Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (2)

Search Parameters:
Keywords = random midpoint displacement method

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 4189 KB  
Article
Statistical Study of the Bias and Precision for Six Estimation Methods for the Fractal Dimension of Randomly Rough Surfaces
by Jorge Luis Flores Alarcón, Carlos Gabriel Figueroa, Víctor Hugo Jacobo, Fernando Velázquez Villegas and Rafael Schouwenaars
Fractal Fract. 2024, 8(3), 152; https://doi.org/10.3390/fractalfract8030152 - 7 Mar 2024
Cited by 6 | Viewed by 2407
Abstract
The simulation and characterisation of randomly rough surfaces is an important topic in surface science, tribology, geo- and planetary sciences, image analysis and optics. Extensions to general random processes with two continuous variables are straightforward. Several surface generation algorithms are available, and preference [...] Read more.
The simulation and characterisation of randomly rough surfaces is an important topic in surface science, tribology, geo- and planetary sciences, image analysis and optics. Extensions to general random processes with two continuous variables are straightforward. Several surface generation algorithms are available, and preference for one or another method often depends on the specific scientific field. The same holds for the methods to estimate the fractal dimension D. This work analyses six algorithms for the determination of D as a function of the size of the domain, variance, and the input value for D, using surfaces generated by Fourier filtering techniques and the random midpoint displacement algorithm. Several of the methods to determine fractal dimension are needlessly complex and severely biased, whereas simple and computationally efficient methods produce better results. A fine-tuned analysis of the power spectral density is very precise and shows how the different surface generation algorithms deviate from ideal fractal behaviour. For large datasets defined on equidistant two-dimensional grids, it is clearly the most sensitive and precise method to determine fractal dimension. Full article
(This article belongs to the Special Issue Fractal Analysis and Its Applications in Geophysical Science)
Show Figures

Figure 1

12 pages, 2830 KB  
Article
Development of a New Method for the Quantitative Generation of an Artificial Joint Specimen with Specific Geometric Properties
by Seungbeom Choi, Sudeuk Lee, Hoyoung Jeong and Seokwon Jeon
Sustainability 2019, 11(2), 373; https://doi.org/10.3390/su11020373 - 12 Jan 2019
Cited by 3 | Viewed by 3775
Abstract
A rock joint is a planar discontinuity that has significant influence on the mechanical and hydraulic characteristics of rock mass. Laboratory experiments are often conducted on a joint to investigate and provide fundamental information for rock mass analysis. Although joint roughness and mechanical [...] Read more.
A rock joint is a planar discontinuity that has significant influence on the mechanical and hydraulic characteristics of rock mass. Laboratory experiments are often conducted on a joint to investigate and provide fundamental information for rock mass analysis. Although joint roughness and mechanical aperture exert great effects on the experimental results, controlling them in quantitative manner is quite complicated and consumptive in terms of specimen preparation. A new and simple method for the quantitative generation of the joint specimen was proposed in this study. Based on random midpoint displacement method, a joint specimen with a void space inside was generated. Parametric studies for the roughness and mechanical aperture were carried out, and as a result, the two joint properties could be controlled by manipulating input parameters of random midpoint displacement method. In order to validate the proposed method, two joint specimens, which had different levels of roughness and aperture, were generated and printed. Surface coordinates of the specimens were obtained by a 3D laser scanner, and calculated to make a comparison between the target values and the estimated values. Results showed that the method was capable of generating joint specimens with satisfactory precision. Full article
Show Figures

Figure 1

Back to TopTop