Real Surface Research Articles

Direct numerical simulation of channel flow with real surface roughness using a ghost cell immersed boundary method

This paper investigates the impact of real surface roughness on channel flow using direct numerical simulation assisted by a ghost cell immersed boundary method (DNS-GCIBM). The principles and implementations of DNS-GCIBM are first introduced. Two test cases, including the two-dimensional flow around a cylinder and the three-dimensional flow in a sinusoidal roughness channel are employed to demonstrate the practicability and accuracy of the proposed approach, especially in numerical studies on the rough wall-bounded flow. Using DNS-GCIBM, channel flows under conditions of Ma = 0.3 and Reτ≈300, with both the real-world and regular roughness surfaces are studied. The results are statistically analyzed using the triple decomposition technique. The outer layer similarity in the streamwise mean velocity and Reynolds stress profiles indicate that the impact of roughness on the boundary layer primarily localizes within roughness sub-layer. In the streamwise mean velocity profile, both regular and real-world roughness surfaces induce obvious increase to the roughness function ΔU+ as roughness height Ra increases, while discrepancy of ΔU+ between the two types of roughness can be found. Furthermore, turbulence statistics are sensitive to the variations of Ra. As Ra increases, it becomes challenging to organize coherent structures near the wall, resulting in the reduction of streamwise Reynolds stress intensity. In addition, although the skin friction coefficient and ΔU+ are almost the same, the real-world roughness and the corresponding equivalent regular roughness manifest different flow structures near the wall. The real-world roughness contributes greater spatial inhomogeneity but lower turbulence intensity.

Shear Resistance Evolution of Geogrid-Aggregate Interfaces under Direct Shear: Insights from 3D DEM Simulations

This paper presents a mesoscopic evaluation of the shear resistance evolution of geogrid-aggregate interfaces subjected to direct shear loading. A three-dimensional discrete element method (DEM) model was developed based on experimental data. The tensile response of geogrid were simulated through a series of calibration tests. Aggregate with complex particle shapes were simulated to accurately capture the interlocking effect among aggregates based on the real particle surface. The individual shear resistance components were quantified based on particle displacement field and contact distribution characteristics. The influences of aperture-aggregate size ratio and geogrid stiffness on the shear resistance components are discussed. The results indicate that the peak value of shear resistance component follows a descending order from frictional resistance of aggregate, to passive resistance of transverse rib, and to geogrid-aggregate interface frictional resistance. During the shear process, the frictional resistance of aggregate becomes active first, followed by the geogrid-aggregate interface frictional resistance, and then the development of passive resistance of transverse ribs starts with a certain lag. Optimizing the geogrid-aggregate size ratio and utilizing geogrids with higher rib stiffness could enhance the passive resistance of transverse ribs but would not significantly affect the geogrid-aggregate interface frictional resistance and frictional resistance of aggregate.

Waves from compact SeaSonde® High Frequency radars in the southeastern Bay of Biscay: measurement performance under different noise and wind conditions

Global concern on extreme events is increasing the need for real time monitoring of the wave fields in coastal areas. High Frequency (HF) radars, a remote sensing technology widely applied to measure near real time surface coastal currents with demonstrated accuracy, can also play a major role in the operational monitoring of waves height, period and direction. However, the ability of HF radar to measure waves can be jeopardized by specific ocean-meteorological and environmental conditions. Thus, a case-to-case analysis and parameterization is necessary to ensure the best data in each study area. In the southeastern (SE) Bay of Biscay, the EuskOOS HF radar network, composed by two compact HF radar stations provides hourly surface waves data in near real time. In this work, we analyze the effects of wind and noise levels on the radar skills for wave measurement, compared with existing in-situ data obtained by an offshore buoy. Then, the HF radar wave measurements for 2022 are analyzed with special focus on the most energetic observed wave events. The analysis performed versus in-situ data shows that both stations present reliable and accurate data for waves over 1.5 m, in agreement to what can be expected for a 4.46 MHz radar. The highest correlations are observed for waves > 4 m significant wave height, which demonstrates the capabilities for monitoring highly energetic events. Interference and noise detected on very precise time slots significantly reduced the availability and reliability of the measurements. Also, local winds blowing from land direction were found to affect the agreement between radar and in-situ measurements. Recommendations extracted from the analysis are provided, with the aim that they can be extended to other HF networks for more accurate wave monitoring.

