A Three-Level Approach to Texture Mapping and Synthesis on 3D Surfaces

Author(s):  
Kersten Schuster ◽  
Philip Trettner ◽  
Patric Schmitz ◽  
Leif Kobbelt

We present a method for example-based texturing of triangular 3D meshes. Our algorithm maps a small 2D texture sample onto objects of arbitrary size in a seamless fashion, with no visible repetitions and low overall distortion. It requires minimal user interaction and can be applied to complex, multi-layered input materials that are not required to be tileable. Our framework integrates a patch-based approach with per-pixel compositing. To minimize visual artifacts, we run a three-level optimization that starts with a rigid alignment of texture patches (macro scale), then continues with non-rigid adjustments (meso scale) and finally performs pixel-level texture blending (micro scale). We demonstrate that the relevance of the three levels depends on the texture content and type (stochastic, structured, or anisotropic textures).

2019 ◽  
Vol 54 (13) ◽  
pp. 1691-1703
Author(s):  
Oliver Rimmel ◽  
David May

Dry fiber placement has a large potential for manufacturing preforms for primary-load components at minimum scrap rate and fiber crimp. Yet, challenging impregnation behavior due to low permeability of these preforms during liquid composite molding imposes a need for further research to optimize preform structure for higher permeability. For full understanding of flow behavior within these preforms, flow has to be considered on micro scale (in between single fibers), on meso scale (in between single rovings or strands), and on macro scale (on scale of parts to be manufactured). While macro and meso scale can be measured in experiments or derived from filling times in real processes, micro scale is usually not easily assessable and accessible for standard textile materials. Analytical approaches are limited to regular fiber arrangements (square and hexagonal) that are strongly differing from real arrangements. The present work deals with application of a numerical solver to random fiber arrangements to determine micro permeability transverse to the fiber orientation, for later use in meso- and macro-scaled models. As a premise for reliable calculation, guidelines for boundary conditions as well as size and resolution of the representative volume element are elaborated in the course of this work. Calculated out-of-plane micro permeabilities are subsequently compared to real experiments and show good accordance. The influence of binder particles on micro permeability has not yet been conclusively clarified.


AIChE Journal ◽  
2016 ◽  
Vol 63 (2) ◽  
pp. 501-516 ◽  
Author(s):  
Berend van Wachem ◽  
Kyrre Thalberg ◽  
Johan Remmelgas ◽  
Ingela Niklasson-Björn

Author(s):  
Rafael Cámara Artigas ◽  
Fernando Díaz del Olmo ◽  
Jose Ramon Martinez Batlle

An analytical and cartographic method of biomass distribution and plant formations at a multi-scalar level is developed based on bioclimatic variables extracted from the Thornthwaite Water Balance (WB) and the Bioclimatic Balances (BB) of Montero de Burgos & González Rebollar. As a result, a distribution map involving Types of Bioclimatic Regimens (TBR) is obtained leading to the identification of a multi-scale classification at different levels: zonal (macro-scale) with 5 types, regional (meso-scale) with 27 types, and local (micro-scale) with 162 plant formations subtypes, conditioned by lithology-soils, the relief exposure to wind or sunstroke respectively and obtained through the combination of TBR and ombroclimates.


Author(s):  
Konstantinos Tserpes ◽  
Christos Kora

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. FE models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS PDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.


Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 106 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. Numerical models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS APDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.


Pedagogika ◽  
2013 ◽  
Vol 112 (4) ◽  
pp. 140-147
Author(s):  
Ewa Jurczyk - Romanowska

The purpose of the present paper is to compare three levels of discourse on the subject of the 21st century family. The macro scale is represented by the ideas of the International Year of the Family + 20, the meso scale – by the postulates of the government of Poland aimed at the implementation of international presumptions in Poland. The reality experienced by single parents and its inherent evaluation of the realization of the government’s postulates constitutes the micro scale. Comparison of the three perspectives allows for a discernment of the shortcomings of the government’s postulates as well as the somewhat superficial character of the undertaken actions.


2015 ◽  
Author(s):  
Naresh Thadhani ◽  
Arun Gokhale ◽  
Jason Quenneville ◽  
Jennifer Breidenich ◽  
Manny Gonzales ◽  
...  

Author(s):  
Feng Li ◽  
Gulnigar Ablat ◽  
Siqi Zhou ◽  
Yixin Liu ◽  
Yufeng Bi ◽  
...  

AbstractIn ice and snow weather, the surface texture characteristics of asphalt pavement change, which will significantly affect the skid resistance performance of asphalt pavement. In this study, five asphalt mixture types of AC-5, AC-13, AC-16, SMA-13, SMA-16 were prepared under three conditions of the original state, ice and snow. In this paper, a 2D-wavelet transform approach is proposed to characterize the micro and macro texture of pavement. The Normalized Energy (NE) is proposed to describe the pavement texture quantitatively. Compared with the mean texture depth (MTD), NE has the advantages of full coverage, full automation and wide analytical scale. The results show that snow increases the micro-scale texture because of its fluffiness, while the formation of the ice sheets on the surface reduces the micro-scale texture. The filling effect of snow and ice reduces the macro-scale texture of the pavement surface. In a follow-up study, the 2D-wavelet transform approach can be applied to improve the intelligent driving braking system, which can provide pavement texture information for the safe braking strategy of driverless vehicles.


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