Surface Orientation from Texture Autocorrelation

We report on a refinement of our technique for determining the orientation of a textured surface from the two-point autocorrelation function of its image. We replace our previous assumptions of isotropic texture by knowledge of the autocorrelation moment matrix of the texture when viewed head on. The orientation of a textured surface is then deduced from the effects of foreshortening on these autocorrelation moments. This technique is applied to natural images of planar textured surfaces and gives significantly improved results when applied to anisotropic textures which under the assumption of isotropy mimic the effects of projective foreshortening. The potential practicality of this method for higher level image understanding systems is discussed

Application of ASTAR/precession electron diffraction technique to quantitatively study defects in nanocrystalline metallic materials

Nanocrystalline metallic materials have the potential to exhibit outstanding performance which leads to their usage in challenging applications such as coatings and biomedical implant devices. To optimize the performance of nanocrystalline metallic materials according to the desired applications, it is important to have a decent understanding of the structure, processing and properties of these materials. Various efforts have been made to correlate microstructure and properties of nanocrystalline metallic materials. Based on these research activities, it is noticed that microstructure and defects (e.g., dislocations and grain boundaries) play a key role in the behavior of these materials. Therefore, it is of great importance to establish methods to quantitatively study microstructures, defects and their interactions in nanocrystalline metallic materials. Since the mechanisms controlling the properties of nanocrystalline metallic materials occur at a very small length scale, it is fairly difficult to study them. Unfortunately, most of the characterization techniques used to explore these materials do not have the high enough spatial resolution required for the characterization of these materials. For instance, by applying complex profile-fitting algorithms to X-ray diffraction patterns, it is possible to get an estimation of the average grain size and the average dislocation density within a relatively large area. However, these average values are not enough for developing meticulous phenomenological models which are able to correlate microstructure and properties of nanocrystalline metallic materials. As another example, electron backscatter diffraction technique also cannot be used widely in the characterization of these materials due to problems such as relative poor spatial resolution (which is ~90 nm) and the degradation of Kikuchi diffraction patterns in severely deformed nano-size grain metallic materials. In this study, ASTAR/precession electron diffraction is introduced as a relatively new orientation microscopy technique to characterize defects (e.g., geometrically necessary dislocations and grain boundaries) in challenging nanocrystalline metallic materials. The capability of this characterization technique to quantitatively determine the dislocation density distributions of geometrically necessary dislocations in severely deformed metallic materials is assessed. Based on the developed method, it is possible to determine the distributions and accumulations of dislocations with respect to the nearest grain boundaries and triple junctions. Also, the competency of this technique to study the grain boundary character distributions of nanocrystalline metallic materials is presented

Non-invasive Quantification of Alveolar Morphometry Measurements in Older Never-smokers

Diffusion-weighted noble gas pulmonary magnetic resonance imaging (MRI) provides in vivo images with a contrast uniquely sensitive to molecular displacement at cellular and sub-cellular length scales. We estimated the external airway radius (R) and internal airway radius (r) of the alveolar dimensions to evaluate potential differences in acinar duct morphometries in healthy older never-smokers and compared those with a group of ex-smokers. The acinar duct and alveolar MRI morphometry results were within the physiologically-valid range of parameters. Estimated values of internal (r) and external (R) airway radius as well as alveolar sheath (h) and mean linear intercept (Lm) for individual subjects were similar with low variance. Results showed that MRI measurements of lung air space size in healthy older never-smokers were elevated compared to previous results reported in younger never-smokers, and lower than in age-matched ex-smokers (p\u3c.05). Specifically, older never-smokers had significantly lower external and internal airway radius and mean linear intercept, but higher alveolar sheath thickness, alveolar density and surface area-to-volume ratio than ex-smokers (p\u3c.05). Such results are compatible with the senile emphysematous changes to healthy parenchyma that accompany aging. These results demonstrate the potential MRI has with regards to replacing histology and lung stereology as the gold standard for measuring pulmonary acinus microstructure

