Statistical Roughness Parameters Research Articles

Research analysis of data-driven submarine navigation adaptation zones based on factor analysis

The study of gravity anomaly adaptation zones holds significant importance in resource exploration, environmental studies, and marine development. This paper initially collected and preprocessed data on gravity anomalies, dividing them into 16 sub-regions. Subsequently, five statistical parameters of gravity field characteristicsstandard deviation, roughness, gradient, gravity entropy, and planar correlationwere introduced, and factor analysis was employed to compute scores for each area. Finally, MATLAB software was utilized to construct a three-dimensional distribution map of gravity anomaly values. The results indicate that factor analysis demonstrates promising applications in the research of data-driven submarine navigation adaptation zones.

Research analysis of data-driven submarine navigation adaptation zones based on factor analysis

The study of gravity anomaly adaptation zones holds significant importance in resource exploration, environmental studies, and marine development. This paper initially collected and preprocessed data on gravity anomalies, dividing them into 16 sub-regions. Subsequently, five statistical parameters of gravity field characteristicsstandard deviation, roughness, gradient, gravity entropy, and planar correlationwere introduced, and factor analysis was employed to compute scores for each area. Finally, MATLAB software was utilized to construct a three-dimensional distribution map of gravity anomaly values. The results indicate that factor analysis demonstrates promising applications in the research of data-driven submarine navigation adaptation zones.

Evolution of surface roughness of notched steel details under fatigue loading

A fatigue crack initiates on the surface of the steel members, which can be attributed to the extrusions and intrusions caused by cyclic loading. The surface roughness parameters, including the statistical surface roughness and maximum surface roughness parameters, can characterize the increase in extrusion and intrusion. Six notched specimens were loaded with cyclic loading, and the evolution of the surface roughness parameters was monitored during the test to explore the characteristics of the surface roughness during the fatigue loading procedure in the high-cycle fatigue regime and clarify the effects of the initial surface finish and load ratio on the surface roughness evolution. Based on the test results, it was found that the 3D average surface roughness Sa and 3D root-mean-square surface roughness Sq were preferable for detecting the onset of fatigue cracks compared with the 2D average surface roughness Ra and 2D root-mean-square surface roughness Rq. The 3D maximum valley depth, Sv, was an effective indicator of the fatigue crack initiation location, except for compression-dominant fatigue loading. The evolution patterns of the 3D average surface roughness, Sa, and 3D root-mean-square surface roughness Sq during fatigue loading can be classified into three phases: instant response, damage accumulation, and crack-induced response. In addition, surface polishing is recommended for evaluation using 2D surface roughness parameters. However, it is not mandatory for evaluations using 3D surface roughness parameters. The effects of typical load ratios (0.1, −1, and 10) on the evolution pattern of the 3D statistical surface roughness parameters, especially in the instant response phase, were also investigated.

Influence of roughness on the early corrosion of API steels by atomic force microscopy (AFM): A real-time assessment

Roughness surface significantly affects the corrosion process of steels. However, this relationship in early stages at the local level has not been well studied. The mechanisms associated with the beginning of corrosion are thus not well known. Likewise, the lateral distribution of roughness is rarely considered, which can lead to inaccurate representations of surface features. Herein, the effect of roughness on the deterioration of carbon steels was locally studied by means of a fluid cell (FC) coupled to an atomic force microscope (AFM). The steel studied was prepared using grit papers with different abrasive particle sizes (#600, #1500, #2000) and exposed to artificial seawater for 4 h. A power spectral density (PSD) approach, which considered lateral distribution of surface roughness, was used to compare with traditional statistical roughness parameters. According to the roughness evolution, the corrosion susceptibility was #600 > #1500 > #2000, indicating greater corrosion resistance for smoother surfaces. The calculus carried out for estimating the corrosion rate as function roughness variation dictates that there may be up to three stages in the onset of corrosion. The first and third stages show a low corrosion rate (considerably less than 4 ×10−6 A/cm2), while the middle stage reflects an accelerated corrosion rate (up to 5.3 ×10−5 A/cm2 for #600 at 2 h). These results were in concordance with conventional electrochemical impedance spectroscopy tests. This method is proposed as a preventive strategy for the assessment of pipeline materials integrity which are used for transporting petroleum industry products.

