Search Results (1,060)

This study investigates the hydrodynamic performance of ships entering a ship lift compartment that is under the influence of upstream channel geometry and proposes a mechanical traction scheme to enhance operational safety and efficiency. Utilizing a Reynolds-averaged Navier–Stokes (RANS)-based computational fluid dynamics (CFD) approach with overlapping grid technology, numerical simulations were conducted for both single and grouped ships navigating through varying water depths, speeds, and shore distances. The results revealed significant transverse force oscillations near the floating navigation wall due to unilateral shore effects, posing risks of deviation. The cargo ship experienced drastic resistance fluctuations in shallow-to-very-shallow-water transitions, while tugboats were notably affected by hydrodynamic interactions during group entry. A mechanical traction system with a four-link robotic arm was designed and analyzed kinematically and statically, demonstrating structural feasibility under converted real-ship traction forces (55.1 kN). The key findings emphasize the need for collision avoidance measures in wall sections and validate the proposed traction scheme for safe and efficient ship entry/exit. This research provides critical insights for optimizing ship lift operations in restricted waters. Full article

The demand for large-scale, heavy-duty autonomous pavement-sweeping robots is rising due to urban growth, hygiene needs, and labor shortages. Ensuring their health and safe operation in dynamic outdoor environments is vital, as terrain unevenness and slope gradients can accelerate wear, increase maintenance costs, and pose safety risks. This study introduces an AI-driven condition monitoring (CM) framework designed to detect terrain unevenness and slope gradients in real time, distinguishing between safe and unsafe conditions. As system vibration levels and energy consumption vary with terrain unevenness and slope gradients, vibration and current data are collected for five CM classes identified: safe, moderately safe terrain, moderately safe slope, unsafe terrain, and unsafe slope. A simple-structured one-dimensional convolutional neural network (1D CNN) model is developed for fast and accurate prediction of the safe to unsafe classes for real-time application. An in-house developed large-scale autonomous pavement-sweeping robot, PANTHERA 2.0, is used for data collection and real-time experiments. The training dataset is generated by extracting representative vibration and heterogeneous slope data using three types of interoceptive sensors mounted in different zones of the robot. These sensors complement each other to enable accurate class prediction. The dataset includes angular velocity data from an IMU, vibration acceleration data from three vibration sensors, and current consumption data from three current sensors attached to the key motors. A CM-map framework is developed for real-time monitoring of the robot by fusing the predicted anomalous classes onto a 3D occupancy map of the workspace. The performance of the trained CM framework is evaluated through offline and real-time field trials using statistical measurement metrics, achieving an average class prediction accuracy of 92% and 90.8%, respectively. This demonstrates that the proposed CM framework enables maintenance teams to take timely and appropriate actions, including the adoption of suitable maintenance strategies. Full article

Introduction: Near-infrared fluorescence (NIRF) imaging with indocyanine green (ICG) is now widely regarded as a valuable aid in decision-making for complex hepatobiliary procedures, with increasing support from recent studies. Methods: We performed a systematic review following PRISMA guidelines, utilizing PubMed, CINAHL, and EMBASE databases to locate studies on the perioperative use ICG in pediatric hepatobiliary surgeries. Two independent reviewers assessed all articles for eligibility based on predefined inclusion criteria. We collected data on study design, patient demographics, surgical indications, ICG dosing, timing of ICG injection, and perioperative outcomes. Results: Forty-three articles, including 930 pediatric patients, from 1989 to 2025 met the inclusion criteria for narrative synthesis in our systematic review, of which 22/43 (51.2%) were retrospective studies, 15/43 were case reports (34.9%), 3/43 (7.0%) were experimental studies, and the other three were prospective comparative studies (7.0%). The current clinical applications of ICG in hepatobiliary pediatric surgery include bile duct surgery (cholecystectomy, choledochal cyst, biliary atresia), reported in 17 articles (39.5%), liver tumor resection, reported in 15 articles (34.9%), liver transplantation, reported in 6 articles (14.6%), and liver function determination, reported in 5 articles (12.2%). Conclusions: ICG fluorescence navigation in pediatric hepatobiliary surgery is a highly promising and safe technology that allows for the intraoperative localization of anatomic biliary structures, aids in the identification and resection of liver tumors, and can accurately determine hepatic function. The lack of comparative and prospective studies, and the variability of the dose and timing of administration are the main limitations. Full article

