Unstructured Grid Generation Techniques and Software

The Workshop on Unstructured Grid Generation Techniques and Software was conducted for NASA to assess its unstructured grid activities, improve the coordination among NASA centers, and promote technology transfer to industry. The proceedings represent contributions from Ames, Langley, and Lewis Research Centers, and the Johnson and Marshall Space Flight Centers. This report is a compilation of the presentations made at the workshop

Comportamento mecânico de espumas de ligas de alumínio modeladas com recurso a micro-tomografia computorizada de raios-X

In recent years, there has been an increase in interest in cellular materials for structural applications, especially cellular metals (e.g., metal foams made of aluminium and its alloys). These closed-cell and open-cell foams usually have complex cellular structures resulting from the foaming process and their mechanical properties are governed by their cellular structures and by the properties of the base material. However, their mechanical characterization is difficult and most of the times can result in the destruction of the foam specimen. In this study, X-ray microcomputed tomography (µCT) was used together with finite element modelling to develop numerical models to estimate the elastic moduli and evaluate the effects of processing of the information obtained with the µCT scans in the final results. Such a technique complements experimental testing and brings great versatility. In order to accomplish this task, different thresholding techniques (segmentation) were applied to the 2D slices, which are the result of µCT scans, with special focus on a manual global technique with the mass as a quality indicator. Then, some reconstruction algorithms (e.g. Marching Cubes 33) were used to create 3D tessellated models in the STL format, which were oversampled (excessive number of faces) and with errors. Therefore, a simplification/clean-up procedure was applied to solve those issues, being analysed in terms of mass maintenance, shape maintenance with the Hausdorff algorithm and face quality, i.e., face aspect ratio. Two different procedures were evaluated, with and without small structural imperfections, so that the impact of the procedures could be analysed as well as the effect of the presence of small defects. The results obtained were evaluated and compared to several analytical and theoretical models, models based on representative unit-cells and experimental results in terms of the relation between the relative density and the relative Young’s modulus. Results demonstrated that the developed procedures were very good at minimizing changes in mass and shape of the geometries while providing good face quality, i.e., face aspect ratio. The models were also shown to be able to predict the properties of metallic foams in accordance with the findings of other researchers. In addition, the process of obtaining the models and the presence of small structural imperfections were shown to have a great impact on the final results.Nos últimos anos, tem-se verificado um aumento do interesse na área dos materiais celulares, mais especificamente metais celulares, para aplicações estruturais (por exemplo, espumas metálicas de alumínios e as suas ligas). Estas espumas de célula aberta e fechada têm, normalmente, uma estrutura celular complexa resultante do processo de espumação e as suas propriedades mecânicas dependem das suas estruturas celulares e das propriedades do material base. No entanto, a caracterização mecânicas destes materiais é difícil e resulta, regularmente, na destruição dos specimens de espuma. Neste estudo, Micro-Tomografia Computorizada de Raios-X (µCT) foi aplicada juntamente com modelação por elementos finitos para desenvolver modelos numéricos que conseguem estimar os módulos de elasticidade e avaliar os efeitos do processamento da informação obtida pelos scans de µCT nos resultados finais. Esta técnica complementa os procedimentos experimentais e traz uma grande versatilidade. Para se completar a tarefa proposta, diferentes métodos de segmentação foram aplicados às fatias 2D, que são resultantes dos scans de µCT, com especial atenção num método de segmentação manual global que utiliza a massa como indicador de qualidade. Depois disso, alguns algoritmos de reconstrução, por exemplo, Marching Cubes 33, foram aplicados para criar modelos 3D de faces triangulares no formato STL que demonstram sobreamostragem (excessiva quantidade de faces) e alguns erros. Por essa razão, um procedimento de simplificação/limpeza foi aplicado para resolver estes problemas, sendo analisados em termos de preservação de massa, preservação de forma com o algoritmo de Hausdorff e qualidade das faces, ou seja, razão de proporção. Dois procedimentos diferentes foram avaliados, um com e outro sem pequenos defeitos estruturais para que se consiga analisar não só o impacto do processamento dos modelos assim como o efeito da presença de pequenos defeitos. Os resultados obtidos foram comparados com vários modelos analíticos e teóricos, modelos baseados em células unitárias representativas e resultados experimentais com base na relação entre a densidade relativa e o modulo de Young relativo. Os resultados demonstraram que os procedimentos desenvolvidos são bons a preservar a massa e forma das geometrias deixando as faces com boa qualidade. Verificou-se também que os modelos foram capazes de prever as propriedades das espumas metálicas em concordância com o trabalho de outros investigadores. Adicionalmente, mostrou-se que o processo de obtenção dos modelos e a presença de pequenas imperfeiçoes estruturais tem um impacto relevante nos resultados finais.Mestrado em Engenharia Mecânic

