Wind power gears will be excessively worn due to lubrication failure during ***,the tribological properties of rubbing pairs are improved by filling solid lubricants into surface *** texture design,three types of topo...
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Wind power gears will be excessively worn due to lubrication failure during ***,the tribological properties of rubbing pairs are improved by filling solid lubricants into surface *** texture design,three types of topological textures(Circle(C),Hexagon(H),and Circle/Hexagon(CH))were obtained by cell topology optimization,and then three cases with 20%,30%,and 40%density were designed for each ***,SnAgCu and TiC were deposited in texture of AISI 4140 steel(AS)to obtain 9 kinds of self-lubricating *** them,AS with 30%CH density(AS-CH30)exhibits excellent mechanical and tribological *** with AS-C and AS-H,the maximum equivalent stress of AS-CH was decreased by 10.86%and 5.37%,*** coefficient and wear rate of AS-CH30 were 79.68%and 78%lower than those of *** excellent tribological performances of AS-CH30 can be attributed to the synergistic effect of topological surface and solid *** surface can not only reduce fluctuation of equivalent stress,but also promote the stored lubricants to be easily transferred at the contact interface to form a 200 nm lubricating film containing solid lubricants(mainly),oxides and wear debris.
For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation *** models typically fall into two categories:data-driven models and physical mode...
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For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation *** models typically fall into two categories:data-driven models and physical models,each offering unique advantages but also facing ***-informed neural networks(PINNs)provide a robust framework to integrate data-driven models with physical principles,ensuring consistency with underlying physics while enabling generalization across diverse operational *** study introduces a PINN-based approach to reconstruct open circuit voltage(OCV)curves and estimate key ageing parameters at both the cell and electrode *** parameters include available capacity,electrode capacities,and lithium inventory *** proposed method integrates OCV reconstruction models as functional components into convolutional neural networks(CNNs)and is validated using a public *** results reveal that the estimated ageing parameters closely align with those obtained through offline OCV tests,with errors in reconstructed OCV curves remaining within 15 *** demonstrates the ability of the method to deliver fast and accurate degradation diagnostics at the electrode level,advancing the potential for precise and efficient battery health management.
Al and Mg alloy high pressure die castings(HPDC)are increasingly used in automotive *** microstructures in the castings have decisive effect on the casting mechanical properties,in which the microstructure characteris...
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Al and Mg alloy high pressure die castings(HPDC)are increasingly used in automotive *** microstructures in the castings have decisive effect on the casting mechanical properties,in which the microstructure characteristics are fundamental for the investigation of the microstructure-property *** the past decade,the microstructure characteristics of HPDC Al and Mg alloys,especially micro-pores andα-Fe,have been investigated from two-dimensional(2D)to threedimensional with X-ray micro-computed tomography(μ-CT).This paper provides an overview of the current understanding regarding the 3D characteristics and formation mechanisms of microstructures in HPDC alloys,their spatial distributions,and the impact on mechanical ***,it outlines future research directions for the formation and control of heterogeneous microstructures in HPDC alloys.
Flexible full-textile pressure sensor is able to integrate with clothing directly,which has drawn extensive attention from scholars *** the realization of flexible full-textile pressure sensor with high sensitivity,wi...
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Flexible full-textile pressure sensor is able to integrate with clothing directly,which has drawn extensive attention from scholars *** the realization of flexible full-textile pressure sensor with high sensitivity,wide detection range,and long working life remains *** recognition tasks necessitate intricate sensor arrays that require extensive data processing and are susceptible to *** human skin is capable of interpreting tactile signals,such as sliding,by encoding pressure changes and performing complex perceptual *** by the skin,we have developed a simple dip-and-dry approach to fabricate a full-textile pressure sensor with signal transmission layers,protective layers,and sensing *** sensor achieves high sensitivity(2.16 kPa^(−1)),ultrawide detection range(0 to 155.485 kPa),impressive mechanical stability of 1 million loading/unloading cycles without fatigue,and low material *** signal transmission layers that collect local signals enable real-world complicated task recognition through one single *** developed an artificial Internet of Things system utilizing a single sensor,which successfully achieved high accuracy in 4 tasks,including handwriting digit recognition and human activity *** results demonstrate that skin-inspired full-textile sensor paves a promising route toward the development of electronic textiles with important potential in real-world applications,including human–machine interaction and human activity detection.
A systematic comparative correlation between the as-cast microstructure and mechanical properties of Al5Cu2Ni/xFeNb (x = 1, 3, and 5%) composites is fabricated by a two-step electromagnetic stir casting technique via ...
