Maxence Bigerelle’s research while affiliated with French National Centre for Scientific Research and other places

Surfaces are the privileged places of interaction between physical phenomena and objects. Roughness studies, especially when performing multiscale analysis, are tools of choice to understand physical phenomena and their scales of application. However, profilometers, especially optical systems, must compromise between field of measurement and resolutions. Stitching is an assembling technique aiming to solve this compromise by combining elementary maps, such as images or topographies. Stitching generates high resolution over a large field of measurement maps, which increases the measurable scale range and facilitates the correct identification of physical phenomena at their scales of application. This article proposes a review of 3D topography stitching algorithms. After explanations on the use cases of 3D topography stitching, the stitching procedure from elementary maps acquisition to the obtention of the stitched map is described step-by-step. Secondly, errors in measurement and stitching are presented with the sources of errors and the error evaluation methods. Lastly, the mathematical modelling of 3D topography is detailed to better understand the optimization process used in the in-plane and out-of-plane registration steps of the stitching algorithms. Comparison of algorithms involved in stitching are proposed so that researchers might find the most suitable algorithm to their needs. Overall, this work aims at introducing researchers and metrologists to important multidisciplinary notions for the use and design of 3D topography stitching algorithms and offers a tutorial-based approach.

Finding the relevant scale to observe the influence of a process is one of the most important purposes of multiscale surface characterization. This study investigates various methods to determine a pertinent scale for evaluating the relationship between the relative area and grit blasting pressure. Several media types were tested alongside two different methods for calculating the relative area and three bootstrapping approaches for scale determination through regression. Comparison with the existing literature highlights innovations in roughness parameter characterization, particularly the advantages of relative area over traditional parameters like Sa. This study also discusses the relevance of different media types in influencing surface topography. Additionally, insights from a similar study on the multiscale Sdq parameter and blasting pressure correlation are integrated, emphasizing a scale relevance akin to our Sdr method’s 120 µm cut-off length. Overall, our findings suggest a pertinent scale of 10,000 µm² for the Patchwork method and a 120 µm cut-off length for the Sdr method, derived from bootstrapping on residual regression across all media. At the relevant scale, every value of R² inferior to 0.83 is not significant with the threshold of 5% for the two methods of calculation of the relative area. This study enhances the understanding of how media types and blasting pressures impact surface topography, offering insights for refining material processing and surface treatment strategies.

Surface roughness significantly affects the performance of microelectromechanical systems (MEMS) and piezoelectric films. This study investigates the impact of surface roughness on the mechanical properties of thin piezoelectric films using nanoindentation and scanning probe microscopy (SPM). Four piezoelectric films with different thicknesses (220, 350, and 450 nm) and substrate configurations (LNO/SiO2/Si or LNO/Si) were analyzed. A discriminant analysis revealed that the fractal dimension is more effective than the arithmetic mean height (Sa) for distinguishing surfaces, with only 2% misclassification versus 25% for Sa. A multiscale analysis identified the Smr2 parameter with low-pass filtering at 140 nm as highly effective for surface discrimination, achieving only 0.1% misclassification. The analysis of the roughness parameter Sa at various scales showed that band-pass filtering at 500 nm yielded a 0.7% misclassification rate, indicating its relevance for fractal roughness characterization. Most relevant roughness parameters for mechanical property correlation were found: Smr2 with low-pass filtering at 500 nm correlated best with hardness (R² = 0.82), and Vvc with low-pass filtering at 2 nm correlated best with reduced elastic modulus (R² = 0.84). These results demonstrate that surface roughness features like valley volume and voids significantly impact the apparent mechanical properties of piezoelectric films.

In various applications, dry friction could induce vibrations. A well-known example is frictional braking systems in ground transportation vehicles involving a sliding contact between a rotating and a stationary part. In such scenarios, the emission of high-intensity noise, commonly known as squeal, can present human health risks based on the noise’s intensity, frequency, and occurrences. Despite the importance of squeal in the context of advancing urbanization, the parameters determining its occurrence remain uncertain due to the complexity of the involved phenomena. This study aims to identify a relevant operando indicator for predicting squeal occurrences. To this end, a pin-on-disc test rig was developed to replicate various contact conditions found in road profiles and investigate resulting squealing. Each test involves a multimodal instrumentation, complemented by surface observations. It is illustrated that the enhanced thermal indicator identified is relevant because it is sensitive to the thermomechanical and tribological phenomena involved in squealing.

With a view to improve measurements, this paper presents a statistical approach for characterizing the behaviour of roughness parameters based on measurements performed on ground surface topographies (grit #080/#120). A S neoxTM (Sensofar®, Terrassa, Spain), equipped with three optical instrument modes (Focus Variation (FV), Coherence Scanning Interferometry (CSI), and Confocal Microscopy (CM)), is used according to a specific measurement plan, called Morphomeca Monitoring, including topography representativeness and several time-based measurements. Previously applied to the Sa parameter, the statistical approach based here solely on the Quality Index (QI) has now been extended to a multi-parameter approach. Firstly, the study focuses on detecting and explaining parameter disturbances in raw data by identifying and quantifying outliers of the parameter’s values, as a new first indicator. This allows us to draw parallels between these outliers and the surface topography, providing reflection tracks. Secondly, the statistical approach is applied to highlight disturbed parameters concerning the instrument mode used and the concerned grit level with two other indicators computed from QI, named homogeneity and number of modes. The applied method shows that a cleaning of the data containing the parameters values is necessary to remove outlier values, and a set of roughness parameters could be determined according to the assessment of the indicators. The final aim is to provide a set of parameters which best describe the measurement conditions based on monitoring data, statistical indexes, and surface topographies. It is shown that the parameters Sal, Sz and Sci are the most reliable roughness parameters, unlike Sdq and S5p, which appear as the most unstable parameters. More globally, the volume roughness parameters appear as the most stable, differing from the form parameters. This investigated point of view offers thus a complementary framework for improving measurement processes. In addition, this method aims to provide a global and more generalizable alternative than traditional methods of uncertainty calculation, based on a thorough analysis of multi-parameter and statistical indexes.