Humic substances mediated superior photochemical pollutant conversion on defective TiO2 in environmentally relevant matrices: The key roles of oxygen vacancy in surface interactions, oxidant activation and radical generation

Ubiquitous humic substances usually exhibit strong interfering effects on target pollutant removal in advanced water purification. This work aims to develop a photochemical conversion system on the nonstoichiometric TiO2 for pollutant removal in environmentally relevant matrices. In this synergistic reaction system, the redox-reactive humic substances and defective oxygen vacancies can serve as the organic electron transfer mediator and the key surface reactive sites, respectively. This system achieves a superior pollutant degradation in real surface water at low oxidant concentrations. Reactive oxygen vacancies on the TiO2 surface and sub-surface are of considerable interest for this photochemical reaction system. By engineering defective oxygen vacancies on high-energy {001} polar facet, the surface and electronic interactions between tailored TiO2 and humic substances are greatly strengthened for the promoted electron transfer and oxidant activation. Rendered by the strong surface affinity and molecular activation, defective oxygen vacancies thermodynamically and dynamically promote reactive chain reactions for free radical formation, including the selective O2 reduction to ·O2− and the H2O2 activation to ·OH. Our findings take new insights into environmental geochemistry, and provide an effective strategy to in-situ boost the humic substances-mediated water purification without secondary pollution. Environmental implicationHumic substances are widely distributed in aquatic environment, thus playing important roles in environmental geochemistry. For example, humic substances can achieve good surface adsorption through electrostatic adsorption, ligand exchange and electronic interactions with typical TiO2 to form reactive ligand-metal charge transfer complexes for pollutant degradation. Inspired by the unique properties of surface and sub-surface oxygen vacancies, the defective TiO2 was designed to refine the humic substances-mediated photochemical reactions. A superior reactivity was measured for pollutant degradation. Our findings provide an effective strategy to boost naturally photochemical decontamination in environmentally relevant matrices.

Deciphering Structure-Activity Relationship Towards CO2 Electroreduction over SnO2 by A Standard Research Paradigm.

Authentic surface structures under reaction conditions determine the activity and selectivity of electrocatalysts, therefore, the knowledge of the structure-activity relationship can facilitate the design of efficient catalyst structures for specific reactivity requirements. However, understanding the relationship between a more realistic active surface and its performance is challenging due to the complicated interface microenvironment in electrocatalysis. Herein, we proposed a standard research paradigm to effectively decipher the structure-activity relationship in electrocatalysis, which is exemplified in the CO2 electroreduction over SnO2 . The proposed practice has aided in discovering authentic/resting surface states (Sn layer) of SnO2 accountable for the electrochemical CO2 reduction reaction (CO2 RR) performance under electrocatalytic conditions, which then is corroborated in the subsequent CO2 RR experiments over SnO2 with different morphologies (nanorods, nanoparticles, and nanosheets) in combination with in situ characterizations. This proposed methodology is further extended to the SnO electrocatalysts, providing helpful insights into catalytic structures. It is believed that our proposed standard research paradigm is also applicable to other electrocatalytic systems, in the meantime, decreases the discrepancy between theory and experiments, and accelerates the design of catalyst structures that achieve sustainable performance for energy conversion.

Deciphering Structure‐Activity Relationship Towards CO2 Electroreduction over SnO2 by A Standard Research Paradigm

AbstractAuthentic surface structures under reaction conditions determine the activity and selectivity of electrocatalysts, therefore, the knowledge of the structure‐activity relationship can facilitate the design of efficient catalyst structures for specific reactivity requirements. However, understanding the relationship between a more realistic active surface and its performance is challenging due to the complicated interface microenvironment in electrocatalysis. Herein, we proposed a standard research paradigm to effectively decipher the structure‐activity relationship in electrocatalysis, which is exemplified in the CO2 electroreduction over SnO2. The proposed practice has aided in discovering authentic/resting surface states (Sn layer) of SnO2 accountable for the electrochemical CO2 reduction reaction (CO2RR) performance under electrocatalytic conditions, which then is corroborated in the subsequent CO2RR experiments over SnO2 with different morphologies (nanorods, nanoparticles, and nanosheets) in combination with in situ characterizations. This proposed methodology is further extended to the SnO electrocatalysts, providing helpful insights into catalytic structures. It is believed that our proposed standard research paradigm is also applicable to other electrocatalytic systems, in the meantime, decreases the discrepancy between theory and experiments, and accelerates the design of catalyst structures that achieve sustainable performance for energy conversion.

