Characterization Of Surface Topography Research Articles

Evaluation of high-frequency roughness measurement errors for composite and ceramic surfaces after machining

Precise characterisation of surface topography is of the greatest importance since many factors directly affect the accuracy of the whole measurement process. In this paper, the variety of surface topographies from machined composite and ceramic workpieces was studied with a special emphasis on the measurement results. Surfaces were subjected to the ground diamond, honing and milling processes. Measurement results were analysed in terms of the application of the procedure for the removal of the high-frequency noise. Bandwidth characteristics were supported by the studies of autocorrelation and power spectral functions. It was found, that examination of noisy data, especially its isotropic properties, is crucial in the enhancement of the noise-removal methods. The proposed procedure was validated through direction and profile characterisation. The spline filtering technique with a 7.5 μm cut-off was encouraged against other generally used filtering techniques for the reduction of high-frequency measurement noise considering the study based on the power spectral, autocorrelation and direction functions. The proposed methodology was validated by comparing it to the averaged results of 3 time repeated measurements of the composite and ceramic surfaces after machining. The main advantage of the proposal is reducing the time of data processing due to the fast and easy-to-implement usage of general surface topography analysis functions, available in the commercial software of the measuring instrument.

Two 3D Fractal-Based Approaches for Topographical Characterization: Richardson Patchwork versus Sdr.

Various methods exist for multiscale characterization of surface topographies, each offering unique insights and applications. The study focuses on fractal-based approaches, distinguishing themselves by leveraging fractals to analyze surface complexity. Specifically, the Richardson Patchwork method, used in the ASME B46.1 and ISO 25178 standards, is compared to the Sdr parameter derived from ISO 25178-2, with a low-pass Gaussian filter for multiscale characterization. The comparison is performed from the relative area calculated on topographies of TA6V samples grit blasted with different pressures and blasting materials (media). The surfaces obtained by grit blasting have fractal-like characteristics over the scales studied, enabling the analysis of area development at multiple levels based on pressure and media. The relative area is similar for both methods, regardless of the complexity of the topographies. The relevance scale for each calculation method that significantly represents the effect of grit blasting pressure on the increased value of the relative area is a tiling of 7657.64 µm² of triangle area for the Patchwork method and a 124.6 µm cut-off for the low-pass Gaussian filter of the Sdr method. These results could facilitate a standard, friendly, new fractal method for multiscale characterization of the relative area.

Multiscale analysis of hierarchical flax-epoxy biocomposites with nanostructured interphase by xyloglucan and cellulose nanocrystals

Natural biological systems feature hierarchical nanostructured architectures achieving high strength and toughness. In this work, the spontaneous adsorption of xyloglucan (XG) and cellulose nanocrystals (CNC) onto flax fabrics is considered to develop hierarchical interphases with improved interfacial adhesion in epoxy-based biocomposites. A multi-scale analysis is carried out, from the nano & micrometric scale with the characterization of fibre surface topography, work of adhesion and interfacial shear strength (IFSS) between flax fibres and epoxy resin, to the macroscopic scale with the transverse mechanical properties of biocomposites. At the fibre scale, XG and CNC increase the surface roughness of flax fibres, as well as their adhesion to epoxy resin with IFSS improved by 60 %, up to 22.3 MPa. At the composite scale, the treatments have a major influence on the cohesion of flax cell walls and microstructure of the biocomposites. Transverse tensile tests reveal both cohesive and adhesive interfacial failure.