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.

A new method is proposed to investigate the measurement variation of instruments and their ability to discriminate two TA6V surfaces obtained by grinding with SiC grit papers (80 and 120). Three optical measurement technologies included into a single apparatus, namely Confocal Microscopy (CM), Focus Variation (FV) and Coherence Scanning Interferometry (CSI), were used to measure both ground surfaces according to a specific experimental protocol (MorphoMeca Monitoring) based on measurement iterations and repetitions. From the measurements, four indices were built from the Sa roughness parameter to assess the Quality (ratio of the topographical variability over the measurement noise), the Drift (related to surface fluctuations) and the Stability (estimation of the temporal drift using a second order autoregressive model) of the three measurement technologies (modes), as well as their Relevance (computed from an analysis of variance) to discriminate ground surfaces with close roughness. For these investigated surfaces, it was especially highlighted that the Quality Index is four times higher for the CSI mode than for the FV and CM modes. All the used measurement modes experienced small drifting (Drift Index) during the measurements. The CSI mode was slightly more sensitive to drift than the FV and CM modes. The Stability Index indicated that there was no memory effect between two acquisitions for each measurement mode, i.e., the temporal drift did not depend on the measurement mode. Moreover, the three measurement modes are able to discriminate the two ground surfaces with the same accuracy through the Sa parameter. However, the Sa values may vary depending on the measurement modes, and it was finally shown that the Sa parameter is minimized by 0.03 μm for the FV mode compared with the CSI mode, due to its smoothing effect.

Distinguishing between right-handed and left-handed painters in the realm of painting is a question approached from various angles across different disciplines. Each approach, whether it's from neuropsychology, the study of the artwork itself, or the artist's imprint on the work, contributes insights to the burning question of whether the myth of the left-handed painter being more talented than their right-handed counterparts holds true. In this study, we introduce an experimental method involving both left-handed and right-handed painters to determine if the surface topography of brushstrokes presents relevant parameters for differentiating handedness. After conducting an analysis of variance (ANOVA), we isolated relevant roughness parameters, the most significant are the mean hill roundness (Shrn) and the maximum dale aspect ratio (Sdarx). These parameters exhibit significant differences based on the painter's dominant hand. Other parameters also provide insights into the reliability of our study, specifically the texture direction (Std), which shows no difference among the painters. The results are discussed. These findings pave the way for a more comprehensive understanding of the painter's stroke in the process of art painting creation.

A new instrument using reflectance transformation imaging (RTI), named MorphoLight, has been developed for surface characterization. This instrument is designed to be adjustable to surfaces, ergonomic, and uses a combination of high-resolution imaging functions, i.e., focus stacking (FS) and high dynamic range (HDR), to improve the image quality. A topographical analysis method is proposed with the instrument. This method is an improvement of the surface gradient characterization by light reflectance (SGCLR) method. This aims to analyze slope/curvature maps, traditionally studied in RTI, but also to find the most relevant lighting position and 3D surface parameter which highlight morphological signatures on surfaces and/or discriminate surfaces. RTI measurements and analyses are performed on two zones, sky and sea, of a naval painting which have the same color palette but different painting strokes. From the statistical analysis using bootstrapping and analysis of variance (ANOVA), it is highlighted that the high-resolution images (stacked and tonemapped from HDR images) improve the image quality and make it possible to better see a difference between both painting zones. This difference is highlighted by the fractal dimension for a lighting position (θ, φ) = (30°, 225°); the fractal dimension of the sea part is higher because of the presence of larger brushstrokes and painting heaps.

Stitching methods allow one to measure a wider surface without the loss of resolution. The observation of small details with a better topographical representation is thus possible. However, it is not excluded that stitching methods generate some errors or aberrations on topography reconstruction. A device including confocal microscopy (CM), focus variation (FV), and coherence scanning interferometry (CSI) instrument modes was used to chronologically follow the drifts and the repositioning errors on stitching topographies. According to a complex measurement plan, a wide measurement campaign was performed on TA6V specimens that were ground with two neighboring SiC FEPA grit papers (P#80 and P#120). Thanks to four indicators (quality, drift, stability, and relevance indexes), no measurement drift in the system was found, indicating controlled stitching and repositioning processes for interferometry, confocal microscopy, and focus variation. Measurements show commendable stability, with interferometric microscopy being the most robust, followed by confocal microscopy, and then focus variation. Despite variations, robustness remains constant for each grinding grit, minimizing interpretation biases. A bootstrap analysis reveals time-dependent robustness for confocal microscopy, which is potentially linked to human presence. Despite Sa value discrepancies, all three metrologies consistently discriminate between grinding grits, highlighting the reliability of the proposed methodology.