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Butcher, Cliff. "A Multi-Scale Damage Percolation Model Of Ductile Fracture." Thesis, Fredericton: University of New Brunswick, 2011. http://hdl.handle.net/1882/35391.
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The traditional approach to modeling ductile fracture involves homogenizing the microstructure of a material into a simple, equivalent geometry from which the relevant constitutive laws can be derived. While attractive from a modeling perspective, critical details of the microstructure are lost in this homogenization process such as the particle size, shape, orientation, distribution and degree of clustering. Since void initiation and evolution is a highly localized phenomenon originating within heterogeneous particle clusters, these models fail to accurately predict fracture. These limitations can be overcome using a promising new technique known as damage percolation modeling that requires no idealizations or approximations of the microstructure. In this approach, digital imaging techniques or x-ray microtomography can be used to obtain the particle distribution in a material. Using this information, micromechanical models are applied to characterize void and crack formation leading to failure at the individual particle scale. The damage percolation model represents the future in material modeling as it directly relates changes in the local microstructure to the overall material behaviour.
In this research, the first fully-coupled multi-scale damage percolation model has been developed to predict fracture in advanced materials with heterogeneous particle distributions. In the first phase of this work, a sophisticated damage percolation model is developed using the latest micromechanical models to characterize void nucleation, growth, and coalescence in three-dimensions for general loading conditions. A novel strategy is proposed to determine the stress state within the reinforcing particles and inclusions to facilitate the development of a void nucleation model based solely upon the particle properties.
The percolation model was implemented into a commercial finite-element code using so-called “percolation elements” to capture the complex stress- and strain-gradients that develop during deformation. A particle field generator is developed and integrated into the finite-element code to create representative particle distributions within the percolation elements to provide stochastic predictions of fracture that reflect
the experimental variation. Finally, the percolation model is validated numerically and experimentally for an automotive-grade aluminum alloy in a notched tensile test used for material characterization. The complete multi-scale percolation model predicts fracture as a direct consequence of the stress state, material properties and the local conditions within the microstructure.
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Bonis, Ioannis. "Optimisation and control methodologies for large-scale and multi-scale systems." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/optimisation-and-control-methodologies-for-largescale-and-multiscale-systems(6c4a4f13-ebae-4d9d-95b7-cca754968d47).html.
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Distributed parameter systems (DPS) comprise an important class of engineering systems ranging from "traditional" such as tubular reactors, to cutting edge processes such as nano-scale coatings. DPS have been studied extensively and significant advances have been noted, enabling their accurate simulation. To this end a variety of tools have been developed. However, extending these advances for systems design is not a trivial task . Rigorous design and operation policies entail systematic procedures for optimisation and control. These tasks are "upper-level" and utilize existing models and simulators. The higher the accuracy of the underlying models, the more the design procedure benefits. However, employing such models in the context of conventional algorithms may lead to inefficient formulations. The optimisation and control of DPS is a challenging task. These systems are typically discretised over a computational mesh, leading to large-scale problems. Handling the resulting large-scale systems may prove to be an intimidating task and requires special methodologies. Furthermore, it is often the case that the underlying physical phenomena span various temporal and spatial scales, thus complicating the analysis. Stiffness may also potentially be exhibited in the (nonlinear) models of such phenomena. The objective of this work is to design reliable and practical procedures for the optimisation and control of DPS. It has been observed in many systems of engineering interest that although they are described by infinite-dimensional Partial Differential Equations (PDEs) resulting in large discretisation problems, their behaviour has a finite number of significant components , as a result of their dissipative nature. This property has been exploited in various systematic model reduction techniques. Of key importance in this work is the identification of a low-dimensional dominant subspace for the system. This subspace is heuristically found to correspond to part of the eigenspectrum of the system and can therefore be identified efficiently using iterative matrix-free techniques. In this light, only low-dimensional Jacobians and Hessian matrices are involved in the formulation of the proposed algorithms, which are projections of the original matrices onto appropriate low-dimensional subspaces, computed efficiently with directional perturbations.The optimisation algorithm presented employs a 2-step projection scheme, firstly onto the dominant subspace of the system (corresponding to the right-most eigenvalues of the linearised system) and secondly onto the subspace of decision variables. This algorithm is inspired by reduced Hessian Sequential Quadratic Programming methods and therefore locates a local optimum of the nonlinear programming problem given by solving a sequence of reduced quadratic programming (QP) subproblems . This optimisation algorithm is appropriate for systems with a relatively small number of decision variables. Inequality constraints can be accommodated following a penalty-based strategy which aggregates all constraints using an appropriate function , or by employing a partial reduction technique in which only equality constraints are considered for the reduction and the inequalities are linearised and passed on to the QP subproblem . The control algorithm presented is based on the online adaptive construction of low-order linear models used in the context of a linear Model Predictive Control (MPC) algorithm , in which the discrete-time state-space model is recomputed at every sampling time in a receding horizon fashion. Successive linearisation around the current state on the closed-loop trajectory is combined with model reduction, resulting in an efficient procedure for the computation of reduced linearised models, projected onto the dominant subspace of the system. In this case, this subspace corresponds to the eigenvalues of largest magnitude of the discretised dynamical system. Control actions are computed from low-order QP problems solved efficiently online.The optimisation and control algorithms presented may employ input/output simulators (such as commercial packages) extending their use to upper-level tasks. They are also suitable for systems governed by microscopic rules, the equations of which do not exist in closed form. Illustrative case studies are presented, based on tubular reactor models, which exhibit rich parametric behaviour.
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Chew, Yin Hoon. "Multi-scale whole-plant model of Arabidopsis growth to flowering." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8008.
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In this study, theoretical and experimental approaches were combined, using Arabidopsis as the studied species. The multi-scale model incorporates the following, existing sub-models: a phenology model that can predict the flowering time of plants grown in the field, a gene circuit of the circadian clock network that regulates flowering through the photoperiod pathway, a process-based model describing carbon assimilation and resource partitioning, and a functional-structural module that determines shoot structure for light interception and root growth. First, the phenology model was examined on its ability to predict the flowering time of field plantings at different sites and seasons in light of the specific meteorological conditions that pertained. This analysis suggested that the synchrony of temperature and light cycles is important in promoting floral initiation. New features were incorporated into the phenology model that improved its predictive accuracy across seasons. Using both lab and field data, this study has revealed an important seasonal effect of night temperatures on flowering time. Further model adjustments to describe phytochrome (phy) mutants supported the findings and implicated phyB in the temporal gating of temperature-induced flowering. The improved phenology model was next linked to the clock gene circuit model. Simulation of clock mutants with different free-running periods highlighted the complex mechanism associated with daylength responses for the induction of flowering. Finally, the carbon assimilation and functional-structural growth modules were integrated to form the multi-component, whole-plant model. The integrated model was successfully validated with experimental data from a few genotypes grown in the laboratory. In conclusion, the model has the ability to predict the flowering time, leaf biomass and ecosystem exchange of plants grown under conditions of varying light intensity, temperature, CO2 level and photoperiod, though extensions of some model components to incorporate more biological details would be relevant. Nevertheless, this meso-scale model creates obvious application routes from molecular and cellular biology to crop improvement and biosphere management. It could provide a framework for whole-organism modelling to help address global issues such as food security and the energy crisis.
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Deserranno, Dimitri. "A Multi-Scale Finite Element Model of the Cardiac Ventricles." Case Western Reserve University School of Graduate Studies / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=case1148984314.
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Saavedra, Flores Erick Isaac. "Computational multi-scale constitutive model for wood cell-wall mechanics." Thesis, Swansea University, 2011. https://cronfa.swan.ac.uk/Record/cronfa43160.
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Paquet, Daniel. "Adaptive Multi-level Model for Multi-scale Ductile Fracture Analysis in Heterogeneous Aluminum Alloys." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1324565883.
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Raghavan, Prasanna. "Multi-scale analysis of elastic and debonding composites by an adaptive multi-level computational model." Columbus, Ohio : Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1073013372.
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Thesis (Ph. D.)--Ohio State University, 2004.Title from first page of PDF file. Document formatted into pages; contains xvi, 162 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Somnath Ghosh, Dept. of Mechanical Engineering. Includes bibliographical references (p. 155-162).