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In the tapping-mode atomic force microscope(TM-AFM),the probe tip continuously taps the sample surface,which may cause plastic deformation of the sample and result in energy *** energy dissipation of the probe is clos...
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In the tapping-mode atomic force microscope(TM-AFM),the probe tip continuously taps the sample surface,which may cause plastic deformation of the sample and result in energy *** energy dissipation of the probe is closely related to the scanned phase *** quantify the energy dissipation due to plastic indentations of the sample,this study utilized a combination of molecular dynamics(MD)simulations and experiments on single-crystal copper samples,including multiple nano-indentation *** energy dissipation of the probe due to the plastic deformation of the sample was calculated by integrating the hysteresis curve of the indentation depth versus the force applied to the *** simulation results are in good agreement with the experimental *** sets of results have demonstrated that the plastic energy dissipation decreases as the number of indentations increases,and eventually the energy of the probe tends to *** equilibrium energy dissipation is associated with other dissipation ***,it was observed that,after hundreds of taps,the dissipated energy of plastic deformation could be ignored,implying that the scanned image may not reflect the plasticity information of the sample after multiple taps of the probe on the sample surface for scanning.
The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram *** dynamic expansion of the cavity induces liquid pressure variations...
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The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram *** dynamic expansion of the cavity induces liquid pressure variations,potentially causing catastrophic damage to the *** studies mainly focus on non-deforming projectiles,such as fragments,with limited exploration of shaped charge *** this paper,a uniquely experimental system was designed to record cavity profiles in behind-armor liquid-filled containers subjected to shaped charge jet *** impact process was then numerically reproduced using the explicit simulation program ANSYS LS-DYNA with the Structured Arbitrary Lagrangian-Eulerian(S-ALE)*** formation mechanism,along with the dimensional and shape evolution of the cavity was ***,the influence of the impact kinetic energy of the jet on the cavity characteristics was *** findings reveal that the cavity profile exhibits a conical shape,primarily driven by direct jet impact and inertial *** expansion rates of both cavity length and maximum radius increase with jet impact kinetic *** the impact kinetic energy is reduced to 28.2 kJ or below,the length-to-diameter ratio of the cavity ultimately stabilizes at approximately 7.
Attention deficit hyperactivity disorder (ADHD) is a type of neurodevelopmental disease affecting the mental health of children and adults. Individuals with ADHD show various symptoms such as inattention, hyperactivit...
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Attention deficit hyperactivity disorder (ADHD) is a type of neurodevelopmental disease affecting the mental health of children and adults. Individuals with ADHD show various symptoms such as inattention, hyperactivity, and impulsivity. Early diagnosis of ADHD helps to alter neural connections and refine symptoms. The clinical practice to diagnose ADHD is through subjective measures and does not significantly capture the underlying structural and functional mechanisms of the brain. Therefore, it is crucial to explore other approaches such as Artificial Intelligence (AI) to improve the accuracy and efficacy of ADHD diagnosis. Consequently, in this article we systematically investigate various Machine Learning (ML) and Deep Learning (DL) approaches as well as different diagnostic tools or modalities employed for the identification of ADHD. Particularly, a Systematic Literature Review (SLR) is conducted to review and analyze 98 selected studies published from 2021 to 2024. Subsequently, the selected studies are grouped into five categories based on the modalities utilized in these studies: physiological signals (37), magnetic resonance imaging (31), questionnaires (11), motion data (8), and others (11). We also analyze AI models which indicates that 45 studies utilized ML models, 33 studies employed DL models, and 20 studies used both. However, there are still some gaps in current research such as a lack of publicly available datasets except MRI and EEG. Although datasets for MEG and actigraphy exist, but they are underexplored and have been utilized in only a few studies. While DL models like CNNs and ANNs have been increasingly applied in recent years for ADHD diagnosis, there is a shortage of advanced DL models, including transfer learning approaches like ResNet and VGG. Additionally, there is a lack of interpretability in AI models, particularly DL models. Furthermore, most studies focus on individual modalities for ADHD diagnosis, and despite many studies showing
This research examines the interactions between fracture depth and crack location on a cantilever beam’s dynamic response under thermomechanical loads. The structure’s stiffness is significantly influenced by temper...
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Recently, manufacturers and engineers have increasingly focused on developing natural fiber-reinforced composites, which often outperform synthetic fiber-based composites in various aspects. This study involves the pr...
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