Surface topography characterization of USMM during machining of zirconia ceramic using silicon carbide abrasives: An experimental and simulation approach

Zirconia is a highly biodegradable ceramic material with excellent fracture resistance, in biomedical engineering, particularly dental implants. This research work has been focused on optimizing the quality of micro-hole generation in zirconia ceramic through ultrasonic micromachining (USMM). Three key process parameters such as abrasive slurry concentration, tool feed rate, and power rating are considered in this research work. The material removal rate, overcut, and taper angle are considered as responses. Response surface methodology has been employed for modeling during the USMM process, and a mathematical model has been developed to understand material removal mechanisms. Finite element analysis has been utilized to provide insights into the impacting process for industry requirements. A 3D model has been created to perform dynamic analysis under practical conditions. Multi-objective optimization has been applied to achieve optimum material removal rate (MRR), overcut, and taper angle. From multi-objective optimization, a slurry concentration of 49.59% g/l, tool feed rate of 1.16 mm/min, and power rating of 386.87 W has been found and in this parameter settings maximum MRR of 0.5333 mm3/min, minimum taper angle of 0.3428 degrees, and minimum overcut of 36.64 µm has been obtained during machining of ZrO2 ceramics.

A methodology for the 3D characterization of surfaces using X-ray computed tomography: Application to additively manufactured parts

Many studies highlight the significance of three-dimensional surface topography characterization in assessing its effect on the mechanical or functional properties of materials. This is especially obvious for parts made by additive manufacturing (AM), known for their complex shape and surface topographies. However, a vast majority of 3D characterizations have constraints regarding the macroscopic geometry of the parts they can probe. At the microscale, they are also unable to account for hidden surface features, e.g. notches hidden by unmelted powder particles. Even with the use of X-ray Computed Tomography (XCT) - a tool with the potential to circumvent these issues -data is often reduced to 2D or 2.5D formats for easier analysis, but this leads to a loss of information. This underscores the need for XCT data post-treatment tools to perform thorough 3D surface characterizations. Herein, we introduce a methodology for local roughness and curvature characterization of surfaces of complex shapes using XCT. This method has been designed to be user-friendly, especially for those without extensive data analysis expertise. It provides a comprehensive 3D characterization and efficiently tackles the issues caused by hidden features. After a detailed description of our methodology, we give a first illustrative example based on architected structures fabricated by Electron Powder Bed Fusion (E-PBF). By integrating roughness and curvature metrics, we also derive a parameter indicative of the stress concentrations caused by surface irregularities.

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.

Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading

Advances in remote sensing and small unmanned aircraft systems (sUAS) have been applied to various precision agriculture applications. However, there has been limited research on the accuracy of real-time kinematic (RTK) sUAS photogrammetric elevation surveys, especially in preparation for precision agriculture practices that require precise topographic surfaces, such as increasing irrigation system efficiency. These practices include, but are not limited to, precision land grading, placement of levees, multiple inlet rice irrigation, and computerized hole size selection for furrow irrigation. All such practices rely, in some way, on the characterization of surface topography. While agro-terrestrial (ground-based) surveying is the dominant method of agricultural surveying, aerial surveying is emerging and attracting potential early adopters. This is the first study of its kind to assess the accuracy, precision, time, and cost efficiency of RTK sUAS surveying in comparison to traditional agro-terrestrial techniques. Our findings suggest sUAS are superior to ground survey methods in terms of relative elevation and produce much more precise raster surfaces than ground-based methods. We also showed that this emergent technology reduces costs and the time it takes to generate agricultural elevation surveys.

Detailed evaluation of topographical effects of Hirtisation post-processing on electron beam powder bed fusion (PBF-EB) manufactured Ti-6Al-4V component

Metal additive manufacturing surface topographies are complex and challenging to characterise due to e.g. steep local slopes, re-entrant features, varying reflectivity and features of interest in vastly different scale ranges. Nevertheless, average height parameters such as Ra or Sa are commonly used as sole parameters for characterisation. In this paper, a novel method for selecting relevant parameters for evaluation is proposed and demonstrated using a case study where the smoothing effects after three processing steps of the electro chemical post-process Hirtisation of a metal AM surface are quantified. The method uses a combination of conventional areal texture parameters, multiscale analysis and statistics and can be used to efficiently achieve a detailed and more relevant surface topography characterisation. It was found that the three process steps have different effects on the surface topography regarding the types and sizes of features that were affected. In total, Sdq was reduced by 97 %, S5v was reduced by 81 % and Sa was reduced by 78 %. A surface texture with much lower average roughness, less deep pits and less steep slopes was produced, which is expected to be beneficial for improved fatigue properties.

