Profile and Areal Surface Parameters for Fatigue Fracture Characterisation

Macek, Wojciech; Branco, R.; Szala, Mirosław; Marciniak, Zbigniew; Ulewicz, Robert; Sczygiol, N.; Kardasz, Piotr

doi:10.20944/preprints202005.0275.v1

Cited by 21 publications

(4 citation statements)

References 46 publications

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“…Moreover, in many noise-detection procedures, the profile (2D) assessments were defined as potentially more decisive than the areal (3D) analysis [ 80 ]. Profile and areal surface topography analysis with specifications of values of surface texture parameters can be increasingly valuable in many engineering appliances [ 81 ]. Nonetheless, the proposed noise reduction method (HFN, in this instance) included areal appliances of spline algorithms.…”

Section: Materials Measurement Process and Applied Methodsmentioning

confidence: 99%

Suppression of the High-Frequency Errors in Surface Topography Measurements Based on Comparison of Various Spline Filtering Methods

Podulka

2021

Materials

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The metrology of so-called “engineering surfaces” is burdened with a substantial risk of both measurement and data analysis errors. One of the most encouraging issues is the definition of frequency-defined measurement errors. This paper proposes a new method for the suppression and reduction of high-frequency measurement errors from the surface topography data. This technique is based on comparisons of alternative types of noise detection procedures with the examination of profile (2D) or surface (3D) details for both measured and modelled surface topography data. In this paper, the results of applying various spline filters used for suppressions of measurement noise were compared with regard to several kinds of surface textures. For the purpose of the article, the influence of proposed approaches on the values of surface topography parameters (from ISO 25178 for areal and ISO 4287 for profile standards) was also performed. The effect of the distribution of some features of surface texture on the results of suppressions of high-frequency measurement noise was also closely studied. Therefore, the surface topography analysis with Power Spectral Density, Autocorrelation Function, and novel approaches based on the spline modifications or studies of the shape of an Autocorrelation Function was presented.

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Section: Materials Measurement Process and Applied Methodsmentioning

confidence: 99%

Suppression of the High-Frequency Errors in Surface Topography Measurements Based on Comparison of Various Spline Filtering Methods

Podulka

2021

Materials

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“…Moreover, after 30 h of testing damaged areas were analysed using stick profilometer Form Talysurf Series 50 mm Intra (Taylor Hobson Ltd., Leicester, UK). The surface roughness parameters: arithmetical mean height (S a ) and maximum height (S z ) [ 48 , 49 ] were determined according to the ISO 25178 standard [ 50 ]. To state the effect of the cavitation load on the phase transformations, the X-ray diffraction (XRD) measurements were conducted before and after the total time of CE testing (30 h).…”

Section: Methodsmentioning

confidence: 99%

Effect of Nitrogen Ion Implantation on the Cavitation Erosion Resistance and Cobalt-Based Solid Solution Phase Transformations of HIPed Stellite 6

et al. 2021

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From the wide range of engineering materials traditional Stellite 6 (cobalt alloy) exhibits excellent resistance to cavitation erosion (CE). Nonetheless, the influence of ion implantation of cobalt alloys on the CE behaviour has not been completely clarified by the literature. Thus, this work investigates the effect of nitrogen ion implantation (NII) of HIPed Stellite 6 on the improvement of resistance to CE. Finally, the cobalt-rich matrix phase transformations due to both NII and cavitation load were studied. The CE resistance of stellites ion-implanted by 120 keV N+ ions two fluences: 5 × 1016 cm−2 and 1 × 1017 cm−2 were comparatively analysed with the unimplanted stellite and AISI 304 stainless steel. CE tests were conducted according to ASTM G32 with stationary specimen method. Erosion rate curves and mean depth of erosion confirm that the nitrogen-implanted HIPed Stellite 6 two times exceeds the resistance to CE than unimplanted stellite, and has almost ten times higher CE reference than stainless steel. The X-ray diffraction (XRD) confirms that NII of HIPed Stellite 6 favours transformation of the ε(hcp) to γ(fcc) structure. Unimplanted stellite ε-rich matrix is less prone to plastic deformation than γ and consequently, increase of γ phase effectively holds carbides in cobalt matrix and prevents Cr7C3 debonding. This phenomenon elongates three times the CE incubation stage, slows erosion rate and mitigates the material loss. Metastable γ structure formed by ion implantation consumes the cavitation load for work-hardening and γ → ε martensitic transformation. In further CE stages, phases transform as for unimplanted alloy namely, the cavitation-inducted recovery process, removal of strain, dislocations resulting in increase of γ phase. The CE mechanism was investigated using a surface profilometer, atomic force microscopy, SEM-EDS and XRD. HIPed Stellite 6 wear behaviour relies on the plastic deformation of cobalt matrix, starting at Cr7C3/matrix interfaces. Once the Cr7C3 particles lose from the matrix restrain, they debond from matrix and are removed from the material. Carbides detachment creates cavitation pits which initiate cracks propagation through cobalt matrix, that leads to loss of matrix phase and as a result the CE proceeds with a detachment of massive chunk of materials.

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“…The results of its analysis, including calculating the values of ST parameters, can affect the classification of the produced parts as those suitable for efficient operation. In fact, the ST is often called a fingerprint of the manufacturing process that many valuable and accurate information, e.g., wear resistance [ 1 , 2 ], lubricant retention [ 3 ], sealing [ 4 ], friction [ 5 ], fatigue [ 6 ], material contact in general, can be gained directly from its studies. Moreover, ST analysis is often an integral part of process control.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Surface Topography Feature Size Density and Distribution on the Results of a Data Processing and Parameters Calculation with a Comparison of Regular Methods

Podulka

2021

Materials

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In this paper, the influence of occurrence of surface texture features on the values of surface topography parameters calculated after the application of various data processing techniques was presented. Different types of surface topographies were considered, as follows: cylinder liners, some with additionally burnished dimples, turned, ground, milled, laser-textured, composite, ceramic, or isotropic in general. The effects of feature size on the areal form removal, noise suppressions, or end-effect reducing in surface texture measurements were studied. The variations of the ISO 25178 standard surface topography parameters were taken into consideration in detail. It was assumed that some of the feature sizes, distributions, and densities have a substantial impact on the values of surface topography parameters calculated after applications of regular (commonly used) algorithms and procedures, defined as basic operations, provided for raw surface texture data obtained directly from the measurement process. In the end, some of the practical applications for receiving the relevant values of surface topography parameters were proposed.

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Profile and Areal Surface Parameters for Fatigue Fracture Characterisation

Cited by 21 publications

References 46 publications

Suppression of the High-Frequency Errors in Surface Topography Measurements Based on Comparison of Various Spline Filtering Methods

Suppression of the High-Frequency Errors in Surface Topography Measurements Based on Comparison of Various Spline Filtering Methods

Effect of Nitrogen Ion Implantation on the Cavitation Erosion Resistance and Cobalt-Based Solid Solution Phase Transformations of HIPed Stellite 6

The Effect of Surface Topography Feature Size Density and Distribution on the Results of a Data Processing and Parameters Calculation with a Comparison of Regular Methods

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