Spreading Process Research Articles

Study on oil film spreading characteristics on the jet lubricating tooth surface of aviation herringbone gear

Purpose During the oil lubrication process of aviation herringbone gears, lubricating oil is injected into and spreads around the tooth surface. Its spreading characteristics directly affect the lubrication state and transmission efficiency of gears. This study aims to investigate the effect of changing the injection parameters and gear operating conditions on the oil film deposition during injection lubrication. Design/methodology/approach The computational fluid dynamics method was used to establish the computational domain for the simulation and optimization using an orthogonal test. The oil film spreading and thickness of the tooth surface were calculated with the change in gear speed, fuel injection distance and fuel injection speed. Optimized oil injection lubrication parameters were obtained, and design ideas were provided for the oil injection lubrication analysis of aviation herringbone gears. Findings Under different operating conditions, such as varying the injection speed, gear rotational speed and injection distance, there were differences in the distribution of the lubricating oil film formed on the tooth surface. The thickness of the oil film decreases as the distance from the injection port increases. The thickness of the oil film deposition can be increased by increasing the injection velocity and reducing the gear rotation speed. The injection distance had a relatively small effect on the spreading thickness of the deposited oil film, affecting only the dynamic spreading process of oil film deposition. Furthermore, the simulation results are compared with the analytical calculation results, and finally the experimental verification is carried out. Originality/value Oil spray lubrication characteristics are important for achieving precise gear lubrication designs in the aerospace field. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0250/

Crowd Density Estimation via Global Crowd Collectiveness Metric

Drone-captured crowd videos have become increasingly prevalent in various applications in recent years, including crowd density estimation via measuring crowd collectiveness. Traditional methods often measure local differences in motion directions among individuals and scarcely handle the challenge brought by the changing illumination of scenarios. They are limited in their generalization. The crowd density estimation needs both macroscopic and microscopic descriptions of collective motion. In this study, we introduce a Global Measuring Crowd Collectiveness (GMCC) metric that incorporates intra-crowd and inter-crowd collectiveness to assess the collective crowd motion. An energy spread process is introduced to explore the related crucial factors. This process measures the intra-crowd collectiveness of individuals within a crowded cluster by incorporating the collectiveness of motion direction and the velocity magnitude derived from the optical flow field. The global metric is adopted to keep the illumination-invariance of optical flow for intra-crowd motion. Then, we measure the motion consistency among various clusters to generate inter-crowd collectiveness, which constitutes the GMCC metric together with intra-collectiveness. Finally, the proposed energy spread process of GMCC is used to merge the inter-crowd collectiveness to estimate the global distribution of dense crowds. Experimental results validate that GMCC significantly improves the performance and efficiency of measuring crowd collectiveness and crowd density estimation on various crowd datasets, demonstrating a wide range of applications for real-time monitoring in public crowd management.

An adaptive differential evolution algorithm driven by multiple probabilistic mutation strategies for influence maximization in social networks

Influence maximization is a critical research topic of social network analysis, particularly with the increasing involvement of individuals in the global networked society. The purpose of the problem is to identify k influential nodes from the social network and activate them initially to maximize the expected number of influenced nodes at the end of the spreading process. Although some meta-heuristics based on swarm intelligence or biological evolution have been proposed to tackle this intractable problem, further investigation is required to refine the exploration and exploitation operations based on the iterative information from the evolutionary process. In this paper, an adaptive differential evolution algorithm driven by multiple probabilistic mutation strategies is proposed for the influence maximization problem. In order to enhance the evolutionary capability of the later stages of the discrete differential evolution, the mutation in the framework, consisting of three policies, namely comprehensive learning particle swarm mutation strategy, differential mutation strategy, and perturbation strategy, is implied based on different probabilistic models. An adaptive local search strategy is presented to improve the local optimum results based on a potential alternative library consisting of structural hole nodes, which guides the differential evolution to find a more optimal solution. Experimental results on six real-world social networks demonstrate the competitive performance of the proposed algorithm in terms of both efficacy and efficiency compared to state-of-the-art algorithms.

