Search Results (228)

Vertical axis wind turbines (VAWTs) are promising systems for urban wind energy applications because of their compact layout, omni-directional operation, and favorable integration potential. However, their broader deployment remains limited by poor self-starting capabilities and relatively low aerodynamic efficiency compared to horizontal axis wind turbines. In this study, a passive flow control concept for a straight-bladed VAWT is numerically investigated using a NACA0012 airfoil modified with 45° inclined perforations on the extrados. Four perforated configurations were generated and compared with the baseline profile through a two-stage computational approach. First, steady 2D computational fluid dynamics (CFD) simulations of the isolated airfoils were performed at a free stream velocity of 12 m/s over an angle of attack range of 0–180°. Subsequently, the most relevant aerodynamic trends were assessed at rotor level using transient 2D Moving Mesh simulations for a three-bladed wind turbine with tip speed ratios (TSRs) between 0.5 and 3.5. All perforated variants exhibited higher lift than the baseline airfoil, while the configuration with smaller, denser perforations distributed over the downstream two-thirds of the extrados provided the best overall aerodynamic performance. At TSR = 2.5, this geometry increased the mean moment coefficient from 0.044 to 0.0525 and the power coefficient from 0.109 to 0.131, corresponding to an increase in power output of approximately 20%. These results indicate that inclined extrados perforations constitute a promising passive strategy for improving the aerodynamic performance of small straight-bladed VAWTs, although further 3D and experimental validations are required. Full article

Organic eggplant production in the United States is challenged by flea beetles, which stunt eggplant growth and reduce yield. Across four experiments between 2019 and 2024, we compared the effects of various pest management strategies on flea beetle abundance, damage, and marketable yield in eggplant production, focusing on row covers and organic insecticides in later years of the study. Treatments included fine-mesh row covers, organic insecticides, and untreated controls (all years); reflective plastic mulch (2019); various essential oils (2019–2020); conventional insecticide control (2019–2020); and spunbonded row covers (2019–2021). Low flea beetle pressure was observed in 2019 and 2020; consequently, experiments were moved to fields under organic management with more frequent cultivation of solanaceous crops in 2021 and 2024. Samples taken near row cover removal at flowering revealed significantly more flea beetles in the control than fine-mesh row cover treatments in 2019, 2020, and 2021. However, there were never significant differences in flea beetle abundance in samples collected at transplanting or at harvesting. Flea beetle feeding damage at flowering was significantly lower in all row cover treatments than the untreated control in 2019, 2021, and 2024 and the organic insecticide treatment in 2019 and 2021; data was not collected in 2020. There was no difference between treatments in marketable yield in 2019 and 2020; however, the marketable yields of fine-mesh row cover treatments maintained over the entire growing season were 82% and 471% higher than the organic insecticide treatments in 2021 and 2024, respectively. These results indicate that fine-mesh row covers may be a viable pest management strategy in organic eggplant production. Full article

Net cleaning robots have been playing an increasingly important role in offshore aquaculture due to their efficiency and labor-saving capabilities. However, in practice, these robots are still entirely teleoperated and require constant, skilled human operation. The mesh intersection points, which serve as a structural feature of the nets, provide valuable visual cues for robot self-localization and net damage identification. Therefore, the detection and tracking of these points are crucial for developing autonomous net cleaning robots. To achieve intersection point detection, we propose NPUNet-lite, a lightweight model based on U-Net. This model significantly minimizes computational resources and model size while preserving high detection accuracy. For reliable point tracking, we develop the NlPTrack algorithm, which incorporates an iterative closest point-based association strategy to meet spatial constraints between points within a frame, and a cascaded association strategy to satisfy homographic and epipolar constraints across adjacent frames. We build a dataset from videos collected during a robotic cleaning task to train and evaluate our methods. The experimental results indicate that our segmentation network achieves comparable accuracy to advanced networks, yet with a substantial reduction in computational cost. Meanwhile, the tracking method successfully tracks the majority of intersection points across scenarios where the robot moves in different directions. Full article

In this work, the Material Point Method (MPM) is reviewed for application in the microelectronics industry. Microelectronic processes often involve large deformations, evolving interfaces, multiphysics coupling, and complex geometries that challenge conventional mesh-based methods such as the finite element method (FEM). Meshless methods provide an alternative solution that avoids these issues. A comparison is made between Smoothed Particle Hydrodynamics (SPH), Element Free Galerkin (EFG), peridynamics, Radial Basis Function–Finite Difference (RBF-FD), and MPM, evaluated with respect to convergence, consistency and stability, boundary enforcement, adaptivity, coupling, and industrial applicability. Based on this assessment, MPM and its main variants (BSMPM, GIMP, CPDI, and TLMPM) are examined in depth. The method’s ability to address large deformations, moving interfaces, contact, history-dependent material behavior, and multiphysics interactions is examined. The underfill process is used as a representative use case to illustrate challenges such as free surface flow, void formation, thermomechanical coupling, and residual stress. Overall, MPM shows strong potential, although further benchmarking and validation are required for widespread industrial adoption. Full article

