Search Results (60,904)

In response to the urgent requirement for sustainable power supply for deep-sea or offshore underwater sensing equipment, this work investigates autonomous power generation aboard marine vessels. The vertical vibrations induced by wave excitation at the bottom of the vessel are utilized to drive the vibration energy harvesters on the deck for power generation. In a scenario involving automatic steering, a multiplicity of magnetoelectric harvesters mounted on the deck would move vertically in response to surface wave motion, enabling continuous conversion of wave energy into electrical power. The key feature of this study is that the ship-based self-power generation system is simple to install and safe, with the vibration energy harvesters mounted above the sea surface to avoid the unpredictable underwater sea conditions. This study presents a numerical case analysis of a three-magnet energy harvester designed to generate induced electrical power under wave conditions characterized by a speed of V = 3.0 m/s, amplitude of Z_o = 0.4 m, and wavelength of λ = 2.0 m. Prior to optimizing the ship-based energy harvester, the mathematical model of a three-magnet vibration system was validated against experimental data to ensure accuracy. Subsequently, a sensitivity study was performed to evaluate the influence of wave parameters (e.g., amplitude and wavelength) and the harvester’s geometric parameters on the electrical power output. To maximize power generation, the flower pollination algorithm—an efficient bio-inspired optimization method known for its robustness in global search—was integrated with the objective function defined as the root-mean-square electrical power. Simulation results indicate that the optimized harvester is capable of producing up to 0.1943 W. These findings highlight the potential of ship-based energy harvesters as a sustainable and reliable source of electrical power. Full article

In general, condition monitoring (CM) and noise, vibration and harshness (NVH) are often treated as separate disciplines, despite the fact that both rely on vibration measurements. CM relies on broadband statistical metrics such as RMS, kurtosis, and envelope analysis to detect faults. Meanwhile, NVH investigates tonal excitation mechanisms related to gear mesh frequency (GMF) and its modulation components. In this study, we investigate whether a numerical relationship can be established between classical CM indicators and physically based tonal excitation indicators derived from frequency–domain analysis. Using healthy and damaged benchmark gearbox recordings, Spearman correlation analysis was performed between broadband metrics and GMF-related tonal features, including GMF-band energy and absolute sideband energy. Results show moderate but statistically significant correlations between RMS, envelope peak amplitude, and tonal indicators, whereas kurtosis exhibits no meaningful association. Additionally, tonal response amplification in the damaged gearbox is shown to be non-uniformly distributed across sensor locations, indicating sensor-dependent structural sensitivity rather than uniform response growth. These findings demonstrate that broadband CM indicators partially encode changes in tonal excitation-related response, establishing a reproducible data-driven bridge between diagnostic condition monitoring and NVH excitation analysis. Full article

Coal is the primary energy source in China and has long dominated energy consumption, serving as both the cornerstone for safeguarding national energy security and the backbone of stable energy supply. Despite the gradual improvement in the level of fully mechanized and intelligent mining in recent years, as well as the remarkable progress achieved in safe and efficient mining technologies, significant challenges are still encountered in the horizontal slicing mining of steeply inclined coal seams. This study was conducted against the engineering backdrop of the steeply inclined extra-thick coal seam in the Yimen Coal Mine, Sichuan Province. A combination of theoretical analysis, FLAC3D numerical simulation, and on-site monitoring was employed to investigate the support technology for mining roadways. Considering the geological occurrence conditions, roadway dimensions, and service life, the bolt (cable) + steel strip + metal mesh system was selected as the basic support method, with shed supports supplemented for reinforcement in areas with special geological structures or fractured surrounding rock. A non-uniform roadway support technology for horizontal slicing mining of steeply inclined extra-thick coal seams was proposed. The optimal support parameters of the roadways were determined through numerical simulation, and favorable support effects were verified by field measurements. Full article

Background/Objectives: Creatine is a supplement that, beyond its physiological effects, has been shown to have positive effects on cognitive abilities. In our previous study, we showed that a single dose of 0.35 g/kg creatine induces changes in brain metabolism during sleep deprivation and reduces deterioration in cognitive performance. The present study investigates whether supplementation of a lower dose is associated with cognitive effects during sleep deprivation, focusing exclusively on cognitive performance outcomes. Methods: Twenty-nine healthy subjects performed cognitive tests at the evening baseline and 3, 5.5, and 7.5 h after receiving a single dose of creatine monohydrate (0.2 g/kg) or a placebo during a total of 21 h of sleep deprivation (SD). Results: The results show a mitigating effect of creatine on sleep deprivation-induced deterioration in logical and numerical tasks, language-related processing speed, and the Psychomotor Vigilance Test (PVT). Compared to males, females benefit more in logic, PVT and processing speed in language and logic tasks. Conclusions: Our results show that a dose of 0.2 g/kg creatine is associated with a reduced deterioration in cognitive performance during sleep deprivation. Although the effect is less pronounced than with a high dose of 0.35 g/kg, there is still an improvement of up to 12%. Full article