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Rukavina, Tea. "Multi-scale damage model of fiber-reinforced concrete with parameter identification." Thesis, Compiègne, 2018. http://www.theses.fr/2018COMP2460/document.
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Dans cette thèse, plusieurs approches de modélisation de composites renforcés par des fibres sont proposées. Le matériau étudié est le béton fibré, et dans ce modèle, on tient compte de l’influence de trois constituants : le béton, les fibres, et la liaison entre eux. Le comportement du béton est analysé avec un modèle d’endommagement, les fibres d'acier sont considérées comme élastiques linéaires, et le comportement sur l'interface est décrit avec une loi de glissement avec l’extraction complète de la fibre. Une approche multi-échelle pour coupler tous les constituants est proposée, dans laquelle le calcul à l'échelle macro est effectué en utilisant la procédure de solution operator-split. Cette approche partitionnée divise le calcul en deux phases, globale et locale, dans lesquelles différents mécanismes de rupture sont traités séparément, ce qui est conforme au comportement du composite observé expérimentalement. L'identification des paramètres est effectuée en minimisant l'erreur entre les valeurs calculées et mesurées. Les modèles proposés sont validés par des exemples numériquesIn this thesis, several approaches for modeling fiber-reinforced composites are proposed. The material under consideration is fiber-reinforced concrete, which is composed of a few constituents: concrete, short steel fibers, and the interface between them. The behavior of concrete is described by a damage model with localized failure, fibers are taken to be linear elastic, and the behavior of the interface is modeled with a bond-slip pull-out law. A multi-scale approach for coupling all the constituents is proposed, where the macro-scale computation is carried out using the operator-split solution procedure. This partitioned approach divides the computation in two phases, global and local, where different failure mechanisms are treated separately, which is in accordance with the experimentally observed composite behavior. An inverse model for fiber-reinforced concrete is presented, where the stochastic caracterization of the fibers is known from their distribution inside the domain. Parameter identification is performed by minimizing the error between the computed and measured values. The proposed models are validated through numerical examples
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Thatte, Azam. "Multi-scale multi-physics model and hybrid computational framework for predicting dynamics of hydraulic rod seals." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37272.
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Rod seals are one of the most critical components of hydraulic systems. However, the fundamental physics of seal behavior is still poorly understood and the seal designers have virtually no analytical tools with which to predict the behavior of potential seal designs. In pursuit of a comprehensive physics based seal analysis/ design tool, in this work, a multi-scale multi-physics (MSMP) seal model is developed. The model solves the transient problem involving macro-scale viscoelastic deformation mechanics, macro-scale contact, micro-scale two phase fluid mechanics in the sealing zone, micro-scale asperity contact mechanics and micro-scale deformation mechanics of the sealing edge in a strongly coupled manner. The model takes into account surface roughness, mixed lubrication, cavitation and two phase flow, transient squeeze film effects and the dynamic operation as well as the effect of macro/micro/nano scale viscoelasticity. A hybrid finite element-finite volume-statistical computational framework is developed to solve the highly coupled multi-physics interactions of the MSMP model simultaneously. Surface characterization experiments are performed to extract the parameters like RMS roughness, asperity density, autocorrelation length and asperity radius needed by MSMP. To remove the high frequency noise without removing the high frequency real surface features, a wavelet transform based adaptive surface extraction method is implemented. Dynamic mechanical analysis (DMA) is performed to extract the macro-scale viscoelastic parameters of the seal. Through atomic force microscopy (AFM) experiments, the local micro/nano scale elastic moduli were found to be varying within two orders of magnitude higher than the bulk of the polymer. Significant differences in local stiffness, adhesion and the relaxation time scales of individual surface asperities were also observed. With the MSMP model, dynamic seal performance was analyzed. The results confirmed the mixed lubrication and the effect of surface roughness. Thicker fluid films during instroke and cavitation during the outstroke were found to be important for non-leakage. Seal behavior was a function of the complex dual dependence on the time varying sealed pressure and hydrodynamic effects. Viscoelasticity is seen to critically affect the leakage and friction characteristics. It produces thicker fluid films and produces a significant increase in Poiseuille component of flow during instroke. Ignoring viscoelasticity leads to under-prediction of the time required to reach the zero leakage state. Several high pressure - high frequency sealing applications were analyzed. In such applications, a new phenomenon of "secondary contact" was observed. Viscoelastic creep was seen to critically affect the contact pressure and hence the friction characteristics. In high frequency applications, viscoelasticity induced significant differences in Poiseuille flow and friction force from cycle to cycle. Cycle frequency was seen to play an important role in governing visco-elastohydrodynamics and the leakage of such seals. The seals need to be designed by considering the relationship between relaxation time scales of the polymer and the cycle frequencies. Study also revealed the presence of characteristics like "critical temperature" and "critical frequency". Using the multi-physics modeling capability of MSMP framework, several novel seal designs using smart materials like piezo-ceramic embedded polymers are proposed and analyzed. The MSMP computational framework developed here has a great potential to be used as a stand-alone seal design and analysis software in academic and industrial research.
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Schindler, Felix [Verfasser], and Mario [Akademischer Betreuer] Ohlberger. "Model reduction for parametric multi-scale problems / Felix Schindler ; Betreuer: Mario Ohlberger." Münster : Universitäts- und Landesbibliothek Münster, 2016. http://d-nb.info/1140917668/34.
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Peterson, Eric W. "Tire-Road Friction Coefficient Estimation Using a Multi-scale, Physics-based Model." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/51148.
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The interaction between a tire and road surface is of critical importance as the motion of a car in both transient and steady-state maneuvers is predicated on the friction forces generated at the tire-road interface. A general method for predicting friction coefficients for an arbitrary asphalt pavement surface would be an invaluable engineering tool for designing many vehicle safety and performance features, tire design, and improving asphalt-aggregate mixtures used for pavement surfaces by manipulating texture. General, physics-based methods for predicting friction are incredibly difficult, if not impossible to realize—However, for the specific case of rubber sliding across a rough surface, the primary physical mechanisms responsible for friction, notably rubber hysteresis, can be modeled.
The objective of the subsequent research is to investigate one such physics model, referred to as Persson Theory, and implement the constitutive equations into a MatLab® code to be solved numerically. The model uses high-resolution surface measurements, along with some of the physical properties of rubber as inputs and outputs the kinetic friction coefficient. The Persson model was successfully implemented into MatLab® and high resolution measurements (from optical microscopy and imaging software) were obtained for a variety of surfaces. Friction coefficients were calculated for each surface and compared with measured friction values obtained from British Pendulum testing. The accuracy and feasibility of the Persson model are discussed and results are compared with a simpler, semi-empirical indenter model. A brief discussion of the merits and drawbacks of the Persson model are offered along with recommendations for future research based on the information acquired from the present study.Master of Science
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Wang, Cong. "A Multi-Scale, Multi-Continuum and Multi-Physics Model to Simulate Coupled Fluid Flow and Geomechanics in Shale Gas Reservoirs." Thesis, Colorado School of Mines, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10684514.
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In this study, several efficient and accurate mathematical models and numerical solutions to unconventional reservoir development problems are developed. The first is the three-dimensional embedded discrete fracture method (3D-EDFM), which is able to simulate fluid flow with multiple 3D hydraulic fractures with arbitrary strike and dip angles, shapes, curvatures, conductivities and connections. The second is a multi-porosity and multi-physics fluid flow model, which can capture gas flow behaviors in shales, which is complicated by highly heterogeneous and hierarchical rock structures (ranging from organic nanopores, inorganic nanopores, less permeable micro-fractures, more permeable macro-fractures to hydraulic fractures). The third is an iterative numerical approach combining the extended finite element method (X-FEM) and the embedded discrete fracture method (EDFM), which is developed for simulating the fluid-driven fracture propagation process in porous media.
Physical explanations and mathematical equations behind these mathematical models and numerical approaches are described in detail. Their advantages over alternative numerical methods are discussed. These numerical methods are incorporated into an in-house program. A series of synthetic but realistic cases are simulated. Simulated results reveal physical understandings qualitatively and match with available analytical solutions quantitatively. These novel mathematical models and computational solutions provide numerical approaches to understand complicated physical phenomena in developing unconventional reservoirs, thus they help in the better management of unconventional reservoirs.
