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We report on viscous adhesion measurements conducted in sphere-plane geometry between a rigid sphere and soft surfaces submerged in silicone oils. Increasing the surface compliance leads to a decrease in the adhesive strength due to elastohydrodynamic deformation of the soft surface during debonding. The force-displacement and fluid film thickness-time data are compared to an elastohydrodynamic model that incorporates the force measuring spring and finds good agreement between the model and data. We calculate the pressure distribution in the fluid and find that, in contrast to debonding from rigid surfaces, the pressure drop is non-monotonic and includes the presence of stagnation points within the fluid film when a soft surface is present. In addition, viscous adhesion in the presence of a soft surface leads to a debonding process that occurs via a peeling front (located at a stagnation point), even in the absence of solid–solid contact. As a result of mass conservation, the elastohydrodynamic deformation of the soft surface during detachment leads to surfaces that come closer as the surfaces are separated. During detachment, there is a region with fluid drainage between the centerpoint and the stagnation point, while there is fluid infusion further out. Understanding and harnessing the coupling between lubrication pressure, elasticity, and surface interactions provides material design strategies for applications such as adhesives, coatings, microsensors, and biomaterials. [ABSTRACT FROM AUTHOR]

To reduce the friction, wear, and temperature of the piston-cylinder liner friction pair, we designed and processed 27 kinds of bio-inspired textured pistons with cylindrical pits. Based on the experimental optimization design method, friction test, wear test, and thermal imaging test were carried out. Results show that the textured pistons can significantly reduce the friction. Various texture parameters have different effects on the mean friction force. The wear of the textured pistons is significantly less than that of the standard piston. The influence of the texture parameters on piston wear are analyzed through range analysis, regression equation, and 3D response surface method. The standard piston suffers from serious wear and tear. The cylindrical pit texture can supply lubrication and store abrasive particles, which can improve the wear condition of the textured piston surface to a certain extent. The friction heat of the textured pistons is small, which can reduce the average temperature of the friction pair. • Inspired by earthworms and leeches, 27 kinds of textured pistons with cylindrical pits were designed and fabricated. • The wear of the textured pistons is significantly less than that of the standard piston. • The cylindrical pit texture can supply lubrication and store abrasive particles, which can improve the wear condition of the textured piston surface to a certain extent. • The cylindrical pit texture can supply lubrication, store abrasive particles, and improve the wear condition to a certain extent. [ABSTRACT FROM AUTHOR]

Abstract Reliable operating conditions of hydrostatic turntables are prerequisite to ensuring machine tool performance. The hydrostatic turntable is affected by multiple working conditions, therefore, methods for evaluating turntable load-carrying capacity has become research hotspot. In this paper, by analyzing bearing capacity, parameters closely related to the support performance of turntables are selected as recognition features and an artificial neural network (ANN) training method is proposed. The ANN method is based on numerical solutions of over-determined nonlinear equations (ODNE) to intelligently evaluate turntable performance. In this study, ANN and ODNE training are applied to evaluate the performance of hydrostatic turntables. Finally, to verify the feasibility of the method, an intelligent monitoring system is established to collect data on machine tools. Highlights • Factors influencing the performance of hydrostatic turntable were determined by analyzing the carrying ability of oil pads. • Based on the ANN structure for fast calculation of optimal weights, an ODNE training method was presented. • For intelligent monitoring of a hydrostatic turntable, BP and ODNE training are both recommended for training the ANN. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to study the nonlinear supporting performance of hydrostatic ram under the impact of cutting force and search for an optimal solution to improve its stiffness.Design/methodology/approach The Reynolds equation was applied to resolve the carrying capability of a single oil pad numerically, and an iteration method was used to analyze the nonlinear supporting force and stiffness of a pair of oil pads placed face-to-face. The total offset of ram could be obtained after the displacement of aspectant oil pads was solved by the bisection method. From the comparison of the offset values of ram evaluated under different support conditions, the optimal solution was determined.Findings In this study, an optimized oil supply allocation, concluded as 1.16:0.84, is proposed to improve the performance of hydrostatic ram supporting structure.Originality/value The supporting performance of hydrostatic ram could be improved by appropriate allocation of oil supply without extra energy consumption. [ABSTRACT FROM AUTHOR]

Understanding and harnessing the coupling between lubrication pressure and elasticity provides materials design strategies for applications such as adhesives, coatings, microsensors, and biomaterials. Elastic deformation of compliant solids caused by viscous forces can also occur during dynamic force measurements in instruments such as the surface forces apparatus (SFA) or the atomic force microscope (AFM). We briefly review hydrodynamic interactions in the presence of soft, deformable interfaces in the lubrication limit. More specifically, we consider the scenario of two surfaces approaching each other in a viscous fluid where one or both surfaces is deformable, which is also relevant to many force measurement systems. In this article the basic theoretical background of the elastohydrodynamic problem is detailed, followed by a discussion of experimental validation and considerations, especially for the role of elastic deformation on surface forces measurements. Finally, current challenges to our understanding of soft hydrodynamic interactions, such as the consideration of substrate layering, poroelasticity, viscoelasticity, surface heterogeneity, as well as their implications are discussed. [ABSTRACT FROM AUTHOR]