Roughness evaluation of turned composite surfaces by analysis of the shape of autocorrelation function

In this paper, the application of an Autocorrelation Function for the characterisation of surface topography was validated. The roughness evaluation of turned composite surfaces was supported by sophisticated studies of the Autocorrelation Function properties, considering especially the shape of the function. Details were measured with the optical method. The selection of the surface roughness evaluation procedures was carried out based on the Autocorrelation Function for both profile and areal analyses. Moreover, the application of various types of regular analysis methods, proposed in commercial software, like regular Gaussian regression and robust Gaussian functions, median de-noising, regular isotropic Spline, and fast Fourier transform filters, was proposed for the evaluation of surface topography parameters from the ISO 25178 standards. It was found that many common techniques, like commonly used filters, spectral analysis, and characterisation of texture direction, were supported by the proposed Autocorrelation Function studies. Moreover, the hard thresholding technique was found to be valuable in the comprehensive noise-suppression analysis.

Influence of Surface Contaminants and Hydrocarbon Pellicle on the Results of Wettability Measurements of Titanium.

Hydrophilicity/hydrophobicity-or wettability-is a key surface characterization metric for titanium used in dental and orthopedic implants. However, the effects of hydrophilicity/hydrophobicity on biological capability remain uncertain, and the relationships between surface wettability and other surface parameters, such as topography and chemistry, are poorly understood. The objective of this study was to identify determinants of surface wettability of titanium and establish the reliability and validity of the assessment. Wettability was evaluated as the contact angle of ddH2O. The age of titanium specimens significantly affected the contact angle, with acid-etched, microrough titanium surfaces becoming superhydrophilic immediately after surface processing, hydrophobic after 7 days, and hydrorepellent after 90 days. Similar age-related loss of hydrophilicity was also confirmed on sandblasted supra-micron rough surfaces so, regardless of surface topography, titanium surfaces eventually become hydrophobic or hydrorepellent with time. On age-standardized titanium, surface roughness increased the contact angle and hydrophobicity. UV treatment of titanium regenerated the superhydrophilicity regardless of age or surface roughness, with rougher surfaces becoming more superhydrophilic than machined surfaces after UV treatment. Conditioning titanium surfaces by autoclaving increased the hydrophobicity of already-hydrophobic surfaces, whereas conditioning with 70% alcohol and hydrating with water or saline attenuated pre-existing hydrophobicity. Conversely, when titanium surfaces were superhydrophilic like UV-treated ones, autoclaving and alcohol cleaning turned the surfaces hydrorepellent and hydrophobic, respectively. UV treatment recovered hydrophilicity without exception. In conclusion, surface roughness accentuates existing wettability and can either increase or decrease the contact angle. Titanium must be age-standardized when evaluating surface wettability. Surface conditioning techniques significantly but unpredictably affect existing wettability. These implied that titanium wettability is significantly influenced by the hydrocarbon pellicle and other contaminants inevitably accumulated. UV treatment may be an effective strategy to standardize wettability by making all titanium surfaces superhydrophilic, thereby allowing the characterization of individual surface topography and chemistry parameters in future studies.

A mixed-lubricated friction model of water lubricated bearing based on fractal theory

To the water lubricated bearing, its mixed-lubricated friction model is generally established based on the traditional statistical model, whose accuracy is not high due to the inaccurate characterization of surface topography. Therefore, this paper employs the fractal theory that has scale-independent characteristics and high precision to characterize the surface topography of the bearing and journal, and then establishes the fractal contact model of asperity, combining the average Reynolds equation of the film, proposes a mixed-lubricated friction model based on fractal theory. The scanning experiments of surface topography are carried out to obtain the fractal parameters and measurements of the friction coefficient are performed to verify the effectiveness of the proposed mixed-lubricated model. Subsequently, the proposed mixed-lubricated friction model is employed to analyze the effects of the number of groove, the position of groove and the fractal parameters on the lubrication and friction characteristics of the water lubricated bearing. Results indicate when the grooves are in the non-main load-carrying regions, the friction characteristics of the bearing slightly changes, and the lower surface roughness is beneficial to improve the lubrication and friction properties of the bearing.