The growing consumption of oil and gas resources and the increasing difficulty of extraction have created major challenges for traditional manufacturing and maintenance, particularly in the timely supply of critical components, customized production, and complex structure fabrication. Additive manufacturing (AM) technology, with its high design freedom, precision, and rapid prototyping, provides new approaches to address these issues. However, systematic reviews of related efforts are scarce. This paper reviews the applications and progress of metal and non-metal AM technologies in oil and gas extraction and gathering engineering, focusing on the just-in-time (JIT) manufacturing of failed components, the manufacturing and repair of specialized equipment and tools for oil and gas extraction and gathering, and artificial core and reservoir geological modeling fabrication. AM applications in this field remain exploratory and face challenges with regard to their standards, supply chains, materials, and processes. Future research should emphasize developing materials and processes for extreme conditions, optimizing process parameters, establishing standards and traceability systems, and integrating AM with digital design and reverse engineering to support efficient, safe, and sustainable industry development. This work aims to provide a reference for advancing AM research and engineering applications in the oil and gas sector. Full article

Aero-engine casings with excellent impact resistance are a practical requirement for ensuring the safe operation of aero-engines. In this paper, we report on numerical simulations of broken rotating blades impacting aluminum honeycomb sandwich casings under different temperatures and optimization of structural parameters. Firstly, an impact test system with adjustable temperature was established. Restricted by the temperature range of the strain gauge, ballistic impact tests were carried out at 25 °C, 100 °C, and 200 °C. Secondly, a finite element (FE) model including a pointed bullet and an aluminum honeycomb sandwich plate was built using LS-DYNA. The corresponding simulations of the strain–time curve and damage conditions showed good agreement with the test results. Then, the containment capability of the aluminum honeycomb sandwich aero-engine casing at different temperatures was analyzed based on the kinetic energy loss of the blade, the internal energy increment of the casing, and the containment state of the blade. Finally, with the design objectives of minimizing the casing mass and maximizing the blade kinetic energy loss, the structural parameters of the casing were optimized using the multi-objective genetic algorithm (MOGA). Full article

Concrete is a fundamental material in structural engineering, widely used in critical infrastructure such as bridges, nuclear power plants, and dams. These structures may be subjected to extreme dynamic loads resulting from natural disasters, industrial accidents, or missile impacts. Therefore, a comprehensive understanding of concrete behavior under high strain rates is essential for safe and resilient design. Experimental investigations, particularly spalling tests, have highlighted the strain-rate sensitivity of concrete in dynamic tensile loading conditions. This study presents a macroscopic 3D discrete element model specifically developed to simulate the dynamic response of concrete subjected to extreme loading. Unlike conventional continuum-based models, the proposed discrete element framework is particularly suited to capturing damage and fracture mechanisms in cohesive materials. A key innovation lies in incorporating a physically grounded strain-rate dependency directly into the local cohesive laws that govern inter-element interactions. The originality of this work is further underlined by the validation of the discrete element model under dynamic tensile loading through the simulation of spalling tests on normalstrength concrete at strain rates representative of severe impact scenarios (30–115 s⁻¹). After calibrating the model under quasi-static loading, the simulations accurately reproduce key experimental outcomes, including rear-face velocity profiles and failure characteristics. Combined with prior validations under high confining pressure, this study reinforces the capability of the discrete element method for modeling concrete subjected to extreme dynamic loading, offering a robust tool for predictive structural assessment and design. Full article