Molecular Dynamics Study of Protein Aggregation at Moving Interfaces.

Repeated compression and dilation of a protein film adsorbed to an interface lead to aggregation and entry of film fragments into the bulk. This is a major mechanism for protein aggregate formation in drug products upon mechanical stress, such as shaking or pumping. To gain a better understanding of these events, we developed a molecular dynamics (MD) setup, which would, in a later stage, allow for in silico formulation optimization. In contrast to previous approaches, the molecules of our model protein human growth hormone displayed realistic shapes, surfaces, and interactions with each other and the interface. This enabled quantitative assessment of protein cluster formation. Simulation outcomes aligned with experimental data on subvisible particles and turbidity, thereby validating the model. Computational and experimental results indicated that compression speed does not affect the aggregation behavior of preformed protein films but rather their regeneration. Protein clusters that formed during compression disassembled upon relaxation, suggesting that the particles originate from a partly compressed state. Desorption studies via steered MD revealed that proteins from compressed systems are more likely to detach as clusters, implying that compression effects at the interface translate into aggregates present in the bulk solution. With the possibility of studying the impact of different variables upon compression and dilation at the interface on a molecular level, our model contributes to the understanding of the mechanisms of protein aggregation at moving interfaces. It also enables further studies to change formulation parameters, interfaces, or proteins.

Completing the picture of field-grown cereal crops: a new method for detailed leaf surface models in wheat.

The leaf angle distribution (LAD) is an important structural parameter of agricultural crops that influences light interception, radiation fluxes and consequently plant performance. Therefore, LAD and its parametrized form, the Beta distribution, is used in many photosynthesis models. However, in field cultivations, these parameters are difficult to assess and cereal crops in particular pose challenges since their leaves are thin, flexible, and often bent and twisted around their own axis. To our knowledge, there is only a very limited set of methods currently available to calculate LADs of field-grown cereal crops that explicitly takes these special morphological properties into account. In this study, a new processing pipeline is introduced that allows for the generation of realistic leaf surface models and the analysis of LADs of field-grown cereal crops from 3D point clouds. The data acquisition is based on a convenient stereo imaging setup. The approach was validated with different artificial targets and results on the accuracy of the 3D reconstruction, leaf surface modeling and calculated LAD are given. The mean error of the 3D reconstruction was below 1mm for an inclination angle range between 0° and 75° and the leaf surface could be quantified with an average accuracy of 90%. The concordance correlation coefficient (CCC) of 99.6% (p-value = [Formula: see text]) indicated a high correlation between the reconstructed inclination angle and the identity line. The LADs for bent leaves were reconstructed with a mean error of 0.21° and a standard deviation of 1.55°. As an additional parameter, the insertion angle was reconstructed for the artificial leaf model with an average error < 5°. Finally, the method was tested with images of field-grown cereal crops and Beta functions were approximated from the calculated LADs. The mean CCC between reconstructed LAD and calculated Beta function was 0.66. According to Cohen, this indicates a high correlation. This study shows that our image processing pipeline can reconstruct the complex leaf shape of cereal crops from stereo images. The high accuracy of the approach was demonstrated with several validation experiments including artificial leaf targets. The derived leaf models were used to calculate LADs for artificial leaves and naturally grown cereal crops. This helps to better understand the influence of the canopy structure on light absorption and plant performance and allows for a more precise parametrization of photosynthesis models via the derived Beta distributions.

Mechanical Alloying Synthesis of AB3 Zirconium Substituted Intermetallic

Abstract: Several ternary RareEarth-Magnesium-Nickel intermetallics (RE-Mg-Ni) emerged in last decade for their specific hydrogen storage capability. Nickel is now considered among strategic metals with recurrent rising price, Magnesium although its good gravimetric facility suffers from frequent oxidation or irreversible poisoning. Zirconium alloys are recognized for their improved anti-corrosion properties with enhanced wear resistance for high temperature machinability in industrial applications or energy research purposes. We proposed in this paper double substitution possibility replacing Magnesium and reducing Nickel charge. We developed new generation of quaternary Zirconium-AB3 intermetallic LaZr2Ni5Al4 using mechanical alloying method. Two binary raw materials are involved in this alloying reaction, the first is LaNi5 and the second is ZrAl2 (Laves phase C14) and both precursors are achieved quasi-quantitively using high frequency induction melting. The final target AB3 compound crystallizes in Trigonal system with space group R-3m (166) and following experimental conditions (Fritsch P7, Ω = 450 rpm) an acceptable synthesis yield (&amp;gt;80%) is obtained starting from 20 hours mechanical alloying. Rietveld refinement is performed to have real matrix parameters and AB3 powder surface is analyzed using Scanning Electron Microscopy.