Image Contrast and Spectral Transmission in Intraocular Lenses with Nd:YAG Pits

Purpose Neodymium yttrium aluminum garnet (Nd:YAG) laser capsulotomy is considered as safe and effective method in the treatment of posterior capsule opacification. Nevertheless, side effects are described. The incorrectly adjusted focus of the laser beam during the procedure can lead to so-called YAG-pits or YAG-shots. In this experimental study, we measured spectral transmission to evaluate the image contrast and analyze the impact of YAG-pits in intraocular lenses (IOL). Methods Acrylic, foldable, one-piece IOLs with 6.0 mm optic and different material properties were studied. These included: monofocal IOLs and enhanced monofocal IOLs with water content of 0.3%, 26.0%, and 4.0% and a refractive index of 1.49, 1.46, and 1.54, respectively. All measurements were done with new, unaltered IOLs and IOLs with YAG-pits. Damage was intentionally created, performing YAG-pits (n = 7) in the central zone (3.5 mm) using a photodisruption laser (2.0mJ). All laboratory measurements were repeated: These included surface topography characterization, United States Air Force (USAF) resolution test chart analysis, spectral transmittance measurements and through focus contrast measurement. Results Significant differences were found between the unaltered lenses and lenses with defects. The YAG-pits within the optic of the IOLs decreased the image contrast and spectral transmission and changed results of USAF test images at the focal position by 62%, 57% and 54%, respectively. In all IOLs a reduction of the relative intensity of total transmitted light was observed between 450 and 700 nm wavelength. Conclusion This experimental study confirmed that the IOL image performance deteriorates with YAG-pits. The total intensity of transmitted light or transmittance (without scattering) was reduced in the wavelength between 450 and 700 nm. The contrast was significantly reduced and USAF test targets showed much worse results compared to unmodified counterparts. There was no systematic difference between monofocal and enhanced monofocal lenses. Further experiments should investigate the effect of YAG-pits on diffractive IOLs.

Surface topography characterization using a simple optical device and artificial neural networks

State-of-the-art methods for quantifying wear in cylinder liners of large internal combustion engines for stationary power generation require disassembly and cutting of the examined liner. This is followed by laboratory-based high-resolution microscopic surface depth measurement that quantitatively evaluates wear based on bearing load curves (also known as Abbott-Firestone curves). Such reference methods are destructive, time-consuming and costly. The goal of the research presented here is to develop nondestructive yet reliable methods for quantifying the surface topography. A novel machine learning framework is proposed that allows prediction of the bearing load curves representing the depth profiles from reflection RGB images of the liner surface. These images can be collected with a simple handheld microscope. A joint deep learning approach involving two neural network modules optimizes the prediction quality of surface roughness parameters as well. The network stack is trained using a custom-built database containing 422 perfectly aligned depth profile and reflection image pairs of liner surfaces of large gas engines. The observed success of the method suggests its great potential for on-site wear assessment of engines during service.

Characterization of surface topography during multi-pass WEDM of MWCNT alumina composites

The thermal spalling action of material removal associated with electrical discharge machining of ceramics results in severe surface debris, cracks, pores, etc. This led to a rough machined surface, ultimately rendering the machined component not susceptible for direct applications. Such a behavior points towards the need to further process the machined surface so as to reduce the net severity of the machined surface. The current work utilizes multi-pass wire electrical discharge machining to enhance the machined surface characteristics of alumina composites. Detailed comparison of the surface characteristics with regards to amplitude, spatial, hybrid and functional volume parameters depicted a superior and homogenous machined surface post multi-pass process. The recast layer severity was minimal as well by incorporation of multi-pass. Furthermore, a detailed analysis of the structural fingerprints of the surface elements depicts actual breakage and subsequent burn-out of the filler material.