3DDA: A Novel Python Toolkit to Analyze 3D‐Dynamic Contact Angles from Molecular Dynamics Simulations

Obtaining fast and reliable contact angles in molecular dynamics simulations is crucial for screening surface wettability. Traditional methods rely on bidimensional density profile analysis to localize the liquid/vapor interface, which may not be optimal at the nanoscale, especially for nonsymmetrical droplets. Herein, 3DDA, a Python‐based code that uses the 3D droplet geometry to determine contact angles and analyze dynamic changes during spreading processes at the nanoscale, is presented. The 3D density profile of liquid molecules is enveloped using the Euclidean 3D convex hull algorithm to locate the contact line at the solid‐, liquid‐, and vapor‐phase boundaries. By fitting a general ellipsoidal function and optimizing it with the limited‐memory Broyden–Fletcher–Goldfarb–Shanno method, the best candidate function is analytically obtained, describing the interface. The angle derived from the ellipsoidal function and the solid boundary is used to gather a collection of contant angles, which are then fed into a kernel density estimator to determine the most probable angle along the contact line during the spreading process. This methodology is tested on systems such as liquid water and metals, demonstrating its efficacy and reliability. Herein, valuable insights are provided into the behavior of liquids, considering droplet asphericity induced by liquid/solid interactions.

Solidification process of hollow metal droplets impacting a substrate

Recently, there has been a renewed interest in hollow droplet impact, as the internal bubble makes a difference in the spreading morphology during thermal spraying and three-dimensional printing. This paper is dedicated to the solidification process of a hollow metal droplet impacting a cold substrate. The influence of initial impact velocity and substrate temperature on the spreading process is numerically investigated by employing a phase-field method coupled with a solidification model. Solidification was shown to strongly alter droplet spreading and the flow state of the center liquid column. To describe the flow state of the center liquid column, three patterns, namely ‘no-jet’, ‘transition region’, and ‘counter-jet’ are defined. The simulation results show that the formation of the center counter-jet is inhibited by the solidification layer when Péclet number Pe<357, where Pe is the ratio of convection rate to diffusion rate. In addition, the critical Pe at which the phenomenon of counter-jet occurs gradually rises with the substrate temperature falling. Finally, a quantitative analysis of the maximum spreading diameter is proposed by establishing an energy conservation equation. The predicted diameters are in good agreement with the simulated results. It allows us to provide a general expression for the hollow droplets' maximum spreading diameter, using the impact and temperature parameters.

Numerical Studies of Influencing Factors on the Homogeneity of the Powder Mixture during the Powder Spreading Process of Powder Bed Fusion–Laser Beam/Metal

Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by powder bed fusion–laser beam/metal (PBF‐LB/M). However, N‐induced pore formation remains a challenge. To overcome this, a combined PBF‐LB/M and hot isostatic pressing (HIP) process is developed. AISI 304L stainless steel powder was mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. This helps to maintain sufficient N content while reducing pore formation. The microstructure is then homogenised by HIP. A major challenge of this process is to maintain the homogeneity of the deposited powder mixture on the powder bed to ensure a consistent N content in the final products. This study combines experimental and numerical methods to address this issue: scanning electron microscopy is used to characterize the microstructure and map the local N content, while various numerical studies based on the discrete element method are carried out to investigate the effects of layer thickness, substrate surface roughness, and powder properties on the intermediate product. The numerical approach effectively predicts the N content distribution and homogeneity on the powder bed. The models are validated with experimental data and optimal process conditions for PBF‐LB/M are identified.

Overdose as a complex contagion: modelling the community spread of overdose events following law enforcement efforts to disrupt the drug market

BackgroundThe opioid overdose mortality crisis in the USA is an ongoing public health epidemic. Ongoing law enforcement strategies to disrupt local unregulated drug markets can have an iatrogenic effect of...