Entropy of real rational surface automorphisms: actions on the fundamental groups

Entropy of real rational surface automorphisms: actions on the fundamental groups

A systematic investigation of detectors for low signal-to-noise ratio EMG signals

Background Active participation of stroke survivors during robot-assisted movement therapy is essential for sensorimotor recovery. Robot-assisted therapy contingent on movement intention is an effective way to encourage patients’ active engagement. For severely impaired stroke patients with no residual movements, a surface electromyogram (EMG) has been shown to be a viable option for detecting movement intention. Although numerous algorithms for EMG detection exist, the detector with the highest accuracy and lowest latency for low signal-to-noise ratio (SNR) remains unknown. Methods This study, therefore, investigates the performance of 13 existing EMG detection algorithms on simulated low SNR (0dB and -3dB) EMG signals generated using three different EMG signal models: Gaussian, Laplacian, and biophysical model. The detector performance was quantified using the false positive rate (FPR), false negative rate (FNR), and detection latency. Any detector that consistently showed FPR and FNR of no more than 20%, and latency of no more than 50ms, was considered an appropriate detector for use in robot-assisted therapy. Results The results indicate that the Modified Hodges detector – a simplified version of the threshold-based Hodges detector introduced in the current study – was the most consistent detector across the different signal models and SNRs. It consistently performed for ~90% and ~40% of the tested trials for 0dB and -3dB SNR, respectively. The two statistical detectors (Gaussian and Laplacian Approximate Generalized Likelihood Ratio) and the Fuzzy Entropy detectors have a slightly lower performance than Modified Hodges. Conclusions Overall, the Modified Hodges, Gaussian and Laplacian Approximate Generalized Likelihood Ratio, and the Fuzzy Entropy detectors were identified as the potential candidates that warrant further investigation with real surface EMG data since they had consistent detection performance on low SNR EMG data.

Chimera metasurface for multiterrain invisibility

Invisibility, a fascinating ability of hiding objects within environments, has attracted broad interest for a long time. However, current invisibility technologies are still restricted to stationary environments and narrow band. Here, we experimentally demonstrate a Chimera metasurface for multiterrain invisibility by synthesizing the natural camouflage traits of various poikilotherms. The metasurface achieves chameleon-like broadband in situ tunable microwave reflection mimicry of realistic water surface, shoal, beach/desert, grassland, and frozen ground from 8 to 12 GHz freely via the circuit-topology-transited mode evolution, while remaining optically transparent as an invisible glass frog. Additionally, the mechanic-driven Chimera metasurface without active electrothermal effect, owning a bearded dragon-like thermal acclimation, can decrease the maximum thermal imaging difference to 3.1 °C in tested realistic terrains, which cannot be recognized by human eyes. Our work transitions camouflage technologies from the constrained scenario to ever-changing terrains and constitutes a big advance toward the new-generation reconfigurable electromagnetics with circuit-topology dynamics.

Assessment of the urban habitat quality service functions and their drivers based on the fusion module of graph attention network and residual network

ABSTRACT Land use/cover change is a major cause of ecological degradation. Reliable LUCC data are essential for evaluating habitat quality. The current method of surface cover classification based on the convolutional neural networks (CNNs) is usually a local spatial operation using a regular convolutional kernel, which ignores the correlation between adjacent image elements. This paper proposes a combination network with two branches, branch 1 uses the K-nearest neighbor clustering algorithm to construct superpixels and then uses the data transformation module to construct a graph attention network (GAT); branch 2 constructs the CNN using attention and residual modules to obtain the spatial and higher-order semantic information of the images. Finally, the features are fused using weighted fusion, and a classification map with less point noise and greater consistency with the real surface coverage is obtained. The classification results of this network are better than those of the other competitive methods. In addition, the urbanization of Sanya has resulted in significant habitat degradation. A good fit ( R 2 in 2020 = 0.639) between habitat quality (HQ) and natural and socioeconomic factors was observed in Sanya. Natural factors are more relevant to HQ than socioeconomic factors and vary spatially.

Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process

Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.

Cadmium oxide nanoparticles doped with nickel and silver: Photocatalytic activity for environmental remediation

In this work, we used a co-precipitation approach to create CdO nanoparticles that were co-doped with nickel (Ni) and silver (Ag). X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) were employed to assess the structural attributes of the nanoparticles that were synthesized. Co-doping with Ni and Ag resulted in a steady rise in nanoparticle crystallite size, increasing from 20.97 nm to 32.16 nm. Following the co-doping procedure, FESEM pictures demonstrated a morphological shift from tiny, rock-like formations in pure CdO to bigger rock-like structures. Energy-dispersive X-ray spectroscopy (EDX) was utilised to explore the compositional characteristics of Ni and Ag-doped CdO nanoparticles. The existence of particles’ agglomerations was observed, which may have limited the real surface area available for gas adsorption and resulted in smaller apparent pore sizes in the Brunauer-Emmett-Teller (BET) investigation. Diffused Reflectance Spectroscopy (DRS) revealed a decline in the band gap from 2.45eV to 2.30eV, which was most likely caused by structural changes caused by cadmium ion replacement or the occupancy of interstitial spaces within the lattice by nickel and silver ions. The chemical and electronic states of the atoms were assessed using X-ray photoelectron spectroscopy (XPS), which examined the formation of defects in the form of oxygen vacancies, which contributed to accelerated photocatalytic performance. The deterioration of Crystal Violet (CV) dye during sunlight exposure utilising co-doped CdO nanoparticles vs pristine CdO is being evaluated in the evaluation of photocatalytic activity. Notably, co-doped nanoparticles improved photocatalytic activity significantly, with CV degradation reaching up to 95 % within 180 min of exposure. The potential of Ni and Ag impregnated CdO nanoparticles as effective photocatalysts for environmental remediation applications is highlighted in this study.

Effects of Mg(II) doping amount on the hydration characteristics of kaolinite surface: Molecular dynamics simulations and experiments

To explore the microscopic effects of Mg(II) doping amount on the hydration characteristics of kaolinite surface, the Mg(II) ions and kaolinite were used as the subjects of research in molecular dynamics simulations and experimental verification to investigate the microscopic effects of the lattice magnesium impurity on the surface hydration of kaolinite. The results indicate that the interaction between H2O and Mg(II)-doped kaolinite (Mg(II)-Kao) surfaces, along with hydrogen bonding at the interface, gradually increase with increasing Mg(II) doping amounts, implying that Mg(II) doping significantly enhance the surface hydration of kaolinite. The hydration of the Mg(II)-doped kaolinite (001) surface (Mg(II)-Kao(001)) is stronger than that of the Mg(II)-doped kaolinite (001¯) surface (Mg(II)-Kao(001¯)) with the same Mg(II) doping amount. As the quantity of Mg(II) doping increased, the contact angle and humidity of the kaolinite surface decrease and progressively increase, respectively, signifying that the hydration level of the kaolinite surface increase. Overall, the main influence of Mg(II) doping on the surface hydration properties of kaolinite is the enhancement of hydration activity and ionic hydration. The results can provide theoretical support for further study of the real clay surface hydration mechanism, efficient treatment of clay-containing mineral processing wastewater and resource utilization of coal measure clay.

Insight into the adsorption and co-adsorption of PPCPs on Ti3C2Tx MXene: Behaviors, mechanisms and application potentials