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Warren, Nicholas J. "A multi-scale computational model of fluid transport in the human bronchial airways /." e-Thesis University of Auckland, 2010. http://hdl.handle.net/2292/5773.
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Thesis (PhD--Bioengineering)--University of Auckland, 2010."Supervised by Dr. AP M.H. Tawhai and Dr E.J. Crampin." " A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Bioengineering." "Auckland Bioengineering Institute." Includes bibliographical references (p. 204-255).
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Ngoc, Anh Giang [Verfasser]. "Multi-scale Model for Fatigue in Carbide-rich Tool Steel / Giang Ngoc Anh." Aachen : Shaker, 2015. http://d-nb.info/1080763902/34.
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Ghodsi, Seyed Hossein. "CHARACTERIZATION OF MULTI-SCALE CONSTITUTIVE MODEL OF COLLAGEN: A MOLECULAR DYNAMICS MODELING APPROACH." Diss., Temple University Libraries, 2015. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/315035.
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Mechanical EngineeringPh.D.
Collagen is the most abundant protein in mammals and has special mechanical behavior that enables it to play an important role in the structural integrity of many tissues, e.g., skin, tendon, bone, cartilage and blood vessels. The mechanical properties of collagen are governed by hierarchical mechanisms in different length-scales from molecule to tissue level. Currently, there is no multi-scale model that can predict the mechanical properties of collagen at macroscopic length scales from the behavior of microstructural elements at smaller length scales. This dissertation aimed at developing a multi-scale model using a bottom-up approach to predict the elastic and viscoelastic behaviors of collagen at length scales spanning from nano to microscale. Creep simulations were performed using steered molecular dynamics (SMD) method on collagen molecules, cross-link, and micro-fibrils with various lengths. A micro-fibril is considered as a combination of two collagen molecules connected by a cross-link. The strain time histories for force levels in the range of 10 to 4000 pN were characterized using quasilinear viscoelastic models. These models were utilized to make a reduced model of a micro-fibril and the reduced models, in turn, were combined to make a model of a fibril up to 300 micrometers in length. The micro-fibril and fibril models were validated with available experimental measurements. Hydrogen bonds rupture and formation of collagen molecule played a central role in its viscoelastic behavior and were used to estimate the creep growth rate. The propagation of force wave in the molecule was shown to be an important factor in providing the time-dependent properties of the fibrils. This propagation was modeled with delay elements and this allowed reducing the micro-fibril model to only three degrees of freedom. In conclusion, the results confirmed that the combination of molecular dynamics simulations and viscoelastic theory could be successfully utilized to investigate the viscoelastic behavior of collagen at small scales. The model reported in this dissertation, lays the groundwork for future studies on collagen, particularly in elucidating how each particular level of hierarchy affects the overall tissue behavior.
Temple University--Theses
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Navarro, Martin. "Fault roughness and fault complexity field study, multi-scale analysis and numerical fault model /." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=966415809.
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Sclaroff, Stanley Edward. "Deformable solids and displacement maps--a multi-scale technique for model recovery and recognition." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/70198.
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Dodd, Josie. "A multi-scale mathematical model for simulating and optimising the growth of Bambara groundnut." Thesis, University of Reading, 2018. http://centaur.reading.ac.uk/78970/.
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A principal objective in agriculture is to maximise food production; this is particularly relevant with the added demands of an ever increasing population, coupled with the unpredictability that climate change brings. Further improvements in productivity can only be achieved with an increased understanding of plant and crop processes. In this respect, mathematical modelling of plants and crops plays an important role. In this thesis we present a two-scale mathematical model of crop yield, that accounts for plant growth and canopy interactions. A system of ordinary differential equations (ODEs) has been developed for each individual plant, where equations are coupled via a term that describes plant competition. Both analytical and numerical methods have been considered to describe this competition. This model has been formulated for an underutilised African legume called bambara groundnut, a drought tolerant crop, which is currently being investigated to be used more widely as a food source in light of climate change and food security. Like many plant species, bambara groundnut exhibits physiological diversity which may affect the overall growth dynamics and crop yield. Such plant diversity is not regularly accounted for in crop scale models. Our model not only allows us to account for plant diversity, but we can investigate the effect of individual plant traits (e.g. plant canopy size and growth rates, planting distance) on the crop scale yield. The mathematical model has been formulated and validated using experimental data collected from the Tropical Crops Research Unit (TCRU) and Future Crops greenhouses at the University of Nottingham. We find that the mathematical model developed in this thesis is able to predict the growth of a population of bambara groundnut well and we go on to optimise the arrangement of individual plants for a series of scenarios. The primary aim of this is to maximise crop yield. Whilst formulated specifically for bambara groundnut, our model may also be extended to other crop species. In this thesis we demonstrate that the model is also able to simulate the growth of oil palm. We then apply the mathematical model to maximise crop yield in an intercropping environment; the planting of two or more species together in the same field area. We again investigate a series of scenarios that require optimisation and find that the optimisation techniques are able to provide plausible recommendations. This work has been undertaken in a multidisciplinary environment involving interactions with Plant Scientists at the University of Nottingham (Nottingham and Malaysia) and the Crops for the Future Research Centre, Malaysia.
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Bryan, Rebecca. "Large scale, multi femur computational stress analysis using a statistical shape and intensity model." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/185087/.
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Bellidega, Krishna Chaitanya. "Multi Scale Computational Model for Deformation Behavior of Non-Metallic Inclusions in Metal Forming." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1483459241280488.
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Zhou, Haiying. "Multi-scale model analysis of O2 transport and metabolism effects of hypoxia and exercise /." Cleveland, Ohio : Case Western Reserve University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1254502393.
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Wong, John Kam-wing. "Three-dimensional multi-scale hydraulic fracturing simulation in heterogeneous material using Dual Lattice Model." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/270542.
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Hydraulic fracturing is a multi-physics multi-scale problem related to natural processes such as the formation of dikes. It also has wide engineering applications such as extraction of unconventional resources, enhanced geothermal energy and carbon capture and storage. Current simulators are highly simplified because of the assumption of homogeneous reservoir. Unconventional reservoirs are heterogeneous owing to the presence of natural fracture network. Because of high computational effort, three-dimensional multi-scale simulations are uncommon, in particular, modelling material as a heterogeneous medium. Lattice Element Method (LEM) is therefore proposed for multi-scale simulation of heterogeneous material. In LEM, material is discretised into cells and their interactions are modelled by lattices, hence a three-dimensional model is simplified to a network of one-dimensional lattice. Normal, shear and rotational springs are used to define the constitutive laws of a lattice. LEM enables desktop computers for simulation of a lattice model that consists of millions of lattices. From simulations, normal springs govern the macroscopic bulk deformation while shear springs govern the macroscopic distortion. There is fluctuation of stresses even under uniform loading which is one of the characteristics of a lattice model. The magnitude increases with the stiffness ratio of shear spring to normal spring. Fracturing process can be modelled by LEM by introducing a microscopic tensile strength and a microscopic shear strength to the lattice properties. The strength parameters can be related to fracture toughness with the length scales of cells. From simulations, the relationships between model parameters and macroscopic parameters that are measurable in experiments are identified. From the simulations of uni-axial tension tests, both the spring stiffness ratio and the applied heterogeneity govern the fracturing process. The heterogeneity increases the ductility at the expense of the reduction on the macroscopic strengths. Different stages of fracturing are identified which are characterised by the model heterogeneity. Heterogeneous models go through the stages of the spatially distributed microscrack formation, the growth of multiple fracture clusters to the dominant fracture propagation. For homogeneous models, one of the microcracks rapidly propagates and becomes a dominant fracture with the absence of intermediate stages. From the uni-axial compression test simulations, the peak compressive stress is reached at the onset of the microscopic shear crack formation. Ductility is governed by the stiffness reduction ratio of a lattice in closed fractured stage to its unfractured stage. A novel Dual Lattice Model (DLM) is proposed for hydraulic fracture simulation by coupling a solid lattice model with a fluid lattice model. From DLM simulations of hydraulic fracturing of the classical penny shape crack problem under hydrostatic condition, the heterogeneities from both the fracture asperity and the applied heterogeneity increase the apparent fracture toughness. A semi-analytical solution is derived to consider the effect of fluid viscosity in the elastic deformation regime. Two asymptotes are identified that gives steep pressure gradients near the injection point and near the fracture tip which are also identified in the DLM simulations. Simulations also show three evolving regimes on energy dissipation/transfer mechanisms: the viscosity dominant, the elastic deformation dominant and the mixture of elastic deformation and toughness.
