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The last stage of the cold rolling process is skin-pass rolling and one of its most significant goals is to obtain appropriate topography on the surface of the sheet steel used extensively such as in automotive industry. The purpose of this paper is to investigate the effect of thickness change and various reduction ratios on roughness transfer of DC04 grade sheet material.

DC04 grade sheet materials with different reduction ratios and several thicknesses were subjected to skin-pass rolling process in the rolling equipment with a two-high roll. Some roughness parameters were determined as a result of roughness measurements from the surfaces of roughened sheet materials.

While the roughness transfer is higher in 1-mm thick material in reduction ratios up to 430 micrometers; in reduction ratios above 430 micrometers, it is higher for 1.5-mm thick materials. As the reduction ratio increases in DC04 grade sheet materials, the homogeneity of the roughness distribution in 1-mm thickness sheet material deteriorates, while the roughness distribution in 1.5-mm thickness sheet material is more homogeneous.

This paper demonstrates how material thickness and reduction ratio affect the roughness transfer in skin-pass rolling. The results obtained can be used by optimizing in manufacturing processes.

The purpose of this paper is to explore the pure squeeze elastohydrodynamic lubrication motion of circular contacts with surface roughness under constant load conditions. The proposed model can reasonably calculate the effects of surface roughness on the transient pressure profiles, film shapes, and normal squeeze velocities during the pure squeeze process.

Based on Christensen's stochastic theory, the transient modified Reynolds equation is derived in polar coordinates to consider the effects of surface roughness. The finite difference method and the Gauss‐Seidel iteration method are used to solve the transient modified Reynolds equation, the elasticity deformation equation, load balance equation, and lubricant rheology equations simultaneously.

The simulation results reveal that the circular type roughness possesses storage oil capacity. Comparatively, the radial type roughness possesses leak oil capacity. Therefore, the film thickness is found with circular type roughness, followed by smooth, and then radial type roughness. In additional, the central dimensionless pressure is found with radial type roughness, followed by smooth, and then circular type roughness.

A numerical method for general applications with surface roughness was developed to investigate the pure squeeze action in an isothermal EHL spherical conjunction under constant load conditions, but without asperities contact.

The main aim of this paper is description of new apparatus and approach for contact less evaluation of surface roughness. For characterization of surface roughness, the procedures based on classical and non‐classical (complexity) parameters are proposed.

For obtaining the roughness profile in the selected direction (on the line transect of the surface), the special arrangements of textile bend around sharp edge is used. The image analysis is used for extraction of surface profile. The system of controlled movement allows one to obtain surface roughness profile in two dimensions.

By using aggregation (cut length principle), the roughness resolution is decreased and roughness profile is created without local roughness variation. After application of cut length principle, the direct combination of slices leads to the creation of roughness surface.

There exists plenty of roughness characteristics based on standard statistics or analysis of spatial processes. For evaluation of suitability of these characteristics, it will be necessary to compare results from sets of textile surfaces.

The measurement of fabric roughness by an RCM device is useful as simple tool for description of roughness in individual slices and in the whole rough plane. This method replaces the traditional contact stylus profiling methods

The reconstruction of surface roughness from individual slices. The utilization of aggregation principle for creation of micro and macro roughness. The evaluation of roughness parameters based on the geometrical characteristics, harmonic analysis and complexity indices.

The purpose of this paper is to provide a quantitative assessment on the effect of wall roughness on the pressure drop of fluid flow in microchannels.

The wall roughness is generated by the method of random midpoint displacement (RMD) and the lattice Boltzmann BGK model is applied. The influences of Reynolds number, relative roughness and the Hurst exponent of roughness profile on the Poiseuille number are investigated.

Unlike the smooth channel flow, Reynolds number, relative roughness and the Hurst exponent of roughness profiles play critical roles on the Poiseuille number Po in rough microchannels. Modeling results indicate that, in rough microchannels, the rough surface configuration intensifies the flow-surface interactions and the wall conditions turn to dominate the flow characteristics. The perturbance of the local flows near the channel wall and the formation of recirculation regions are two main features of the flow-surface interactions.

