Fractal Modeling of Natural Terrain: Analysis and Surface Reconstruction with Range Data

Arakawa, Kaoru; Krotkov, Eric

doi:10.1006/gmip.1996.0035

Cited by 24 publications

(10 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The primary intention of using such a numerically-constructed rough surface is to demonstrate the ability of the developed preprocessing algorithm to design a relevant boundary condition (in 3-D), for the simulation of fracture cementation process. In past years, efficient algorithms have been developed to generate realistic surfaces (Lewis (1987); Arakawa and Krotkov (1996)). However, a detailed comparison of such algorithms merit a separate discussion which in all certainties, is neither the focus nor the highlight of the present work.…”

Section: Numerical Aspectsmentioning

confidence: 99%

Phase ‐ field Modeling of Fracture Cementation Processes in 3 ‐ D

Ankit¹,

Selzer²,

Hilgers³

et al. 2015

JPSR

View full text Add to dashboard Cite

Numerical simulations of fracture cementation contribute to a better understanding of processes involved in their formation and possess the potential to provide valuable insights into the rock deformation history and fluid flow pathways. In this study, the influence of an algorithmically generated fracture surface is investigated, which opens-up temporally along a curved trajectory, on the cement mineralization in 3-D. By adopting a thermodynamically consistent and numerically efficient phasefield approach, the benefits of accounting for an extra third dimensionality are explained. The 3-D simulation results are supplemented by innovative numerical post-processing and advanced visualization techniques. The new methodologies to measure the tracking efficiency of fracture cements reflect the incremental fracture opening and demonstrate the importance of accounting the temporal evolution of grains in 3-D; no such information is usually accessible in field studies and difficult to obtain from laboratory experiments. The grain growth statistics obtained by numerically post-processing the 3-D computational microstructures show that cement's grain boundaries and multi-junctions are preferentially arrested at fracture peaks, thereby, enhancing the tracking behavior of syntectonic rock microstructures. By analyzing the temporal evolution of the numerically simulated microstructure, it is found that the grain multi-junctions are pinned more strongly at the peaks on the fractured surface, as compared to the grain boundaries.

show abstract

Section: Numerical Aspectsmentioning

confidence: 99%

Phase ‐ field Modeling of Fracture Cementation Processes in 3 ‐ D

Ankit¹,

Selzer²,

Hilgers³

et al. 2015

JPSR

View full text Add to dashboard Cite

show abstract

“…For terrain synthesis, Arakawa and Krotkov [5] worked on surface reconstruction with range data; range data refers to natural terrain patterns acquired by a laser rangefinder. They initially estimated the fractal dimension of natural surfaces given range data and then reconstructed natural surfaces using this estimate and the given sparse range data.…”

Section: Image-based Terrain Synthesis Methodsmentioning

confidence: 99%

Feature-rich distance-based terrain synthesis

2009

View full text Add to dashboard Cite

This thesis describes a novel terrain synthesis method based on distances in a weighted graph.The method begins with a regular lattice with arbitrary edge weights; heights are determined by path cost from a set of generator nodes. The shapes of individual terrain features, such as mountains, hills, and craters, are specified by a monotonically decreasing profile describing the cross-sectional shape of a feature, while the locations of features in the terrain are specified by placing the generators. Pathing places ridges whose initial location have a dendritic shape. The method is robust and easy to control, making it possible to create pareidolia effects. It can produce a wide range of realistic synthetic terrains such as mountain ranges, craters, faults, cinder cones, and hills. The algorithm incorporates random graph edge weights, permits the inclusion of multiple topography profiles, and allows precise control over placement of terrain features and their heights.These properties all allow the artist to create highly heterogeneous terrains that compare quite favorably to existing methods.ii

show abstract

“…With regard to self-similar models, as discussed here, there are methods that allow us to find the H parameter from a natural terrain [16]. With the calculation of the grounding resistance of a specific electrode from a flat soil surface, the actual resistance to be measured in the real terrain with a given maximum unevenness will have a confidence interval given by Equation (12) when the non-flat soil surface is considered as the only source of variability for the grounding resistance.…”

Section: Stochastic Model For the Grounding Resistancementioning

confidence: 99%

An Estimate of the Uncertainty in the Grounding Resistance of Electrodes Buried in Two-Layered Soils with Non-Flat Surface

2017

View full text Add to dashboard Cite

Abstract:The influence of the irregular surface of a multi-layered soil on the estimation of the ground resistance of a complex electrode is studied. The electrode is placed in the first layer while the irregular surface is treated as the interface of an inhomogeneous volume filled with air and embedded in the first layer. A wide sample of irregular soils is generated and the variation of the electrode grounding resistance, as a function of a parameter that measures the surface unevenness, is evaluated. A stochastic model of the grounding resistance is proposed for which the variation of the electrode grounding resistance with its horizontal position relative to the surface is studied. The model features allow us to explain the variability found, as we are able to estimate the part of the uncertainty about the electrode grounding resistance measurements due to the non-planar soil surface.

show abstract

Fractal Modeling of Natural Terrain: Analysis and Surface Reconstruction with Range Data

Cited by 24 publications

References 29 publications

Phase ‐ field Modeling of Fracture Cementation Processes in 3 ‐ D

Phase ‐ field Modeling of Fracture Cementation Processes in 3 ‐ D

Feature-rich distance-based terrain synthesis

An Estimate of the Uncertainty in the Grounding Resistance of Electrodes Buried in Two-Layered Soils with Non-Flat Surface

Contact Info

Product

Resources

About