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Manubens-Gil, Linus 1989. "Computationl and modeling approaches to multi-scale anatomical description of neuronal circuitry." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664511.
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During the last century the nervous system has been mainly studied from a reductionistic approach, based on the hypothesis that understanding in depth single neurons or limited neuronal populations would lead to general conclusions on brain function. However, to what extent anatomical details of single neurons can affect the wiring of the networks they form is a largely overlooked question. Intellectual disability provides an excellent opportunity to explore the relevance of fine structural details, because many disorders show specific architectural alterations that correlate with cognitive performance.
In this Thesis, I aimed to study how the network topology of neuronal circuits is affected by dendritic architectural features in a mouse model of intellectual disability, namely Down's syndrome, and upon the rewiring effect of pro-cognitive treatment. I did so from three points of view:
1. The exploration of a 2D minimal computational model of cortical layer II/III parameterized by experimental data on dendritic tree architecture of healthy mice and two Down syndrome mouse models
2. The study of within-region morphological variations of hippocampal CA1 pyramidal neurons and their dependency of spatial embedding and cellularity in healthy mice and a Down syndrome mouse model.
3. The development of an experimental and computational framework for whole brain multiscale assessment and reconstruction.
My work revealed that the dendritic tree architecture and the distribution of synaptic contacts have significant implications on how optimal single neurons are for information processing efficiency and storage capacity, and that those single-neuron features permeate to the network level, determining the computational capacities of neural ensembles.
Also, I found position-dependent neuromorphological inhomogeneities in CA1 pyramids along with variations of neuronal cell density, suggesting that intrinsic properties of CA1 can vary across its extension. Those inhomogeneities were different in healthy and TgDyrk1A mice, possibly affecting emergent functional aspects.
In my Thesis I faced challenges to bridge structure and function and to study morphological inhomogeneities at different scale (single cell and cell population). To solve
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those challenges, I developed computational methods for 3D mapping cellular population and dendritic density and assessed their validity. I also developed a computational modeling framework that allows the instantiation of multi-scale biologically realistic networks. Finally, I optimized the CLARITY whole-brain clearing technique and developed a pipeline to apply our population-based analysis and multi-scale modeling methods to the structural interrogation of whole brains, and to study the implications of the neuronal morphospace on the topology of neuronal circuitry.Durant l’últim segle, el sistema nerviós s’ha estudiat des d’un punt de vista reduccionista, basant-se en la hipòtesi que entendre en profunditat neurones individuals o fraccions petites de poblacions neuronals portaria a conclusions generals sobre la funció del cervell. De totes maneres, fins a quin punt detalls anatòmics de neurones individuals poden afectar la connectivitat de les xarxes que formen, és una qüestió que en gran part s’ha passat per alt. Les discapacitats intel·lectuals proporcionen una oportunitat excel·lent per explorar la rellevància de detalls estructurals, perquè molts trastorns cognitius mostren alteracions arquitectòniques específiques que correlacionen amb habilitats cognitives. En aquesta Tesi, pretenia estudiar com la topologia dels circuits neuronals és afectada per característiques arquitectòniques en un model murí de discapacitat intel·lectual, en concret de síndrome de Down, i per tractaments pro-cognitius amb efectes de remodel·lació de la xarxa. Ho he fet des de tres punts de vista: 1. L’exploració d’un model computacional 2D mínim de la capa cortical II/III parametritzat amb dades experimentals d’arquitectura dendrítica ens els nostres models de síndrome de Down. 2. L’estudi de neurones individuals, la seva diversitat i propietats morfològiques d’escala mesoscòpica en el model murí TgDyrk1A de síndrome de Down. 3. El desenvolupament d’un marc experimental i computacional per a l’estudi del problema des d’una perspectiva multi-escala. La meva feina ha mostrat que l’arquitectura dendrítica i la distribució de contactes sinàptics tenen implicacions significatives en l’optimalitat de neurones individuals per a l’eficiència en el processat d’informació i per a la capacitat d’emmagatzemar memòries, i que aquestes dues quantitats permeen al nivell de xarxa, determinant les capacitats computacionals de conjunts de neurones. També, he trobat variacions neuromorfològiques a CA1 dependents de la posició en neurones piramidals, acompanyades per variacions en densitat cel·lular, apuntat que propietats intrínseques de CA1 poden variar al llarg de la seva extensió. Aquestes inhomogeneitats eren diferents en ratolins sans i TgDyrk1A, possiblement tenint efectes en aspectes funcionals emergents concrets. xiv En la meva Tesi he afrontat reptes en lligar estructura i funció i en l’estudi de les inhomogeneïtats morfològiques en múltiples escales (de cèl·lula individual i de poblacions). Per a assolir aquests reptes, he desenvolupat mètodes computacionals per al mapejat 3D de poblacions cel·lulars i de densitats dendrítiques i he avaluat la seva validesa. També he desenvolupat un marc de modelització que permet l’instanciació multi-escala de xarxes neuronals biològicament realistes. Finalment, he optimitzat la tècnica de clarejat de cervell sencer CLARITY i he desenvolupat un pipeline per a aplicar les nostres eines d’anàlisi de poblacions i els mètodes multi-escala de model·lizatió per a l’anàlisi estructural de cervells sencers, i per a l’estudi de les implicacions del morfoespai neuronal en la topologia de la circuiteria neuronal.
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Bhattacharya-Ghosh, B. "Development of a multi-scale and multi-physics model of the left ventricle and its application in 0D and 3D." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1427189/.
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This thesis describes the development of a multi-scale and multi-physics model of the left ventricle in silico. The model presented here, provides a computational model that allows further insight into the events and mechanism describing the ventricular contraction and relaxation (excitation contraction coupling process) at low computational costs. The formalisms and methods describing the electro-mechanical coupling (from intracellular, to electrical, to flow, to physiology mechanisms) across the scales are presented in a novel manner, coherently combining the various processes of all scales from a biological and mathematical point of view. The multiple scales involved in the model encompass the protein, cellular and organ level. In order to achieve this, at each scale the typical characteristics and mechanisms, such as the Action Potential, cross-bridge kinetics, pressure-volume relationship are simulated, extrapolating the behaviour of a ventricular cardiomyocyte to the whole ventricle. The coupling between the three scales presented is achieved via two links, the intracellular calcium concentration and the cross-bridge kinetics. The generation of force calculated at the organ level gives further insight on the cardiovascular haemodynamics, such as changes in pressure, flow and volume. In collaboration with TU/e, Netherlands, the presented multi-scale and multi-physics model of the left ventricle (developed in MATLAB) is expanded to a whole heart model in SIMULINK, enabling to investigate the behaviour of a healthy heart. Following, a case study of idiopathic dilated cardiomyopathy is conducted. While mainly the effects of idiopathic dilated cardiomyopathy (IDC) are presented in literature, it lacks of quantitative data to describe these effects. To simulate the effects of IDC, as shown in corresponding literature, key parameters across all scales were chosen and modified in the multi-scale model of the heart. A second collaboration with ANSYS UK demonstrates the feasibility of the ventricular multi-scale and multi-physics model as a boundary condition, being coupled to a 3D Model in ANSYS. The interaction and exchange of ventricular pressure and mitral flow between MATLAB and ANSYS, respectively, drives the local haemodynamics of the mitral valve in a CFX model. The 0D-3D coupling sets a foundation and coupling technique that can be further expanded to other models and conduct case studies on pathologies of the heart.
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D'AMATO, VINCENZO STEFANO. "Deep Multi Temporal Scale Networks for Human Motion Analysis." Doctoral thesis, Università degli studi di Genova, 2023. https://hdl.handle.net/11567/1104759.
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The movement of human beings appears to respond to a complex motor system that contains signals at different hierarchical levels.
For example, an action such as ``grasping a glass on a table'' represents a high-level action, but to perform this task, the body needs several motor inputs that include the activation of different joints of the body (shoulder, arm, hand, fingers, etc.).
Each of these different joints/muscles have a different size, responsiveness, and precision with a complex non-linearly stratified temporal dimension where every muscle has its temporal scale.