Modeling accident investigation reports is crucial for elucidating accident causation mechanisms, analyzing risk evolution processes, and formulating effective accident prevention strategies. However, such reports are typically long, hierarchically structured, and information-dense, posing unique challenges for existing language models. To address these domain-specific characteristics, this study proposes SAFE-Transformer, a Structure-Aware and Format-Enhanced Transformer designed for long-document modeling in the emergency safety context. SAFE-Transformer adopts a dual-stream encoding architecture to separately model symbolic section features and heading text, integrates hierarchical depth and format types into positional encodings, and introduces a dynamic gating unit to adaptively fuse headings with paragraph semantics. We evaluate the model on a multi-label accident intelligence classification task using a real-world corpus of 1632 official reports from high-risk industries. Results demonstrate that SAFE-Transformer effectively captures hierarchical semantic structure and outperforms strong long-text baselines. Further analysis reveals an inverted U-shaped performance trend across varying report lengths and highlights the role of attention sparsity and label distribution in long-text modeling. This work offers a practical solution for structurally complex safety documents and provides methodological insights for downstream applications in safety supervision and risk analysis. Full article

This paper presents the construction and analysis of a novel class of alternant codes over Gaussian integers, aimed at enhancing error correction capabilities in high-reliability communication systems. These codes are constructed using parity-check matrices derived from finite commutative local rings with unity, specifically ${\mathbb{Z}}_n\left[i\right],$ where $i^2=-1$. A detailed algebraic investigation of the polynomial $x^n-1$ over these rings is conducted to facilitate the systematic construction of such codes. The proposed alternant codes extend the principles of classical BCH and Goppa codes to complex integer domains, enabling richer algebraic structures and greater error-correction potential. We evaluate the performance of these codes in terms of error correction capability, and redundancy. Numerical results show that the proposed codes outperform classical short-length codes in scenarios requiring moderate block lengths, such as those applicable in certain segments of 5G and IoT networks. Unlike conventional codes, these constructions allow enhanced structural flexibility that can be tuned for various application-specific parameters. While the potential relevance to quantum-safe communication is acknowledged, it is not the primary focus of this study. This work demonstrates how extending classical coding techniques into non-traditional algebraic domains opens up new directions for designing robust and efficient communication codes. Full article

With the development and application of electric vehicles powered by lithium-ion batteries (LIBs) at high altitude, the lack of research on the aging laws and mechanisms of LIBs under a low-pressure aviation environment has become an important obstacle to their safe application. Herein, the influences and mechanisms of high-altitude and low-pressure environment (50 kPa) on the cycling performance of commercial pouch LIBs were systematically studied. The results showed that low air pressure caused a sharp decrease in battery capacity to 46.6% after 200 cycles, with a significant increase in charge transfer impedance by 70%, and the contribution rate of active lithium loss reached 74%. Low air pressure led to irreversible deformation of the battery, resulting in the expansion of the gap between the electrodes, poor electrolyte infiltration, and reduction of the effective lithium insertion area, which in turn induced multiple synergistic accelerated decay mechanisms, including obstructed lithium-ion transmission, reduced interfacial reaction efficiency, increased active lithium consumption, changes in heat generation structure, and a significant increase in heat generation. After applying external force, the deformation of the electrode was effectively suppressed, and the cycle capacity retention rate increased to 87.6%, which significantly alleviated the performance degradation of LIBs in low pressure environment. This work provides a key theoretical basis and engineering solutions for the design of power batteries in high-altitude areas. Full article

The safe transport of cylindrical loads such as metal, paper, or polymer rollers requires specialized securing structures that address the complex dynamic forces encountered during rail movement. This paper presents a structured methodology for the design and verification of such securing systems, combining theoretical analysis, standardized load models, and numerical simulations. The method includes load calculations based on EN 12195-1:2010, EN 15551, and Eurocode 1, and validation through finite element modeling in Ansys Workbench. The proposed structure ensures stability under static and dynamic loads, including acceleration, braking, turning, and wind forces, while optimizing wagon space utilization. Simulation results confirm that the design meets strength and safety criteria without exceeding material stress limits, offering a reliable solution for the secure transport of cylindrical rollers. Full article