Dynamic characteristics of droplet impact on a cold cylindrical surface

The freezing phenomenon often leads to economic and safety losses in various industries. Studying the processes of droplets impact on cold surfaces is beneficial in preventing potential harm. In this study, the processes of droplet impact on a cold cylindrical surface are investigated by high-speed photography. How the dynamic characteristics are affected by Weber number and surface temperature are studied. The results indicate that when the surface temperature is between −25 to −5 °C, an increase in Weber number results in higher initial kinetic energy and greater viscous dissipation. During the spreading process, the initial kinetic energy predominates, leading to an increase in the maximum spreading ratio. However, the rise in viscous dissipation contributes to an increase in the stable ratio. As Weber number increases, both the maximum spreading time and stable time decrease. Over the same range of surface temperatures, a decrease in surface temperature results in increased viscous dissipation, which leads to a reduction in the maximum spreading ratio. The maximum spreading time and stable time, however, are not significantly affected by surface temperature. Moreover, the relationships of the maximum spreading ratios and stable ratios between axial and circumferential directions are constructed respectively. These relationships exhibit similar linear characteristics, which are not affected by the Weber number and surface temperature.

Accelerating Laser Powder Bed Fusion: The Influence of Roller-Spreading Speed on Powder Spreading Performance

The powder spreading process is a fundamental element within the laser powder bed fusion (PBF-LP) framework given its pivotal role in configuring the powder bed. This configuration significantly influences subsequent processing steps and ultimately determines the quality of the final manufactured part. This research paper presents a comprehensive analysis of the impacts of varying spreading speeds, which are enabled by different roller configurations, on powder distribution in PBF-LP. By utilizing extensive Discrete Element Method (DEM) modelling, we systematically examine how spreading speed affects vital parameters within the spreading process, including packing density, mass fraction, and actual layer thickness. Our exploration of various roller configurations has revealed that increasing spreading speed generally decreases packing density and layer thickness for non-rotating, counter-rotating, and forward-rotating rollers with low clockwise rotational speeds (sub-rolling) due to powder dragging. However, a forward-rotating roller with a high clockwise rotational speed (super-rolling) balances momentum transfer, enhancing packing density and layer thickness while increasing surface roughness. This configuration significantly improves the uniformity and density of the powder bed, providing a technique to accelerate the spreading process while maintaining and not reducing packing density. Furthermore, this configuration offers crucial insights into optimizing additive manufacturing processes by considering the complex relationships between spreading speed, roller configuration, and powder spreading quality.

Review of agronomic and kernel quality traits of 273 almond cultivars

AbstractAlmond stands out as one of the best-adapted temperate tree species globally. Its adaptability facilitated a widespread distribution from Central Asia to regions such as the Mediterranean, the United States, and Australia, enabling the adaptation of different genotypes to specific edaphoclimatic conditions. Throughout this spreading process, diverse almond landraces were selected in each growing area, resulting in a collection with varying agronomic and kernel quality properties well adapted to each origin. In addition to these native cultivars, various almond breeding programs, both public and private, released new cultivars to address key issues related to the production and kernel quality of traditional cultivars. This collective effort has resulted in a wide range of cultivars with diverse phenotypic characteristics, available for cultivation and breeding purposes. In this review, we summarize the main agronomic and kernel quality characteristics of globally available cultivated almond germplasm. This germplasm comprises genotypes from Asia, Africa, North America, South America, Australia, and Europe, either locally cultivated or released from breeding programs. For each cultivar, we provide information (if known) on the origin, parentage, year of introduction, self-(in)compatibility, S alleles, blooming time, chilling, and heat requirements, bearing habits, kernel and shell characteristics, harvesting time, tree characteristic, and disease susceptibility/resistance. In conclusion, the global diversity of cultivated almond germplasm presented in this review provides a valuable repository of phenotypic traits and genetic resources to continue advancements in almond cultivation and breeding worldwide.