Hydrostatic systems are considered as essential supporting structures in heavy machine tools. The calculations and analyses for hydrostatic bearings are always laborious because of the involvement of several disciplines such as elastic mechanics, hydromechanics, thermodynamics, and other factors in the design. It is well known that large data and cloud technology are capable of processing and transmission of hydrostatic system studies. In this work, a cloud manufacture model is presented to provide big data storage, transmission, and processing platform for designers, manufacturers, and users of hydrostatic bearings. All participants involved in the manufacturing were linked together by timely information communication in order to ensure that the customized products met with the actual conditions in the cloud server. Based on the actual requirements of the user, the carrying capacity of hydrostatic system was analyzed by a designer using finite difference method and the results were sent to the manufacturer for machining of components. The monitored data from the consumer could be fed back to the designer for performance evaluation through the cloud server. It was found that customized manufacturing tasks could be finished more reliably and efficiently if all participants exchanged the data through cloud platform in real time. [ABSTRACT FROM AUTHOR]

The resistance of fluid infusion inside a thin film that separates an opening gap leads to viscous adhesion. Viscous adhesion can be detrimental for some mechanical devices such as valves or during additive manufacturing processes. On the other hand, it is also a mechanism found in nature for dynamic reversible adhesion. In this article we review analysis and measurements of viscous adhesion. In particular, we give conditions where viscous adhesion dominates over other surface forces. We also describe how characteristics of the solid surfaces such as roughness and elasticity, as well as the compliance of the load cell can be incorporated in the analysis. Finally, we discuss the knowledge gaps and scientific areas where a better understanding of viscous adhesion could be beneficial. Image 1 [ABSTRACT FROM AUTHOR]

Electric submersible pumps (ESPs) are widely used in the oil and gas industry for crude-oil lifting, especially in subsea oil fields or underground storage caverns. The failure of ESPs causes a large economic cost mainly attributed to a break in production continuity, as the ESP cannot be easily replaced. Therefore, the assurance of safe and efficient operation of ESPs has attracted high attention in recent years, although the problem still remains challenging given the complexity of carrying fluid and the mechanical structure of the ESP. In this article, we systematically review both the high-impact, classic contributions and the most up-to-date, current opinions in experimental and numerical advances of viscous effects and two-phase flow in ESPs. We specifically focus on the applications in the oil and gas industry and point out a few current challenges in the operation of ESPs. We aim to guide the audience which is new to the area of ESPs to the correct articles related to their interests, including classic work and recent advances. [ABSTRACT FROM AUTHOR]

Objective: The prediction of upcoming circular walking during linear walking is important for the usability and safety of the interaction between a lower limb assistive device and the wearer. This study aims to build a bilateral elimination rule-based finite class Bayesian inference system (BER-FC-BesIS) with the ability to predict the transition between circular walking and linear walking using inertial measurement units. Methods: Bilateral motion data of the human body were used to improve the recognition and prediction accuracy of BER-FC-BesIS. Results: The mean predicted time of BER-FC-BesIS in predicting the left and right lower limbs' upcoming steady walking activities is 119.32 ± 9.71 ms and 113.75 ± 11.83 ms, respectively. The mean time differences between the predicted time and the real time of BER-FC-BesIS in the left and right lower limbs' prediction are 14.22 ± 3.74 ms and 13.59 ± 4.92 ms, respectively. The prediction accuracy of BER-FC-BesIS is 93.98%. Conclusion: Upcoming steady walking activities (e.g., linear walking and circular walking) can be accurately predicted by BER-FC-BesIS innovatively. Significance: This study could be helpful and instructional to improve the lower limb assistive devices' capabilities of walking activity prediction with emphasis on non-linear walking activities in daily living. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose a method for finding the maximum rotational speed of an inclined turntable at which the stability of the bearing oil film is maintained. Design/methodology/approach: The finite difference method was used to solve the Reynolds equation. Variation of bearing capacity of a tilted hydrostatic turret over time was determined. The combined effect of tilt and rotational speed of the turret on the oil film stability was also analyzed. Findings: When the turntable is operated at low speeds with only small angle of tilt, stability of the oil film is maintained. At lower rotational speeds, a smaller angle of tilt improves the bearing capacity and ensures stability of the oil film. Whereas, higher rotational speeds can have a considerable influence on the bearing capacity. Originality/value: The results demonstrate that the inclination or tilt of the turntable significantly affects the stability of the oil film. [ABSTRACT FROM AUTHOR]