This paper outlines a structural qualification process to assess the use of newly developed high-modulus (HM) glass fiber-reinforced polymer (GFRP) bars with headed ends in the joint between concrete bridge barriers and decks. The main goals of the study are to evaluate the structural performance of GFRP-reinforced TL-5 barrier–deck systems under transverse loading and to determine the pullout capacity of GFRP anchorage systems for both new construction and retrofit applications. The research is divided into two phases. In the first phase, six full-scale Test-Level 5 (TL-5) barrier wall–deck specimens, divided into three systems, were constructed and tested up to failure. The first system used headed-end GFRP bars to connect the barrier wall to a non-deformable thick deck slab. The second system was similar to the first but had a deck slab overhang for improved anchorage. The third system utilized postinstalled GFRP bars in a non-deformable thick deck slab, bonded with a commercial epoxy adhesive as a solution for deteriorated barrier replacement. The second phase involves an experimental program to evaluate the pullout strength of the GFRP bar anchorage in normal-strength concrete. The experimental results from the tested specimens were then compared to the factored applied moments in existing literature based on traffic loads in the Canadian Highway Bridge Design Code. Experimental results confirmed that GFRP-reinforced TL-5 barrier–deck systems exceeded factored design moments, with capacity-to-demand ratios above 1.38 (above 1.17 with the inclusion of an environmental reduction factor of 0.85). A 195 mm embedment length proved sufficient for both pre- and postinstalled bars. Headed-end GFRP bars improved pullout strength compared to straight-end bars, especially when bonded. Failure modes occurred at high loads, demonstrating structural integrity. Postinstalled bars bonded with epoxy performed comparably to preinstalled bars. A design equation for the barrier resistance due to a diagonal concrete crack at the barrier–deck corner was developed and validated using experimental findings. This equation offers a conservative and safe design approach for evaluating barrier–deck anchorage. Full article

The dynamic control of vibrations in skyscrapers is a critical consideration in sustainable building design, particularly in response to environmental excitations such as wind impact or seismic activity. Effective vibration neutralisation plays a crucial role in providing the safety of high-rise buildings. This research introduces an innovative concept for an active vibration damper that operates based on fluid dynamic transport to adaptively alter a skyscraper’s natural frequency, thereby counteracting resonant vibrations. A distinctive feature of this system is an adjustable-length cable mechanism, allowing for the dynamic modification of the pendulum’s effective length in real time. The structure, based on cable length adjustment, enables the PTMD to precisely tune its natural frequency to variable excitation conditions, thereby improving damping during transient or resonance phenomena of the building’s dynamic behaviour. A comprehensive mathematical model based on Lagrangian mechanics outlines the governing equations for this system, capturing the interactions between pendulum motion, fluid flow, and the damping forces necessary to maintain stability. Simulation analyses examine the role of initial excitation frequency and variable damping coefficients, revealing critical insights into optimal damper performance under varied structural conditions. The findings indicate that the proposed pendulum damper effectively mitigates resonance risks, paving the way for sustainable skyscraper design through enhanced structural adaptability and resilience. This adaptive PTMD, featuring an adjustable-length cable, provides a solution for creating safe and energy-efficient skyscraper designs, aligning with sustainable architectural practices and advancing future trends in vibration management technology. The study presented in this article supports the development of modern skyscraper design, with a focus on dynamic vibration control for sustainability and structural safety. It combines advanced numerical modelling, data-driven control algorithms, and experimental validation. From a sustainability perspective, the proposed PTMD system reduces the need for oversized structural components by providing adaptive, efficient damping, thereby lowering material consumption and embedded carbon. Through dynamically retuning structural stiffness and mass, the proposed PTMD enhances resilience and energy efficiency in skyscrapers, lowers lifetime energy use associated with passive damping devices, and enhances occupant comfort. This aligns with global sustainability objectives and new-generation building standards. Full article