Virtual sculpting : an investigation of directly manipulated free-form deformation in a virtual environment

This thesis presents a Virtual Sculpting system, which addresses the problem of Free-Form Solid Modelling. The disparate elements of a Polygon-Mesh representation, a Directly Manipulated Free-Form Deformation sculpting tool, and a Virtual Environment are drawn into a cohesive whole under the mantle of a clay-sculpting metaphor. This enables a user to mould and manipulate a synthetic solid interactively as if it were composed of malleable clay. The focus of this study is on the interactivity, intuitivity and versatility of such a system. To this end, a range of improvements is investigated which significantly enhances the efficiency and correctness of Directly Manipulated Free-Form Deformation, both separately and as a seamless component of the Virtual Sculpting system

Cell Nuclear Morphology Analysis Using 3D Shape Modeling, Machine Learning and Visual Analytics

Quantitative analysis of morphological changes in a cell nucleus is important for the understanding of nuclear architecture and its relationship with cell differentiation, development, proliferation, and disease. Changes in the nuclear form are associated with reorganization of chromatin architecture related to altered functional properties such as gene regulation and expression. Understanding these processes through quantitative analysis of morphological changes is important not only for investigating nuclear organization, but also has clinical implications, for example, in detection and treatment of pathological conditions such as cancer. While efforts have been made to characterize nuclear shapes in two or pseudo-three dimensions, several studies have demonstrated that three dimensional (3D) representations provide better nuclear shape description, in part due to the high variability of nuclear morphologies. 3D shape descriptors that permit robust morphological analysis and facilitate human interpretation are still under active investigation. A few methods have been proposed to classify nuclear morphologies in 3D, however, there is a lack of publicly available 3D data for the evaluation and comparison of such algorithms. There is a compelling need for robust 3D nuclear morphometric techniques to carry out population-wide analyses. In this work, we address a number of these existing limitations. First, we present a largest publicly available, to-date, 3D microscopy imaging dataset for cell nuclear morphology analysis and classification. We provide a detailed description of the image analysis protocol, from segmentation to baseline evaluation of a number of popular classification algorithms using 2D and 3D voxel-based morphometric measures. We proposed a specific cross-validation scheme that accounts for possible batch effects in data. Second, we propose a new technique that combines mathematical modeling, machine learning, and interpretation of morphometric characteristics of cell nuclei and nucleoli in 3D. Employing robust and smooth surface reconstruction methods to accurately approximate 3D object boundary enables the establishment of homologies between different biological shapes. Then, we compute geometric morphological measures characterizing the form of cell nuclei and nucleoli. We combine these methods into a highly parallel computational pipeline workflow for automated morphological analysis of thousands of nuclei and nucleoli in 3D. We also describe the use of visual analytics and deep learning techniques for the analysis of nuclear morphology data. Third, we evaluate proposed methods for 3D surface morphometric analysis of our data. We improved the performance of morphological classification between epithelial vs mesenchymal human prostate cancer cells compared to the previously reported results due to the more accurate shape representation and the use of combined nuclear and nucleolar morphometry. We confirmed previously reported relevant morphological characteristics, and also reported new features that can provide insight in the underlying biological mechanisms of pathology of prostate cancer. We also assessed nuclear morphology changes associated with chromatin remodeling in drug-induced cellular reprogramming. We computed temporal trajectories reflecting morphological differences in astroglial cell sub-populations administered with 2 different treatments vs controls. We described specific changes in nuclear morphology that are characteristic of chromatin re-organization under each treatment, which previously has been only tentatively hypothesized in literature. Our approach demonstrated high classification performance on each of 3 different cell lines and reported the most salient morphometric characteristics. We conclude with the discussion of the potential impact of method development in nuclear morphology analysis on clinical decision-making and fundamental investigation of 3D nuclear architecture. We consider some open problems and future trends in this field.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147598/1/akalinin_1.pd