Modeling of realistic microstructures on the basis of quantitative mineralogical analyses

Diese Forschung zielt darauf ab, den Einsatz realistischer Mineralmikrostrukturen in Mineralverarbeitungssimulationen Simulationen von Aufbereitungsprozessen zu ermöglichen. Insbesondere Zerkleinerungsprozesse, wie z.B. das Brechen und Mahlen von mineralischen Rohmaterialien, werden stark von der mineralischen Mikrostruktur beeinflusst, da die Textur und die Struktur der vielen Körner und ihre mikromechanischen Eigenschaften das makroskopische Bruchverhalten bestimmen. Ein Beispiel: Stellen wir uns vor, wir haben ein mineralisches Material, das im Wesentlichen aus Körnern zweier verschiedener Mineralphasen, wie Quarz und Feldspat, besteht. Wenn die mikromechanischen Eigenschaften dieser beiden Phasen unterschiedlich sind, wird sich dies wahrscheinlich auf das makroskopische Bruchverhalten auswirken. Unter der Annahme, dass die Körner eines der Minerale bei geringeren Belastungen brechen, ist es wahrscheinlich, dass sich ein Riss durch einen Stein dieses Materials durch die schwächeren Körner ausbreitet. Tatsächlich ist dies eine wichtige Eigenschaft für die Erzaufbereitung. Um wertvolle Mineralien aus einem Erz zu gewinnen, ist es wichtig, sie aus dem kommerziell wertlosen Material, in dem sie vorkommen, zu befreien. Dazu ist es wichtig zu wissen und zu verstehen, wie das Material auf Korngrößenebene bricht. Um diesen Bruch simulieren zu können, ist es wichtig, realistische Modelle der mineralischen Mikrostrukturen zu verwenden. Diese Studie zeigt, wie solche realistischen zweidimensionalen Mikrostrukturen auf der Grundlage der quantitativen Mikrostrukturanalyse am Computer erzeugt werden können. Darüber hinaus zeigt die Studie, wie diese synthetischen Mikrostrukturen dann in die gut etablierte Diskrete-Elemente-Methode integriert werden können, bei der der Bruch von mineralischem Material auf Korngrößenebene simuliert werden kann.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 237This research aims to make it possible to use realistic mineral microstructures in simulations of mineral processing. In particular, comminution processes, such as the crushing and grinding of raw mineral materials, are highly aff ected by the mineral microstructure, since the texture and structure of the many grains and their micromechanical properties determine the macroscopic fracture behavior. To illustrate this, consider a mineral material that essentially consists of grains of two diff erent mineral phases, such as quartz and feldspar. If the micromechanical properties of these two phases are diff erent, this will likely have an impact on the macroscopic fracture behavior. Assuming that the grains of one of the minerals break at lower loads, it is likely that a crack through a stone of that material will spread through the weaker grains. In fact, this is an important property for ore processing. In order to extract valuable minerals from an ore, it is important to liberate them from the commercially worthless material in which they are found. For this, it is essential to know and understand how the material breaks at grain-size level. To be able to simulate this breakage, it is important to use realistic models of the mineral microstructures. This study demonstrates how such realistic two-dimensional microstructures can be generated on the computer based on quantitative microstructural analysis. Furthermore, the study shows how these synthetic microstructures can then be incorporated into the well-established discrete element method, where the breakage of mineral material can be simulated at grain-size level.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 23

Estimation of Textured Surface Inclination by Parallel Local Spectral Analysis

When an inclined, uniformly textured surface is viewed by an observer or imaged by a camera, the systematic distortions of the perspective transformation will induce a predictable distribution of shifts in the projected spatial frequencies which compose the texture. By measuring these shifts using a set of filters having suitable spatial, frequency, and orientation resolution, the inclination angles of the original textured surface may be estimated. An algorithm is presented which uses the amplitude distributions of 2D Gabor filters to perform such a calculation. Central to the algorithm is a pair of iteratively executed routines. The fist adjusts local sets of parameters to reduce the error between predicted and measured filter amplitudes. The second propagates the local parameters to neighboring regions to consolidate the estimates of inclination. The algorithm is capable of operating in parallel on any number of regions in the image and with a diverse set of filter inputs

