Search Results (217)

This study aims to investigate the differences in the effects of spraying and immersing methods on edible coatings for halved and pitted plums. Earlier studies have shown that these biodegradable packaging materials can preserve the quality and safety of fruits for an extended shelf life. Halved and pitted plums (variety Stanley) were treated with chitosan and rosehip oil edible coating emulsions by spraying and immersing methods. The treated series were analyzed by physical, physicochemical, microbiological, and sensorial methods during refrigerated storage for nine days, until the onset of microbiological spoilage. At the beginning of the storage, there was a visible difference between the differently treated samples. The untreated series showed the fastest browning. The emulsion-sprayed samples presented the least changes in color, shape, and volume. A weaker effect of the immersion technique can be explained by a deep standing of the fruits in a treating solution or emulsion. Some of the immersed samples have an aqueous texture and received a smaller sensory rating. The advantages and disadvantages of the methods need further investigation, but on a production scale, spraying can guarantee uniform batches. In laboratory circumstances, immersion is an easier method that does not need expensive and difficult-to-use equipment and gives good results. Full article

Corrosion fatigue damage significantly affects the long-term service of marine platforms such as propellers. Fatigue testing of pre-corrosion specimens is essential for understanding damage mechanisms and accurately predicting fatigue life. However, traditional seawater-based tests are time-consuming and yield inconsistent results, making them unsuitable for rapid evaluation of newly developed equipment. This study proposes an accelerated corrosion testing method for ZCuAl₈Mn₁₃Fe₃Ni₂ nickel–aluminum bronze, simulating the marine full immersion zone by increasing temperature, adding H₂O₂, reducing the solution pH, and preparing the special solution. Coupled with the fatigue test of pre-corrosion specimens, the corrosion damage characteristics and their influence on fatigue performance were analyzed. A numerical simulation method was developed to predict the fatigue life of pre-corrosion specimens, showing an average error of 13.82%. The S–N curves under different pre-corrosion cycles were also established. The research results show that using the test solution of 0.6 mol/L NaCl + 0.1 mol/L H₃PO₄-NaH₂PO₄ buffer solution + 1.0 mol/L H₂O₂ + 0.1 mL/500 mL concentrated hydrochloric acid for corrosion acceleration testing shows good corrosion acceleration. Moreover, the test methods ensure accuracy and reliability of the fatigue behavior evaluation of pre-corrosion specimens of the structure under actual service environments, offering a robust foundation for the material selection, corrosion resistance evaluation, and fatigue life prediction of marine structural components. Full article

Promoting domestic fire safety is crucial for preventing and effectively managing risky situations. This study evaluated the effectiveness of virtual environments (VEs) in fire drills to improve citizens’ knowledge and safe behavior in domestic settings. Conducted at the Citizen School for Risk Prevention (CSRP) in Zaragoza (Spain), the experiment involved 20 participants facing a simulated kitchen fire using a combination of physical and virtual extinguishing equipment. A theoretical session accompanied the drills to reinforce learning. Participants were divided into two groups: one completed the drill before and after the theoretical session, while the other completed it only afterward. Performance was assessed based on the ability to extinguish, control, or lose control of the fire. Surveys administered before, immediately after, and three months after training measured knowledge retention and behavioral changes. The results indicate a significant improvement in fire safety awareness and lasting adoption of safe practices. Participants also emerged as safety advocates. This study highlights the potential of combining theoretical instruction with immersive practical training and identifies strategies for replicating this approach in other prevention schools. Full article

As the key non-electric protection equipment of an oil-immersed transformer, the gas relay plays an important role in ensuring the safe operation of the transformer. To further enhance the sensitivity of gas relays for the heavy gas alarm, this paper takes the BF type double float gas relay as the research object and proposes a new method for heavy gas setting, which is based on the internal oil flow acceleration characteristics of the gas relay. Firstly, the analytical derivation of the force acting on the gas relay baffle is carried out, and through theoretical analysis, the internal mechanism of heavy gas action under transient oil flow excitation is revealed. Then, the numerical simulation and experimental research on the variation of oil flow velocity and acceleration under different fault energies are carried out. The results show that with the increase of fault energy, the oil flow velocity fluctuates up and down during heavy gas action, but the oil flow acceleration shows a linear correlation. The oil flow acceleration can be set as the threshold of heavy gas action, and the severity of the fault can be judged. At the same time, the alarm time of the heavy gas setting method based on the oil flow acceleration characteristics is greatly shortened, which can reflect the internal fault of the transformer in time and significantly improve the sensitivity of the heavy gas alarm. Full article