In this study, four pharmaceutical compounds including sulfamethoxazole (SMX), oxytetracycline (OTC), ciprofloxacin (CIP), and ibuprofen (IBU) with different functional groups and pKa, were selected as representative pollutants to systematically investigate the Pharmaceutical and Personal Care Products (PPCPs) adsorption on a nanomaterial Ti3C2Tx MXene in simulated solution and real surface water. The results show that Ti3C2Tx was an excellent PPCPs adsorbent, but the process was affected by the characteristics of pollutants pronouncedly, the obtained maximum adsorption capacity were OTC (210.97 mg/g) > IBU (185.05 mg/g) > CIP (160.60 mg/g) > SMX (68.12 mg/g). Specially, the charge screen effect caused Ti3C2Tx precipitation during CIP adsorption. The response surface methodology analysis indicates that initial solution pH (3–11) had significant effects, while the influence of humic acid (0–10 mg/L) or sodium chloride (0–10 mg/L) was limited, and the interactions between these factors was slight. In the co-adsorption process, the competitive effects reduced the adsorption of SMX and IBU, however, the enhanced positive ionization and the possible electrostatic repulsive interactions promoted that of CIP and OTC. In real surface water, although the influence of natural organic matters was negligible, the preferential adsorption of background metal ions such as aluminum and calcium ions reduced the adsorption capacity of the selected PPCPs by approximately 29.9 % to 88.4 %. Moreover, the adsorbent characterization conjoined with performance examination imply that electrostatic attraction dominated the Ti3C2Tx adsorption of PPCPs, and hydrogen bonding interactions as well as surface complexation might also contributed. These observations suggest that Ti3C2Tx MXene has the potential for use as adsorbent to eliminate aqueous PPCPs, nevertheless, the interference of co-existing metal ions and the stability of adsorbent were also noteworthy.

Influence of manufacturing surface topography on torque and load bearing capacity of hydro-viscous drive clutch under mixed lubrication stage

PurposeHydro-viscous drive (HVD) clutches are widely used in equipment requiring soft start, such as fans and pumps, to transmit torque and adjust speed by changing the gap distance between friction pairs. This paper aims to propose a novel two-parameter evaluation method for HVD during the mixed lubrication stage. The objective is to develop an effective model that establishes the relationship between these parameters and the actual surface topography.Design/methodology/approachIn the presented methods, the fractal features of the real manufacturing surface are calculated based on the power spectrum function by the ultra-depth three-dimensional microscope. After that, the hybrid friction model of the friction plate is established based on mixed elasto-hydrodynamic lubrication theory, boundary friction model and fractal theory. Then the torque and load bearing characteristics of the clutch are obtained, and the influences of the surface fractal features are investigated and discussed. Finally, the Weierstrass–Mandelbrot function is adopted for the surface topography characterization and evaluation.FindingsThe results indicate that the proposed method exhibits good accuracy, while the speed difference between the friction pair exceeds 2,500 rpm. It is concluded that this paper proposed a way to evaluate the torque and loading capacity of HVD considering the real manufacturing surface topography and is helpful for surface optimization.Originality/valueThe originality and value of this study lie in its development of a novel torque and load bearing capacity evaluation method for HVD in mixed lubrication stage, considering manufacturing surface topography and describing the real manufacturing surface.

Gear Hob Base Worm Modelling from a Straight Toothed Generating Rack

The precision of a gear realized by hobbing is mainly influenced by the precision of the base worm, the adequate form of the rake face and the number of resharpenings. Gearing theory states that the base worm of a gear hob must be of involute type. Despite of this, manufacturing technology often admits a convolute worm as gear hob base worm. Due to the rake face grinding technology, there appears a difference between the theoretical and the real surface. On the other hand, the profile modification of the cutting edges occurs due to the re-sharpening. As a result, the cutting edges cannot reproduce that initial basic worm surface from which the gear hob was derived. In our opinion, the computing of the generating surfaces of the basic worm is still an unsolved problem. This paper deals with the study of a worm derived from a straight toothed generating rack. The incidence of an involute worm and that developed from the generating rack is investigated.

Energy dissipation of a contact line moving on a nanotopographical defect.

Understanding the origin of the dissipative mechanisms that control the dynamics of a contact line is a real challenge. In order to study the energy dissipation at the contact line when a moving meniscus encounters topographical defects, we developed atomic force microscopy (AFM) experiments using nanofibers with nanometer scale defects. These experiments realized with three liquids are performed in two AFM modes: the contact mode (C-AFM) is used to measure the energy associated with the contact angle hysteresis in the limit of a static situation, deduced from advancing and receding dipping experiments on an isolated defect; the frequency-modulation mode (FM-AFM) is performed at different amplitudes and then velocities to measure the energy dissipated as the contact line moves over the same defect. Strong dissipation peaks appear above a threshold amplitude characteristic of the liquid and the defect, which is determined by the width of the hysteresis measured in statics. Furthermore, the dissipation energy of the moving contact line measured in dynamics is equal to the hysteresis capillary energy whatever the amplitude and is therefore independent of the contact line velocity. These results point out that the defect contribution to dissipation energy of a moving contact line on real surfaces is only governed by the pinning-depinning energy with no contribution of viscous effects.