Parts such as the fingers responds much faster to brain input than more voluminous body parts such as the shoulder.
The cooperation we have when we perform an action produces smooth, effective, and expressive movement in a complex multiple temporal scale cognitive task.
Following this layered structure, the human body can be described as a kinematic tree, consisting of joints connected.
Although it is nowadays well known that human movement and its perception are characterised by multiple temporal scales, very few works in the literature are focused on studying this particular property.
In this thesis, we will focus on the analysis of human movement using data-driven techniques.
In particular, we will focus on the non-verbal aspects of human movement, with an emphasis on full-body movements.
The data-driven methods can interpret the information in the data by searching for rules, associations or patterns that can represent the relationships between input (e.g. the human action acquired with sensors) and output (e.g. the type of action performed).
Furthermore, these models may represent a new research frontier as they can analyse large masses of data and focus on aspects that even an expert user might miss.
The literature on data-driven models proposes two families of methods that can process time series and human movement.
The first family, called shallow models, extract features from the time series that can help the learning algorithm find associations in the data.
These features are identified and designed by domain experts who can identify the best ones for the problem faced.
On the other hand, the second family avoids this phase of extraction by the human expert since the models themselves can identify the best set of features to optimise the learning of the model.
In this thesis, we will provide a method that can apply the multi-temporal scales property of the human motion domain to deep learning models, the only data-driven models that can be extended to handle this property.
We will ask ourselves two questions: what happens if we apply knowledge about how human movements are performed to deep learning models? Can this knowledge improve current automatic recognition standards?
In order to prove the validity of our study, we collected data and tested our hypothesis in specially designed experiments.
Results support both the proposal and the need for the use of deep multi-scale models as a tool to better understand human movement and its multiple time-scale nature.
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Hilscher, Paul Peter. "Study of multi-scale interaction and dissipation based on gyro-kinetic model in fusion plasmas." Kyoto University, 2013. http://hdl.handle.net/2433/180447.
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Baelden, Camille. "A multi-scale model for piston ring dynamics, lubrication and oil transport in internal combustion engines." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92151.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 215-218).
Fuel consumption reduction of more than 20% can be achieved through engine friction reduction. Piston and piston rings contribute approximately half of the total engine friction and are therefore central to friction reduction efforts. The most common method to reduce mechanical losses from piston rings has been to lower ring tension, the normal force providing sealing between the piston ring and the cylinder liner. However tension reduction can result in additional lubricant consumption. The objective of this thesis is to understand and model the physical mechanisms resulting in flow of oil to the combustion chamber in order to achieve optimal designs of piston rings. The optimal design is a compromise between friction reduction and adequate gas and lubricant sealing performance. To do so a multi-scale curved beam finite element model of piston ring is developed. It is built to couple ring deformation, dynamics and contact with the piston and the cylinder. Oil flow at the interfaces between the ring and the cylinder liner and between the ring and the piston groove can thus be simulated. The piston ring model is used to study the sealing performance of the Oil Control Ring (OCR), whose function is to limit the amount of oil supplied to the ring pack. The contributions of the three main mechanisms previously identified, to oil flow past the OCR are quantified: - Deformation of the cylinder under operating conditions can lead to a loss of contact between the ring and the liner. - Tilting of the piston around its pin can force the OCR to twist and scrape oil from the liner. - Oil accumulating below the OCR can flow to the groove and leak on the top of the OCR The OCR is found to be flexible enough to limit the impact of cylinder deformation on oil consumption. Both ring scraping and flow through the OCR groove can contribute to oil consumption in the range of engine running conditions simulated. Reduction of scraping is possible by increasing the ability of both OCR lands to maintain contact with the liner regardless of piston groove tilt. The flow of oil through the OCR groove can be reduced by designing appropriate draining of oil in the groove and an adequate oil reservoir below the OCR. The piston ring oil transport model developed in this thesis will be a valuable tool to optimize ring pack designs to achieve further ring pack friction reduction without increasing oil consumption.
by Camille Baelden.
Ph. D.
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Ogbonna, Emmanuel. "A multi-parameter empirical model for mesophilic anaerobic digestion." Thesis, University of Hertfordshire, 2017. http://hdl.handle.net/2299/17467.
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Anaerobic digestion, which is the process by which bacteria breakdown organic matter to produce biogas (renewable energy source) and digestate (biofertiliser) in the absence of oxygen, proves to be the ideal concept not only for sustainable energy provision but also for effective organic waste management. However, the production amount of biogas to keep up with the global demand is limited by the underperformance in the system implementing the AD process. This underperformance is due to the difficulty in obtaining and maintaining the optimal operating parameters/states for anaerobic bacteria to thrive with regards to attaining a specific critical population number, which results in maximising the biogas production. This problem continues to exist as a result of insufficient knowledge of the interactions between the operating parameters and bacterial community. In addition, the lack of sufficient knowledge of the composition of bacterial groups that varies with changes in the operating parameters such as temperature, substrate and retention time. Without sufficient knowledge of the overall impact of the physico-environmental operating parameters on anaerobic bacterial growth and composition, significant improvement of biogas production may be difficult to attain. In order to mitigate this problem, this study has presented a nonlinear multi-parameter system modelling of mesophilic AD. It utilised raw data sets generated from laboratory experimentation of the influence of four operating parameters, temperature, pH, mixing speed and pressure on biogas and methane production, signifying that this is a multiple input single output (MISO) system. Due to the nonlinear characteristics of the data, the nonlinear black-box modelling technique is applied. The modelling is performed in MATLAB through System Identification approach. Two nonlinear model structures, autoregressive with exogenous input (NARX) and Hammerstein-Wiener (NLHW) with different nonlinearity estimators and model orders are chosen by trial and error and utilised to estimate the models. The performance of the models is determined by comparing the simulated outputs of the estimated models and the output in the validation data. The approach is used to validate the estimated models by checking how well the simulated output of the models fits the measured output. The best models for biogas and methane production are chosen by comparing the outputs of the best NARX and NLHW models (each for biogas and methane production), and the validation data, as well as utilising the Akaike information criterion to measure the quality of each model relative to each of the other models. The NLHW models mhw2 and mhws2 are chosen for biogas and methane production, respectively. The identified NLHW models mhw2 and mhws2 represent the behaviour of the production of biogas and methane, respectively, from mesophilic AD. Among all the candidate models studied, the nonlinear models provide a superior reproduction of the experimental data over the whole analysed period. Furthermore, the models constructed in this study cannot be used for scale-up purpose because they are not able to satisfy the rules and criteria for applying dimensional analysis to scale-up.
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Kim, Hee Sun. "Nonlinear multi-scale anisotropic material and structural models for prosthetic and native aortic heart valves." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29671.
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Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009.Committee Chair: Haj-Ali, Rami; Committee Member: White, Donald; Committee Member: Will, Kenneth; Committee Member: Yavari, Arash; Committee Member: Yoganathan, Ajit. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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El-Bouri, Wahbi K. "Multi-scale modelling of the microvasculature in the human cerebral cortex." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:8a9409a6-6279-4f7b-a975-b70149732378.
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Cerebrovascular diseases are by far the largest causes of death in the UK, as well as one of the leading causes of adult disability. The brain's healthy function depends on a steady supply of oxygen, delivered through the microvasculature. Cerebrovascular diseases, such as stroke and dementia, can interrupt the transport of blood (and hence oxygen) rapidly, or over a prolonged period of time. An interruption in flow can lead to ischaemia, with prolonged interruptions leading to tissue death and eventual brain damage. The microvasculature plays a key role in the transport of oxygen and nutrients to brain tissue; however, its role in diseases such as dementia is poorly understood, primarily due to the inability of current clinical imaging techniques to resolve microvessels, and due to the complexity of the underlying microvasculature. Therefore, in order to understand cerebrovascular diseases, it is necessary to be able to resolve and understand the microvasculature. In particular, generating large-scale models of the human microvasculature that can be linked back to contemporary clinical imaging is important in helping plug the current imaging gap that exists. A novel statistical model is proposed here that generates such large-scale models efficiently. Homogenization theory is used to generate a porous continuum capillary bed (characterised by its permeability) that allows for the efficient scaling up of the microvasculature. A novel order-based density-filling algorithm is then developed which generates morphologically accurate penetrating arterioles and venules, also demonstrating that the topology of the vessels only has a minor influence on CBF compared to diameter. Finally, the capillary bed and penetrating vessels are coupled into a large voxel-sized model of the microvasculature from which pressure and flux variations through the voxel can be analysed. A decoupling of the pressure and flux, as well as a layering of flow, was observed within the voxel, driven by the topology of the penetrating vessels. Micro-infarctions were also simulated, demonstrating the large local effects they have on the pressure and flux, whilst only causing a minor drop in CBF within the voxel.