Pneumatic drives remain widely used in industrial automation due to their simplicity and reliability, yet their overall energy efficiency is typically low. This study introduces an energy-efficient pneumatic drive concept that enhances braking control and enables compressed air recovery without modifying the actuator’s mechanical design. A transient one-dimensional mathematical model is developed to describe system dynamics and is combined with a particle swarm optimization (PSO) algorithm to determine optimal switching coordinates for the braking phase under constraints on piston motion and positioning accuracy. To assess the validity and limitations of simplified models, the optimized process is additionally investigated using a three-dimensional CFD model with moving mesh and valve control. The CFD model is validated experimentally using pressure measurements in the cylinder chambers. The results reveal that conventional isothermal 1D models underestimate transient pressure and energy parameters by up to 30–35% in systems with air recovery, highlighting the necessity of 3D analysis for accurate energy assessment. Optimization increases the duration of the recovery phase by a factor of 2.8 while maintaining cycle time and improving positioning accuracy. The resulting cycle energy efficiency reaches 53.4%, significantly exceeding typical industrial values. The proposed methodology provides a practical framework for designing energy-efficient pneumatic drives. Full article

We propose a coupled gas–particle two-phase model for particle transport in a compressible carrier gas with interphase momentum and energy exchange, and we incorporate a diffusion-based mechanism to represent gas–particle reactions. The governing equations are discretized in an Arbitrary Lagrangian–Eulerian (ALE) finite-volume framework using an HLLC-type two-dimensional Riemann solver (HLLC-2D). The solver employs a nodal-conservation construction that enforces consistency between numerical fluxes and nodal contact velocities, which helps reduce spurious oscillations near discontinuities on moving meshes. In addition, a particle-search-based Courant–Friedrichs–Lewy(CFL)-like time-step restriction is introduced to enhance robustness in coupled simulations. Numerical tests are presented to assess the method and to illustrate particle-induced modifications of wave dynamics, as well as reaction-driven variations in velocity and temperature fields. Full article

Road defect detection is essential for traffic safety and infrastructure maintenance. Excising automated methods based on 2D image analysis lack spatial context and cannot provide accurate 3D localization required for maintenance planning. We propose a novel framework for road defect mapping from monocular video sequences by integrating differentiable Bird’s-Eye-View (BEV) mesh representation, semantic filtering, and multi-frame temporal fusion. Our differentiable mesh-based BEV representation enables efficient scene reconstruction from sparse observations through MLP-based optimization. The semantic filtering strategy leverages road surface segmentation to eliminate off-road false positives, reducing detection errors by 33.7%. Multi-frame fusion with ray-casting projection and exponential moving average update accumulates defect observations across frames while maintaining 3D geometric consistency. Experimental results demonstrate that our framework produces geometrically consistent BEV defect maps with superior accuracy compared to single-frame 2D methods, effectively handling occlusions, motion blur, and varying illumination conditions. Full article

Implant-based breast reconstruction (IBBR) remains the most common form of post-mastectomy reconstruction worldwide, offering patients a reliable and accessible option to restore breast contour. Advances in surgical technique, biomaterials, and implant technology have driven rapid evolution in the field, with the dual goals of improving aesthetic outcomes and minimizing patient morbidity. The prepectoral plane has been popularized due to the eliminated risk of animation deformity and reduced postoperative pain. Some concerns remain regarding mastectomy flap thickness and long-term oncologic and aesthetic outcomes. Concurrently, nipple-sparing mastectomy has improved aesthetic results and enabled surgeons to move beyond just restoring breast form and improve functional recovery as well, as demonstrated by surgical efforts aimed at restoring nipple–areolar complex (NAC) sensation. Adjunctive use of biologic matrices and synthetic meshes has broadened reconstructive options, while next-generation implants seek to further enhance outcomes. Balanced against these innovations are important oncologic and systemic safety concerns, including breast implant-related cancers and the ongoing debate over breast implant illness (BII). This review highlights eight current “hot topics” in implant-based breast reconstruction: (1) prepectoral reconstruction, (2) nipple-sparing mastectomy, (3) oncoplastic techniques, (4) nipple–areolar complex (NAC) neurotization, (5) biologic matrices and synthetic meshes, (6) next-generation implants, (7) optimizing aesthetic outcomes, and (8) implant-associated cancer and systemic concerns. Together, these areas define the current landscape of innovation, controversy, and future directions in implant-based reconstruction. Full article