The fluid flow in parallel planes with surface roughness is considered in the current study. In other words, only two-dimensional fluid flow is investigated.

The LBM is a very useful tool to investigate the microscale flows.

A new method (RMD) is applied to generate the wall roughness in parallel plane and LBM is conducted to investigate the pressure drop characteristics in rough microchannels.

The purpose of this paper is to explore the effect of surface roughness characterized by fractal geometry on squeeze film damping characteristics in damper of the linear rolling guide, which has not been studied so far.

The stochastic model of film thickness between rail and damper is established by using the two-variable Weierstrass–Mandelbrot function defining multi-scale and self-affinity properties of the rough surface topography. The stochastically averaged Reynolds equation is solved by using the variables separation method to further derive the film pressure distribution, the damping coefficient, the damping force and squeeze film time. The effect of surface roughness on squeeze film damping characteristics of the damper is analyzed and discussed through simulation.

By comparing cases of the rough surface for different fractal parameters and the smooth surface, it is shown that for the isotropic roughness structure, the presence of surface roughness of the damper decreases the squeeze film damping characteristics. It is found that roughness effect on the damping coefficient is associated with the film thickness. In addition, the vibration amplitude effect is negligible for the damper of the linear rolling guide.

To investigate the random surface roughness effect, the rough surface topography of damper of the linear rolling guide is characterized by using the fractal method instead of the traditional mathematical statistics method.

This study aims to investigate the combined effects of roughness and ferrofluid lubricant on finite journal bearing load capacity and squeeze time.

The stochastic theory of Christensen is applied to study the surface roughness effect. The Shliomis model is used to take into account the effects of the rotational viscosity of ferromagnetic particles and their magnetic moment. A finite wire located in the center of the shaft produces the applied magnetic field. A developed computing code allows predicting the effect of the surface roughness on the performance of the considered journal bearing. The good agreement with the results of the literature validates the used approach.

This study shows that unlike longitudinal roughness, the presence of transverse roughness makes the use of ferrofluid more beneficial in terms of increasing the performance of finite journal bearings. This increase is more significant for large relative eccentricities, which present an ideal confinement.

This study shows the effect of two surface roughness patterns on the squeezing performance of a finite journal bearing lubricated by a ferrofluid.

This study aims to present the optimization of parameters and effects of annealing and vapor smoothing post-processing treatments on the surface roughness and tensile mechanical properties of fused deposition modeling (FDM) printed acrylonitrile butadiene styrene (ABS).

Full-factorial test matrices were designed to determine the most effective treatment parameters for post-processing. The parameters for annealing were temperature and time, whereas the parameters for the vapor smoothing were volume of acetone and time. Analysis of surface roughness and tensile test results determined influences of the levels of parameters to find an ideal balance between mechanical properties and roughness.

Optimal parameters for vapor smoothing and annealing were determined. Vapor smoothing resulted in significantly higher improvements to surface roughness than annealing. Both treatments generally resulted in decreased mechanical properties. Of all treatments tested, annealing at 100 °C for 60 min provided the greatest benefit to tensile properties and vapor smoothing with 20 mL of acetone for 15 min provided the greatest benefit to surface roughness while balancing effects on properties.

Vapor smoothing and annealing of FDM ABS have typically been studied independently for their effects on surface roughness and material properties, respectively, with varying materials and manufacturing methods. This study objectively compares the effects of each treatment on both characteristics simultaneously to recommend ideal treatments for maximizing the balance between the final quality and performance of FDM components. The significance of the input variables for each treatment have also been analyzed. These findings should provide value to end-users of 3D printed components seeking to balance these critical aspects of manufacturing.

The purpose of this paper is to study the functionality of additively manufactured (AM) parts, mainly depending on their dimensional accuracy and surface finish. However, the products manufactured using AM usually suffer from defects like roughness or uneven surfaces. This paper discusses the various surface quality improvement techniques, including how to reduce surface defects, surface roughness and dimensional accuracy of AM parts.