Fibre-reinforced additive manufacturing: from design guidelines to advanced lattice structures

In pursuit of achieving ultimate lightweight designs with additive manufacturing (AM), engineers across industries are increasingly gravitating towards composites and architected cellular solids; more precisely, fibre-reinforced polymers and functionally graded lattices (FGLs). Control over material anisotropy and the cell topology in design for AM (DfAM) offer immense scope for customising a part’s properties and for the efficient use of material. This research expands the knowledge on the design with fibre-reinforced AM (FRAM) and the elastic-plastic performance of FGLs. Novel toolpath strategies, design guidelines and assessment criteria for FRAM were developed. For this purpose, an open-source solution was proposed, successfully overcoming the limitations of commercial printers. The effect of infill patterns on structural performance, economy, and manufacturability was examined. It was demonstrated how print paths informed by stress trajectories and key geometric features can outperform conventional patterns, laying the groundwork for more sophisticated process planning. A compilation of the first comprehensive database on fibre-reinforced FGLs provided insights into the effect of grading on the elastic performance and energy absorption capability, subject to strut-and surface-based lattices, build direction and fibre volume fraction. It was elucidated how grading the unit cell density within a lattice offers the possibility of tailoring the stiffness and achieving higher energy absorption than ungraded lattices. Vice versa, grading the unit cell size of lattices yielded no effect on the performance and is thus exclusively governed by the density. These findings help exploit the lightweight potential of FGLs through better informed DfAM. A new and efficient methodology for predicting the elastic-plastic characteristics of FGLs under large strain deformation, assuming homogenised material properties, was presented. A phenomenological constitutive model that was calibrated based upon interpolated material data of uniform density lattices facilitated a computationally inexpensive simulation approach and thus helps streamline the design workflow with architected lattices.Open Acces

Upscaling the evolution of snow microstructure:from 4D image analysis to rigorous models