This study examines first responder training to deliver realistic, adaptable, and scalable solutions aimed at equipping personnel to handle high-risk, rapidly developing scenarios. The proposed method leverages Virtual Reality, Augmented Reality, and digital twins to enable immersive and situationally relevant training for security-critical incidents. The method is structured into three distinct phases: definition, digitization, and implementation. The outcome of this approach is the creation of virtual training scenarios that simulate real situations and incident dynamics. The methodology employs photogrammetric reconstruction, simulation of human behavior through locomotion, and virtual security systems, such as surveillance and drone technology. Alongside the methodology, a case study of a large public event is presented to illustrate its feasibility in real-world applications. This study offers a comprehensive and adaptive structure for the design and deployment of digitally augmented training systems. This provides a practical basis for enhancing readiness in a range of operational domains. Full article

The paper presents the innovative approach to a high-fidelity motorcycle riding simulator based on VR (Virtual Reality)-visualization, equipped with a Gough-Stewart 6-DOF (Degrees of Freedom) motion platform. Such a solution integrates a real-time tension sensor system as a source for highly realistic motion cueing control as well as the servomotor integrated into the steering system. Tension forces are measured at four points on the mock-up chassis, allowing a comprehensive analysis of rider interaction during various maneuvers. The simulator is developed to simulate realistic riding scenarios with immersive motion and visual feedback, enhanced with the simulation of external influences—headwind. This paper presents results of a validation study—pilot experiments conducted to evaluate selected riding scenarios and validate the innovative simulator setup, focusing on force distribution and system responsiveness to support further research in motorcycle HMI (Human–Machine Interaction), rider behavior, and training. Full article

Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. The performance of six machine learning classifiers was systematically evaluated using training and testing data generated through four widely recognized gas ratio schemes. Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. Across all the diagnostic approaches, ensemble models, namely random forest, XGBoost, and LightGBM, consistently outperformed non-ensemble models. Notably, random forest and LightGBM classifiers demonstrated the most robust and superior performance across all schemes, achieving accuracy, precision, recall, and F1 scores between 0.99 and 1, along with Matthew correlation coefficient values exceeding 0.98 in all cases. This robustness suggests that ensemble models are effective at capturing complex decision boundaries and relationships among gas ratio features. Furthermore, beyond numerical classification, the integration of physicochemical and dielectric properties in this study revealed degradation signatures that strongly correlate with thermal fault indicators. Particularly, the CIGRÉ-based classification using a random forest classifier demonstrated high sensitivity in detecting thermally stressed units, corroborating trends observed in chemical deterioration parameters such as interfacial tension and CO₂/CO ratios. Access to over 80 years of operational data provides a rare and invaluable perspective on the long-term performance and degradation of power equipment. This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems. Full article

With the rapid development of marine renewable energy, especially offshore photovoltaic systems, the problem of biofouling of photovoltaic equipment in the marine environment has become increasingly prominent. The attachment of marine organisms such as algae will significantly affect the photoelectric conversion efficiency of photovoltaic panels, thereby reducing the stability and economy of the system. In this study, a composite siloxane coating was designed and prepared. Methyltrimethoxysilane (MTMS) was used as the organosilicon component. The negative potential of the coating was significantly enhanced by incorporating hexagonal boron nitride nanosheets (h-BNNS). This negative potential and the negative charge on the surface of marine organisms, especially algae, would produce electrostatic repulsion, which can effectively reduce the attachment of organisms. The results show that the prepared coating exhibits excellent performance in anti-biofouling, adhesion, chemical stability, transparency, and self-cleaning properties. The transparency of the coating reached 92.7%. After immersion with Chlorella for 28 days, the coverage percentage on the coating surface was only 0.98%, while the coverage percentage on the blank sample was 23.25%. The corrosion resistance and salt resistance of the coating also ensure its stability in complex marine environments, and it has broad application prospects. Full article