Relationship between Joint Roughness Coefficient and Statistical Roughness Parameters and Its Sensitivity to Sampling Interval

Accurate determination of the surface roughness is of significant importance in estimating the mechanical and hydraulic behaviors of rock joints. The correlation between joint roughness coefficient (JRC) and various statistical roughness parameters calculated from digitized Barton’s roughness profiles was explored with Pearson’s correlation coefficient method. The results show the strongest correlation between the standard deviation of the roughness angle and JRC following an excellent linear relationship. In addition, the correlation in the JRC with textural parameters is better than its correlation with amplitude parameters. Twenty-nine rock joint surfaces from fine sandstone, coarse sandstone and granite joint samples with a wide range of surface morphology were digitized using a high-resolution 3D scanner instrument. Further, the statistical roughness parameter values were calculated for each joint profile at eight different sampling intervals for sensitivity analysis of these statistical roughness parameters with regard to the sampling interval. The result indicated that textural parameters generally have a certain degree of dependency on sampling interval, following a power-law relationship. Specifically, when the sampling interval increases, the structure function value increases whereas it decreases for other textural parameters. In contrast, the dependence of the amplitude parameters on the sampling interval is not significant.

Surface Roughness Characterization for Stress Concentration Factor Predictions: A Bayesian Learning Approach

The surface roughness has an important influence on the fatigue life of the structures. The fatigue life reduces due to the stress concentration caused by surface roughness. The stress concentration governs the fatigue crack initiation and propagation. The accurate acquisition of the stress concentration factor of rough surfaces is a key issue in determining fatigue life. Nevertheless, semi-empirical models may be biased for various machining processes. Besides, finite element method simulations cannot give explicit expression of the stress concentration factor. Bayesian learning can construct accurate prediction models which offering a number of additional advantages. In this paper, based on several data pairs constructed by finite element method, the correlation expression between the stress concentration factor and statistical roughness parameters of surfaces is established quickly through Bayesian learning. Compared with some other semi-empirical models, the accuracy and stability of the proposed method are certified. This paper provides a simple and effi-cient approach to determine the stress concentration factor for rough surfaces under different processing conditions.

Inversion of bottom parameters using a backscattering model based on the effective density fluid approximation

An inversion method using backscattering strength is used to obtain bottom parameters. A backscattering model based on the effective density fluid approximation was established as the forward model. The objective function used to scale the mismatch between the model predictions and the measured data (obtained by employing two monostatic transducers with narrow directivity) was established on the assumption that the data errors follow a Gaussian distribution. The maximum a posteriori estimations of inversion parameters were obtained by using a two-step hybrid optimization algorithm combining the differential evolution algorithm and the particle swarm optimization algorithm. The uncertainty and the correlation of inversion parameters were presented using marginal probability distributions and a covariance matrix through Bayesian inversion. Using this method, we can acquire not only geoacoustic parameters (including sound speed and attenuation) but also partial physical parameters of marine sediments and statistical character parameters of seafloor roughness and sediment heterogeneity. Finally, the efficiency of this inversion method was verified through comparison between inversion results and sampling data from sand sediment at the bottom of a water tank.

Attenuation of Rayleigh waves due to surface roughness.

Rayleigh waves are well known to attenuate due to scattering when they propagate over a rough surface. Theoretical investigations have derived analytical expressions linking the attenuation coefficient to statistical surface roughness parameters, namely, the surface's root mean squared height and correlation length and the Rayleigh wave's wavenumber. In the literature, three scattering regimes have been identified-the geometric (short wavelength), stochastic (short to medium wavelength), and Rayleigh (long wavelength) regimes. This study uses a high-fidelity two-dimensional finite element (FE) modelling scheme to validate existing predictions and provide a unified approach to studying the problem of Rayleigh wave scattering from rough surfaces as the same model can be used to obtain attenuation values regardless of the scattering regime. In the Rayleigh and stochastic regimes, very good agreement is found between the theory and FE results both in terms of the absolute attenuation values and for asymptotic power relationships. In the geometric regime, power relationships are obtained through a combination of dimensional analysis and FE simulations. The results here also provide useful insight into verifying the three-dimensional theory because the method used for its derivation is analogous.

Systematic selection and evaluation of relevant surface roughness parameters for the characterisation of the innovative RPM-Synchronous Grinding process