Snow microstructure and its evolution play an important role for various applications of snow physics in cryospheric sciences. The main modes of microstructure evolution in snow are referred to as isothermal and temperature gradient metamorphism. The former describes the coarsening driven by interfacial energy while the latter is dominated by recrystallization processes induced by temperature gradients. An accurate description of these processes in snowpack models is of key importance. However common snowpack models are still based on traditional grain metrics, originally tailored to field observations, and empirical evolution laws. This treatment of snow microstructure is essentially unrelated to recent advances of snow observations by microcomputed tomography (ÎŒCT). The present thesis contributes to the solution of this problem by i) identifying suitable microstructure parameters ii) deriving evolution equations for these from first principles and iii) developing methods that allow to utilize 4D ÎŒCT measurements of snow as a link between local ice crystal growth and upscaled microstructure as relevant on the scales of interest for common snowpack models. To this end, three studies have been conducted. The first study focuses on estimating local ice-crystal growth rates from interface tracking by analyzing 4D ÎŒCT data of in-situ snow metamorphism experiments under isothermal and temperature gradient conditions. For temperature gradient metamorphism diffusion-limited growth is considered, while for isothermal metamorphism the data is compared to kinetics and diffusion limited growth. Despite considerable scatter, in both cases the significance of underlying growth laws could be statistically confirmed. The second study uses ÎŒCT images from a variety of snow samples to investigate the role of grain shape in the context of microwave and optical properties of snow. Grain shape can be objectively defined via size-dispersity of structure from the second moment of either the mean curvature distribution or the chord-length distribution. In addition, a quantitative link between these quantities and the exponential correlation length is shown. The latter is relevant for parameterizing macroscopic properties such as microwave scattering coefficients, dielectric permittivity and thermal conductivity. Finally, a rigorous, upscaled microstructure scheme is developed by deriving mathematically exact evolution equations for the density, specific surface area, the mean and Gaussian curvature and the second moment of mean curvature. The microstructural evolution is driven by local ice crystal growth. All parameters are upscaled by volume averaging and the correctness of the model is confirmed for the time evolution of idealized grains. The model can be compared to 4D ÎŒCT data without any a-priori assumptions. This benchmarking reveals the uncertainties of the interface tracking method which are largely caused by limited temporal and spatial resolution. The model allows to statistically assess the validity of ice crystal growth laws during snow metamorphism. For a temperature gradient experiment it is shown that a diffusion limited growth law is not consistent with the observed decay of the specific surface area. The developed model is a powerful and rigorous tool that is tailored to 4D ÎŒCT data. It connects microscale ice-crystal growth thermodynamics with the macroscale snowpack modeling

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Rock-typing and permeability estimation of thin-bedded reservoir rock by NMR in the presence of diffusion coupling

Conventional interpretation approaches to nuclear magnetic resonance (NMR) measurements of fluid-saturated reservoir rock rely on the assumption that the distributions of transverse relaxation time (T2) and pore size directly correlate. In practical scenarios this assumption is found not to apply in numerous multi-scale porosity structures as a result of what is known as “diffusion coupling” occurring between various pores. This problem has been analyzed in the context of individual pores, but less so for larger regions of interest. For gas reservoirs in particular it arises frequently in the case of thinly laminated reservoirs due to their characteristically small layer thickness and the subsequent shorter distances to be covered by mobile spins and the appreciably higher diffusion coefficients that characterize gas reservoirs. In such instances, rock-typing cannot directly be achieved from NMR measurements. This study employs NMR simulations on tomographic images for the interpretation of NMR measurements in the presence of interbed diffusion coupling. Knowledge about the magnetization decay of the coupling region is used together with prior knowledge of the individual rock types forming the layered rocks in a methodical treatment to establish the coupling strength (ξ_R). Following successful completion of rock-typing, the improvement in the estimation of vertical and horizontal permeabilities was evaluated, which relies on a proper definition of T2lm for each rock-type that corrected for diffusion coupling. The Lattice-Boltzmann (LB) method was also used to assess the enhancements in the NMR permeability estimations. Synthetic consolidated and unconsolidated laminated structures with two distinct grain sizes and various layer thicknesses are used to test the approach both numerically and experimentally. A relationship between strengthening pore coupling and reducing bed thickness was noted, together with the increase in the diffusion coefficient and the decrease in surface relaxivity. In instances of strong pore coupling, the T2 distribution was found to inaccurately represent the inherent bimodal distribution relative to various morphologies. Successful rock-typing was attained through the decoupling procedure by applying the value of (ξ_R) that consequently improve the NMR permeability estimation