There are numerous ways in which generative artificial intelligence (GAI) can be applied in the teaching and learning process. This paper presents one application in the Business Decision Analysis (BDA) course. BDA is considered as the most challenging course in the Graduate Study Program in Economic Entrepreneurship at the University of Zagreb Faculty of Organisation and Informatics; consequently, the teachers continuously analyse possibilities to make the course more attractive for students. The innovative teaching activity at BDA was implemented as a betting shop during the first colloquium (which accounts for 50% of the overall grade). In the activity, GAI analysed learning management system (LMS) data of students’ results (attendance, self-assessment test results, logs in the system) of the initial (pre-course) test, as well as their results of the pub quiz (activity organised a week before the colloquium as a preparatory activity). GAI analysed all the data and predicted the number of points each student will achieve. Additionally, GAI calculated the risk index, average growth (among self-assessment tests) and learning consistency for each student. Finally, GAI created a message for each student that explained what went well in their learning activity, what could be improved, and included a motivational note for the test. The rule was: if a student achieved a higher result than the GAI predicted, the teacher would buy a chocolate for that student. More than 60% percent of students achieved a higher score than was predicted. Surprisingly, exceeding the expected result was not in correlation with the risk indices determined by the GAI. Cluster analysis identified four student profiles consistent with the correlation results, showing weak overall agreement between the predicted and achieved scores, except in the male subgroup, while higher predicted scores were associated with higher average growth and lower risk indices. Qualitative analysis of the GAI application in teaching yielded positive comments, as students perceived the activity as helpful, motivating, and engaging, and would have liked more similar activities. Full article

The puncture force during sewing is a critical factor affecting sewing quality. In this study, the puncture process is divided into five stages, a mechanical model of the puncture process is established, and a quantitative expression is achieved. Using the ANSYS Explicit Dynamics method, a finite element analysis model of the penetration process was developed to investigate the influence of fabric structure (thickness and warp and weft density) and needle geometric parameters (point height, taper angle, and shank diameter) on penetration force. The results indicate the following: Two distinct force peaks occur during needle penetration—one at the instant of fabric piercing and another when the needle shaft enters the fabric. Increasing fabric thickness causes the former peak to rise significantly, while the latter peak increases more gradually. Puncture force decreases significantly with reduced warp and weft density. When density decreased from 85 × 85 TPI to 80 × 80 TPI, the first peak decreased by 18.5% and the second peak by 67.4%. A further decrease in warp and weft density to 75 × 75 TPI resulted in peak reductions of 58.48% and 20.64%, respectively. Additionally, the needle tip cone angle and tip height are critical parameters affecting the peak penetration force. The comparative analysis of improved standard needle tip cone angles and tip heights demonstrates that the modified machine needles exhibit lower peak penetration forces, confirming the effectiveness of the needle improvement methods proposed in this study. The research methodology and results presented herein provide an effective numerical simulation-based approach for needle selection and penetration force evaluation in fabric piercing and sewing. Full article

This wind farm study provides a detailed and deep investigation into numerous aspects of both wind dynamics and the associated wind turbine performance via a wind data analysis utilizing an extrapolated timeframe of 50 years. The major wind characteristics assessed included wind speed and direction, flow inclination, turbulence intensity, and wind speed (average based on extremes) over the entire duration of the evaluated data set. A majority of study results indicated only narrow wind speed ranges (6.3 m/s to 7.0 m/s) for turbine operation within the wind farm. Higher turbine operation speeds than the average measured wind speed may significantly increase turbine energy output. Turbines were evaluated across numerous geographic locations, resulting in average flow inclination (−4.12° to 1.57°) from the vertical to horizontal directions. The variation in flow inclination indicates that there is a geographic component that likely creates a localized terrain impact on turbine performance. Similarly, the measurement of turbulence intensity was also assessed, which indicated elevated levels of turbine mechanical stress and additional requirements for turbine maintenance. Energy production analyses from each turbine in the wind farm exhibited various regions of energy loss, with the highest energy losses associated with select turbines. Full article

