Search Results (19,589)

The study examines in detail the possibility of using well casing as a means for power transmission downhole to high-power equipment, such as pumps. The ultimate goal is to transmit single-phase AC to the well bottom and then convert it into three-phase power to operate the downhole equipment, which is a major challenge for such applications. The focus is set on the particular problem of the contact between the packer slips and the casing, and the study aims to examine it in detail. An analysis of high-voltage effects (arcing, etching, contact welding, and heating) and possible mechanical and chemical failures (fatigue, corrosion, surface treatment, contact pressure, and stresses) is performed. These effects are evaluated using common physics laws, and the mechanical structural behavior of the contact is analyzed through Finite Element Method simulation. The performed calculations and analyses show that this is a viable and innovative solution that eliminates the use of cables (umbilicals), especially for long distances and in deep wells. The main contribution is the validated conceptual design, with physical prototyping and tests planned for the next stage of this research. Full article

This study presents an improved variant of the greater cane rat algorithm (GCRA), called adaptive and global-guided greater cane rat algorithm (AGG-GCRA), which aims to alleviate some key limitations of the original GCRA regarding convergence speed, solution precision, and stability. GCRA simulates the foraging behavior of the greater cane rat during both mating and non-mating seasons, demonstrating intelligent exploration capabilities. However, the original algorithm still faces challenges such as premature convergence and inadequate local exploitation when applied to complex optimization problems. To address these issues, this paper introduces four key improvements to the GCRA: (1) a global optimum guidance term to enhance the convergence directionality; (2) a flexible parameter adjustment system designed to maintain a dynamic balance between exploration and exploitation; (3) a mechanism for retaining top-quality solutions to ensure the preservation of optimal results.; and (4) a local perturbation mechanism to help escape local optima. To comprehensively evaluate the optimization performance of AGG-GCRA, 20 separate experiments were carried out across 26 standard benchmark functions and six real-world engineering optimization problems, with comparisons made against 11 advanced metaheuristic optimization methods. The findings indicate that AGG-GCRA surpasses the competing algorithms in aspects of convergence rate, solution precision, and robustness. In the stability analysis, AGG-GCRA consistently obtained the global optimal solution in multiple runs for five engineering cases, achieving an average rank of first place and a standard deviation close to zero, highlighting its exceptional global search capabilities and excellent repeatability. Statistical tests, including the Friedman ranking and Wilcoxon signed-rank tests, provide additional validation for the effectiveness and importance of the proposed algorithm. In conclusion, AGG-GCRA provides an efficient and stable intelligent optimization tool for solving various optimization problems. Full article

With the advancement of new power system construction, thermostatically controlled loads represented by regional air conditioning systems are being extensively integrated into the grid, leading to a surge in the number of user nodes. This large-scale integration of new loads creates challenges for the grid, as the resulting load data exhibits strong periodicity and randomness over time. These characteristics are influenced by factors like temperature and user behavior. At the same time, spatially adjacent nodes show similarities and clustering in electricity usage. This creates complex spatiotemporal coupling features. These complex spatiotemporal characteristics challenge traditional forecasting methods. Their high model complexity and numerous parameters often lead to overfitting or the curse of dimensionality, which hinders both prediction accuracy and efficiency. To address this issue, this paper proposes a load forecasting method based on spatiotemporal partitioning and collaborative cross-regional attention. First, a spatiotemporal similarity matrix is constructed using the Shape Dynamic Time Warping (ShapeDTW) algorithm and an adaptive Gaussian kernel function based on the Haversine distance. Spectral clustering combined with the Gap Statistic criterion is then applied to adaptively determine the optimal number of partitions, dividing all load nodes in the power grid into several sub-regions with homogeneous spatiotemporal characteristics. Second, for each sub-region, a local Spatiotemporal Graph Convolutional Network (STGCN) model is built. By integrating gated temporal convolution with spatial feature extraction, the model accurately captures the spatiotemporal evolution patterns within each sub-region. On this basis, a cross-regional attention mechanism is designed to dynamically learn the correlation weights among sub-regions, enabling collaborative fusion of global features. Finally, the proposed method is evaluated on a multi-node load dataset. The effectiveness of the approach is validated through comparative experiments and ablation studies (that is, by removing key components of the model to evaluate their contribution to the overall performance). Experimental results demonstrate that the proposed method achieves excellent performance in short-term load forecasting tasks across multiple nodes. Full article