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Giang, Ngoc Anh [Verfasser], Christoph [Akademischer Betreuer] Broeckmann, and Dieter [Akademischer Betreuer] Weichert. "Multi-scale model for fatigue in carbide rich tool steel / Ngoc Anh Giang ; Christoph Broeckmann, Dieter Weichert." Aachen : Universitätsbibliothek der RWTH Aachen, 2015. http://d-nb.info/1127599208/34.
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Ruprecht, Daniel [Verfasser]. "Analysis of a multi-scale asymptotic model for internal gravity waves in a moist atmosphere / Daniel Ruprecht." Berlin : Freie Universität Berlin, 2010. http://d-nb.info/1024784584/34.
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Osorio, Ruben. "Transient Multi-scale Computational Fluid Dynamics (CFD) Model for Thrombus Tracking in an Assit Device Vascular Bed." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5831.
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Heart failure occurs when the heart is not capable to pump blood at a sufficient rate to meet the demands of the body. Depending on the health of the heart, doctors may recommend a heart transplant, but finding a suitable donor is often a long duration process and the patient might be at an advance condition or the patient is not adequate for a heart transplant. In such cases Ventricular assist devices (VAD) are implemented. The purpose of a VAD is to aid the heart to pump the correct amount of blood, by doing so it relives the load that is put on the heart while giving the patient a chance for recovery. This study focuses on observing the hemodynamic effects of implementing a left ventricular assist device (LVAD) along the aortic arch and main arteries. Thrombi creation and transportation is other subject included in the study, due to the fact that thrombi can obstruct blood flow to critical arteries, manly carotid and vertebral. Occlusion of these can lead to a stroke with devastating effects on the neurocognitive functions and even death. A multi-scale CFD analysis a patient specific geometry model is used as well as a lumped system which provides the correct conditions in order to simulate the whole cardiovascular system. The main goal of the study is to understand the difference in flow behavior created by the unsteady pulsatile boundary conditions. The model described in this work has a total cardiac output of 7.0 Liters/ minute, this for a healthy heart. Two cardiac output splits are used to simulate heart failure conditions. The first split consists of 5 Liters/minute flowing through the LVAD cannula and 2 Liters/minute via the aortic root. The second scenario is when heart iv failure is critical, meaning that zero flow is being output by the left ventricle, thus a split of 7 Liter/minute trough the LVAD cannula and 0 Liters/minute traveling through the aortic root. A statistical analysis for the thrombi motion throughout the patient aortic arch was performed in order to quantify the influence that pulsatile flow has on the particles being track. Spherical particles of 2mm, 4mm and 5mm were released and accounted in the statistical analysis for each of the two split configurations. The study focuses on particles that escaped on the outlet boundaries of the upper arteries (Right Carotid, Left Carotid, and Vertebral). Results exhibit the statistical comparison of means for each particle diameter as well as for the overall probability for the steady and unsteady flow condition.M.S.M.E.
Masters
Mechanical and Aerospace Engineering
Engineering and Computer Science
Mechanical Engineering; Thermo-Fluids
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Zhou, Haiying. "Multi-Scale Model Analysis of O2 Transport and Metabolism: Effects of Hypoxia and Exercise." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1254502393.
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Coulter, Melanie. "A multi-spatial-scale characterization of Lark Sparrow habitat and the management implications." Bowling Green State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1213657693.
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Wilson, Tammy L. "A Multi-scale Evaluation of Pygmy Rabbit Space Use in a Managed Landscape." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/706.
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Habitat selection has long been viewed as a multi-scale process. Observed species responses to resource gradients are influenced by variation at the scale of the individual, population, metapopulation, and geographic range. Understanding how species interact with habitat at multiple levels presents a complete picture of an organism and is necessary for conservation of endangered species. The main goal of this dissertation is to evaluate distribution, relative abundance, and habitat selection of a rare species, the pygmy rabbit Brachylagus idahoensis, at multiple scales in order to improve management and conservation for this species.
At the broadest scale, pygmy rabbit occurrence and relative abundance were modeled in the Duck Creek allotment of northern Utah using a hierarchical spatial model. Pygmy rabbits are not easily observable, and the model used two levels of indirect detection to make statistically rigorous spatial predictions. We found that the model predicted the general pattern of rabbit occurrence and abundance within the study area, and that there was spatial heterogeneity in the probability of pygmy rabbit occurrence within a study domain that was known to be occupied. The resulting model framework could be used to develop a long-term monitoring program for pygmy rabbits and other species for which hierarchically nested levels of indirect observation are collected.
The mid-scale analysis evaluated pygmy rabbit home range placement and movement with respect to sagebrush removal treatments using null models based on an optimal central place foraging behavior. While placement of home-range centers did not appear to be affected by the treatments, within-home range movements were farther from treatments than expected by the null models for two rabbits (of eight), and rabbits that approached treatment edges were less likely to enter treatments than expected by chance. Rabbits are not extirpated from sites that have been treated, but the observed reluctance to enter treated patches calls for caution when conducting sagebrush removal treatments near occupied pygmy rabbit burrows.
At the finest level of resolution, the spatial ecology of pygmy rabbit use of burrows was evaluated. Both the placement of burrows in general and pygmy rabbit use of burrows were clustered. While the habitat gradients experienced by each of the rabbits evaluated affected the modeled habitat selection responses, some generalities were observed. Selection of high cover suggests that pygmy rabbit use of burrows may be linked to predator avoidance behavior. Additionally, pygmy rabbit use of clustered burrows affects management actions including: habitat modeling, monitoring, and species introduction. Explicit attention to resource distribution will improve efforts to predict species responses to management actions.
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Mauree, Dasaraden. "Development of a multi-scale meteorological system to improve urban climate modeling." Phd thesis, Université de Strasbourg, 2014. http://tel.archives-ouvertes.fr/tel-01037982.
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This study consisted in the development of a canopy model (CIM), which could be use as an interface between meso-scale models used to simulate urban climate and micro-scale models used to evaluate building energy use. The development is based on previously proposed theories and is presented in different atmospheric conditions, with and without obstable. It has been shown, for example, that to be in coherence with the Monin-Obukhov Similarity Theory, that a correction term has to be added to the buoyancy term of the T.K.E. CIM has also been coupled with the meteorological meso-scale model WRF. A methodology was proposed to take advantage of both models (one being more resolved, the other one integrating horizontal transport terms) and to ensure a coherence of the results. Besides being more precise than the WRF model at the same resolution, this system allows, through CIM, to provide high resolved vertical profiles near the surface.
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Rahman, Mohammad Mahbubur. "Microscale modelling of cellular level transport and deformation during food drying." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/120676/1/Mohammad%20Mahbubur_Rahman_Thesis.pdf.
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This thesis contributed to the development of a microscale drying model to predict the actual moisture distribution and physical quality of food material during the drying process. This research has developed a novel methodology to create realistic cellular geometry from microscopic images of food material which can be used as an exact computational domain for the microscale drying model. The model developed is capable of predicting of the cellular level transport and the anisotropic deformation of food material during the drying. The results obtained from the model were validated against extensive experimental investigations.
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Tourigny, Etienne. "Multi-scale fire modeling in the neotropics: coupling a land surface model to a high resolution fire spread model, considering land cover heterogeneity." Instituto Nacional de Pesquisas Espaciais (INPE), 2014. http://urlib.net/sid.inpe.br/mtc-m21b/2014/05.30.00.36.
