Application of Fractal Geometry to Fracture Forensics, Research and Production

2006 ◽  
Vol 45 ◽  
pp. 1646-1651 ◽  
Author(s):  
J.J. Mecholsky Jr.
Keyword(s):  
Fractal Analysis ◽  
Fractal Geometry ◽  
Crack Size ◽  
Structural Parameter ◽  
New Materials ◽  
Scale Invariant ◽  
Prepared Material ◽  
Reasonable Approach ◽  
Self Similar ◽  
Production Problems

The fracture surface records past events that occur during the fracture process by leaving characteristic markings. The application of fractal geometry aids in the interpretation and understanding of these events. Quantitative fractographic analysis of brittle fracture surfaces shows that these characteristic markings are self-similar and scale invariant, thus implying that fractal analysis is a reasonable approach to analyzing these surfaces. The fractal dimensional increment, D*, is directly proportional to the fracture energy, γ, during fracture for many brittle materials, i.e., γ = ½ E a0 D* where E is the elastic modulus and a0 is a structural parameter. Also, D* is equal to the crack-size-to-mirror-radius ratio. Using this information can aid in identifying toughening mechanisms in new materials, distinguishing poorly fabricated from well prepared material and identifying stress at fracture for field failures. Examples of the application of fractal analysis in research, fracture forensics and solving production problems are discussed.

A Fractal Analysis of Human Cranial Sutures

2003 ◽  
Vol 40 (4) ◽  
pp. 409-415 ◽  
Author(s):  
Jack C. Yu ◽  
Ronald L. Wright ◽  
Matthew A. Williamson ◽  
James P. Braselton ◽  
Martha L. Abell
Keyword(s):  
Fractal Analysis ◽  
Cranial Sutures ◽  
Box Dimension ◽  
Counting Method ◽  
Scale Invariant ◽  
Box Counting ◽  
Invariant Features ◽  
Iteration Functions ◽  
Self Similar ◽  
Box Counting Method

Objectives Many biological structures are products of repeated iteration functions. As such, they demonstrate characteristic, scale-invariant features. Fractal analysis of these features elucidates the mechanism of their formation. The objectives of this project were to determine whether human cranial sutures demonstrate self-similarity and measure their exponents of similarity (fractal dimensions). Design One hundred three documented human skulls from the Terry Collection of the Smithsonian Institution were used. Their sagittal sutures were digitized and the data converted to bitmap images for analysis using box-counting method of fractal software. Results The log-log plots of the number of boxes containing the sutural pattern, Nr, and the size of the boxes, r, were all linear, indicating that human sagittal sutures possess scale-invariant features and thus are fractals. The linear portion of these log-log plots has limits because of the finite resolution used for data acquisition. The mean box dimension, Db, was 1.29289 ± 0.078457 with a 95% confidence interval of 1.27634 to 1.30944. Conclusions Human sagittal sutures are self-similar and have a fractal dimension of 1.29 by the box-counting method. The significance of these findings includes: sutural morphogenesis can be described as a repeated iteration function, and mathematical models can be constructed to produce self-similar curves with such Db. This elucidates the mechanism of actual pattern formation. Whatever the mechanisms at the cellular and molecular levels, human sagittal suture follows the equation log Nr = 1.29 log 1/r, where Nr is the number of square boxes with sides r that are needed to contain the sutural pattern and r equals the length of the sides of the boxes.

Optimal Density Determination of Bouguer Anomaly Using Fractal Analysis (Case of study: Charak area,IRAN)

2005 ◽  
Vol 1 (1) ◽  
pp. 21-24
Author(s):  
Hamid Reza Samadi
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Host Rock ◽  
Bouguer Anomaly ◽  
Research Area ◽  
Density Difference ◽  
Optimal Density

In exploration geophysics the main and initial aim is to determine density of under-research goals which have certain density difference with the host rock. Therefore, we state a method in this paper to determine the density of bouguer plate, the so-called variogram method based on fractal geometry. This method is based on minimizing surface roughness of bouguer anomaly. The fractal dimension of surface has been used as surface roughness of bouguer anomaly. Using this method, the optimal density of Charak area insouth of Hormozgan province can be determined which is 2/7 g/cfor the under-research area. This determined density has been used to correct and investigate its results about the isostasy of the studied area and results well-coincided with the geology of the area and dug exploratory holes in the text area

Fractal analysis and control of the competition model

2016 ◽  
Vol 09 (03) ◽  
pp. 1650045 ◽  
Author(s):  
Mianmian Zhang ◽  
Yongping Zhang
Keyword(s):  
Feedback Control ◽  
Mathematical Models ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Julia Set ◽  
Julia Sets ◽  
Competition Model ◽  
Simulation Results ◽  
Population Competition ◽  
And Control