Modelling porosity and permeability in early cemented carbonates

Cabonate-hosted hydrocarbon reservoirs will play an increasingly important role in the energy supply, as 60% of the world's remaining hydrocarbon resources are trapped within carbonate rocks. The properties of carbonates are controlled by deposition and diagenesis, which includes calcite cementation that begins immediately after deposition and may have a strong impact on subsequent diagenetic pathways. This thesis aims to understand the impact of early calcite cementation on reservoir properties through object-based modelling and Lattice Boltzmann ow simulation to obtain permeability. A Bayesian inference framework is also developed to quantify the ability of Lattice Boltzmann method to predict the permeability of porous media. Modelling focuses on the impact of carbonate grain type on properties of early cemented grainstones and on the examination of the theoretical changes to the morphology of the pore space. For that purpose process-based models of early cementation are developed in both 2D (Calcite2D) and 3D (Calcite3D, which also includes modelling of deposition). Both models assume the existence of two grain types: polycrystalline and monocrystalline, and two early calcite cement types specific to these grain types: isopachous and syntaxial, respectively. Of the many possible crystal forms that syntaxial cement can take, this thesis focuses on two common rhombohedral forms: a blocky form 01¯12 and an elongated form 40¯41. The results of the 2D and 3D modelling demonstrate the effect of competition of growing grains for the available pore space: the more monocrystalline grains present in the sample, the stronger this competition becomes and the lesser the impact of each individual grain on the resulting early calcite cement volume and porosity. The synthetic samples with syntaxial cements grown of the more elongated crystal form 40¯41 have lower porosity for the same monocrystalline grains content than synthetic samples grown following more blocky crystal form 01¯12. Moreover, permeability at a constant porosity is reduced for synthetic samples with the form 40¯41. Additionally, synthetic samples with form 40¯41 exhibit greater variability in the results as this rhombohedral form is more elongated and has the potential for producing a greater volume of cement. The results of the 2D study suggest that for samples at constant porosity the higher the proportion of monocrystalline grains are in the sample, the higher the permeability. The 3D study suggests that for samples with crystal form 01¯12 at constant porosity the permeability becomes lower as the proportion of monocrystalline grains increase, but this impact is relatively minor. In the case of samples with crystal form 40¯41 the results are inconclusive. This dependence of permeability on monocrystalline grains is weaker than in the 2D study, which is most probably a result of the bias of flow simulation in the 2D as well as of the treatment of the porous medium before the cement growth model is applied. The range of the permeability results in the 2D modelling may be artificially overly wide, which could lead to the dependence of permeability on sediment type being exaggerated. Poroperm results of the 2D modelling (10-8000mD) are in reasonable agreement with the data reported for grainstones in literature (0.1-5000mD) as well as for the plug data of the samples used in modelling (porosity 22 - 27%, permeability 200 - 3000mD), however permeability results at any given porosity have a wide range due to the bias inherent to the 2D flow modelling. Poroperm results in the 3D modelling (10 - 30, 000mD) exhibit permeabilities above the range of that reported in the literature or the plug data, but the reason for that is that the initial synthetic sediment deposit has very high permeability (58, 900mD). However, the trend in poroperm closely resembles those reported in carbonate rocks. As the modelling depends heavily on the use of Lattice Boltzmann method (flow simulation to obtain permeability results), a Bayesian inference framework is presented to quantify the predictive power of Lattice Boltzmann models. This calibration methodology is presented on the example of Fontainebleau sandstone. The framework enables a systematic parameter estimation of Lattice Boltzmann model parameters (in the scope of this work, the relaxation parameter τ ), for the currently used calibrations of Lattice Boltzmann based on Hagen-Poiseuille law. Our prediction of permeability using the Hagen-Poiseuille calibration suggests that this method for calibration is not optimal and in fact leads to substantial discrepancies with experimental measurements, especially for highly porous complex media such as carbonates. We proceed to recalibrate the Lattice Boltzmann model using permeability data from porous media, which results in a substantially different value of the optimal τ parameter than those used previously (0.654 here compared to 0.9). We augment our model introducing porosity-dependence, where we find that the optimal value for τ decreases for samples of higher porosity. In this new semi-empirical model one first identifies the porosity of the given medium, and on that basis chooses an appropriate Lattice Boltzmann relaxation parameter. These two approaches result in permeability predictions much closer to the experimental permeability data, with the porosity-dependent case being the better of the two. Validation of this calibration method with independent samples of the same rock type yields permeability predictions that fall close to the experimental data, and again the porosity-dependent model provides better results. We thus conclude that our calibration model is a powerful tool for accurate prediction of complex porous media permeability