scholarly journals MULTI-SCALE AND SCALE DIMENSION PROPERTIES IN SPATIAL RASTER MODELLING – CONCEPT AND CURRENT IMPLEMENTATION

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 339-345
Author(s):  
H. Karim ◽  
A. Abdul Rahman ◽  
M. R. Mohd Salleh
Keyword(s):  
Data Model ◽  
Semantic Information ◽  
Vector Model ◽  
Scale Model ◽  
Successful Implementation ◽  
Data Types ◽  
Raster Data ◽  
Multi Scale ◽  
Current Implementation ◽  
Scale Modelling

Abstract. Various users and applications required different abstraction details of spatial model either in vector or/and raster data types/models. Generating different model abstraction details (e.g. Level of Detail/LOD) produces various drawbacks especially for data model sharing among stakeholders or publics. Different abstraction detail or LOD means different details in geometry, semantic information, attributes as well as different accuracy provided within the vector model (e.g. a certain LOD). On the other hand, raster dataset with different resolutions on certain information or layer (e.g. elevation, land cover, spatial imagery, soil type, thematic raster map and others) could also be considered as multi-scale raster modelling which produces similar drawbacks with additional storage redundancy/consumption and updating works. There are some solutions for vector scale modelling such as CityGML (3D) and multi-scale or vario-scale (2D) modelling induce good solutions for vector; however, there are no solution for raster data type (or model) yet. Thus, a concept description in categorizing and defining multi-scale for multi-resolution raster dataset should be introduced. This paper basically highlights the similarity of spatial 2D vector and raster type GIS dataset, some introduction and properties of raster dataset which able to be defined it as the same level of vector LoD in scale modelling. This paper basically tries to kick off a new multi-scale domain in supporting spatial raster dataset (new idea), which will be then be extend/expand by related researchers near the future. Discussion on successful implementation of vector multi-scale model will be in the paper as well as existing multi-scale approach in storing raster dataset as the main content of the paper. Some potential analysis on related multi-scale raster and validation are also discussed to give brief idea on what is spatial raster capable of; especially to those who are new/not yet engage with this multi-scale spatial raster dataset.

Techniques and Methods of Spatial Data Fusion

2012 ◽  
Vol 263-266 ◽  
pp. 3274-3278
Author(s):  
Hui Ming Yu ◽  
Jian Zhong Guo ◽  
Yi Cheng ◽  
Qian Lou
Keyword(s):  
Data Fusion ◽  
Information Fusion ◽  
Spatial Data ◽  
Data Model ◽  
Semantic Information ◽  
Utilization Efficiency ◽  
Vector Data ◽  
Raster Data ◽  
Information Precision ◽  
Spatial Data Integration

Spatial data fusion is an important method of spatial data acquisition. The aim of multisource spatial data integration and fusion is to improve the information precision and information's utilization efficiency. Vector and raster are the two main spatial data structures. This article discusses vector data fusion from of data model fusion, semantic information fusion and coordinates unification, reviews the main methods of raster data fusion and discusses the key technologies of vector and raster data fusion, and proposes the future developments of spatial data fusion technique.

Multi-Scale Control of Bunsen Section in Iodine-Sulphur Thermochemical Cycle Process

2017 ◽  
Vol 12 (4) ◽  
Author(s):  
Noraini Mohd ◽  
Jobrun Nandong
Keyword(s):  
Hydrogen Production ◽  
Control Strategy ◽  
Sensitivity Study ◽  
Scale Model ◽  
Thermochemical Cycle ◽  
Worst Case ◽  
Multi Scale ◽  
Scale Modelling ◽  
Surface Analysis Method ◽  
Scale Control