Impact of a compound droplet on a solid surface: The effect of the shell on the core

The dynamic behavior of compound droplets impacting a solid surface was studied via experiments over κ (defined as the ratio of the compound droplet shell thickness h to the diameter D0 of compound droplet) ranging from 0 to 0.34, We ranging from 25 to 325 and Re ranging from 165.3 to 3405.2. The spreading diameter ratio, the maximum spreading dynamic contact angle and spreading speed of the core were investigated. Four modalities of the core of compound droplets were observed on the solid surface, including a) core rebound, b) no rebound, c) core splitting rebound, d) core splitting. The results revealed that the thickness of the shell, We, and the viscosity of the shell have a significant effect on the rebound and spreading processes of the core of the compound droplet. The high viscosity oil shell is conducive to its spreading. As the thickness of the oil shell increases, its cushioning effect on the water core also increases. In addition,κ=0.02254We0.503,κ=-0.336e-We121.056+0.319 and κ=0.06086e-We121.056+0.07716e-We121.70598+0.01595 were used to divide the modal boundary of the compound droplet core. Further analysis reveals the correlation between We, Re, βm and.κ,12+Weβm=8+31-cos22.78+84.57κβm3+0.955We1.05Reβm6.5.

Coevolution of non-pharmaceutical interventions and infectious disease spreading in age-structured populations

In the face of emerging major infectious diseases, non-pharmaceutical interventions (NPIs) such as mask-wearing are the primary means of disease control in the early stages due to the lack of effective pharmaceutical interventions. Yet the current understanding of the dynamic feedback loop between NPIs and infectious disease spreading remains limited. In this study, we proposed an asymmetrically coupled dynamic model of the coevolution of mask-wearing behaviour and infectious disease spreading in an age-structured population to describe the bidirectional relationship between NPIs such as mask-wearing and infectious disease spreading. A theoretical analysis framework was developed by extending the microscopic Markov chain method. To reflect the spreading process more realistically, we conducted numerical simulations from a mesoscopic perspective through an age-contact data-driven approach. Critical transition, multi-wave epidemics, multi-transitions, and mixed-phase transitions resulting from the coevolution of mask and disease are observed. The results highlight the critical role of NPIs in controlling disease spreading. The mask-wearing can effectively reduce the daily peak infection density and prevent large-scale outbreaks within a short period. However, it will also prolong the duration of the epidemic and cause the disease to exist in the population for a long time. There is a trade-off between the two. For certain diseases with specific spreading capabilities, pharmaceutical interventions such as vaccination, which can directly reduce the disease’s infectiousness, may result in more people being infected if NPIs are not implemented as early as possible. In addition, results from Anhui indicate that people aged 42 years are at high risk of being infected because of their large population base, which suggests that priority should be given to the prevention and control of this group.

Targeting the TDP-43 low complexity domain blocks spreading of pathology in a mouse model of ALS/FTD

Abnormal cytoplasmic localization and accumulation of pathological transactive response DNA binding protein of 43 kDa (TDP-43) underlies several devastating diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP). A key element is the correlation between disease progression and spatio-temporal propagation of TDP-43-mediated pathology in the central nervous system. Several lines of evidence support the concept of templated aggregation and cell to cell spreading of pathological TDP-43. To further investigate this mechanism in vivo, we explored the efficacy of capturing and masking the seeding-competent region of extracellular TDP-43 species. For this, we generated a novel monoclonal antibody (mAb), ACI-6677, that targets the pathogenic protease-resistant amyloid core of TDP-43. ACI-6677 has a picomolar binding affinity for TDP-43 and is capable of binding to all C-terminal TDP-43 fragments. In vitro, ACI-6677 inhibited TDP-43 aggregation and boosted removal of pathological TDP-43 aggregates by phagocytosis. When injecting FTLD-TDP brain extracts unilaterally in the CamKIIa-hTDP-43NLSm mouse model, ACI-6677 significantly limited the induction of phosphorylated TDP-43 (pTDP-43) inclusions. Strikingly, on the contralateral side, the mAb significantly prevented pTDP-43 inclusion appearance exemplifying blocking of the spreading process. Taken together, these data demonstrate for the first time that an immunotherapy targeting the protease-resistant amyloid core of TDP-43 has the potential to restrict spreading, substantially slowing or stopping progression of disease.