Accurate distance perception and collision reasoning are crucial for robotic manipulation in the confined interior of tokamak vacuum vessels. Traditional mesh- or voxel-based methods suffer from discretization artifacts, discontinuities, and heavy memory requirements, making them unsuitable for continuous geometric reasoning and optimization-based planning. This paper presents an Occupancy-Aware Neural Distance Perception (ONDP) framework that serves as a compact and differentiable geometric sensor for manipulator obstacle avoidance in reactor-like environments. To address the inadequacy of conventional sampling methods in such constrained environments, we introduce a Physically-Stratified Sampling strategy. This approach moves beyond heuristic adaptation to explicitly dictate data distribution based on specific engineering constraints. By injecting weighted quotas into critical safety buffers and enforcing symmetric boundary constraints, we ensure robust gradient learning in high-risk regions. A lightweight neural network is trained directly in physical units (millimeters) using a mean absolute error loss, ensuring strict adherence to engineering tolerances. The resulting model achieves approximately 2–3 mm near-surface accuracy and supports high-frequency distance and normal queries for real-time perception, monitoring, and motion planning. Experiments on a tokamak vessel model demonstrate that ONDP provides continuous, sub-centimeter geometric fidelity. Crucially, benchmark results confirm that the proposed method achieves a query frequency exceeding 15 kHz for large-scale batches, representing a 5911× speed-up over mesh-based queries. This breakthrough performance enables its seamless integration with trajectory optimization and model-predictive control frameworks for confined-space robotic manipulation. Full article

Dam-break flows involve strong non-linearity and complex fluid–solid interactions, often causing severe flooding and structural damage. Particle-based CFD methods, such as the Moving Particle Semi-implicit (MPS) method, are effective in modeling such flows due to their mesh-free, Lagrangian nature. This study presents an improved MPS method with a novel friction model and enhanced fluid–solid interaction scheme to simulate dam-break-induced flows over fixed and mobile beds. The model is validated using experimental and analytical benchmarks, demonstrating improved accuracy and stability. Simulation results show that mobile beds significantly influence wave attenuation, energy dissipation, and sediment transport. In particular, step-down bed conditions promote sediment motion and modify wave behavior. These findings emphasize the importance of accounting for mobile seabed dynamics in numerical modeling of coastal and dam-break scenarios. The proposed MPS model offers a reliable and efficient tool for capturing key phenomena associated with fluid–solid interactions in naval and ocean engineering applications. Full article

Background: Childhood obesity is a pressing global health challenge. Analyzing the efficacy of interventions is crucial to mitigate its impact and inform effective public health policies. This study aimed to conduct a systematic review of interventions (SRI) targeting school-aged children with obesity. Our goal was to identify the key components that contribute to the success of integrated interventions addressing diet/nutrition (D/N), physical activity (PA), and socioemotional skills. Methods: The Cochrane Collaboration methodology and the PRISMA statement were followed. The SRI included the following criteria, established a priori: studies that addressed obesity in school-aged children, including one or more interventions related to physical activity (PA), diet/nutrition (D/N), or socioemotional skills. Following the PICO (Population, Intervention, Comparison, and Outcome) framework, we searched six digital databases using relevant keywords and MeSH terms. The Mixed-Methods Appraisal Tool (MMAT) was used to assess article quality via “function group string” methods. Finally, a thematic synthesis of the SRI findings was conducted. The protocol for this study was registered in PROSPERO (CRD4202454214). Results: Initial screening yielded 127 articles. Following critical appraisal with the MMAT, studies with inadequate methodology, solely descriptive designs, unclear results, or interventions shorter than six months were excluded. Ultimately, 10 studies remained, eight of which included two of the three components of interest (D/N or PA). Conclusions: In this overview, many interventions were presented for the prevention of overweight and obesity in school-age children; however, methodological and standardized limitations still exist that hinder the establishment of effective interventions. Engaging families and teachers as active participants in interventions significantly enhanced effectiveness in both the D/N and PA domains. However, an analysis of current interventions highlights a stark gap in multisectoral and integrated approaches to tackling childhood obesity. This presents a remarkable opportunity for future initiatives to move beyond fragmented efforts and embrace a holistic model that unites families, schools, and communities to promote healthy lifestyles. Full article