Lotka–Volterra population competition model plays an important role in mathematical models. In this paper, Julia set of the competition model is introduced by use of the ideas and methods of Julia set in fractal geometry. Then feedback control is taken on the Julia set of the model. And synchronization of two different Julia sets of the model with different parameters is discussed, which makes one Julia set change to be another. The simulation results show the efficacy of these methods.

scholarly journals On the fractal nature of complex syntax and the timescale problem

2020 ◽  
Vol 10 (4) ◽  
pp. 697-721
Author(s):  
D. Reid Evans
Keyword(s):  
Complex Systems ◽  
Dynamic Systems Theory ◽  
Self Similarity ◽  
Scale Invariant ◽  
Complex Dynamic Systems ◽  
Complex Syntax ◽  
Dynamic Relationship ◽  
Self Similar ◽  
Multiple Component ◽  
Dynamic Relationships

Fundamental to complex dynamic systems theory is the assumption that the recursive behavior of complex systems results in the generation of physical forms and dynamic processes that are self-similar and scale-invariant. Such fractal-like structures and the organismic benefit that they engender has been widely noted in physiology, biology, and medicine, yet discussions of the fractal-like nature of language have remained at the level of metaphor in applied linguistics. Motivated by the lack of empirical evidence supporting this assumption, the present study examines the extent to which the use and development of complex syntax in a learner of English as a second language demonstrate the characteristics of self-similarity and scale invariance at nested timescales. Findings suggest that the use and development of syntactic complexity are governed by fractal scaling as the dynamic relationship among the subconstructs of syntax maintain their complexity and variability across multiple temporal scales. Overall, fractal analysis appears to be a fruitful analytic tool when attempting to discern the dynamic relationships among the multiple component parts of complex systems as they interact over time.

Fractal Geometry as a Bridge between Realms

2013 ◽  
pp. 25-43 ◽  
Author(s):  
Terry Marks-Tarlow
Keyword(s):  
Fractal Geometry ◽  
Open Systems ◽  
Autonomous Systems ◽  
Mathematical Notation ◽  
Deep Space ◽  
The Unconscious ◽  
Self And Other ◽  
Branching Structures ◽  
Self Similar ◽  
Multidimensional Objects

This chapter describes fractal geometry as a bridge between the imaginary and the real, mind and matter, conscious and the unconscious. Fractals are multidimensional objects with self-similar detail across size and/or time scales. Jung conceived of number as the most primitive archetype of order, serving to link observers with the observed. Whereas Jung focused upon natural numbers as the foundation for order that is already conscious in the observer, I offer up the fractal geometry as the underpinnings for a dynamic unconscious destined never to become fully conscious. Throughout nature, fractals model the complex, recursively branching structures of self-organizing systems. When they serve at the edges of open systems, fractal boundaries articulate a paradoxical zone that simultaneously separates as it connects. When modeled by Spencer-Brown’s mathematical notation, full interpenetration between inside and outside edges translates to a distinction that leads to no distinction. By occupying the infinitely deep “space between” dimensions and levels of existence, fractal boundaries contribute to the notion of intersubjectivity, where self and other become most entwined. They also exemplify reentry dynamics of Varela’s autonomous systems, plus Hofstadter’s ever-elusive “tangled hierarchy” between brain and mind.

Fractal analysis of a new generation of HVOF sprayed coatings based on optical surface metrology

2016 ◽  
Vol 83 (6) ◽  
Author(s):  
Yibo Zou ◽  
Markus Kästner ◽  
Eduard Reithmeier
Keyword(s):  
Fractal Dimension ◽  
Fractal Analysis ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Confocal Laser Scanning Microscope ◽  
Confocal Laser ◽  
Surface Metrology ◽  
Roughness Parameters ◽  
Scale Invariant ◽  
Sprayed Coatings

AbstractIn this article, fractal analysis combined with roughness measurement is proposed to characterize the new generations of HVOF sprayed coatings' surface textures. Two-dimensional and three-dimensional box counting algorithms are introduced to determine the fractal dimension, which is considered as a scale-invariant parameter and is able to describe chaos and complexity of the surface. For surface roughness metrology, a confocal laser scanning microscope with different lenses is used to acquire the areal topography, providing a sequence of height maps with different image resolutions. Typical areal roughness parameters are assessed based on the international standard ISO-25178. The results show that the fractal dimension is a powerful tool to depict the nature of the surface texture of the investigated coatings. Moreover, it is found that the traditional amplitude roughness parameters depend strongly on the range of the measurement field as well as the datasets' resolution, whereas the fractal dimension is rather invariant to the scales of the measured datasets. Finally, the correlation between the fractal dimension and roughness parameters is given at the end of this paper.