There are many different types of popular AM methods. Unfortunately, these AM methods are susceptible to different kinds of surface defects in the product. As a result, pre- and postprocessing efforts and control of various AM process parameters are needed to improve the surface quality and reduce surface roughness.

In this paper, the various surface quality improvement methods are categorized based on the type of materials, working principles of AM and types of finishing processes. They have been divided into chemical, thermal, mechanical and hybrid-based categories.

The review has evaluated the possibility of various surface finishing methods for enhancing the surface quality of AM parts. It has also discussed the research perspective of these methods for surface finishing of AM parts at micro- to nanolevel surface roughness and better dimensional accuracy.

This paper represents a comprehensive review of surface quality improvement methods for both metals and polymer-based AM parts.

The purpose of this paper was to study the possibility of using smartphone roughness measurements for developing pavement roughness regression models as a function of pavement age, traffic loading and traffic volume variables. Also, the effects of patching and pavement distresses on pavement roughness were investigated. The work focused on establishing pavement roughness prediction models and applying these models to pavement management systems (PMS) to help decision-makers choose the best maintenance and rehabilitation (M&R) options by using cost-effective methods.

Signal processing techniques including filtering and processing techniques were used to obtain the International Roughness Index (IRI) from raw acceleration data collected from smartphone accelerometer sensors. The obtained IRI values were inputted as a dependent variable in analytical regression models as well as several independent variables with proper transformations.

According to the study results, several regression models were developed with a big variation in the coefficients of determination (R²). However, the best models included pavement age, accumulated traffic volume (∑TV) and construction quality factor (CQF) with R² equal to 0.63. It was also found that the effects of pavement distresses and patching was significant at a-level < 0.05. The patching effect on pavement roughness was found higher than the effect of other pavement distresses.

The presented results and methods in this paper could be used in the future predictions of pavement roughness and help the decision-makers to estimate M&R needs. The work focused on establishing IRI prediction models and applying these models to the PMS to help decision-makers choose the best M & R options.

To develop sound pavement roughness models, it is essential to collect roughness data using automated procedures. However, applying these procedures in developing countries faces several difficulties such as the high price and operation costs of roughness equipment and lack of technical experience. The advantage of using IRI values taken from smartphones is that the roughness evaluation survey may be expanded to cover the full road network at a cheaper cost than with automated instruments. Therefore, if the roughness survey covers more roads, the prediction model’s accuracy will be improved.

Modeling helps to determine how structural parameters of fabric affect the surface of a fabric and also identify the way they influence fabric properties. Moreover, it helps to estimate and evaluate without the complexity and time-consuming experimental procedures. The purpose of this study is to develop and select the best regression model equations for the prediction and evaluation of surface roughness of plain-woven fabrics.

In this study, a linear and quadratic regression model was developed for the prediction and evaluation of surface roughness of plain-woven fabrics, and the capability in accuracy and reliability of the two-model equation was determined by the root mean square error (RMSE). The Design-Expert AE11 software was used for developing the two model equations and analysis of variance “ANOVA.” The count and density were used for developing linear model equation one “SMD1” as well as for quadratic model equation two “SMD2.”

From results and findings, the effects of count and density and their interactions on the roughness of plain-woven fabric were found statistically significant for both linear and quadratic models at a confidence interval of 95%. The count has a positive correlation with surface roughness, while density has a negative correlation. The correlations revealed that models were strongly correlated at a confidence interval of 95% with adjusted R² of 0.8483 and R² of 0.9079, respectively. The RMSE values of the quadratic model equation and linear model equation were 0.1596 and 0.0747, respectively.

Thus, the quadratic model equation has better capability accuracy and reliability in predictions and evaluations of surface roughness than a linear model. These models can be used to select a suitable fabric for various end applications, and it was also used for tests and predicts surface roughness of plain-woven fabrics. The regression model helps to reduce the gap between the subjective and objective surface roughness measurement methods.