Information-rich quality controls prediction model based on non-destructive analysis for porosity determination of AISI H13 produced by electron beam melting

The number of materials processed via additive manufacturing (AM) technologies has rapidly increased over the past decade. As of these emerging technologies, electron beam powder bed fusion (EB-PBF) process is becoming an enabling technology to manufacture complex-shaped components made of thermal-cracking sensitive materials, such as AISI H13 hot-work tool steel. In this process, a proper combination of process parameters should be employed to produce dense parts. Therefore, one of the first steps in the EB-PBF part production is to perform the process parameter optimization procedure. However, the conventional procedure that includes the image analysis of the cross-section of several as-built samples is time-consuming and costly. Hence, a new model is introduced in this work to find the best combination of EB-PBF process parameters concisely and cost-effectively. A correlation between the surface topography, the internal porosity, and the process parameters is established. The correlation between the internal porosity and the melting process parameters has been described by a high robust model (R2adj = 0.91) as well as the correlation of topography parameters and melting process parameters (R2adj = 0.77–0.96). Finally, a robust and information-rich prediction model for evaluating the internal porosity is proposed (R2adj = 0.95) based on in situ surface topography characterization and process parameters. The information-rich prediction model allows obtaining more robust and representative model, yielding an improvement of about 4% with respect to the process parameter-based model. The model is experimentally validated showing adequate performances, with a RMSE of 2% on the predicted porosity. This result can support process and quality control designers in optimizing resource usage towards zero-defect manufacturing by reducing scraps and waste from destructive quality controls and reworks.

Characterization and filtering of profile and areal surface topography by combining the discrete Legendre and cosine transforms

In the standardized processing of surface topography data, the form removal and filtering operations are clearly separated. This is reflected in the current ISO standards concerning profile surface texture and areal surface texture, the ISO 21920 and the ISO 25178 series respectively. When the scale-limited surface texture is significant compared to the form to be removed, for example with additive manufactured surfaces, the dependence of the surface Fourier spectrum on the removed form and orientation may become significant. This may lead to interaction between the form removal and filtering operations. To counter this interaction, in this paper, the lower-order discrete Legendre polynomials that describe the form are combined with cosine functions that describe the surface texture. This set of base functions is orthonormalized using a Gram-Schmidt procedure. This results in a set of orthonormal functions that allow an independent parameterization of both form and texture. The concept and the related theory are given and illustrated using examples of filtering profiles and areal topographies, description of cylinders and treatment of missing data. The examples show that the concept as presented in this paper is useful for filtering surfaces with a dominant form and can be used in the parametrization of surfaces and cylindrical geometries. Also, the methods presented here can be used for filtering and parametrization in the case of missing points in the data, actual holes in the profile or non-rectangular surfaces.

Reduction in Errors in Roughness Evaluation with an Accurate Definition of the S-L Surface

Characterization of surface topography, roughly divided into measurement and data analysis, can be valuable in the process of validation of the tribological performance of machined parts. Surface topography, especially the roughness, can respond straightly to the machining process and, in some cases, is defined as a fingerprint of the manufacturing. When considering the high precision of surface topography studies, the definition of both S-surface and L-surface can drive many errors that influence the analysis of the accuracy of the manufacturing process. Even if precise measuring equipment (device and method) is provided but received data are processed erroneously, the precision is still lost. From that matter, the precise definition of the S-L surface can be valuable in the roughness evaluation allowing a reduction in the rejection of properly made parts. In this paper, it was proposed how to select an appropriate procedure for the removal of the L- and S- components from the raw measured data. Various types of surface topographies were considered, e.g., plateau-honed (some with burnished oil pockets), turned, milled, ground, laser-textured, ceramic, composite, and, generally, isotropic. They were measured with different (stylus and optical) methods, respectively, and parameters from the ISO 25178 standard were also taken into consideration. It was found that commonly used and available commercial software methods can be valuable and especially helpful in the precise definition of the S-L surface; respectively, its usage requires an appropriate response (knowledge) from the users.