We present the multifunctional force microscope (MFM), a normal and lateral force-measuring instrument with in situ imaging. In the MFM, forces are calculated from the normal and lateral deflection of a cantilever as measured via fiber optic sensors. The motion of the cantilever is controlled normally by a linear micro-translation stage and a piezoelectric actuator, while the lateral motion of the sample is controlled by another linear micro-translation stage. The micro-translation stages allow for travel distances that span 25 mm with a minimum step size of 50 nm, while the piezo has a minimum step size of 0.2 nm, but a 100 μm maximum range. Custom-designed cantilevers allow for the forces to be measured over 4 orders of magnitude (from 50 μN to 1 N). We perform probe tack, friction, and hydrodynamic drainage experiments to demonstrate the sensitivity, versatility, and measurable force range of the instrument. [ABSTRACT FROM AUTHOR]

We present the multifunctional force microscope (MFM), a normal and lateral force-measuring instrument with in situ imaging. In the MFM, forces are calculated from the normal and lateral deflection of a cantilever as measured via fiber optic sensors. The motion of the cantilever is controlled normally by a linear micro-translation stage and a piezoelectric actuator, while the lateral motion of the sample is controlled by another linear micro-translation stage. The micro-translation stages allow for travel distances that span 25 mm with a minimum step size of 50 nm, while the piezo has a minimum step size of 0.2 nm, but a 100 μm maximum range. Custom-designed cantilevers allow for the forces to be measured over 4 orders of magnitude (from 50 μN to 1 N). We perform probe tack, friction, and hydrodynamic drainage experiments to demonstrate the sensitivity, versatility, and measurable force range of the instrument. [ABSTRACT FROM AUTHOR]

• In this article, we systematically reviewed and analyzed COVID-19 trends, policies and vital epidemiological indicators, quantifying the impact of COVID-19 on electricity consumption. • We introduced a data-driven approach to predict the electricity consumption in non-COVID-19 scenario. • We bridged the knowledge gap between key energy and epidemiological parameters, finding a statistic correlation between energy loss and effective reproductive number (R t). In addition to the tremendous loss of life due to coronavirus disease 2019 (COVID-19), the pandemic created challenges for the energy system, as strict confinement measures such as lockdown and social distancing compelled by governments worldwide resulted in a significant reduction in energy demand. In this study, a novel, quantitative and uncomplex method for estimating the energy consumption loss due to the pandemic, which was derived from epidemiological data in the beginning stages, is provided; the method bonds a data-driven prediction (LSTM network) of energy consumption due to COVID-19 to an econometric model (ARDL) so that the long- and short-term impact can be synthesized with adequate statistical validation. The results show that energy loss is statistically correlated with the time-changing effective reproductive number (R t) of the disease, which can be viewed as quantifying confinement intensity and the severity of the earlier stages of the pandemic. We detected a 1.62% decrease in electricity consumption loss caused by each percent decrease in R t on average. We verify our method by applying it to Germany and 5 U.S. states with various social features and discuss implications and universality. Our results bridge the knowledge gap between key energy and epidemiological parameters and provide policymakers with a more precise estimate of the pandemic's impact on electricity demand so that strategies can be formulated to minimize losses caused by similar crises. [ABSTRACT FROM AUTHOR]

Erosion is one of the most common forms of material failure and equipment damage in gas transmission pipelines. Shale gas fields use hydraulic fracturing whereby solid particles are often carried in the gas flow, and the pipeline is in a high-pressure state, which is more likely to cause erosion. The prediction of particle erosion regulation in gas-solid two-phase flow is an effective means to ensure the safe operation of shale gas fields. In this paper, an integrated CFD-DPM model is established to investigate the erosion of 90° elbow in a shale gas field under gas-solid two-phase flow, employing the realizable k-ε turbulence model, discrete phase model, and erosion rate prediction model. The reliability of the proposed numerical models is verified by comparing the predicted data with the experimental data. Moreover, the effects of six important factors on maximum erosion rate are analyzed, including gas velocity, mass flow rate of sand particles, particle diameter, shape coefficient of sand particles, pipeline diameter, elbow radius of curvature. Specifically, the results indicate that the gas velocity, mass flow rate and shape coefficient of sand particles are positively correlated with the maximum erosion rate, while the pipe diameter and the elbow radius of curvature are negatively correlated with the maximum erosion rate. A new correlation was developed, which included four dimensionless groups, namely Reynolds number, diameter ratio, density ratio and particle number. The correlation can be used to predict maximum corrosion rate of elbows. This work can provide data reference and theoretical basis for mitigating the erosion rate of pipelines and managing the integrity of gas pipelines. [ABSTRACT FROM AUTHOR]