This paper presents an integrated methodology for remote monitoring, technical training and early warning systems in virtual reality environments oriented towards Industry 4.0. The proposal incorporates an engine modeled as a digital twin in Unity 3D, connected to physical sensors, and transmitted through an IoT platform. This architecture allows continuous monitoring and immersive visualization, in addition to generating alerts when operating conditions exceed critical limits, allowing users to simulate fault conditions in real time and perform interactive training without putting equipment or operators at risk. This work proposes a low-cost simulation platform, based on virtual reality and real-time digital twins, designed to support training and capacity building in industrial environments. This methodology seeks to propose general guidelines that allow the integration of these technologies in a general way to enrich both preventive and predictive maintenance mechanisms, as well as training processes. Full article

This study presents a novel investigation into immersive teleoperation systems using collaborative, device-agnostic interfaces for advancing smart haptics in industrial assistive applications. The research focuses on evaluating the quality of experience (QoE) of users interacting with a teleoperation system comprising a local robotic arm, a robot gripper, and heterogeneous remote tracking and haptic feedback devices. By employing a modular device-agnostic framework, the system supports flexible configurations, including one-user-one-equipment (1U-1E), one-user-multiple-equipment (1U-ME), and multiple-users-multiple-equipment (MU-ME) scenarios. The experimental set-up involves participants manipulating predefined objects and placing them into designated baskets by following specified 3D trajectories. Performance is measured using objective QoE metrics, including temporal efficiency (time required to complete the task) and spatial accuracy (trajectory similarity to the predefined path). In addition, subjective QoE metrics are assessed through detailed surveys, capturing user perceptions of presence, engagement, control, sensory integration, and cognitive load. To ensure flexibility and scalability, the system integrates various haptic configurations, including (1) a Touch kinaesthetic device for precision tracking and grounded haptic feedback, (2) a DualSense tactile joystick as both a tracker and mobile haptic device, (3) a bHaptics DK2 vibrotactile glove with a camera tracker, and (4) a SenseGlove Nova force-feedback glove with VIVE trackers. The modular approach enables comparative analysis of how different device configurations influence user performance and experience. The results indicate that the objective QoE metrics varied significantly across device configurations, with the Touch and SenseGlove Nova set-ups providing the highest trajectory similarity and temporal efficiency. Subjective assessments revealed a strong correlation between presence and sensory integration, with users reporting higher engagement and control in scenarios utilizing force feedback mechanisms. Cognitive load varied across the set-ups, with more complex configurations (e.g., 1U-ME) requiring longer adaptation periods. This study contributes to the field by demonstrating the feasibility of a device-agnostic teleoperation framework for immersive industrial applications. It underscores the critical interplay between objective task performance and subjective user experience, providing actionable insights into the design of next-generation teleoperation systems. Full article

Metal casting foundries present hazardous working conditions, making traditional training methods costly, time-consuming, and potentially unsafe. To address these challenges, this study presents a Virtual Reality (VR) training framework developed for the Tennessee Tech University (TTU) Foundry. The objective is to enhance introductory training and safety education by providing an immersive, interactive, and risk-free environment where trainees can familiarize themselves with safety protocols, equipment handling, process workflows, and machine arrangements before engaging with real-world operations. The VR foundry environment is designed using Unreal Engine, a freely available software tool, to create a high-fidelity, interactive simulation of metal casting processes. This system enables real-time user interaction, scenario-based training, and procedural guidance, ensuring an engaging and effective learning experience. Preliminary findings and prior research indicate that VR-based training enhances learning retention, improves hazard recognition, and reduces training time compared to traditional methods. While challenges such as haptic feedback limitations and initial setup costs exist, VR’s potential in engineering education and industrial training is substantial. This work-in-progress study highlights the transformative role of VR in foundry training, contributing to the development of a safer, more efficient, and scalable workforce in the metal casting industry. Full article

Virtual Reality (VR) has emerged as a promising tool for history education, offering immersive and interactive learning experiences. However, its implementation in educational settings presents several challenges that remain under-explored. This systematic review, conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology, aims to identify the main technical, usability, economic, psychological, social, and ethical challenges associated with the use of VR in history teaching. A literature search was performed in the Scopus (Elsevier) database, retrieving 2794 studies, from which a final selection of 14 papers was made based on predefined eligibility criteria. The findings indicate that interoperability issues, high hardware and software requirements, and navigation difficulties hinder VR integration. Moreover, usability concerns, including complex interfaces and cognitive overload, affect both students and educators, emphasizing the need for specialized teacher training. Economic barriers, such as the high cost of VR equipment and software, limit accessibility in resource-constrained institutions. Additionally, psychological and social challenges, including user discomfort, confusion between reality and fiction, and ethical concerns, were identified. These findings highlight the necessity of addressing these limitations to optimize VR’s pedagogical potential in history education. Future research should focus on developing cost-effective solutions, enhancing usability, and designing comprehensive training programs to facilitate the effective adoption of VR in educational contexts. Full article