The key to high performances and long lifetimes of machine components in lubricated contacts is often the surface topography. Its characteristics can be derived in numerous ways from 3D topography measurements, but these procedures do not follow any existing standards, resulting in limited comparability. In this work, we present a new, universally applicable workflow to reveal the most significant roughness parameters for a comprehensive description of differences in surface topographies. This workflow, based on principal component analysis (PCA), offers a standardization of parameter selection. It is applied to RPM-Synchronous Grinding (RSG), a novel grinding process that enables the production of non-circular geometries without an oscillating movement. To increase trust in this new technique, knowledge on how the process parameters affect the surface topography is required. Numerous statistical roughness parameters were derived from 3D confocal light microscopy as well as 2D tactile measurements on each ground workpiece. We apply the proposed workflow and find that, for the selected RSG parameter variations, Rq is the most relevant roughness parameter to capture changes in the surface topography. The 100 % fused white aluminum oxide grinding wheel, opposite grinding direction, and a low specific material removal rate result in the smoothest surfaces. A high degree of usage of the grinding wheel leads to higher Rq values, but there is a trend to reach a plateau value. The RSG machined workpieces are compared to conventionally ground and shortly run camshafts. The camshafts have Rq values in the range of the rougher RSG machined surfaces, but there are significant differences in the parameters Ssk, Sku, Sv and Vvv. Provided the number of workpieces is high enough for statstical analysis, we propose to apply our workflow for the selection of the most relevant roughness parameters to describe the differences between surfaces obtained by different machining parameters and processes.

Quantifying geometric tip-sample effects in AFM measurements using certainty graphs

Abstract One of the challenges faced in accurately measuring nanoscale surface roughness using Atomic Force Microscopy (AFM) techniques are the geometric interactions of the surface with the AFM probe-tip. What is the significance of these effects, and to what extent do they reduce the effectiveness of an AFM as a nanospatial measurement tool of surfaces with roughness? The aim of this work is to develop a framework by which an AFM user would be able to automatically [1] quantify the magnitude these effects from geometric tip-sample interactions have on measurement accuracy. In turn, the AFM user would then be able to make an informed decision on whether additional methods need to be applied to correct these measurements. To accomplish this, a numerical model is developed that can generate sets of ‘true’ stochastic surfaces of various statistical roughness parameters as well as various probe-tip shapes. The model then simulates, using such probe-tips, the scanning procedure of an AFM on such sets of surfaces to produce corresponding measurement images. The difference, due to geometric tip-sample interactions, between the ‘true’ surfaces and the measured images is quantified, over various ranges of roughness parameters for different probe-tips, with a novel certainty metric to create certainty graphs. These graphs show for a given tip, the significance of the tip effects due to surface roughness and thus the extent of measurement inaccuracy.

A unified approach to model the effect of porosity and high surface roughness on the fatigue properties of additively manufactured Ti6-Al4-V alloys

In this article, we propose a model that can account for the effect of porosity and high surface roughness on the fatigue crack initiation of AM Ti6Al4V alloys in moderate and high cycle fatigue regimes. Within these fatigue regimes, the applied force to the component is below the yield stress, however, defective features, viz., porosity and high surface roughness, can act as stress raisers. As a consequence, local plasticity can occur. To capture this phenomenon, a nonlinear isotropic kinematic hardening elasto-plasticity model is employed in our finite element (FE) model. For creating the geometry of the FE models, inputs from fractography analyses and surface roughness measurements are needed. From fractography analyses, the shape of pores formed by gas bubbles during manufacture appears quite regular. Thus, these pores are modeled as circles in FE models. The size of these pores and their distance to a free surface of the tested specimens are extracted from Scanning Electron Microscope images. Moreover, it has been mentioned in the literature that statistical parameters of surface roughness cannot fully describe the detrimental effect of this type of defect to the fatigue life of the associated component. Thus, in our FE model, the surface topography, which was measured using stylus-based profilometer, is explicitly modeled. The finite element results are then post-processed by our in-house software to extract the Smith–Watson–Topper (SWT) fatigue indicator parameter (FIP). The SWT parameter is calculated at each element centroid of the FE mesh, i.e., the local indicator. Afterward, an average value of the SWT parameter over a so-called critical area whose center is located at the considered centroid is also calculated, i.e., the average indicator. The results show that the local SWT indicator is too conservative in predicting the fatigue life of the AM Ti64 alloys while the average SWT one can provide good results.

Theory for admittance voltammetry of reversible two step electron transfer process with DC bias at rough and fractal electrodes

We developed a phenomenological theory for DC-bias dependent electrochemical impedance response and admittance voltammetry of reversible two-step electron transfer (EE) process at randomly rough and fractal electrodes. The power spectrum of roughness is used to incorporate the statistical information of surface randomness. For the finite fractal model, statistical morphological parameters of roughness, viz., fractal dimension (DH), topothesy length (ℓτ) and lower cut-off length (ℓ), significantly influence the admittance response. The magnitude of admittance increases with an increase in the roughness of fractal electrode (e.g. increase in the value of DH or ℓτ or decrease in ℓ) for both the electron transfer steps. The magnitude of admittance with the variation of DC potential at fixed temporal frequency unravels the multi-electron transfer process. The two step electron transfer process has two characteristic peaks in their plot. The enhanced roughness of electrode increases the height of the admittance peaks and the regions around it (obtained at different fixed frequencies). Our theory is validated with experimental data for the ethyl viologen system at a moderately rough Pt electrode. Finally, our current methodology for admittance voltammetry has the dual advantage of impedance as well as of voltammetry.

