Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?
نویسندگان
چکیده
The random process theory (RPT) has been widely applied to predict the joint probability distribution functions (PDFs) of asperity heights and curvatures of rough surfaces. A check of the predictions of RPT against the actual statistics of numerically generated random fractal surfaces and of real rough surfaces has been only partially undertaken. The present experimental and numerical study provides a deep critical comparison on this matter, providing some insight into the capabilities and limitations in applying RPT and fractal modeling to antireflective and hydrophobic rough surfaces, two important types of textured surfaces. A multi-resolution experimental campaign by using a confocal profilometer with different lenses is carried out and a comprehensive software for the statistical description of rough surfaces is developed. It is found that the topology of the analyzed textured surfaces cannot be fully described according to RPT and fractal modeling. The following complexities emerge: (i) the presence of cut-offs or bi-fractality in the power-law powerspectral density (PSD) functions; (ii) a more pronounced shift of the PSD by changing resolution as compared to what expected from fractal modeling; (iii) inaccuracy of the RPT in describing the joint PDFs of asperity heights and curvatures of textured surfaces; (iv) lack of resolution-invariance of joint PDFs of textured surfaces in case of special surface treatments, not accounted by fractal modeling. Notice: this is the author’s pre-print of a work that was accepted for publication in Journal of Physics D: Applied Physics. Changes resulting from the publishing process, such as editing, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was published in J. Phys. D: Appl. Phys. 48 (2015) 045301 (12pp), DOI: 10.1088/0022-3727/48/4/045301 ________________________________________________________________________________
منابع مشابه
Topological structure on generalized approximation space related to n-arry relation
Classical structure of rough set theory was first formulated by Z. Pawlak in [6]. The foundation of its object classification is an equivalence binary relation and equivalence classes. The upper and lower approximation operations are two core notions in rough set theory. They can also be seenas a closure operator and an interior operator of the topology induced by an equivalence relation on a u...
متن کاملTOPOLOGICAL SIMILARITY OF L-RELATIONS
$L$-fuzzy rough sets are extensions of the classical rough sets by relaxing theequivalence relations to $L$-relations. The topological structures induced by$L$-fuzzy rough sets have opened up the way for applications of topological factsand methods in granular computing. In this paper, we firstly prove thateach arbitrary $L$-relation can generate an Alexandrov $L$-topology.Based on this fact, w...
متن کاملImproving security of double random phase encoding with chaos theory using fractal images
This study presents a new method based on the combination of cryptography and information hiding methods. Firstly, the image is encoded by the Double Random Phase Encoding (DRPE) technique. The real and imaginary parts of the encoded image are subsequently embedded into an enlarged normalized host image. DRPE demands two random phase mask keys to decode the decrypted image at the destination. T...
متن کاملAnalysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension
Introduction: Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obl...
متن کاملApplication of Rough Set Theory in Data Mining for Decision Support Systems (DSSs)
Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...
متن کامل