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This study aims to investigate the rarefaction effects on flow and thermal performances of an equivalent sand-grain roughness model for aerodynamic thrust bearing.

In this study, a model of gas lubrication thrust bearing was established by modifying the wall roughness and considering rarefaction effect. The flow and lubrication characteristics of gas film were discussed based on the equivalent sand roughness model and rarefaction effect.

The boundary slip and the surface roughness effect lead to a decrease in gas film pressure and temperature, with a maximum decrease of 39.2% and 8.4%, respectively. The vortex effect present in the gas film is closely linked to the gas film’s pressure. Slip flow decreases the vortex effect, and an increase in roughness results in the development of slip flow. The increase of roughness leads to a decrease for the static and thermal characteristics.

This work uses the rarefaction effect and the equivalent sand roughness model to investigate the lubrication characteristics of gas thrust bearing. The results help to guide the selection of the surface roughness of rotor and bearing, so as to fully control the rarefaction effect and make use of it.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

In this study, experimental studies were carried out using different process parameters of the soft pneumatic gripper (SPG) fabricated by the fused deposition modeling method. In the experimental studies, the surface quality of the gripper was examined by determining four different levels and factors. The experiment was designed to estimate the surface roughness of the SPG.

The methodology consists of an experimental phase in which the SPG is fabricated and the surface roughness is measured. Thermoplastic polyurethane (TPU) flex filament material was used in the fabrication of SPG. The control factors used in the Taguchi L16 vertical array experimental design and their level values were determined. Analysis of variance (ANOVA) was performed to observe the effect of printing parameters on the surface quality. Finally, regression analysis was applied to mathematically model the surface roughness values obtained from the experimental measurements.

Based on the Taguchi signal-to-noise ratio and ANOVA, layer height is the most influential parameter for surface roughness. The best surface quality value was obtained with a surface roughness value of 18.752 µm using the combination of 100 µm layer height, 2 mm wall thickness, 200 °C nozzle temperature and 120 mm/s printing speed. The developed model predicted the surface roughness of SPG with 95% confidence intervals.

It is essential to examine the surface quality of parts fabricated in additive manufacturing using different variables. In the literature, surface roughness has been examined using different factors and levels. However, the surface roughness of a soft gripper fabricated with TPU material has not been examined previously. The surface quality of parts fabricated using flexible materials is very important.

First, the effect of magnetic field intensity and nano-ferrofluid concentrations on surface roughness was evaluated in magnetic minimum quantity lubrication (MMQL). Then, the effect of lubricant flow rate and nozzle position on surface roughness was investigated in MQL, MMQL, electrostatic MQL (EMQL) and electromagnetic MQL (EMMQL).

This study examined the performance of MQL under magnetic and electric fields in turning AISI 304 stainless steel in terms of surface roughness and compared the results with those obtained from wet cutting and MQL turning operations. To prepare the nano-ferrofluid used in different states of MQL, Fe₃O₄ nanoparticles were added to the base fluid.

The results showed that the surface roughness under the EMMQL technique decreased by 36% and 49.4% on average compared with wet and MQL techniques, respectively. The lubrication technique affected the surface roughness by 90.2%, whereas it was 8.3% for the lubricant flow rate. EMQL and EMMQL techniques had no significant difference in their effects on surface roughness. In the innovative MMQL technique, the nano-ferrofluid concentration of 6% and magnetic field intensity of 93 G resulted in lower surface roughness of the workpiece relative to other counterparts.

Examining previously published studies showed that using nano-ferrofluids under a magnetic field for cooling purposes in machining processes have less considered by researchers. This study applies an innovative method of lubrication under the concurrent effect of magnetic and electric fields, called EMMQL, to improve the efficiency of MQL in machining hard-to-cut materials. For comprehensively inspecting the newly presented method, the effects of several parameters, including the nano-ferrofluid concentration, magnetic field intensity, lubricant flow rate and position of lubricant spray nozzle, on the surface roughness of workpiece in turning of AISI 304 stainless steel are investigated.