The rapid emergence of Industry 4.0 technologies has transformed manufacturing, requiring a workforce skilled in automation, data-driven decision-making, and process optimisation. While traditional education includes structured formats such as lectures and tutorials, it may not always equip graduates with the hands-on expertise demanded by modern industrial challenges. This study presents a Mixed Reality (MR)-based educational framework that promotes interactive experiences to enhance students’ engagement with and understanding of Industry 4.0 concepts, aiming to bridge the skills gap through immersive Virtual Learning Factories (VLFs). The framework was developed using a mixed-methods approach, combining qualitative feedback with quantitative benchmarking. A proof-of-concept MR application was developed and tested at the (Anonymised), simulating Industry 4.0 scenarios in an engineering education context to validate the framework. The findings indicate that MR-based learning improved students’ engagement with the academic content, leading to better knowledge retention and deeper conceptual understanding. The students also demonstrated enhanced problem-solving, process optimisation, and adaptability compared to traditional methods. The immersive nature of MR provided an interactive, context-rich environment that fostered active learning. This research highlights MR’s potential as a transformative educational tool, aligning academic training with industry needs. Future research is recommended to evaluate the framework’s scalability and long-term effectiveness. Full article

To address the protective demands of marine engineering equipment in complex corrosive environments, this study proposes an environmentally friendly composite coating based on carboxylated graphene oxide (CGO)-modified water-based epoxy organosilicon resin. By incorporating varying mass fractions (0.05–0.25%) of CGO into the resin matrix via mechanical blending, the microstructure, corrosion resistance, and long-term corrosion kinetics of the coatings were systematically investigated. The results demonstrate that the coating with 0.15 wt.% CGO (designated as KCG15) exhibited optimal comprehensive performance: its corrosion current density (I_corr = 4.37 × 10⁻⁸ A/cm²) was two orders of magnitude lower than that of the pure resin coating, while its low-frequency impedance modulus (∣Z∣_0.1Hz = 4.99 × 10⁶ Ω⋅cm²) is significantly enhanced, accompanied by improved surface compactness. The coating achieved a 97% inhibition rate against sulfate-reducing bacteria (SRB) through synergistic physical disruption and electrostatic repulsion mechanisms. Long-term corrosion kinetics analysis via 60-day seawater immersion identified three degradation phases—permeation (0–1 day), blockage (1–4 days), and failure (7–60 days)—with structural evolution from microcrack networks to foam-like blistering ultimately reducing by 97.8%. Furthermore, a 180-day atmospheric exposure test confirms the superior weatherability and adhesion of the KCG15 coating, with only minor discoloration observed due to its hydrophobic surface. This work provides theoretical and technical foundations for developing marine anti-corrosion coatings that synergize environmental sustainability with long-term protective performance. Full article

To address the key challenges of poor real-time interaction, insufficient integration of operating rules, and limited virtual–physical synergy in current carrier-based aircraft scheduling simulations, this study proposes an immersive digital twin platform that integrates a two-layer genetic algorithm (GA) with hardware-in-the-loop (HIL) semi-physical validation. The platform architecture combines high-fidelity 3D visualization-based modeling (of aircraft, carrier deck, and auxiliary equipment) with real-time data exchange via TCP/IP, establishing a collaborative virtual–physical simulation environment. Three key innovations are presented: (1) a two-tier genetic algorithm (GA)-based scheduling model is proposed to coordinate global planning and dynamic execution optimization for carrier-based aircraft operations; (2) a systematic constraint integration framework incorporating aircraft taxiing dynamics, deck spatial constraints, and safety clearance requirements into the scheduling system, significantly enhancing tactical feasibility compared to conventional approaches that oversimplify multidimensional operational rules; (3) an integrated virtual–physical simulation architecture merging virtual reality interaction with HIL verification, establishing a collaborative digital twin–physical device platform for immersive visualization of full-process operations and dynamic spatiotemporal evolution characterization. Experimental results indicate that this work bridges the gap between theoretical scheduling algorithms and practical naval aviation requirements, offering a standardized testing platform for intelligent carrier-based aircraft operations. Full article