This study addresses a two-dimensional anomalous solute transport process within a two-zone fractal porous medium. A mathematical formulation is developed to characterise transport phenomena in a non-homogeneous porous domain. The medium consists of two interacting regions: one containing mobile fluid and the other containing immobile fluid, between which mass transfer occurs. In the mobile-fluid region, solute transport is governed by the convection–diffusion equation. In contrast, the immobile-fluid region is described using a first-order kinetic model. The problem of solute injection through a designated boundary point is formulated and numerically implemented. The effects of anomalous transport behaviour on solute migration and filtration characteristics are examined. The study further evaluates the pressure field, filtration velocity distribution, and solute concentration in both zones. Full article

Aluminum–vanadium (Al–V) master alloy is a key raw material for manufacturing high-end alloys, but the internal temperature transient field during its self-propagating high-temperature synthesis (SHS) is nearly impossible to measure in situ. This work develops a numerical simulation framework for Al–V master alloy SHS, featuring a novel temperature–time dual-criteria adaptive moving heat source and a gas–liquid–solid three-phase heat transfer model coupled with temperature-dependent thermophysical properties. The model, implemented in ANSYS Fluent via a customized user-defined function (UDF), is experimentally validated with a maximum temperature error below 7%. Results reveal that higher compact relative density accelerates combustion wave propagation, while increased slagging agent content exerts an inhibitory effect. This study provides a theoretical and quantitative tool for mechanism analysis and industrial process optimization of Al–V master alloy SHS production. Full article

In recent years, fractional HIV models have received increasing attention. This study derives a fractional HIV model using the continuous-time random walk (CTRW) method, endowing the mathematical model with physical significance. Based on the transmission characteristics of HIV, the proposed model considers extrinsic infectivity, intrinsic infectivity, and drug control, specifically as follows: the extrinsic infectivity is a constant independent of the infection time; the intrinsic infectivity is a power-law function that depends on drug efficacy and infection time; the drug efficacy rate follows a Mittag–Leffler distribution with a long-term effect. Based on these considerations, a fractional HIV model with drug control is established in this paper. In addition, the global asymptotic stability of the equilibrium and the sensitivity analysis of the basic reproduction number $R_0$ are studied, and the theoretical results are verified by numerical simulations. The results show that reducing extrinsic infectivity, controlling intrinsic infectivity, and the drug efficacy rate are crucial in controlling the spread of HIV. Full article

This work presents an evaluation of the effectiveness of active ventilation methods compared to passive ventilation methods in a typical B + GF + 9 building, focusing on the impact of burner height location on smoke control performance. The numerical model was validated using a full-scale room fire experiment involving a 4350 kJ/s wood crib load, where the HRR was calibrated via the mass loss method, achieving an RMSE of 210 kW and MRE of 5.04%. FDS simulations were conducted across six scenarios involving burners on the ground, fifth, and ninth floors. The findings demonstrate that, while natural ventilation allows the stairwell to reach lethal conditions with temperatures exceeding 180 °C and CO concentrations above 0.24%, the implementation of top-level mechanical pressurization maintains temperatures below the 60 °C tenability threshold. The mechanical ventilation system extended the Available Safe Egress Time (ASET) by 75% to 110%, with effectiveness increasing as the burner elevation approached the fan location. Overall, the study provides a validated approach for transforming stairwells into protected refuge zones in existing mid-rise buildings. Overall, merging empirical with computational methods is a proven basis for simulating scaled-up, complicated layouts. This guarantees accurate initial conditions when analyzing urban fire emergencies. Full article

Fuel cell technologies are increasingly investigated as alternatives to conventional auxiliary diesel generators in order to enhance shipboard energy efficiency and reduce greenhouse gas emissions. This study presents a unified and uncertainty-driven system-level assessment of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) systems operating as auxiliary power sources on a 200 m bulk carrier. Both technologies are evaluated under identical vessel characteristics, operating profiles, auxiliary load levels (360–600 kW), and cost assumptions, and are benchmarked directly against a conventional three–diesel-generator configuration. A modular numerical framework is developed to model propulsion–auxiliary interactions for ship speeds between 10 and 14 knots. SOFC systems are assessed using grey, bio-derived, and green natural gas pathways, while PEMFC systems are examined under grey, blue, and green hydrogen supply routes. Performance indicators include annual fuel consumption, carbon dioxide (CO₂) emission reduction, net present value (NPV), internal rate of return (IRR), payback period (PBP), and marginal abatement cost (MAC). Economic uncertainty is explicitly embedded in the framework through Monte Carlo simulation, where fuel prices (±20%) and capital costs are sampled across defined ranges, generating probabilistic distributions rather than single deterministic estimates. This uncertainty-centred approach enables assessment of robustness, downside risk, and probability of profitability. Results show that replacing a single operating 600 kW diesel generator with fuel cell systems reduces auxiliary fuel energy demand by 25–35% for SOFC and approximately 15–25% for PEMFC relative to the diesel benchmark. Annual CO₂ reductions range from 1.1 to 1.3 kt for SOFC systems and 1.8–2.8 kt for PEMFC configurations. Under grey fuel pathways, median NPVs reach approximately 2–4.5 M$ for SOFC and 9–17 M$ for PEMFC as load increases, with IRRs exceeding 15% and 30%, respectively. Transitional pathways exhibit narrower margins, while renewable pathways remain more sensitive to fuel price variability. The findings demonstrate that fuel pathway cost dominates lifecycle outcomes under uncertainty and that hydrogen-based PEMFC systems exhibit the strongest economic resilience within the examined market ranges. The framework provides structured, uncertainty-aware decision support and establishes a foundation for integration into model-based systems engineering (MBSE) environments for early stage ship energy system design. Full article