Modelling study on pedestrian evacuation dynamics considering exit selection behaviour under flood disaster

Flood spreading in metro stations is a dangerous hazard that frequently causes casualties and property losses. However, pedestrian evacuation under flood spreading scenarios has not been fully investigated. To fill this gap,we propose an extend Floor-Field model incorporating flood spreading and exit selection behaviour of individuals. In the model, the dynamic flood spreading process on metro platforms is expressed by using a simulation software named Mike21. The optimal exit selected by pedestrians in each step is decided on three factors, that is pedestrian density around the exit, pedestrian distance to the exit, and water depth at the exit. Meanwhile, the movement speed of pedestrain also changes with the water depth at each time step. Based on this, the transition probability to neighbor cell including static field, dynamic field, height field, and water flow field is calculated. This results in a flood evacuation model considering the pedestrian's behaviour when choosing an exit. The effects of flooding, pedestrian density, different exit selection behaviours, water flow field, and inlet flow on evacuation were thoroughly analysed. The analysis demonstrates that the likelihood of flooding significantly impacts the evacuation of pedestrians from the subway station; the more flooding is taken into account, the more influential the impact. In addition, the effect of inlet flow on evacuation is also noteworthy; considering exit selection behaviour can significantly increase the effectiveness of evacuation. The study's findings can be used to develop evacuation plans for flooded metro stations.

Mathematical modeling of pollution of underground aquifers due to mining of minerals

Purpose. The research aims to create a mathematical model of salt contamination spreading through underground aquifers in the event of depressurization of the hydrocarbon production well crater for further assessment of environmental and economic damage from these processes. Methods. To predict the environmental and economic damage from salt contamination, the distribution of concentrations of harmful substances was investigated, taking into account the number of supply sources and their intensity over time, based on situ studies at the Rybalske Oil Field, Okhtyrskyi District of Sumska Oblast in Ukraine, where there were technological failures wells, accompanied by open fountains with the release of large amounts of highly mineralized water and the formation of craters. Mathematical modelling methods were used to process the data from the study of accidental technogenic pollution of underground aquifers. Findings. Based on real data from the study of the processes of potential salt contamination spread in fresh aquifers as a result of accidents at hydrocarbon production facilities, a mathematical model of salt contamination spreading in drinking groundwater in the event of depressurization of an oil field well crater has been developed. Potential economic losses in case of possible groundwater contamination with highly mineralized solution, which can into drinking groundwater aquifers, are substantiated. It has been established that in connection with the occurrence of an emergency situation due to the release of formation water to the surface in the territory of oil and gas fields, the formation of technogenic meromictic reservoirs is possible, which is confirmed by the example of the Rybalske Oil Field. It is proved that the total mineralization of crater water increases linearly with depth of the reservoir occurrence, and a similar dependence is characteristic of the chloride ion content. Originality. For the first time, a multicomponent mathematical model of mineral salt migration processes in underground freshwater aquifers in the case of depressurization of a meromictic reservoir has been developed. Practical implications. The research results obtained using numerical methods make it possible to predict the processes of spreading harmful substances in drinking underground aquifers as a result of emergencies at oil and gas fields, taking into account the number of sources of pollutants penetrating the study area, the heterogeneity of properties of the environment into which the harmful substance enters, and to assess the dynamics of changes in the concentration of these substances and time with further assessment of environmental and economic damage from these processes.

A simplicial SSIS epidemic model with the outgoing pressure

A new simplicial epidemic model that considers the pressure of out-going is proposed to describe the characteristics of clustering on disease transmission more accurately. In addition, the probability evolution equations of nodes in each state are obtained by the quenched mean-field method. Furthermore, we analyze the conditions of the existence and the stability of the equilibrium points. Subsequently, the sensitivity analysis of the parameters is investigated, and it can be concluded that the degree about pairwise transmission rate has great impact on the propagation threshold. Our simulation results indicate that the system produces forward bifurcation or backward bifurcation via the one-parameter bifurcation diagram, and the bistable state of the system appears under certain conditions. Meanwhile, we obtain the transition conditions of the system from the disease-free equilibrium state to the bistable state through the divisional diagram. It is also noticed that the pressure of out-going plays a crucial role in the spreading process of diseases. On the one hand, the increasing of the pressure of out-going leads to the decreasing of the disease transmission threshold and a faster outbreak of disease. On the other hand, an increase in the individuals without the pressure of out-going causes the increasing of transmission threshold and a slower outbreak of disease.