This work presents a study on the fabrication of polymethyl methacrylate (PMMA) coatings on NiTi alloys using the spin-coating technique, combining numerical simulation with COMSOL Multiphysics 6.3 and experimental validation. This study provides a numerical framework and parametric study of a COMSOL-based simulation framework for estimating the PMMA coating thickness during the spin-coating process. We present an axisymmetric numerical framework, consistent with classical analytical trends; we provide parametric maps (viscosity, rpm, volume) to delimit thickness ranges (e.g., 100–300 μm). Limitations with no experimental validation are included and evaporation is not modeled; therefore, the figures are indicative estimates. The spin-coating parameters, such as the rotation speed, internal pressure, viscosity of the PMMA solution, and initial volume of the polymer solution, are considered important factors for the simulation process. The coating parameters determine the thickness of the coating layer achieved during the process of spin coating. The 2D axisymmetric flow considers internal factors of a surface tension of 0.07 N·m, a contact angle of 90°, and a density of 1150 kg/m³ for the coating process without evaporation effects. The moving mesh (coating layer) is considered a free surface without any slip boundary with the substrate surface. The coating thickness was determined by various rotations and dynamic viscosities, using a simulation method. The experimental findings and simulation output of the coating thickness as a function of various dynamic viscosities and rotations match well. The final coating thickness ranged from 100 to 300 μm, depending on a viscosity of 11 mPa·s and 100, 500 rpm. Full article

The link between oral health and Alzheimer’s disease (AD) has gained increasing attention in recent years. Emerging evidence suggests that this association is bidirectional, involving both biological mechanisms and behavioral consequences that reinforce one another over time. Literature Review: A narrative synthesis of systematic reviews, meta-analyses, and scoping reviews published between January 2010 and March 2024 was conducted. Searching was performed in four electronic databases (PubMed, Scopus, the Web of Science, and the Cochrane Library), using a combination of MeSH terms and free-text keywords related to dementia and oral health. Inclusion criteria targeted human studies published in English with full-text access and a clear focus on the interplay between oral status and Alzheimer’s disease. Results: The reviewed literature indicates that periodontal disease, tooth loss, and oral microbiome alterations may contribute to neuroinflammation and cognitive decline, potentially influencing the onset and progression of AD. Conversely, Alzheimer’s disease negatively affects oral health through impaired self-care, reduced motor coordination, salivary changes, and altered pain perception. Conclusions: By mapping out these interconnections, the findings support a shift in perspective; oral health should be considered a relevant factor in both the prevention and management of Alzheimer’s disease. Dentistry and neurology must move closer together in clinical practice, particularly in the care of older adults. Promoting oral health is not just about preserving teeth; it may be part of preserving cognitive function and quality of life. Full article

Emergency surfacing acts as the final line of defense in preserving the operational viability of submarines, playing a crucial role in their safety. To investigate the dynamic characteristics of submarine emergency surfacing, utilizing whole moving mesh technology, a method for coupled simulation of high-pressure air blowing out water tanks and emergency surfacing motion of submarines is proposed, enhancing the simulation’s fidelity to real-world dynamics. Based on meeting the requirements for simulation accuracy, utilizing the coupled simulation model, this study explored the effects of varying expulsion pressures on submarine motion parameters including depth, roll, pitch, and yaw angles. The findings indicate that the hull emerges slightly earlier and reaches a marginally higher point when coupling effects are accounted for compared to scenarios where these effects are neglected. At consistent expulsion pressures, as the pitch and roll angles increase and the back pressure decreases, the expulsion rate from the ballast tank accelerates. Higher expulsion pressures result in quicker surfacing of the hull, smaller amplitude of pitch angles, and larger amplitudes of roll angles, while the changes in yaw angle displayed no clear pattern. The methodologies and conclusions of this study offer valuable insights for the design and operational strategies of actual submarines. Full article

Addressing the insufficient research on the aerodynamic performance of the coupled last stage and exhaust hood structure in compact marine steam turbines under off-design conditions, this paper establishes for the first time a fully three-dimensional coupled model. It systematically analyzes the influence of the last-stage moving blade shrouds and exhaust hood stiffeners on steam flow loss, static pressure recovery, and vibrational excitation. The research methodology includes the following: employing a hybrid structured-unstructured meshing technique, conducting numerical simulations based on the Shear Stress Transport (SST) turbulence model, and utilizing the static pressure recovery coefficient, total pressure loss coefficient, and cross-sectional flow velocity non-uniformity as performance evaluation metrics. The principal findings are as follows: (1) After installing self-locking shrouds on the moving blades, steam flow loss is reduced by 4.7%, and the outlet pressure non-uniformity decreases by 12.3%. (2) Although the addition of cruciform stiffeners in the diffuser section of the exhaust hood enhances structural rigidity, it results in an 8.4% decrease in the static pressure recovery coefficient, necessitating further optimization of geometric parameters. (3) The coupled model exhibits optimal aerodynamic performance at a 50% design flow rate and 100% design exhaust pressure. The results provide a theoretical basis for the structural optimization of low-noise compact steam turbines. Full article