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Land-Use and Land-Cover Change (LUCC) is a major cause of biomass burning in neotropical ecosystems, through logging and slash-and-burn clearing of forests for agriculture and subsequent pasture burning. Current Dynamic Vegetation Models (DGVMs), the land surface components of Earth System Models (ESMs), are incapable of modeling fire processes in tropical rainforests, and do not represent the local-scale land surface properties and processes associated with LUCC and fire spread. The modeling of the complex interactions between LUCC, climate change, droughts and fire in the tropics requires a framework to simulate these components and their interactions across multiple scales. A new modeling framework is proposed, in order to better represent fire in the neotropics within DGVMs, by simulating fire spread and its interactions with LUCC and the global Earth System. This study consists of three parts: the implementation of \emph{subgrid tiling} in the INLAND DGVM and a multi-scale framework to down-scale the model to a finer scale; the implementation of a simple fire spread model and one-way coupling (downscaling) with the INLA:\"D mo del ; the validation of global burned area products in the "are of deforestation" for mo del calibration and validation. The implementation of \emph{subgrid tiling} in the INLAND DGVM has made it possible to represent different land surface types (natural or modified by human activities) inside a given mo del grid cell. However further work is needed in order to parametrize landscapes infiuenced by human activities. The custom fire spread model, coupled to the INLAND model, has demonstrated the ability to simulate realistic fire spread patterns and sensitivity to various parameters such as land cover type, deforestation patterns, the presence of roads, and wind speed and direction. Further work is needed in order to improve the parametrizations and consider air and fuel moisture and fuel content, as well as up-scaling the results to the coupled DGVM. The validation of global burned area products in the "are of deforestation" brings sufficient confidence in using these products for the calibration and validation of the fire components of DGVMs and ESMs in this region. This study has demonstrated the potential of the multi-scale modeling framework for studying the synergies between climate change, LUCC and fire in the neotropics.A mudança do uso e cobertura da terra (LUCC; \emph{Land-Use and Land-Cover Change}) é uma das principais causas de incêndios nas florestas neotropicais, principalmente pelo desmatamento e queima da floresta primária para usos agrícolas e subsequente queima de pasto. Os atuais Modelos Globais de Vegetação Dinâmica (DGVMs; \emph{Dynamic Vegetation Models}), os quais são o componente superficial de Modelos do Sistema Terrestre (ESMs; \emph{Earth System Models}), são incapazes de representar os processos do fogo em florestas tropicais úmidas e não representam em escala local as propriedades da superfície terrestre e os processos associados com o LUCC e a propagação do fogo. A modelagem das interações complexas entre LUCC, mudanças climáticas, secas e as queimadas nos trópicos requer um quadro para simular os diferentes componentes e suas interações em múltiplas escalas. Propõe-se um novo ambiente de modelagem para melhor representar o fogo nos ecossistemas neotropicais dentro dos DGVMs, simulando a propagação do fogo e as relações com LUCC e o sistema terrestre global. Este projeto de pesquisa consiste em três partes: implementação de \emph{subgrid tiling} no modelo INLAND e de um ambiente de modelagem multi-escala para fazer o \emph{downscaling} do modelo para a escala mais fina: implementação de um modelo simples de propagação do fogo e acoplamento unidirecional (downscaling) com o modelo INLAND; e validação de produtos globais de área queimada no "arco do desmatamento" para calibração e validação de modelos. A implementação de \emph{subgrid tiling} no modelo INLAND tornou possível a representação de diferentes tipos de superfície (naturais ou modificados por atividades humanas) dentro de uma determinada célula de grade do modelo. Ainda assim mais estudos são necessários a fim de parametrizar paisagens influenciadas pelas atividades humanas. O modelo de propagação do fogo, acoplado ao modelo INLAND, demonstrou a habilidade em simular padrões realistas de propagação do fogo e sensibilidade à mudança de vários parâmetros, como o tipo de cobertura do solo, os padrões de desmatamento, a presença de estradas, e as velocidade e direção do vento. Em estudos futuros são necessários melhorias nas parametrizações e inclusão da umidade do ar e dos combustíveis, e a quantidade de combustível, bem como o \emph{upscaling} dos resultados para a DGVM acoplado. A validação de produtos globais de área queimada no "arco do desmatamento" traz confiança suficiente para o uso desses produtos na calibração e validação dos componentes de fogo dos DGVMs e ESMs nessa área. Este estudo demonstrou o potencial deste ambiente de modelagem multi-escala para estudar as sinergias entre mudanças climáticas, LUCC e fogo nos neotrópicos.
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Zareie, Rajani Hamid Reza. "Development of a three-dimensional multi-scale model to study the formation of solidification defects in fusion welding." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/57601.
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One of the long-standing challenges in joining of aluminum alloys is the occurrence of
solidification defects, i.e. hot cracking and porosity, since these defects significantly increase manufacturing costs. This research project investigates the formation of solidification defects through development of a novel and comprehensive 3-D multi-scale and multi-physics numerical study and then application to the GTA welding of the aluminum alloy AA6061. The developed multi-scale model is composed of four different modules: 1) Solidification, 2) Deformation, 3) Fluid flow, and 4) Defect formation. The solidification module numerically reconstructs the 3-D microstructure of semisolid welds using a granular model of solidification. Specifically, a modified Voronoi tessellation algorithm is used to generate an unstructured grid representing the weld microstructure. The reconstructed microstructure contains both columnar and equiaxed grains and varies as a function of welding process parameters. Then, the Scheil equation is used in combination with the temperature field obtained through the Rosenthal equation and the reconstructed 3D microstructure to simulate solidification. This module outputs the evolving 3D structure of the semisolid weld composed of solid grains and a network of micro liquid channels for use by the deformation and fluid flow modules as the simulation geometry. The deformation module analyzes via finite elements the deformation of the semisolid weld due to externally applied strains and self-induced strains such as thermo-mechanical strains and solidification shrinkage in order to obtain local strain rates within the micro liquid channels. The local strain rates outputted by the deformation module feed a fluid flow analysis module in which the pressure field within the semisolid weld is calculated. Finally, the defect formation module uses various defect formation models to link the pressure field and the local strain rates to the formation of solidification defects including micro cracks and hydrogen porosity.Applied Science, Faculty of
Engineering, School of (Okanagan)
Graduate
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Deshmukh, Kavita Pradeep Thiagarajan Ganesh. "Nano finite element modeling of the mechanical behavior of biominerals using a multi-scale (Virtual Internal Bond) model." Diss., UMK access, 2006.
Find full textAbstract:
Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2006."A thesis in civil engineering." Typescript. Advisor: Ganesh Thiagarajan. Vita. Title from "catalog record" of the print edition Description based on contents viewed Oct. 30, 2007. Includes bibliographical references (leaves 72-73). Online version of the print edition.
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Liang, Jiajian [Verfasser], and Ullrich [Akademischer Betreuer] Martin. "Metaheuristic-based dispatching optimization integrated in multi-scale simulation model of railway operation / Jiajian Liang ; Betreuer: Ullrich Martin." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2017. http://d-nb.info/1130148564/34.
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Liu, Yang Ph D. Massachusetts Institute of Technology. "A multi-scale model integrating both global ring pack behavior and local oil transport in internal combustion engines." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108944.
Full textAbstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 213-217).
Improving fuel economy of internal combustion engines is one of the major focuses in automotive industry. The piston ring friction contributes as much as 25% of total mechanical loss in internal combustion engines [1] and is an area of great interests to the automotive industry in their overall effort to improve engine efficiency. However, typical methods to reduce friction loss from piston ring pack, such as ring tension reduction, may cause additional oil consumption. A compromise between reduction of friction loss and control of gas leakage and oil consumption needs to be made, which requires a deep understanding of oil transport mechanism. This compromise gives rise to the interest in modeling work. Both experimental results and previous experience showed that oil film distribution on the piston varies significantly along the circumference and the oil leakage occurs locally. Therefore to predict oil transfer across different ring pack regions, one needs to integrate both global and local processes. This work is aimed at establishing an enduring framework for all the cycle-based processes at different length scales. As a first step, a multi-scale multi-physics piston ring pack model was developed by coupling the structural dynamics of the piston rings with gas flows and local interactions at ring-groove and ring-liner interfaces. A curved beam finite element method was adopted to calculate the ring structural response to interaction between the ring and the liner as well as the ring and the groove. Compared to a traditional straight beam finite element method, the curved beam separates the structural mesh and contact grid by utilizing the shape functions. In this work, a multi-length-scale ring pack model was, for the first time, successfully assembled. This model bears its fundamental values to truly reflect the integral results of all the relevant mechanisms. The significance of the current work is that it demonstrated such an integration of all the length scales is possible for a cycle model with a reasonable computation cost. With the current model, one can realistically investigate the effects of all kinds of piston and liner distortion, piston secondary motion, bridging, and lube-oil dilution on gas sealing, oil transport and lubrication. As a result, optimization of the ring designs and the part of block design contributing to bore distortion can be coordinated to reduce development costs.
by Yang Liu.
