, and product yields. Thermogravimetric analysis revealed multi-step solid-state decomposition, while microwave hydrolysis (125–200 °C, 15–60 min, 400 W) demonstrated strong dependence on acid type. HCl achieved complete conversion, whereas phosphoric and formic acids exceeded 95%. Kinetic analysis under H₃PO₄ followed pseudo-first-order behavior, with rate constants (0.015–0.141 min⁻¹ at 200 °C) and activation energies reflecting feedstock structure: 53.1 kJ mol⁻¹ (WS-13), 56.5 kJ mol⁻¹ (WS-24), 87.1 kJ mol⁻¹ (C-resin), and 99.9 kJ mol⁻¹ (C-fiber). Monomer yields varied by substrate: WS-13 achieved 62.4% at 200 °C and 45 min (ACA 46%, CPL 16%), WS-24 yielded 62.0% (primarily ACA), C-fiber reached 69.7% (ACA-dominant), and C-resin produced 53.8%. These results show that oligomer-rich wastes are kinetically favored for rapid hydrolysis at lower energy cost, while C-fiber maximizes aminocaproic acid recovery. Overall, microwave-assisted hydrolysis provides a selective, energy-efficient pathway for PA6 circularity, offering design parameters for reactor operation and process optimization. Full article

Hybrid AC/DC microgrids have emerged as a promising solution for integrating diverse renewable energy sources, enhancing efficiency, and strengthening resilience in modern power systems. However, existing control schemes exhibit critical shortcomings that limit their practical effectiveness. Traditional linear controllers, designed around nominal operating points, often fail to maintain stability under large load and generation fluctuations. Optimization-based methods are highly sensitive to model inaccuracies and parameter uncertainties, reducing their reliability in dynamic environments. Intelligent approaches, such as fuzzy logic and ML-based controllers, provide adaptability but suffer from high computational demands, limited interpretability, and challenges in real-time deployment. These limitations highlight the need for robust control strategies that can guarantee reliable operation despite disturbances, uncertainties, and varying operating conditions. Numerical performance indices demonstrate that the reviewed robust control strategies outperform conventional linear, optimization-based, and intelligent controllers in terms of system stability, voltage and current regulation, and dynamic response. This paper provides a comprehensive review of recent robust control strategies for hybrid AC/DC microgrids, systematically categorizing classical model-based, intelligent, and adaptive approaches. Key research gaps are identified, including the lack of unified benchmarking, limited experimental validation, and challenges in integrating decentralized frameworks. Unlike prior surveys that broadly cover microgrid types, this work focuses exclusively on hybrid AC/DC systems, emphasizing hierarchical control architectures and outlining future directions for scalable and certifiable robust controllers. Also, comparative results demonstrate that state of the art robust controllers—including H∞-based, sliding mode, and hybrid intelligent controllers—can achieve performance improvements for metrics such as voltage overshoot, frequency settling time, and THD compared to conventional PID and droop controllers. By synthesizing recent advancements and identifying critical research gaps, this work lays the groundwork for developing robust control strategies capable of ensuring stability and adaptability in future hybrid AC/DC microgrids. Full article

This work examines the effect of gadolinium (Gd) promotion on nickel-based SBA-16 catalysts for the dry reforming of methane (DRM), with the goal of improving syngas production by optimizing catalyst composition and operating conditions. Catalysts with varying Gd loadings (0.5–3 wt.%) were synthesised using co-impregnation. XRD, N₂ physisorption, FTIR, XPS, and H₂-TPR–CO₂-TPD–H₂-TPR were used to examine the structural features, textural properties, surface composition, and redox behaviour of the catalysts. XPS indicated formation of enhanced metal–support interactions, while initial and post-treatment H₂–TPR analyses showed that moderate Gd loadings (1–2 wt.%) maintained a balanced distribution of reducible Ni species. The catalysts were tested for DRM performance at 800 °C and a gas hourly space velocity (GHSV) of 42,000 mL g⁻¹ h⁻¹. 1–2 wt.% Gd-promoted catalysts achieved the highest H₂ (~67%) and CO yield (~76%). Response surface methodology (RSM) was used to identify optimal reaction conditions for maximum H₂ yield. RSM predicted 848.9 °C temperature, 31,283 mL g⁻¹ h⁻¹ GHSV, and a CH₄/CO₂ ratio of 0.61 as optimal, predicting a H₂ yield of 96.64%, which closely matched the experimental value of H₂ yield (96.66%). The 5Ni–2Gd/SBA-16 catalyst exhibited minimal coke deposition, primarily of a graphitic character, as evidenced by TGA–DSC and Raman analyses. These results demonstrate the synergy between catalyst design and process optimization in maximizing DRM efficiency. Full article