Some Critical Thoughts on Computational Materials Science

1. A Model is a Model is a Model is a Model The title of this report is of course meant to provoke. Why? Because there always exists a menace of confusing models with reality. Does anyone now refer to “first principles simulations”? This point is well taken. However, practically all of the current predictions in this domain are based on simulating electron dynamics using local density functional theory. These simulations, though providing a deep insight into materials ground states, are not exact but approximate solutions of the Schrödinger equation, which - not to forget - is a model itself [1]. Does someone now refer to “finite element simulations”? This point is also well taken. However, also in this case one has to admit that approximate solutions to large sets of non-linear differential equations formulated for a (non-existing) continuum under idealized boundary conditions is what it is: a model of nature but not reality. But us let calm down and render the discussion a bit more serious: current methods of ground state calculations are definitely among the cutting-edge disciplines in computational materials science and the community has learnt much from it during the last years. Similar aspects apply for some continuum-based finite element simulations. After all this report is meant to attract readers into this exciting field and not to repulse them. And for this reason I feel obliged to first make a point in underscoring that any interpretation of a research result obtained by computer simulation should be accompanied by scrutinizing the model ingredients and boundary conditions of that calculation in the same critical way as an experimentalist would check his experimental set-up

The Spine of the Cosmic Web

We present the SpineWeb framework for the topological analysis of the Cosmic Web and the identification of its walls, filaments and cluster nodes. Based on the watershed segmentation of the cosmic density field, the SpineWeb method invokes the local adjacency properties of the boundaries between the watershed basins to trace the critical points in the density field and the separatrices defined by them. The separatrices are classified into walls and the spine, the network of filaments and nodes in the matter distribution. Testing the method with a heuristic Voronoi model yields outstanding results. Following the discussion of the test results, we apply the SpineWeb method to a set of cosmological N-body simulations. The latter illustrates the potential for studying the structure and dynamics of the Cosmic Web.Comment: Accepted for publication HIGH-RES version: http://skysrv.pha.jhu.edu/~miguel/SpineWeb

Modeling, Estimation, and Pattern Analysis of Random Texture on 3-D Surfaces

To recover 3-D structure from a shaded and textural surface image involving textures, neither the Shape-from-shading nor the Shape-from-texture analysis is enough, because both radiance and texture information coexist within the scene surface. A new 3-D texture model is developed by considering the scene image as the superposition of a smooth shaded image and a random texture image. To describe the random part, the orthographical projection is adapted to take care of the non-isotropic distribution function of the intensity due to the slant and tilt of a 3-D textures surface, and the Fractional Differencing Periodic (FDP) model is chosen to describe the random texture, because this model is able to simultaneously represent the coarseness and the pattern of the 3-D texture surface, and enough flexible to synthesize both long-term and short-term correlation structures of random texture. Since the object is described by the model involving several free parameters and the values of these parameters are determined directly from its projected image, it is possible to extract 3-D information and texture pattern directly from the image without any preprocessing. Thus, the cumulative error obtained from each pre-processing can be minimized. For estimating the parameters, a hybrid method which uses both the least square and the maximum likelihood estimates is applied and the estimation of parameters and the synthesis are done in frequency domain. Among the texture pattern features which can be obtained from a single surface image, Fractal scaling parameter plays a major role for classifying and/or segmenting the different texture patterns tilted and slanted due to the 3-dimensional rotation, because of its rotational and scaling invariant properties. Also, since the Fractal scaling factor represents the coarseness of the surface, each texture pattern has its own Fractal scale value, and particularly at the boundary between the different textures, it has relatively higher value to the one within a same texture. Based on these facts, a new classification method and a segmentation scheme for the 3-D rotated texture patterns are develope