This study presents the results of shell-side pressure drop calculations for a model shell-and-tube heat exchanger with an inner shell diameter of 200 mm and an effective tube length of 518 mm. The tube bundle consisted of 85 copper tubes (12/10 mm) arranged in a staggered layout with a pitch ratio of 1.5. The exchanger contained nine segmental baffles with a 25% cut, spaced 48 mm apart. The mean temperature of the hot water flowing on the shell side was 69 °C, and the mass flow rate varied in the range of 1–6 kg/s. In particular, the effects of the tube bundle diameter, nozzle diameter, and sealing strips on the pressure drop were investigated. The calculations employed the extended Bell–Delaware method and the VDI method. The results were compared with calculations performed using Aspen EDR and with numerical simulations carried out in OpenFOAM and Ansys Fluent. The comparison shows that the difference in total pressure drop estimation can reach up to 40% depending on the method used. Full article

Bioethics education has become established as an essential component for addressing the ethical challenges associated with biomedical development, biotechnology, and decision-making in the healthcare field. Although numerous studies have analyzed the teaching of bioethics among medical students and other health professions, empirical research on bioethics literacy in religious formation contexts remains limited. The objective of this study was to evaluate the level of bioethical knowledge (here operationalized as bioethics literacy) among Catholic seminarians in Colombia and to explore the psychometric properties of a questionnaire designed to measure bioethics literacy in this population. A cross-sectional observational study was conducted through the administration of a structured questionnaire consisting of 32 multiple-choice items with a single correct answer addressing philosophical foundations, personalist bioethics, bioethical principles, clinical bioethics, and issues related to biotechnology. A total of 216 complete questionnaires were analyzed using descriptive statistics and exploratory psychometric analyses, including item difficulty and discrimination, internal consistency, and exploratory factor analysis. The results showed a moderate overall level of bioethics literacy, with better performance in applied domains such as clinical bioethics and bioethical principles, and lower levels of correct responses in philosophical foundations and personalist bioethics. The questionnaire showed moderate internal consistency and a preliminary factorial structure, suggesting its usefulness as an exploratory tool for assessing bioethical knowledge in seminary educational contexts. These results highlight the importance of strengthening the integration between philosophical and theological education and the applied analysis of bioethical problems in seminary educational programs. Full article

In karst tunnel engineering, water-filled cavities located above the tunnel crown, under the combined effects of excavation disturbance and hydraulic pressure, are prone to triggering water and mud inrush disasters. The thickness of the water-resisting rock layer is therefore a key factor controlling the stability of the surrounding rock. To address the difficulty in accurately characterizing the mechanical behavior of the crown of horseshoe-shaped tunnels using conventional circular plate or beam models, this study innovatively develops an explicit analytical model for the minimum safe thickness of the water-resisting rock layer based on clamped elliptical thin plate theory and Kirchhoff plate theory, incorporating the influence of cross-sectional geometry. Parametric sensitivity analysis indicates that both karst water pressure and tunnel crown height significantly amplify the required minimum safe thickness, whereas an increase in the tensile strength of the surrounding rock effectively reduces the thickness demand. Specifically, when the karst water pressure increases from 2.5 MPa to 4.5 MPa, the minimum safe thickness rises from 7.5 m to 10.0 m, showing an approximately linear growth trend. The analytical model is further validated through numerical simulations under different “water pressure–thickness” conditions. The results demonstrate that at the calculated recommended thickness, the surrounding rock achieves stable convergence after excavation. High tensile stress and elevated pore pressure zones are mainly concentrated near the tunnel crown, without the formation of through-going tensile failure. Engineering application indicates that the proposed model can provide a quantitative basis for the design of water-resisting rock layer thickness and the assessment of water inrush risk in karst tunnels. Full article