scholarly journals TBRs, a methodology for the multi-scalar cartographic analysis of the distribution of plant formations

2020 ◽  
Author(s):  
Rafael Cámara Artigas ◽  
Fernando Díaz del Olmo ◽  
Jose Ramon Martinez Batlle
Keyword(s):  
Water Balance ◽  
Distribution Map ◽  
Biomass Distribution ◽  
Micro Scale ◽  
Multi Scale ◽  
Macro Scale ◽  
Bioclimatic Variables ◽  
Different Levels ◽  
Meso Scale ◽  
Scale Classification

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.

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 106 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

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.

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

2018 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

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.

Multi-scale density detection for yarn-dyed fabrics with deformed repeat patterns

2016 ◽  
Vol 87 (20) ◽  
pp. 2524-2540 ◽  
Author(s):  
Dejun Zheng ◽  
Lingheng Wang
Keyword(s):  
Computation Time ◽  
Registration Method ◽  
Decomposition Approach ◽  
Micro Scale ◽  
Detection Model ◽  
Multi Scale ◽  
Fabric Density ◽  
Macro Scale ◽  
Dyed Fabrics ◽  
Dyed Fabric

A new method combining the characteristics of macro-scale texture repeat patterns and micro-scale interwoven yarns of fabric images was proposed for yarn-dyed fabric density detection. The method was formulated in a research framework of multi-scale image processing and analysis. Firstly, a structure–texture decomposition approach was used to extract texture information and woven pattern details from the macro-scale fabric image. Secondly, a texture unit detection model was proposed to extract the texture units and to detect the yarn skewness in these texture units. Thirdly, a simple yet effective image registration method and a lightness gradient projection method were adopted to analyze the micro-scale fabric image and obtain the yarn locations in a texture unit. Finally, the average fabric density was calculated by coupling the near-regular features of texture units and yarn locations. The experiments showed that the proposed method was effective in detecting hundreds of yarns in the fabric samples and the computation time was very reasonable.

Modeling transverse micro flow in dry fiber placement preforms

2019 ◽  
Vol 54 (13) ◽  
pp. 1691-1703
Author(s):  
Oliver Rimmel ◽  
David May
Keyword(s):  
Flow Behavior ◽  
Liquid Composite Molding ◽  
Textile Materials ◽  
Micro Scale ◽  
Fiber Placement ◽  
Macro Scale ◽  
Out Of Plane ◽  
Numerical Solver ◽  
Analytical Approaches ◽  
Meso Scale

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.

Multi-Scale Stereolithography Using Shaped Beams

2017 ◽  
Author(s):  
Huachao Mao ◽  
Yuen-Shan Leung ◽  
Yuanrui Li ◽  
Pan Hu ◽  
Wei Wu ◽  
...  
Keyword(s):  
Laser Beam ◽  
Tool Path ◽  
Three Dimensional ◽  
Laser Exposure ◽  
Micro Scale ◽  
Multi Scale ◽  
Good Surface ◽  
Single Scale ◽  
Macro Scale ◽  
Micro Patterns

Current Stereolithography (SL) can fabricate three-dimensional (3D) objects in a single scale level, e.g. printing macro-scale or micro-scale objects. However, it is difficult for the SL printers to fabricate a 3D macro-scale object with micro-scale features. In the paper a novel SL-based multi-scale fabrication method is presented to address such a problem. The developed SL process can fabricate multi-scale features by dynamically changing the shape and size of a laser beam. Different shaped beams are realized by switching apertures with different micro-patterns. The laser beam without using any micro-patterns is used to fabricate the macro-scale features, while the shaped laser beams with smaller sizes are used to fabricate micro-patterned features. Accordingly, the tool path planning method for the multi-scale fabrication process are developed so that macro-scale and micro-scale features can be built by using different layer thicknesses, laser exposure time, and scanning paths. Compared with the conventional SL process based on a fixed laser beam size, our process can fabricate multi-scale features in a 3D object. It also has fast fabrication speed and good surface quality.