Small-scale thermal treatment systems can provide environmentally improved sewage sludge treatment due to processing sludge locally, which lowers transport costs and emissions. However, the combined effect of confined volume and complex sludge properties makes achieving strict regulations on flue gas emissions and end-ash composition challenging. System development thus requires the use of advanced, 3D CFD simulation supported studies. An important step forward regarding these is the application of combustion models which introduce tailored surrogate fuels and apply detailed chemical kinetics to achieve a high-fidelity combustion description in confined volumes. In relation to this, the paper presents an innovative computationally efficient sewage sludge surrogate-based combustion model capable of defining surrogates, tailored to sewage sludge, and capable of providing detailed insight into reaction zone evolution in small-scale sludge incineration systems. The validity of the proposed model and surrogates is confirmed via simulated temperatures differing from measurements in the small-scale system for less than 30 K. The validated model of a small-scale system is used in the parametric analysis of variable air–fuel ratios, higher fuel moisture presence, varying bed temperature, and varying thermal power to enable unprecedentedly accurate and efficient definition of design features of small-scale systems and to provide key guidelines for operation optimization. Full article

Wireless Sensor Networks (WSNs) consist of numerous battery-powered sensor nodes that operate with limited energy, computation, and communication capabilities. Designing routing strategies that are both energy-efficient and attack-resilient is essential for extending network lifetime and ensuring secure data delivery. This paper proposes Adaptive Federated Reinforcement Learning-Hunger Games Search (AFRL-HGS), a Hybrid Routing framework that integrates multiple advanced techniques. At the node level, tabular Q-learning enables each sensor node to act as a reinforcement learning agent, making next-hop decisions based on discretized state features such as residual energy, distance to sink, congestion, path quality, and security. At the network level, Federated Reinforcement Learning (FRL) allows the sink node to aggregate local Q-tables using adaptive, energy- and performance-weighted contributions, with Polyak-based blending to preserve stability. The binary Hunger Games Search (HGS) metaheuristic initializes Cluster Head (CH) selection and routing, providing a well-structured topology that accelerates convergence. Security is enforced as a constraint through a lightweight trust and anomaly detection module, which fuses reliability estimates with residual-based anomaly detection using Exponentially Weighted Moving Average (EWMA) on Round-Trip Time (RTT) and loss metrics. The framework further incorporates energy-accounted control plane operations with dual-format HELLO and hierarchical ADVERTISE/Service-ADVERTISE (SrvADVERTISE) messages to maintain the routing tables. Evaluation is performed in a hybrid testbed using the Graphical Network Simulator-3 (GNS3) for large-scale simulation and Kali Linux for live adversarial traffic injection, ensuring both reproducibility and realism. The proposed AFRL-HGS framework offers a scalable, secure, and energy-efficient routing solution for next-generation WSN deployments. Full article