Breaking waves and the equilibrium range of wind-wave spectra

1997 ◽  
Vol 342 ◽  
pp. 377-401 ◽  
Author(s):  
S. E. BELCHER ◽  
J. C. VASSILICOS
Keyword(s):  
High Frequency ◽  
Wind Wave ◽  
Breaking Waves ◽  
Breaking Wave ◽  
Wave Spectra ◽  
Scale Invariant ◽  
Self Similar ◽  
Dynamical Properties ◽  
Dynamical Balance ◽  
Equilibrium Range

When scaled properly, the high-wavenumber and high-frequency parts of wind-wave spectra collapse onto universal curves. This collapse has been attributed to a dynamical balance and so these parts of the spectra have been called the equilibrium range. We develop a model for this equilibrium range based on kinematical and dynamical properties of breaking waves. Data suggest that breaking waves have high curvature at their crests, and they are modelled here as waves with discontinuous slope at their crests. Spectra are then dominated by these singularities in slope. The equilibrium range is assumed to be scale invariant, meaning that there is no privileged lengthscale. This assumption implies that: (i) the sharp-crested breaking waves have self-similar shapes, so that large breaking waves are magnified copies of the smaller breaking waves; and (ii) statistical properties of breaking waves, such as the average total length of breaking-wave fronts of a given scale, vary with the scale of the breaking waves as a power law, parameterized here with exponent D.

Similarity Hashing: A Computer Vision Solution to the Inverse Problem of Linear Fractals

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 39-50 ◽  
Author(s):  
John C. Hart ◽  
Wayne O. Cochran ◽  
Patrick J. Flynn
Keyword(s):  
Computer Vision ◽  
Inverse Problem ◽  
Heuristic Search ◽  
Fractal Geometry ◽  
Self Similarity ◽  
Geometric Hashing ◽  
Numerical Minimization ◽  
Self Similar ◽  
Vision Algorithm ◽  
Fractal Representation

The difficult task of finding a fractal representation of an input shape is called the inverse, problem of fractal geometry. Previous attempts at solving this problem have applied techniques from numerical minimization, heuristic search and image compression. The most appropriate domain from which to attack this problem is not numerical analysis nor signal processing, but model-based computer vision. Self-similar objects cause an existing computer vision algorithm called geometric hashing to malfunction. Similarity hashing capitalizes on this observation to not only detect a shape's morphological self-similarity but also find the parameters of its self-transformations.

scholarly journals A family of singular functions and its relation to harmonic fractal analysis and fuzzy logic

2016 ◽  
Vol 14 (1) ◽  
pp. 1039-1052 ◽  
Author(s):  
Enrique de Amo ◽  
Manuel Díaz Carrillo ◽  
Juan Fernández-Sánchez
Keyword(s):  
Fuzzy Logic ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Hausdorff Dimensions ◽  
Singular Functions ◽  
Parameterized Family

AbstractWe study a parameterized family of singular functions which appears in a paper by H. Okamoto and M. Wunsch (2007). Various properties are revisited from the viewpoint of fractal geometry and probabilistic techniques. Hausdorff dimensions are calculated for several sets related to these functions, and new properties close to fractal analysis and strong negations are explored.

scholarly journals The Banach-Tarski Paradox Dictates Snyergistic Routes for Scale-Free Neurodynamics

2020 ◽  
Author(s):  
Arturo Tozzi ◽  
James F. Peters
Keyword(s):  
Information Transfer ◽  
Neural Dynamics ◽  
Free Oscillations ◽  
Scale Invariant ◽  
Brain Areas ◽  
Scale Free ◽  
Cortical Oscillations ◽  
The Central Nervous System ◽  
Self Similar ◽  
Physical Changes

Neuroscientists are able to detect physical changes in information entropy in available neurodata. However, the information paradigm is inadequate to fully describe nervous dynamics and mental activities such as perception. This paper provides an effort to build explanations to neural dynamics alternative to thermodynamic and information accounts. We recall the Banach–Tarski paradox (BTP), which informally states that, when pieces of a ball are moved and rotated without changing their shape, a synergy between two balls of the same volume is achieved instead of the original one. We show how and why BTP might display this physical and biological synergy meaningfully, making it possible to tackle nervous activities. The anatomical and functional structure of the central nervous system’s nodes and edges allows to perform a sequence of moves inside the connectome that doubles the amount of available cortical oscillations. In particular, a BTP-based mechanism permits scale-invariant nervous oscillations to amplify and propagate towards far apart brain areas. Paraphrasing the BPT’s definition, we could state that: when a few components of a self-similar nervous oscillation are moved and rotated throughout the cortical connectome, two self-similar oscillations are achieved instead of the original one. Furthermore, based on topological structures, we illustrate how, counterintuitively, the amplification of scale-free oscillations does not require information transfer.

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