The purpose of this study is an assessment of the existing roughness models to simulate the flow in the narrow gap between corotating and rough disks. A specific configuration of the flow through the gap, which forms a minichannel with variable cross sections and rotating walls, makes it a complex problem and, therefore, worth discussing in more detail.

Two roughness models were examined, the first one was based on the wall function modification by application of the shift in the dimensionless velocity profile, and the second one was based on the correction of turbulence parameters at the wall, proposed by Aupoix. Due to the lack of data to validate that specific case, the approach to deal with was selected after a systematic study of reported test cases. It started with a zero-pressure-gradient boundary layer in the flow over a flat plate, continued with flow through minichannels with stationary walls, and finally, focused on the flow between corotating discs, pertaining each time to smooth and rough surfaces.

The limitations of the roughness models were highlighted, which make the models not reliable in the application to minichannel flows. It concerns turbulence models, near-wall discretization and roughness approaches. Aupoix’s method to account for roughness was selected, and the influence of minichannel height, mass flow rate, fluid properties and roughness height on the velocity profile between corotating discs in both smooth and rough cases was discussed.

The originality of this study is the evaluation and validation of different methods to account for the roughness in rotating mini channels, where the protrusions can cover a substantial part of the channel. Flow behavior and performance of different turbulence models were analyzed as well.

This study aims to apply an electrochemical grinding (ECG) technology to improve the material removal rate (MRR) under the premise of certain surface roughness in machining U71Mn alloy.

The effects of machining parameters (electrolyte type, grinding wheel granularity, applied voltage, grinding wheel speed and machining time) on the MRR and surface roughness are investigated with experiments.

The experiment results show that an electroplated diamond grinding wheel of 46# and 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte is more suitable to be applied in U71Mn ECG. And the MRR and surface roughness are affected by machining parameters such as applied voltage, grinding wheel speed and machining time. In addition, the maximum MRR of 0.194 g/min is obtained with the 15 Wt.% NaCl electrolyte, 17 V applied voltage, 1,500 rpm grinding wheel speed and 60 s machining time. The minimum surface roughness of Ra 0.312 µm is obtained by the 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte, 13 V applied voltage, 2,000 rpm grinding wheel speed and 60 s machining time.

Under the electrolyte scouring effect, the products and the heat generated in the machining can be better discharged. ECG has the potential to improve MRR and reduce surface roughness in machining U71Mn.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0341/

The purpose of this paper is to calculate the meshing stiffness of nutation face gear considering the roughness, establish the calculation method of time-varying meshing stiffness of rough tooth surface and analyze the influence of roughness, load and other factors on the meshing stiffness of tooth surface.

The Weierstrass–Mandelbrot (W-M) function in the Majumdar–Bhushan model is used to characterize the rough contact line of the tooth surface, the normal height and radius of the micro convex body are calculated and the contact flexibility of the contact point of the tooth surface is obtained. The contact flexibility and the bending shear deformation flexibility obtained previously are substituted into the improved deformation compatibility equation for iterative calculation, and the time-varying meshing stiffness of the nutation face gear considering the roughness is obtained.

Compared with ABAQUS finite element simulation results, it is found that the meshing stiffness curve of rough tooth surface is more gentle than that of smooth tooth surface, the meshing stiffness value is smaller and the meshing stiffness change is smaller at the position where the number of gear teeth coincide changes.

In the process of calculating contact deformation, the fractal theory W-M function is used to characterize the contact line of the rough nutation face gear, and the deformation coordination condition considering roughness is improved. Therefore, the method of time-varying meshing stiffness considering roughness can obtain more accurate results, which provides theory and data for the subsequent dynamics analysis of the nutation face gear transmission.

This study aims to enhance the lubrication performance of thrust bearings. The influence of columnar convex–concave compound microtexture on bearing performance is investigated

Based on the compound microtexture model of thrust bearings, considering surface roughness and turbulent effect, the variation of lubrication characteristics with the change in the compound microtexture parameters is studied.