Dilute Polymer Droplets Show Generalized Wetting Dynamics via an Average Viscosity.

Despite the prevalence of non-Newtonian fluids in various practical applications, comprehensive dynamic wetting models are lacking. Existing models often oversimplify complex rheological behavior, limiting our ability to predict wetting dynamics. This work introduces and experimentally validates a generalized model for the dynamic wetting of non-Newtonian shear-thinning fluids (dilute polymer solutions) on solid substrates. We experimentally analyzed 12 different shear-thinning fluids using both a power-law model and Carreau-Yasuda model. The data clearly show that the dynamic contact angle can be generalized using an average viscosity to capture rheological changes during droplet spreading. The average viscosity was defined using the fluid's constitutive model over shear rates relevant to the spreading process. Using a small droplet approximation, we propose and validate a semianalytical spreading model to predict the basal radius of non-Newtonian droplets. The model agrees well with the experimental data. Additionally, the average viscosity was used to define a spreading time scale, which is capable of collapsing the spreading of different non-Newtonian fluids onto a master spreading curve. This work offers significant potential for predicting the dynamic shape and spreading of non-Newtonian fluids with complex rheologies in a range of applications and industrial processes.

Assessing the impact of disease incidence and immunization on the resilience of complex networks during epidemics

Disease severity through an immunized population ensconced on a physical network topology is a key technique for preventing epidemic spreading. Its influence can be quantified by adjusting the common (basic) methodology for analyzing the percolation and connectivity of contact networks. Stochastic spreading properties are difficult to express, and physical networks significantly influence them. Visualizing physical networks is crucial for studying and intervening in disease transmission. The multi-agent simulation method is useful for measuring randomness, and this study explores stochastic characteristics of epidemic transmission in various homogeneous and heterogeneous networks. This work thoroughly explores stochastic characteristics of epidemic propagation in homogeneous and heterogeneous networks through extensive theoretical analysis (positivity and boundedness of solutions, disease-free equilibrium point, basic reproduction number, endemic equilibrium point, stability analysis) and multi-agent simulation approach using the Gilespie algorithm. Results show that Ring and Lattice networks have small stochastic variations in the ultimate epidemic size, while BA-SF networks have disease transmission starting before the threshold value. The theoretical and deterministic aftermaths strongly agree with multi-agent simulations (MAS) and could shed light on various multi-dynamic spreading process applications. The study also proposes a novel concept of void nodes, Empty nodes and disease severity, which reduces the incidence of contagious diseases through immunization and topologies.

Effect of blade geometry on the powder spreading process in additive manufacturing

In powder-bed-based additive manufacturing, the quality of the powder bed is closely related to the geometry of the blade used during the powder spreading process. In this study, the spreading process with the vertical blade, inclined blade, and round blade with different radii was performed by discrete element method to investigate the effects of blade geometry on powder spreading. The results show that at the same spreading parameters, the round blade caused the highest density than inclined blade and vertical blade. Increasing the round blade radius can improve the packing density of the powder bed, but it has little effect on the uniformity. The increase in packing density is related to the transitional smoothness of the blade surface at the entrance of the powder bed. The smoother the shape transition of the blade surface at the powder bed entrance, the powders enter the powder bed more gently, so more powders enter the powder bed, resulting in higher packing density. The results may provide suggestions for improving the laser melting process.

Spreading Processes With Layer-Dependent Population Heterogeneity Over Multilayer Networks

Spreading Processes With Layer-Dependent Population Heterogeneity Over Multilayer Networks