Fundamental scales of adhesion and area–scale fractal analysis

Brown, Christopher; Siegmann, S.

doi:10.1016/s0890-6955(01)00057-8

Cited by 62 publications

(38 citation statements)

References 2 publications

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“…Scale-sensitive fractal analysis is based on the principle that the apparent area of a rough surface depends on the scale of observation. A complete account of scale-sensitive fractal analysis in given in the ASME standard [7] and demonstrations of the method is presented in for example [8][9][10].…”

Section: Methodsmentioning

confidence: 99%

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A Method Development for Correlation of Surface Finish Appearance of Die Surfaces and Roughness Measurement Data

Berglund

Rosén

2009

Tribol Lett

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In die and mould manufacturing, the method used for quality control of finished surfaces is usually visual and tactile inspection of the finish, which is not easily quantifiable. In the present study, an evaluation of the connection between surface finish appearance and measured surface roughness was carried out using scalesensitive fractal analysis to find functional correlations and to determine suitable cut-off limits for functional data filtration. A selection of ball-nose end-mills in combination with two different tool steels (hardness 39 and 47 HRC) were used to manufacture surfaces that were inspected and measured. It was found that the method developed in the present study for evaluating functional correlations and designing filters worked well. It was also found that there is a correlation between the surface roughness parameter Sq and the surface finish appearance and that this correlation is stronger in certain wavelengths on the surface.

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Section: Methodsmentioning

confidence: 99%

“…The analysis method 'scale-sensitive fractal analysis' [7] has in previous studies been successfully used to examine functional correlations at different scales [8][9][10] and seemed to be a suitable part of the complete method to be developed in this work.…”

Section: Introductionmentioning

confidence: 99%

A Method Development for Correlation of Surface Finish Appearance of Die Surfaces and Roughness Measurement Data

Berglund

Rosén

2009

Tribol Lett

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“…Scale-sensitive fractal analysis [13] has been used to statistically discriminate rough surfaces and to find correlations with surface behavior for various applications [14,25] including optical scattering. [26] Length-scale fractal analysis can be used to statistically discriminate surfaces where R a measurement cannot.…”

Section: Characterization Of Surface Roughness By Length-scale Analysismentioning

confidence: 99%

“…[12] Scale-sensitive fractal analysis has the benefit of characterizing the surface over a range of scales [13] that could apply to different scales of interaction. [14] Length-scale fractal analysis is based on the principle from fractal geometry that the length of a rough profile depends on the scale of observation.…”

Section: Introductionmentioning

confidence: 99%

The influence of substrate surface roughness on microstrip transmission line loss using conventional analyses and length‐scale fractal analysis

Vincent

Powers

Bar‐On

2009

Surface & Interface Analysis

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Two components of conductor topography can impact conductor loss for signals in the GHz frequency range: conductor-ceramic interface roughness and conductor edge angle. This study is an experimental investigation of the influence of these conductor topographies on conductor loss in microstrip circuits produced by thick-film technology. The aluminum nitride ceramic substrates have different surface roughnesses due to different surface finish processes. The substrate surfaces were characterized using conventional and length-scale fractal analysis. The conductor-ceramic interface was measured with a contact profilometer. The conductor edge angle and conductor edge profile were measured optically. It was found that there is a direct correlation between conductor loss and conductor edge angle, whereas there is an inverse correlation between loss and substrate roughness or relative length of the conductor-ceramic interface. This is the opposite result to the conventional expectation of surface roughness effects on conductor loss. There is also a negative correlation between conductor edge angle and surface roughness or relative length. The loss behavior can be explained by the interaction of the conductor paste with the surfaces during processing. The paste tends to spread more on the smoother surfaces, and thus creates an elongated edge of diminishing cross-section and a small edge angle. This leads to greater conductor loss.

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“…It has been shown for friction [3] [12], fracture surfaces [6], and adhesion [5] that the strength of functional correlations can depend on using the appropriate scale from a multi-scale characterization of the surface area. These works used multi-scale geometric characterizations and multi-scale regression analyses; specifically, they evaluated the relative areas over a range of scales and then performed regression analyses over these same scales to determine the strength of the correlations between friction, fracture, and adhesion with relative areas, all with respect to scale.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale curvature tensor analysis of machined surfaces

Bartkowiak

Brown

2016

Archives of Mechanical Technology and Materials

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A B S T R A C TThis paper demonstrates the use of multi-scale curvature analysis, an areal new surface characterization technique for better understanding topographies, for analyzing surfaces created by conventional machining and grinding. Curvature, like slope and area, changes with scale of observation, or calculation, on irregular surfaces, therefore it can be used for multi-scale geometric analysis. Curvatures on a surface should be indicative of topographically dependent behavior of a surface and curvatures are, in turn, influenced by the processing and use of the surface. Curvatures have not been well characterized previously. Curvature has been used for calculations in contact mechanics and for the evaluation of cutting edges. In the current work two parts were machined and then one of them was ground. The surface topographies were measured with a scanning laser confocal microscope. Plots of curvatures as a function of position and scale are presented, and the means and standard deviations of principal curvatures are plotted as a function of scale. Statistical analyses show the relations between curvature and these two manufacturing processes at multiple scales.

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Fundamental scales of adhesion and area–scale fractal analysis

Cited by 62 publications

References 2 publications

A Method Development for Correlation of Surface Finish Appearance of Die Surfaces and Roughness Measurement Data

A Method Development for Correlation of Surface Finish Appearance of Die Surfaces and Roughness Measurement Data

The influence of substrate surface roughness on microstrip transmission line loss using conventional analyses and length‐scale fractal analysis

Multi-scale curvature tensor analysis of machined surfaces

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