AbstractHydrogen is considered as an environmental friendly energy carrier but its actual impact on the environment depends on the way it is produced. A strategy of plant-wide modelling and advanced process control with optimization is currently developed for the Hydrogen production via the Iodine-Sulphur thermochemical cycle process. The objectives of this paper are two-folds: (1) to optimize the trade-off between steady-state profitability and dynamic operability of the Bunsen section subject to multiple constraints, and (2) to design practical control strategy based on the multi-scale control concept. A multi-scale modelling for the Bunsen section in the Hydrogen production via the Iodine-Sulphur thermochemical cycle process is presented. Based on this multi-scale model, a practical control design is developed and applied to Bunsen section. The suitable sets of control variables and manipulated variables are chosen via a sensitivity study incorporating the multivariate Response Surface Analysis method. By dint of simulation study, it can be shown that the proposed control strategy is able to produce a good closed-loop performance where its robustness depends strongly on the selected schemes of Bunsen section. It is worth highlighting that, the proposed multi-scale control strategy demonstrates robust performance in the face of the worst case uncertainty scenario.

scholarly journals A framework for multi-scale modelling

2014 ◽  
Vol 372 (2021) ◽  
pp. 20130378 ◽  
Author(s):  
B. Chopard ◽  
Joris Borgdorff ◽  
A. G. Hoekstra
Keyword(s):  
Numerical Simulations ◽  
Science And Technology ◽  
Scale Model ◽  
Computer Implementation ◽  
Modelling Language ◽  
Scale Separation ◽  
Multi Scale ◽  
Single Scale ◽  
Scale Modelling ◽  
Definition Of

We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology.

scholarly journals Multi-scale damage modelling in a ceramic matrix composite using a finite-element microstructure meshfree methodology

2016 ◽  
Vol 374 (2071) ◽  
pp. 20150276 ◽  
Author(s):  
L. Saucedo-Mora ◽  
T. J. Marrow
Keyword(s):  
Finite Element ◽  
Structural Integrity ◽  
Ceramic Matrix Composite ◽  
Scale Model ◽  
Damage Development ◽  
Component Level ◽  
Composite Tube ◽  
Multi Scale ◽  
Load Carrying ◽  
Scale Modelling

The problem of multi-scale modelling of damage development in a SiC ceramic fibre-reinforced SiC matrix ceramic composite tube is addressed, with the objective of demonstrating the ability of the finite-element microstructure meshfree (FEMME) model to introduce important aspects of the microstructure into a larger scale model of the component. These are particularly the location, orientation and geometry of significant porosity and the load-carrying capability and quasi-brittle failure behaviour of the fibre tows. The FEMME model uses finite-element and cellular automata layers, connected by a meshfree layer, to efficiently couple the damage in the microstructure with the strain field at the component level. Comparison is made with experimental observations of damage development in an axially loaded composite tube, studied by X-ray computed tomography and digital volume correlation. Recommendations are made for further development of the model to achieve greater fidelity to the microstructure. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’.

Interfacial and Strain Energy Analysis from Ab Initio Based Hierarchical Multi-Scale Modelling: The Al-Mg-Si Alloy β'' Phase

2014 ◽  
Vol 794-796 ◽  
pp. 640-645 ◽  
Author(s):  
Flemming J.H. Ehlers ◽  
Stéphane Dumoulin ◽  
Knut Marthinsen ◽  
Randi Holmestad
Keyword(s):  
Density Functional ◽  
Accurate Determination ◽  
Test System ◽  
Host Lattice ◽  
Scale Model ◽  
Linear Elasticity Theory ◽  
Multi Scale ◽  
Β Phase ◽  
Scale Modelling ◽  
Model Scheme

Precipitate-host lattice interface studies have not traditionally been viewed as requiring hybrid model schemes for accurate determination of the interfacial and strain energies. On the other hand, the interfaces of main hardening precipitates of age hardenable alloys are often characterized by both high levels of coherency and considerable subsystem misfits. Near the interface, linear elasticity theory evidently fails in such cases to fully correctly predict the subsystem strains. Further, density functional theory based studies on isolated supercells may prove inadequate in capturing strain influences on the chemical interactions underlying the interfacial energy. Recent work within the group has focussed on the implementation of a first principles based hierarchical multi-scale model scheme, capable of determining the interfacial and strain energies for thesamemodel system. Choosing the fully coherent Al-Mg-Si alloy main hardening phase β'' as our test system and limiting our studies to 2D, we discuss the variation in these energies with changing precipitate cross-section morphology and size.