Evaluation of Topographical Co-Cr-Mo Alloy Surface Changes After Various Finishing Treatments.

PurposeTo quantify the influence of three different finishing treatments on the cobalt-chromium-molybdenum (Co-Cr-Mo) alloy surface based on stereometric analysis parameters.Materials and methodsEighteen specimens were casted from an extra-hard alloy (Wironit®, BEGO, Bremen, Germany). The samples were distributed into three groups (n = 6 samples per group) dependent on different polishing techniques applied, as follows: A group, only electropolished (EP) samples; B group, after EP, an additional mechanical polishing process was applied to the surface by rubber discs and a polishing paste (RP); C group, after EP, an additional mechanical polishing process was completed by rubber discs, polishing paste and finally by a rotating deer leather wheel (RPDL). Samples were imaged by atomic force microscopy (AFM) in a contact mode, in air, at room temperature.ResultsThe evaluation of the microtexture of the sample surface was made based on the 3-D roughness parameters. The lowest statistical surface roughness parameters were found in the RP samples, whereas the highest values were obtained from the EP samples.ConclusionsThe experiments described can help manufacturers identify the most appropriate parameters and their ranges within which optimal surface characteristics can be achieved.

Tribological Properties of Multifilament Aluminum Oxide Yarns on Contact with Submicro Rough Surfaces

The tribological properties of multifilament aluminum oxide yarns were studied during frictional contact with submicro rough surfaces with known statistical roughness parameters. The tangential drag coefficient largely depends on roughness isotropy of the contact surfaces, the relative position of the asperities of the contacting surfaces and the nature of wetting of the surfaces with a sizing emulsion. The stability of the friction coefficient in the experiments of the first series with the arrangement of the yarns in the direction of sliding of the counterpart is higher than for the experiments of the second series when the yarns are at a 90° angle to the direction of sliding of the counterpart.

SURFACE ROUGHNESS OF ELECTROSPUN NANOFIBROUS MATS BY A NOVEL IMAGE PROCESSING TECHNIQUE

A novel technique based on image processing inspired by the simple assumption for the first time to assess the roughness of nanofibrous mats based on grayscale variations is proposed. The height of a nanofibrous mat in different regions of the surface is simulated by grayscale variations in the image while the relation between grayscale and height is obtained as a linear function. The roughness is obtained by measuring height variations in the surface profile. Statistical roughness parameters of nanofibrous mats are also obtained from direct measurement with roughness profilometry and atomic force microscopy (AFM) for comparison of the roughness of nanofibrous mats between direct measurement and proposed method. The AFM is the most suitable surface measuring instrument for roughness measurement on the nanofibrous mat. So that, in this study the relation between the obtained statistical roughness parameters and the AFM result follows a low coefficient of expansion. Therefore, the two methods give results in satisfactorily close agreement. This proposed method not only exhibits all mentioned advantages, but has also been very simple, accurate, and useful for surface roughness prediction in nanofibrous mats.

Topological Characterization of Machined Edges Prepared by Different Cutting Methods, and Edge Evolution in Tensile Deformation

To understand better on edge cracking in sheet metal forming, the edge preparation methods, edge topological characteristics, and its evolution in uniaxial tension are investigated. Tensile specimens were prepared by waterjet cutting, milling, and EDM methods. The as-machined and fractured edges were measured with a Laser Scanning Confocal Microscope (LSCM (Keyence VK-9710), which provides statistical roughness parameters and raw data of surface 3D surface geometry at up to 1nm z-direction resolution, allowing topological analysis The edge evolution during tensile straining was reported achieved by interrupted tensile tests at different strains, and replication of the edge surfaces without unloading using a metallurgical replica technique, for post-measurement after the tests. The quality of the three edge preparation methods and the effect on edge cracking in tension are investigated.

Scale-depended Choice of Scanning Rate for AFM Measurements

Three samples with different high of topography features were measured at different scanning rate. We also presented statistical and fractal analyses for definition of the surface morphometrics. They can be used for calculation and evaluation of the images' distortion that takes place during scanning rate and proved to be helpful while controlling the measurement. Basing on the results we came to the conclusion that fractal analysis, the statistical surface roughness parameters and AFM may provide us with a deeper understanding of the physical phenomena taking place in the sample-tip interface. This is why, fractal analysis and statistical surface roughness parameters are useful information for the further improvement of calibration system. This approach can be applied for choosing scanning parameters properly, taking into consideration the geometry of the sample and for the microscope calibration by geometrical sizes of features.