The Mediterranean soft-shell turtle (Trionyx triunguis) is classified as critically endangered by the IUCN. Effective conservation requires a clear understanding of its reproductive strategies and population structure. By combining mitochondrial DNA tandem repeat-region profiling with genome-wide SNP data obtained through 3RADseq, we gained high-resolution insights into the genetic composition and breeding behavior of Mediterranean populations. Our results revealed complex reproductive dynamics, including multiple paternity, sperm storage, and repeated nesting within a single season—strategies that enhance genetic diversity in small, fragmented populations. Using SNP-based kinship inference, we estimated the number of breeding females and identified full and half-sibling groups, offering a robust genomic framework for assessing population size and structure. Genetic similarity patterns highlighted moderate differentiation among Israeli river populations, suggesting some connectivity, while samples from Türkiye were clearly distinct, reflecting long-term geographic and genetic separation. This integrative approach provides a scalable, repeatable tool for long-term monitoring. The combined use of maternal and biparental markers enables detailed tracking of genetic diversity, breeding contributions, and demographic trends—key elements for designing informed, adaptive conservation strategies. Full article

This study proposes a precast concrete bridge pier system designed to enhance seismic resilience and post-earthquake reparability. The structural configuration integrates ultra-high-performance concrete (UHPC), externally replaceable steel-angle energy-dissipating components, and unbonded post-tensioned tendons. The seismic performance of the system was evaluated through quasi-static tests under cyclic loading. Experimental results demonstrated that the proposed pier exhibited stable hysteretic behavior and minimal residual displacement, effectively concentrating damage within the intended plastic hinge region. The superior strength of UHPC further contributed to improved load-bearing capacity and less localized concrete compressive damage at the rocking interface. The external steel angles improved the energy dissipation capacity of the precast column significantly, and its external arrangement made the post-earthquake replacement much easier as compared to internal energy dissipation bars. The feasibility of the proposed seismic-resilient pier system was successfully validated, offering a promising solution for bridge design in high-seismic-intensity regions. Full article

This review explores the current state and future potential of bioplastics as sustainable alternatives to conventional fossil-based polymers. It provides a detailed examination of the classification, molecular structures, and synthetic routes of major bioplastics, including polylactic acid (PLA), polyglycolic acid (PGA), polycaprolactone (PCL), polybutylene succinate (PBS), polybutylene adipate-co-terephthalate (PBAT), and polyhydroxyalkanoates (PHAs). Special emphasis is placed on the unique properties and degradation behaviors of each material across various environmental conditions, such as industrial composting, soil, and marine ecosystems. The manuscript further discusses advanced strategies in polymer design, such as copolymerization, reactive blending, and incorporation of nano- or micro-scale additives, to enhance flexibility, thermal resistance, barrier properties, and mechanical integrity. In addition to technical advancements, the review critically addresses key limitations impeding large-scale commercialization, including high production costs, limited availability of bio-based monomers, and inadequate end-of-life treatment infrastructure. Finally, future research directions are proposed to advance the development of fully bio-based, functionally tunable, and circular bioplastics that meet the performance demands of modern applications while reducing environmental impact. Full article

This paper investigates the design of a coastal cycling route that integrates principles of sustainable mobility with the perceptual qualities of the urban landscape. In response to contemporary environmental challenges, the promotion of cycling as an alternative mode of transport necessitates the development of urban green infrastructure that is not only functionally adequate but also perceptually engaging. The research draws upon established theoretical frameworks, particularly the concepts of spatial legibility and visual sequencing articulated by Kevin Lynch and Gordon Cullen, to examine how the experience of landscape can influence cycling behavior in urban development. Methodologically, the study combines a comprehensive literature review with a spatial and perceptual analysis of a selected coastal corridor in the Attica region in Greece, extending from Kallithea to Glyfada. The route is segmented into types based on physical, visual, and sensory characteristics, allowing for targeted design interventions. Key variables such as enclosure, vegetation, noise levels, and visual accessibility are evaluated to inform design strategies that enhance user experience and safety. The findings suggest that incorporating perceptual design elements into cycling infrastructure can significantly contribute to increased usage, environmental sustainability, resilience, and the overall improvement of urban coastal environments. Full article

This study investigates a UDETA-modified polyurethane–urea (PUU) self-healing coating for wind turbine blades, focusing on its ability to autonomously repair surface erosion damage under realistic environmental conditions. A multiphysics finite element model was developed to couple temperature, moisture, and stress effects on crack healing, and a Gaussian process regression (GPR) model was trained on 35 experimental data points to predict the mobile fraction and healing thresholds with high accuracy (R² = 0.79, MAE = 0.059). The diffusion coefficient of water in the PUU matrix was determined as 11.03 × 10⁻⁷ mm²/s, and stress-driven moisture accumulation at crack tips was shown to accelerate crack healing. Erichsen cupping test simulations were conducted to reproduce experimental crack patterns, demonstrating brittle behavior in dehydrated coatings with a Young’s modulus of 50 MPa and critical principal strains of 0.48. An exponential healing function was incorporated into the computational model and validated against experiments, predicting significant crack healing within 24 h of humidity exposure. These findings provide quantitative design criteria for self-healing coatings, enabling the selection of UDETA content, thickness, and curing strategies to extend wind turbine blade service life while reducing maintenance costs. Full article