Three-dimensional Reconstruction of Microscopic Image Based on Multi-ST Algorithm

2020 ◽  
Vol 64 (2) ◽  
pp. 20506-1-20506-7
Author(s):  
Min Zhu ◽  
Rongfu Zhang ◽  
Pei Ma ◽  
Xuedian Zhang ◽  
Qi Guo
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Scale Model ◽  
Microscopic Image ◽  
Multi Scale ◽  
Gaussian Pyramid ◽  
Cost Aggregation ◽  
Dimensional Reconstruction ◽  
Image Pairs ◽  
Accurate Matching

Abstract Three-dimensional (3D) reconstruction is extensively used in microscopic applications. Reducing excessive error points and achieving accurate matching of weak texture regions have been the classical challenges for 3D microscopic vision. A Multi-ST algorithm was proposed to improve matching accuracy. The process is performed in two main stages: scaled microscopic images and regularized cost aggregation. First, microscopic image pairs with different scales were extracted according to the Gaussian pyramid criterion. Second, a novel cost aggregation approach based on the regularized multi-scale model was implemented into all scales to obtain the final cost. To evaluate the performances of the proposed Multi-ST algorithm and compare different algorithms, seven groups of images from the Middlebury dataset and four groups of experimental images obtained by a binocular microscopic system were analyzed. Disparity maps and reconstruction maps generated by the proposed approach contained more information and fewer outliers or artifacts. Furthermore, 3D reconstruction of the plug gauges using the Multi-ST algorithm showed that the error was less than 0.025 mm.

Effects of parametric uncertainty on multi-scale model predictions of shock response of a pressed energetic material

2019 ◽  
Vol 125 (23) ◽  
pp. 235104 ◽  
Author(s):  
Sangyup Lee ◽  
Oishik Sen ◽  
Nirmal Kumar Rai ◽  
Nicholas J. Gaul ◽  
K. K. Choi ◽  
...  
Keyword(s):  
Energetic Material ◽  
Parametric Uncertainty ◽  
Scale Model ◽  
Multi Scale ◽  
Model Predictions ◽  
Shock Response

Multi-scale modelling of woven carbon fibre reinforced epoxy

2021 ◽  
Author(s):  
Alexandru Szabo ◽  
Radu Negru ◽  
Alexandru-Viorel Coşa ◽  
Liviu Marşavina ◽  
Dan-Andrei Şerban
Keyword(s):  
Carbon Fibre ◽  
Multi Scale ◽  
Scale Modelling

scholarly journals The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2454
Author(s):  
Yue Sun ◽  
Yanze Yu ◽  
Jinhao Guo ◽  
Minghai Zhang
Keyword(s):  
Habitat Selection ◽  
Environmental Factors ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Scale Model ◽  
Winter Habitat ◽  
Multi Scale ◽  
Optimal Scale ◽  
Scale Models ◽  
Selection Of

Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to assess habitat selection. The results showed that: (1) Univariate logistic regression analysis showed that the response scale of red deer to environmental factors was different among different covariate. The optimal scale of the single covariate was 800–3200 m, slope (SLP), altitude (ELE), and ratio of deciduous broad-leaved forests were 800 m in large scale, except that the farmland ratio was 200 m in fine scale. The optimal scale of road density and grassland ratio is both 1600 m, and the optimal scale of net forest production capacity is 3200 m; (2) distance to forest edges, distance to cement roads, distance to villages, altitude, distance to all road, and slope of the region were the most important factors affecting winter habitat selection. The outcomes of this study indicate that future studies on the effectiveness of habitat selections will benefit from multi-scale models. In addition to increasing interpretive and predictive capabilities, multi-scale habitat selection models enhance our understanding of how species respond to their environments and contribute to the formulation of effective conservation and management strategies for ungulata.

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