Limits in measurements of contact lens surface profile using atomic force microscopy.

In the paper the results of AFM surface profile measurements of seven new long-wear contact lenses (CL) available in Poland are presented. Calculated statistical roughness parameters are shown, namely standard deviation (RMS), mean roughness, maximum difference between peak and valley, skewness, and kurtosis. It is demonstrated that CLs manufactured using recent methods, such as two-stage polimerisation or extending silicon chains exhibit small RMS, less than 10 nm, in comparison with older generation CLs which maintains RMS on the level of tens of nanometers. Then, a comparison of results obtained using a typical silicon tip and a silicon tip covered with alkylsilane is also demonstrated. As a result, roughness parameters, such as RMS, are higher for the case of alkylsilane-coated tip than for a typical silicon tip, 8.39 ± 0.16 nm vs. 6.22 ± 0.9 nm, which leads to the conclusion that the proper choice of the tip material significantly influences the outcome of the experiment. Finally, the reliability and limits of such measurements are discussed.

Geometric analysis of the influence of perpendicularity of a spindle axis of the milling machine on the surface quality

This paper deals with analyzes of the influence of the perpendicularity of the spindle of the milling machine on the machined surface. This is part of the geometric errors of machine tools and in a direct manner constitutes a defect on the quality of the workpiece. Therefore, the surface roughness is particularly sensitive to the cutting speed, the feed rate, round of teeth default, the tool tip radius and the cutter teeth number. This article examines the characteristics of the surface topography of steel parts, in finishing machining using milling cutters. The study is conducted by computer simulation tests and experimental part using surface condition monitoring instruments, taking into consideration the round teeth default. The variation of the inclination of the spindle of the milling machine in three positions (90° + 30′, 90°, and 90°–30′) shows a good agreement between the simulation and the experimental results for sharp and moderately worn tools. Similarly, this study showed that the presented model could thus be integrated into systems computer-aided design and computer-aided manufacturing. Finally, the physical and statistical parameters of roughness during milling at position 90° confirmed that, when the defect of the perpendicularity is eliminated to the maximum, the best surface conditions are obtained.

Estimating and Extracting of the Surface Profile Waviness by Use of the Spatial Notch Filters in the Roughness Profile Analysis

Classical surveying of the machined surface quality is performed very often with using roughness profile recording by means of contact mechanical profilometer [4-7]. Also classical attitude to the profile run elaboration is to regard it as to a curve composed of the three main components: shape – treated mostly as deterministic, waviness – treated essentially as deterministic with some probabilistic component, and roughness itself – treated to as purely probabilistic. The question is: how to estimate this three components quantitatively and extract for individual evaluation. In our works we have developed methodical procedures of profile elaboration divided into three major steps: shape estimation and extraction with using polynomials of the order fitted to the evaluated profile, waviness estimation and extraction with using spatial filtering methods employing so called notch filters, statistical roughness estimation with using the set of tests and methods devoted especially to roughness runs of the purely probabilistic type. The notch filters are filters cutting out one, well determined spatial frequency λ0 from the spectrum of frequencies related with investigated profile. The second but not less important advantage of this choose, was the phase characteristics of this filter, which tends rapidly to zero outside the “notch” band, not distorting unfiltered spatial signal. The width of cutting “notch” is controlled with using one independent variable Q. Our methodology is based upon cutting out a set of frequencies from the profile, tuned separately for to achieve as well reflection of the periodic impulse-like signal as possible, due to the well known theorem of decomposing physical, periodical signals into their harmonic components. In our researches we have employed the set of 8 filters providing us with good results even with profiles “scared” with substantial tracks of periodically acting tool. Of course, it is still possible to employ even greater number of filters, due to their low numerical complexness. Also the comparison has been performed with the profile not affected by waviness for to convince, that this type of filter simply do not affect the probabilistic roughness component. All of the profile elaboration stages have been checked due to their spatial spectrum with using classical tool – FFT transform of the roughness profile autocovariance function. As the major check of the proposed procedure correctness, i.e. proper extraction of the waviness component without disturbing of the statistical roughness parameters we assumed checking of the shape factor Rq/Ra before and after waviness extraction, which turned to be the same at the good level of accuracy. Our results, basing on simple and fundamental frequency analysis seems to be the good alternative to much complicated and time consuming analysis based on wavelet transforms in different forms.