In recent years, efforts have focused on developing repairable, malleable, and recyclable thermoset materials to reduce the growing volume of polymer waste and extend the lifetime of existing polymeric materials. Specifically, associative covalent adaptable networks (CANs), also known as vitrimers, have received considerable attention. In this work, photopolymerizable vitrimers were prepared by combining crosslinkers containing β-amino esters in their structure with hydroxylated acrylate or methacrylate monomers, with the aim of reprocessing these materials through the activation of transesterification reactions. The network design and photopolymerization conditions were optimized to ensure the successful formation of the vitrimers. Tunable mechanical and thermal properties were achieved by varying their chemical composition. Furthermore, the reprocessing ability of these materials was confirmed through thermal treatments. Additionally, these vitrimers exhibited the ability to undergo hydrolysis in basic aqueous media, providing an alternative pathway for recycling. Full article

This paper presents the design of an ultrabroadband solar absorber, developed using a metamaterial stack composed of only two materials, consisting of alternating layers of Cr and SiO₂. Starting with a Cr layer as the substrate, multiple pairs of Cr and SiO₂ were stacked sequentially, where one Cr layer and one SiO₂ layer constitute a single pair. To further enhance performance, a cylindrical Cr structure was added to the top. A key innovation of this work lay in its material simplicity and cost efficiency, relying solely on two inexpensive materials, Cr and SiO₂. Additionally, the inclusion of the top Cr cylinder was found to significantly enhance absorptivity. Simulations demonstrate that removing this feature led to a noticeable reduction in absorptivity of approximately 10% across the 500–2000 nm wavelength range. Another important finding is the effect of the number of Cr–SiO₂ pairs on absorption behavior. When the number of pairs increases from four to five, the average absorptivity decreases slightly, but the absorption bandwidth is notably broadened. Further increasing six pairs resulted in a marginal increase in bandwidth, while maintaining the average absorptivity. Moreover, a low-absorptivity dip at 360 nm was slightly mitigated, rising to approximately 0.900. Based on these insights, a six-pair metamaterial structure was chosen for further optimization. Utilizing COMSOL Multiphysics^® simulation software (version 6.0), the absorber was successfully engineered to achieve high performance across an exceptionally broad spectral range, from 200 nm to 2160 nm. Under optimal design parameters, it exhibited an average absorptivity of 0.950, with absorptivity consistently exceeding 0.900 throughout this range. This demonstrates the absorber’s strong potential for efficient solar energy harvesting using a structurally simple and cost-effective design. Full article

In the research, a novel accelerometer concept leveraging the mode-localization phenomenon is put forward. The sensor measures external acceleration through monitoring changes in the relative amplitude ratio among coupled resonators. The sensing part of the presented accelerometer comprises a doubly clamped beam coupled with a cantilever beam. Its design ensures the initial bending mode of the clamped beam approximates the secondary bending mode of the cantilever. Drawing on Euler–Bernoulli beam theory, the governing formulas of the coupled resonators are deduced and analyzed via Galerkin discretization integrated with the multiple-scale method. During working in both linear as well as nonlinear operating regions, this sensor’s dynamic behavior can be tuned by adjusting the drive voltage. The obtained results demonstrate that the nonlinear dynamics increases the accelerometer sensitivity, which can be further enhanced by adjusting the coupling voltage without severe mode overlap. The presented model offers one viable method to enhance the overall performance in multi-mode MEMS accelerometers. Full article