Investigating the seismic damage mechanism of large underground complexes is essential for the safe development of urban underground space. This paper examines a five-story and three-span underground complex situated in a soft soil site. Shaking table tests were designed and conducted on both the free field and the soil–underground complex interaction system. The time–frequency evolution of the free field under various seismic motions was investigated. A combined experimental and numerical simulation approach was employed to examine the seismic response of the soil–underground complex interaction system. The structural deformation evolution, stress distribution, and development process of plastic damage under different seismic motions were analyzed. The results reveal that soft soil exhibits a significant energy amplification effect under far-field long-period ground motions. Structural deformation is mainly governed by horizontal shear. Under strong seismic excitation, plastic damage first initiates at the end of the bottom-story columns and extends to column-to-slab and wall-to-slab connections, where abrupt stiffness changes occur. Under the far-field long-period ground motion, the structural deformation, stress distribution, and plastic damage are significantly greater than those under the Shanghai artificial wave. These findings provide valuable insights for the seismic design of large underground complexes in soft soil sites. Full article

Artificial intelligence (AI)-powered mental health chatbots have evolved quickly as scalable means for psychological support, bringing novel solutions through natural language processing (NLP), mobile accessibility, and generative AI. This systematic literature review (SLR), following PRISMA 2020 guidelines, collates evidence from 25 published, peer-reviewed studies between 2020 and 2025 and reviews therapeutic techniques, cultural adaptation, technical design, system assessment, and ethics. Studies were extracted from seven academic databases, screened against specific inclusion criteria, and thematically analyzed. Cognitive behavioral therapy (CBT) was the most common therapeutic model, featured in 15 systems, frequently being used jointly with journaling, mindfulness, and behavioral activation, followed by emotion-based approaches, which were featured in seven systems. Innovative techniques like GPT-based emotional processing, multimodal interaction (e.g., AR/VR), and LSTM-SVM classification models (greater than 94% accuracy) showed increased conversation flexibility but missed long-term clinical validation. Cultural adaptability was varied, and effective localization was seen in systems like XiaoE, okBot, and Luda Lee, while Western-oriented systems had restricted contextual adaptability. Accessibility and inclusivity are still major challenges, especially within low-resource settings, since digital literacy, support for multiple languages, and infrastructure deficits are still challenges. Ethical aspects—data privacy, explainability, and crisis plans—were under-evidenced for most deployments. This review is different from previous ones since it focuses on cultural adaptability, ethics, and hybrid public health incorporation and proposes a comprehensive approach for deploying AI mental health chatbots safely, effectively, and inclusively. Central to this review, symmetry is emphasized as a fundamental idea incorporated into frameworks for cultural adaptation, decision-making processes, and therapeutic structures. In particular, symmetry ensures equal cultural responsiveness, balanced user–chatbot interactions, and ethically aligned AI systems, all of which enhance the efficacy and dependability of mental health services. Recognizing these benefits, the review further underscores the necessity for more rigorous academic research into the development, deployment, and evaluation of mental health chatbots and apps, particularly to address cultural sensitivity, ethical accountability, and long-term clinical outcomes. Full article

Compliant force control is a fundamental capability for enabling robots to interact safely and effectively with dynamic and uncertain environments. This paper presents a comprehensive survey of compliant force control strategies, intending to enhance safety, adaptability, and precision in applications such as physical human–robot interaction, robotic manipulation, and collaborative tasks. The review begins with a classification of compliant control methods into passive and active approaches, followed by a detailed examination of direct force control techniques—including hybrid and parallel force/position control—and indirect methods such as impedance and admittance control. Special emphasis is placed on advanced compliant control strategies applied to structurally complex robotic systems, including aerial, mobile, cable-driven, and bionic robots. In addition, intelligent compliant control approaches are systematically analyzed, encompassing neural networks, fuzzy logic, sliding mode control, and reinforcement learning. Sensorless compliance techniques are also discussed, along with emerging trends in hardware design and intelligent control methodologies. This survey provides a holistic view of the current landscape, identifies key technical challenges, and outlines future research directions for achieving more robust, intelligent, and adaptive compliant force control in robotic systems. Full article