Thrust vectoring technology significantly improves the manoeuvrability and environmental adaptability of unmanned aerial vehicles by dynamically regulating the direction and magnitude of thrust. In this paper, the principles and applications of mechanical thrust vectoring technology, fluidic thrust vectoring technology and the distributed electric propulsion system are systematically reviewed. It is shown that the mechanical vector nozzle can achieve high-precision control but has structural burdens, the fluidic thrust vectoring technology improves the response speed through the design of no moving parts but is accompanied by the loss of thrust, and the distributed electric propulsion system improves the hovering efficiency compared with the traditional helicopter. Addressing multi-physics coupling and non-linear control challenges in unmanned aerial vehicles, this paper elucidates the disturbance compensation advantages of self-disturbance rejection control technology and the optimal path generation capabilities of an enhanced path planning algorithm. These two approaches offer complementary technical benefits: the former ensures stable flight attitude, while the latter optimises flight trajectory efficiency. Through case studies such as the Skate demonstrator, the practical value of these technologies in enhancing UAV manoeuvrability and adaptability is further demonstrated. However, thermal management in extreme environments, energy efficiency and lack of standards are still bottlenecks in engineering. In the future, breakthroughs in high-temperature-resistant materials and intelligent control architectures are needed to promote the development of UAVs towards ultra-autonomous operation. This paper provides a systematic reference for the theory and application of thrust vectoring technology. Full article

Over the past decade, many software enterprises have migrated from monolithic to microservice architectures to enhance scalability, maintainability, and performance. However, this transition presents significant challenges, requiring considerable development efforts, research, customization, and resource allocation over extended periods. Furthermore, the success of migration is not guaranteed, highlighting the complexities organizations face in modernizing their software systems. To address these challenges, this study introduces Mono2Micro, a comprehensive framework designed to automate the migration process while preserving structural integrity and optimizing service boundaries. The framework focuses on three core patterns: database patterns, service decomposition, and communication patterns. It leverages machine learning algorithms, including Random Forest and Louvain clustering, to analyze database query patterns along with static and dynamic database model analysis, which enables the identification of relationships between models, facilitating the systematic decomposition of microservices while ensuring efficient inter-service communication. To validate its effectiveness, Mono2Micro was applied to a student information system for faculty management, demonstrating its ability to streamline the migration process while maintaining functional integrity. The proposed framework offers a systematic and scalable solution for organizations and researchers seeking efficient migration from monolithic systems to microservices. Full article

Redox flow batteries (RFBs) are a promising technology for large-scale energy storage due to their safety, scalability, and design flexibility. This study investigated a tiron-A (4,5-dihydroxybenzene-1,3-disulfonic acid)/tungstosilicic acid (TSA) RFB system, focusing on optimizing the supporting electrolyte and the volumetric ratio of the catholyte (tiron-A) to anolyte (TSA). Electrochemical characteristics, confirmed by CV and EIS, showed that sulfuric acid was the most suitable supporting electrolyte due to its excellent cell potential and lower ohmic resistance compared to sodium chloride and sodium hydroxide electrolytes. To address the inherent electron capacity imbalance between tiron-A (two electrons) and TSA (four electrons), various volumetric ratios were evaluated. The cell with the 3:1 tiron-A:TSA ratio exhibited optimal performance, achieving the highest discharge capacity, excellent cycle stability, and consistent energy efficiency. The electrochemical impedance spectroscopy results revealed that the ohmic resistance was minimized at the 3:1 ratio. This stable, low-ohmic resistance, coupled with a significant reduction in charge transfer resistance after cycling, was confirmed as the dominant factor for the improved long-term performance. These findings demonstrate an effective strategy for developing a high-performance performance tiron-A/TSA RFB system. Full article

High-overload testing equipment is a key platform for evaluating mechanical performance under extreme conditions, requiring specialized functional design to meet stringent operational demands. The current design process faces numerous challenges, including overreliance on designers’ experience, incomplete requirement analysis, and insufficient automation, resulting in suboptimal solutions. To address these issues, in this study, we propose an integrated method based on axiomatic design (AD) and the Theory of Inventive Problem Solving (TRIZ). This method systematically decomposes technical specifications, maps requirements to a structural framework, and resolves design conflicts using inventive principles. The method employs a comprehensive evaluation framework combining the analytic hierarchy process (AHP) and quality function deployment (QFD) to quantitatively assess candidate designs. It facilitates the development of efficient, standardized high-load testing equipment solutions, enhancing design reliability and innovation capabilities. Full article