Estimation of spatial distribution and symmetry of textile materials using lacunarity

Grzybowski, Jacek; Błachowicz, Tomasz

doi:10.25367/cdatp.2020.1.p180-185

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…In conclusion, succolarity and lacunarity were shown to be linearly correlated with the complexity of biomaterials. Additionally, a variety of research areas, including geophysics, 68 image processing, 69 medicine, 70 material science, 71 rock permeability, 72 satellite images, 73 and complexity of DNA 74 use succolarity and lacunarity.…”

Section: Introductionmentioning

confidence: 99%

Vision‐based probabilistic post‐earthquake loss estimation for reinforced concrete shear walls

Azhari,

Hamidia,

Rouhani

2024

Structural Concrete

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In this paper, a probabilistic methodology based on image analysis is proposed for earthquake‐induced loss estimation in rectangular reinforced concrete shear walls (RCSWs) in compliance with FEMA P‐58. The methodology is developed using a databank of 285 surface crack patterns gathered from the result of experimental research on 99 rectangular RCSWs with wide‐ranging structural and geometric characteristics. For the complexity extraction, three fractal geometry indices of the damaged specimens are taken into consideration. Fragility functions are generated to determine the probability of exceeding a FEMA P‐58 compliant damage state based on the various methods of repair for specific complexity indices. The fragility functions are obtained using four common probabilistic distributions including lognormal, Weibull, gamma, and beta. The fitness of the fragility curves is examined by two goodness‐of‐fit tests, namely the Kolmogorov–Smirnov test and Lilliefors test. Results show that the Weibull is the best‐fitting distribution for the majority of damage states and succolarity possesses the best results in goodness‐of‐fit tests among fractal geometry indices. Empirical loss indices are also derived in this paper aimed at optimizing the goodness‐of‐fits. Finally, the proposed procedure is utilized for a sample specimen from the databank at various damage levels.

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Section: Introductionmentioning

confidence: 99%

Vision‐based probabilistic post‐earthquake loss estimation for reinforced concrete shear walls

Azhari,

Hamidia,

Rouhani

2024

Structural Concrete

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Probabilistic Postearthquake ASCE 41-17 Compliant Performance Level Identification for Shear-Dominated RC Shear Walls via Crack Image Analysis

Azhari,

Hamidia

2025

J. Struct. Eng.

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Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions

et al. 2021

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Two-dimensional structures, either periodic or random, can be classified by diverse mathematical methods. Quantitative descriptions of such surfaces, however, are scarce since bijective definitions must be found to measure unique dependency between described structures and the chosen quantitative parameters. To solve this problem, we use statistical analysis of periodic fibrous structures by Hurst exponent distributions. Although such a Hurst exponent approach was suggested some years ago, the quantitative analysis of atomic force microscopy (AFM) images of nanofiber mats in such a way was described only recently. In this paper, we discuss the influence of typical AFM image post-processing steps on the gray-scale-resolved Hurst exponent distribution. Examples of these steps are polynomial background subtraction, aligning rows, deleting horizontal errors and sharpening. Our results show that while characteristic features of these false-color images may be shifted in terms of gray-channel and Hurst exponent, they can still be used to identify AFM images and, in the next step, to quantitatively describe AFM images of nanofibrous surfaces. Such a gray-channel approach can be regarded as a simple way to include some information about the 3D structure of the image.

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Estimation of spatial distribution and symmetry of textile materials using lacunarity

Cited by 3 publications

References 14 publications

Vision‐based probabilistic post‐earthquake loss estimation for reinforced concrete shear walls

Vision‐based probabilistic post‐earthquake loss estimation for reinforced concrete shear walls

Probabilistic Postearthquake ASCE 41-17 Compliant Performance Level Identification for Shear-Dominated RC Shear Walls via Crack Image Analysis

Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions

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