Application of an EMMS Model for Bubbly Fluidized Bed

2017 ◽  
Vol 372 ◽  
pp. 170-179
Author(s):  
Daniel A. Kestering ◽  
Flavia F.S. Zinani ◽  
George C. Bleyer
Keyword(s):  
Multi Scale ◽  
Macro Scale ◽  
Scale Models ◽  
Fluid Bed ◽  
Computational Fluid Dynamics Cfd ◽  
Geldart Groups ◽  
Coarse Grids ◽  
Individual Particles ◽  
Meso Scale ◽  
Good Agreement

In computational fluid dynamics (CFD) of fluidization processes, the modeling of drag between fluid and particles has a direct effect on the results. The EMMS (Energy Minimization Multi-Scale) models are based on the micro-scale of individual particles and the macro scale of equipment to model the meso-scale phenomena related to particle clustering, which directly affect the drag between fluid and particles. The EMMS/bubbling model was introduced as a change from the classic EMMS model to specific bubbling fluid bed conditions. The present work aims to apply the EMMS/bubbling model in the CFD of Geldart-D particles fluidized by air. The results were compared with results from the literature. It was observed that, for particles of Geldart groups A and B, the results using the EMMS/bubbling model agreed well with the literature. The CFD results for Geldart-D particles showed good agreement with the literature results for this method using coarse grids.

scholarly journals Bayesian stochastic multi-scale analysis via energy considerations

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Muhammad S. Sarfaraz ◽  
Bojana V. Rosić ◽  
Hermann G. Matthies ◽  
Adnan Ibrahimbegović
Keyword(s):  
Nonlinear Approximation ◽  
Computational Cost ◽  
Cementitious Materials ◽  
Model Errors ◽  
Stored Energy ◽  
Standard Material ◽  
Multi Scale ◽  
Macro Scale ◽  
Optimal Material ◽  
Meso Scale

AbstractMulti-scale processes governed on each scale by separate principles for evolution or equilibrium are coupled by matching the stored energy and dissipation in line with the Hill-Mandel principle. We are interested in cementitious materials, and consider here the macro- and meso-scale behaviour of such a material. The accurate representations of stored energy and dissipation are essential for the depiction of irreversible material behaviour, and here a Bayesian approach is used to match these quantities on different scales. This is a probabilistic upscaling and as such allows to capture, among other things, the loss of resolution due to scale coarsening, possible model errors, localisation effects, and the geometric and material randomness of the meso-scale constituents in the upscaling. On the coarser (macro) scale, optimal material parameters are estimated probabilistically for certain possible behaviours from the class of generalised standard material models by employing a nonlinear approximation of Bayes’s rule. To reduce the overall computational cost, a model reduction of the meso-scale simulation is achieved by combining unsupervised learning techniques based on a Bayesian copula variational inference with functional approximation forms.

Finite Element Modeling of Multi-Scale Thermal Contact Resistance

2008 ◽  
Author(s):  
M. K. Thompson
Keyword(s):  
Finite Element ◽  
Contact Resistance ◽  
Thermal Contact Resistance ◽  
Unit Area ◽  
Thermal Contact ◽  
Contact Model ◽  
Micro Scale ◽  
Multi Scale ◽  
Macro Scale ◽  
Scale Surface

Many traditional macro scale finite element models of thermal contact systems have incorporated the effect of micro scale surface topography by applying a constant value of thermal contact conductance (TCC) per unit area to the regions in contact. However, it has been very difficult to determine an appropriate TCC value for a given system and analysts typically had to rely on experimental data or values from the literature. This work presents a method for predicting micro scale TCC per unit area by incorporating micro scale surface roughness in a multi-scale iterative thermal/structural finite element contact model. The resulting TCC value is then used in a macro scale thermal/structural contact model with apparent surface form to predict the thermal contact resistance and overall thermal resistance for a commercial power electronics module.

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