Background: Bone regeneration is a key therapeutic objective in periodontology, particularly in the treatment of alveolar defects caused by periodontal disease, dentoalveolar trauma, or surgical interventions. Among current regenerative strategies, collagen-enriched biomaterials have demonstrated an active role in modulating cellular behavior during bone repair. However, the specific effects of different collagen formulations on human dental pulp stem cells (hDPSCs) have not yet been fully characterized. Objective: To evaluate the impact of xenogeneic bone grafts with and without collagen—OsteoBiol^® Gen-Os^® (GO), OsteoBiol^® GTO^® (GTO), and Geistlich Bio-Oss^® (BO)—on cell viability, adhesion, migration, osteogenic differentiation, and mineralization potential of hDPSCs, and to explore the molecular mechanisms underlying their effects. Methods: In vitro assays were conducted to assess viability (MTT and fluorescence staining), adhesion (SEM), migration (wound healing assay), and mineralization (Alizarin Red S staining). Gene expression analyses (RT-qPCR) were performed for adhesion/migration markers (FN, SDF-1, COL1A1), angiogenic/proliferation markers (VEGF, FGF2), and osteogenic differentiation markers (RUNX2, ALP, COL1A1). Results: GO showed a higher early expression of genes associated with adhesion, migration, angiogenesis (FN, SDF-1, VEGF and FGF2: p < 0.05; COL1A1: p < 0.01), and osteogenic differentiation (7 days: COL1A1 and ALP (p < 0.001)); (14 days: RUNX2, ALP: p < 0.001; COL1A1: p < 0.05), indicating a sequential activation of molecular pathways and mineralization capacity comparable to the control group. GTO demonstrated the best biocompatibility, with significantly higher cell viability (p < 0.05), strong adhesion, and markedly increased mineralization at 21 days (p < 0.001), despite moderate early gene expression. BO showed reduced cell viability at 10 mg/mL (p < 0.05) and 20 mg/mL (p < 0.001), with mineralization levels similar to the control group. Conclusion: Collagen-based xenografts demonstrate favorable interactions with hDPSCs, enhancing viability and promoting osteogenic differentiation. Our findings suggest that beyond the presence of collagen, the specific formulation of these biomaterials may modulate their biological performance, highlighting the importance of material design in optimizing regenerative outcomes. Clinical Significance: The formulation of collagen in xenogeneic bone substitutes may be a determining factor in enhancing periodontal regenerative outcomes by modulating the early cellular response and osteogenic activity in stem cell-based tissue engineering. Full article

A cost-effective Fe-Cr-Mo-B-Si-C metamorphic alloy (HXA5) was newly designed and fabricated as coating material using the high-velocity oxygen fuel (HVOF) thermal spray process, and its microstructure and dry wear resistance were investigated in comparison with a conventional HVOF WC-12Co coating. The HXA5 coating material consisted of a splat area and un-melted powder area. The splat area contained metallic glass, (Cr,Fe)₂B, Cr₂B, and minor Fe-based BCC phases, and the un-melted powder area was composed of Fe-based BCC, (Cr,Fe)₂B, and Cr₂B phases. Room-temperature wear tests revealed that HVOF HXA5 coating material exhibited wear resistance comparable to HVOF WC-12Co coating over ~8.4 km sliding and even superior performance at high-stress wear conditions. This superior wear behavior of HXA5 coating material was attributed to the minimal hardness difference between the metallic glass and boride, the plasticity of the metallic glass, and the formation of a lubricating tribofilm. The wear mechanisms and the influence of alloying elements on glass-forming ability were also discussed. Full article

As MEMS design encounters growing challenges, particularly stiction between movable and stationary electrodes, dielectric charging, pull-in instability, and multi-valued response characteristics, the integration of dimple-equipped structures has emerged as a pivotal solution to mitigate these fundamental issues. Consequently, this study investigates the dynamic behavior of an electrostatically actuated double-clamped microbeam incorporating dimples and contact pads. While the dimples enhance the beam’s travel range, they may also induce an impact mode upon contact with the landing pads, leading to complex nonlinear dynamic phenomena. A reduced-order model was developed to numerically solve the governing equation of motion. The microbeam’s response was analyzed both with and without dimples using multiple analytical techniques, including bifurcation diagrams and discrete excitation procedures near the impacting regime. The findings demonstrate that the inclusion of dimples effectively suppresses stiction, pull-in instability, and multi-valued responses. The results indicate that upon contacting the landing pads, the beam exhibits pronounced nonlinear dynamic behaviors, manifesting as higher-period oscillations such as period-3, period-4 and period-5 and then fully developed chaotic attractors. Indeed, this specifically demonstrates the potential of using the dynamic transition from a steady-state to a chaotic response to build novel MEMS sensors. Full article

This paper proposes and investigates a novel multilevel thin-walled energy-absorbing structure. The proposed design demonstrates superior energy absorption capability compared to conventional single-stage structures through its additional energy-absorbing mechanism that activates after the initial peak force. Based on the Super Folding Element (SFE) theory, we derive theoretical calculation expressions to characterize the structure’s behavior. Dynamic impact experiments validate the theoretical model. Furthermore, we introduce an innovative allowable criterion for structural optimization and implement multi-objective crashworthiness optimization to identify the optimal configuration. The optimization results exhibit remarkable consistency with both numerical simulations and theoretical predictions, confirming the effectiveness of our approach. Full article