Surface characterization and analysis of textured injection moulded PC-ABS automotive interior components

Automotive interior components are produced by injection moulding due to its cost effectiveness in mass production. The surfaces of these components are textured to control the appearance and other surface functional properties such as wear and scratch resistance. Key challenges lie in replicating the features of mould tool with high aspect ratio which are influenced by the polymer and large number of process variables. Hence, to control the aesthetic properties, it is important to improve the understanding of the replication of textured surfaces and its relationship with measured gloss. In this study, the surface topography of PC-ABS samples is investigated using coherence scanning interferometry. Replication of two types- coarse and fine grain surface texture are investigated to identify the effects of tool temperature, injection speed and holding pressure. Areal surface parameters are scrutinized for the quantitative characterization and discrimination of study samples surface topographies. The correlations between process parameters, measured gloss and areal surface parameters are discussed. The results show significant influence of process variables on the replication of surface topography and measured gloss. The grain pattern governed the set of surface parameters selected and the variation in gloss. The process variables are observed to influence different region or distribution of specific surface features represented by surface parameters.

Uncertainty budget of a large-range nanopositioning platform based on Monte Carlo simulation

The objective of precision systems design is to obtain machines with very high and totally predictable work-zone accuracies. In already functional systems, where the errors can be measured, this is achieved by error correction and compensation. The aim of this work is to propose an uncertainty budget methodology to obtain the final measuring uncertainty of precise measuring systems, after error compensation. The case study is a nanopositioning platform, referred as NanoPla, with a confocal sensor integrated as measuring instrument. The NanoPla performs precise positioning in a large range of 50 mm × 50 mm, and its target is surface topography characterization, at a submicrometre scale. After performing the uncertainty budget of the NanoPla, Monte Carlo method is used to obtain the final measuring uncertainty along the whole NanoPla working range, considering all the casuistry. By studying the results, the authors are able to propose solutions to minimize the final measuring uncertainty.

Experimental estimation of thermal contact conductance across pressed copper–copper contacts at cryogenic-temperatures

• Present experimental work presents a valuable database of TCC in cryogenics. • Reports systematic estimates of TCC for copper contacts on which data are scarce. • Effects of broad temperature, pressure, roughness on TCC are covered in vacuum. • Anomalous TCC trend at low temperature is correlated to thermo-physical properties. • Proposes generalized empirical correlations of TCC with temperature and pressure. The accurate estimation of thermal contact conductance (TCC) is a fundamental need towards the optimal design of any cryogen-free conduction-based cooling systems, which routinely utilizes mechanically pressed components of bare copper to form the heat conduction path. There exists a dearth of databases and reliable correlation for TCC between bare copper contacts for such applications. Present work is an experimental study, which has been performed systematically to address the requirement of design engineers for such applications. A novel experimental setup has been made to carry out axial heat transfer experiments between copper contacts under a varying set of temperature and pressure parameters of 50 to 300 K and 0.5 to 8 MPa, respectively. The surface roughness at the contact between copper specimens varied between 0.8 and 10 μ m . The TCC has shown a non-linear variation with temperature in the 50 to 300 K. The temperature-dependent thermophysical properties, nature of asperities deformation, and surface topography characterization were considered in analyzing the results. This effectively helps in dealing with the coupled nature of the TCC problem and thus enhances the accuracy, reliability, and scope of the present study performed at sub-ambient ranges under a varying set of selected parameters. The TCC results have also been compared with theoretical model predictions, and the improvements needed in them are highlighted. Finally, an empirical correlation of the reduced dimensionless TCC with dimensionless temperature and dimensionless pressure has been proposed, which covers a wide deformation range of the asperities, temperature, and surface roughness than existing models in the literature. The proposed correlation consistently explains the non-linear dependence of TCC with temperature and pressure and provides a direct means to the design engineers for the TCC estimation at cryogenic temperatures.