The results indicate that, compared with circular microtexture, the maximum pressure of compound microtexture of thrust bearings increases by 7.42%. Optimal bearing performance is achieved when the internal microtexture depth is 0.02 mm. Turbulent flow states and surface roughness lead to a reduction in the optimal depth. The maximum pressure and load-carrying capacity of the bearing decrease as the initial angle increases, whereas the friction coefficient increases with the increase in the initial angle. The lubrication performance is best for bearings with a circumferential parallel arrangement of microtexture.

The novel composite microtexture with columnar convex-concave is proposed, and the computational model of thrust bearings is set. The influence of surface roughness and turbulent flow on the bearing performance should be considered for better conforming with engineering practice. The effect of microtexture depth, arrangement method and distribution position on the lubrication performance of the compound microtexture thrust bearing is investigated, which is of great significance for improving tribology, thrust bearings and surface microtexture theory.

The purpose of this paper is to study the correlation between different topographies and the reaction of Ulva Linza fouling species.

In this research, topographies with a different method, such as hot embossing and hot pulling, were achieved, and biological analyses were done with macroalgae Ulva Linza cells. The effect of topography via local binding geometry (honeycomb size gradients) and Wenzel roughness on the settling of Ulva microorganisms was tested.

As a result, Ulva spores confirmed different reactions to a similar set of tapered microstructures that was in agreement with the results on distinct honeycombs. The local binding geometry and the Wenzel roughness factor “r” were dominant on settling of Ulva Linza spores.

The reaction of an organism at the interface of vehicles’ substrate is powerfully affected by surface topographies.

The best embedment occurred on structures with bigger sizes than Ulva Linza’s spores. The density of settled spores was proportional to Wenzel roughness and the spores favour to attach to “kink sites” positions.

Unfortunately, unpleasant aggregation of marine biofouling on marine vehicles’ surfaces, generate terrific difficulties in the relevant industry.

There was a sharp relationship between Wenzel roughness and settle of Ulva Linza spores. The local binding geometry and the Wenzel roughness factor “r” were dominant on settling of Ulva Linza spores.

This work aims to describe the face milling analysis on Inconel X-750 superalloy using coated carbides. The formed chips and tool wear were further analyzed at different cutting parameters. The various impact of cutting parameters on chip morphology was also analyzed. Superalloys, often referred to as heat-resistant alloys, have exceptional tensile, ductile and creep strength at high operating temperatures and good fatigue strength, and often better corrosion and oxidation resistance at extreme heat. Because of these qualities, these alloys account for more than half of the weight of sophisticated aviation, biomedical and thermal power plants today. Inconel X-750 is a high-temperature nickel-based superalloy that is hard to machine because of its extensive properties. At last, the discussion regarding the tool wear mechanism was analyzed and discussed in this article.

The machining parameters for the study are cutting speed, feed rate and depth of cut. One factor at a time approach was implemented to investigate the effect of cutting parameters on the cutting forces, surface roughness and material removal rate. The scatter plot was plotted between cutting parameters and target functions (cutting forces, surface roughness and material removal rate). The six levels of cutting speed, feed rate and depth of cut were taken as cutting parameters.

The cutting forces are primarily affected by the cutting parameters, tool geometry, work material etc. The maximum forces Fx were encountered at 10 mm/min cutting speed, 0.15 mm/rev feed rate and 0.4 mm depth of cut, further maximum forces Fy were attained at 10 mm/min cutting speed, 0.25 mm/rev feed rate and 0.4 mm depth of cut and maximum forces Fz were attained at 50 mm/min cutting speed, 0.05 mm/rev feed rate and 0.4 mm depth of cut. The maximum surface roughness value was observed at 40 mm/min cutting speed, 0.15 mm/rev feed rate and 0.5 mm depth of cut.

The effect of machining parameters on cutting forces, surface roughness, chip morphology and tool wear for milling of Inconel X-750 high-temperature superalloy is being less researched in the present literature. Therefore, this research paper will give a direction for researchers for further studies to be carried out in the domain of high-temperature superalloys. Furthermore, the different tool wear mechanisms at separate experimental trials have been explored to evaluate and validate the process performance by conducting scanning electron microscopy analysis. Chip morphology has also been evaluated and analyzed under the variation of selected process inputs at different levels.