Ph. D.
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Sumner, T. "Sensitivity analysis in systems biology modelling and its application to a multi-scale model of blood glucose homeostasis." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19896/.
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Biological systems typically consist of large numbers of interacting components and involve processes at a variety of spatial, temporal and biological scales. Systems biology aims to understand such systems by integrating information from all functional levels into a single cohesive model. Mathematical and computational modelling is a key part of the systems biology approach and can be used to produce composite models which describe systems across multiple scales. One of the major diculties in constructing models of biological systems is the lack of precise parameter values which are often associated with a high degree of uncertainty. This uncertainty in parameter values can be incorporated into the modelling process using sensitivity analysis, the systematic investigation of the relationship between uncertain model inputs and the resulting variation in the model outputs. This thesis discusses the use of global sensitivity analysis in systems biology modelling and addresses two main problem areas: the application of sensitivity analysis to time dependent model outputs and the analysis of multi-scale models. An approach to the analysis of time dependent model outputs which makes use of principal component analysis to extract the key modes of variation from the data, is presented. The analysis of multi-scale models is addressed using group-based sensitivity analysis which enables the identication of the most important sub-processes in the model. Together these methods provide a new methodology for sensitivity analysis in multi-scale systems biology modelling. The methodology is applied to a composite model of blood glucose homeostasis that combines models of processes at the sub-cellular, cellular and organ level to describe the physiological system. The results of the analysis suggest three main points about the system: the mobilisation of calcium by glucagon plays a minor role in the regulation of glycogen metabolism; auto-regulation of hepatic glucose production by glucose is important in regulating blood glucose levels; time-delays between changes in blood glucose levels, the release of insulin by the pancreas and the eect of the hormone on hepatic glucose production are important in the possible onset of ultradian glucose oscillations. These results suggest possible directions for further study into the regulation of blood glucose.
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Holly, D. Christopher. "Multi-scale evaluation of mechanisms associated with the establishment of a model invasive species in Mississippi Imperata cylindrica /." Diss., Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-06052008-155216.
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Neureither, Lara [Verfasser], Carsten [Gutachter] Hartmann, Tony [Gutachter] Lelièvre, and Christof [Gutachter] Schütte. "Irreversible multi-scale diffusions: time scales and model reduction / Lara Neureither ; Gutachter: Carsten Hartmann, Tony Lelièvre, Christof Schütte." Cottbus : BTU Cottbus - Senftenberg, 2019. http://d-nb.info/120227546X/34.
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Corona, Núñez Rogelio Omar. "Multi-analysis of potential and actual above ground biomass in a tropical deciduous forest in Mexico." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28844.
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Natural tropical deciduous forest (TDF) is considered with a medium to small height (< 15 m). Particularly, in Mexico TDF shows a remnant of 36.2% of primary forest driving changes in the structure and species composition. This vegetation in Mexico is mainly transformed into grassland for cattle raising, and agriculture, primarily for self-consumption. More information about the ecology and the social pressures on this vegetation can be seen in Chapter I. The general methods, including sampling allocation and collection, characteristics of the study site, as well the procedure of the research proposal is presented in Chapter II. The main aim of this thesis is to improve the accuracy of predictions of net carbon emissions and the spatial distribution of AGB in the Tropical Deciduous Forest of Mexico. To address this aim, it is important to take into consideration the forest structure, spatial patterns and processes in a natural forest in a multi-scale analysis; also, it is necessary to characterize the spatial socio-economic drivers that influence current AGB losses. With the understanding of such elements, it is possible to reconstruct the potential carbon stocks and estimate the allocation of net carbon emissions due to deforestation and forest degradation. This study shows that it is possible to count net carbon emissions caused by deforestation and forest degradation at a landscape scale. To come to such estimates, it was necessary to reduce the different sources of uncertainty. Chapter III explores different elements that drive the AGB allocation in a mature forest. The AGB in the mature forest was considered as the potential AGB that the forest could get assuming that it has reached its steady state. Different field sampling strategies and allometric equations were evaluated to account for uncertainty in the AGB estimations. The results showed that small sampling design (300-400 m2) and large-sized plots (4 ha) produce the same tree distribution for trees: ≥30 cm in DBH as well as in AGB. These results contradict what has been reported for others (Chave et al., 2004 and 2005) when they refer to the general definition of tropical forest. However, those other studies referred to forests with a much higher precipitation and which can be classified as tropical rain (perennial) forest (Chave et al., 2004). In the tropical deciduous forest, the kind considered in this study, AGB tends to be allocated in small-sized trees. Diverse biophysical characteristics that may drive AGB allocation were considered over different spatial scales. Water stress was the main driver for AGB density at different spatial scales. Nutrients showed little significance to explain AGB as other studies have suggested in secondary forests and/or chronosequences. With this understanding, Chapter IV shows the use of different multi-variable models. Parsimonious models were the result of the variables selection and sensitivity test. Most of the methodologies showed a better performance to explain AGB allocation than a null-model. However, when they were contrasted with independent observations over different spatial resolutions, it was possible to conclude that only GLM was capable of reproducing the spatial patterns, and its estimations were close to observations. Nevertheless, some observations with very large AGB densities were underestimated by the model. This underestimation was related to the presence of few very large-sized trees. These two chapters depict the possibility of accounting for the potential AGB, and the uncertainty, namely whether the landscape could reach it with the absence of human disturbance. Once the potential AGB map was built and validated, it was transformed to carbon stock, using a local carbon concentration estimate. This potential carbon stock map was contrasted to the different available maps of current carbon stocks. Consequently, it was possible to estimate net carbon emissions due to deforestation and forest degradation (Chapter V), suggesting that the general models tend to agree in the total carbon loss. However, there are some spatial discrepancies in the magnitudes of change. Main differences between maps can be reduced by diverse socio-ecological constraints that dominate the landscape. This is important because it may be possible to make future adjustments that would reduce variability, enabling more accurate AGB estimations. However, to individually account for deforestation and forest degradation, more detailed sources of local information are necessary, such as socio-economic variables. Therefore models with a bottom-up perspective would lead to a better understanding and representation of the landscape. Finally, the growing rural population will have larger demands for wood and food, so while remote or protected areas may have the potential for storing high AGB, forest close to settlements and access routes are likely to continue being disturbed, unless affordable alternatives are available for the sustainable use of the forest. In conclusion, the estimation of spatial heterogeneity of AGB in the landscape is of great importance when measuring carbon stocks and ecological dynamics. Various elements influence the AGB allocation in the mature forest. Among all of them, water availability played the most decisive part of various spatial scales. My models support the hypothesis that water availability plays the major role in explaining AGB in Mexico on a local, sub-regional and landscape scale. Model selection produced contrasting AGB estimates and patterns. Moreover, the results of this study tell us that there is not a clear consensus among various current AGB maps. However, they also show that with a multi-model comparison it is possible to identify carbon emissions drivers and calculate total carbon emissions due to forest disturbances. Socio-economic variables played the major role in explaining AGB losses. Therefore, future studies should look into a bottom-up approach for a better understanding and representation of current AGB.
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Erbertseder, Karin Maria [Verfasser], and Rainer [Akademischer Betreuer] Helmig. "A multi-scale model for describing cancer-therapeutic transport in the human lung / Karin Maria Erbertseder. Betreuer: Rainer Helmig." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2012. http://d-nb.info/1023040921/34.
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Contarino, Christian. "A holistic multi-scale mathematical model of the murine extracellular fluid systems and study of the brain interactive dynamics." Doctoral thesis, Università degli studi di Trento, 2018. https://hdl.handle.net/11572/368994.
Full textAbstract:
Recent advances in medical science regarding the interaction and functional role of fluid compartments in the central nervous system have attracted the attention of many researchers across various disciplines. Neurotoxins are constantly cleared from the brain parenchyma through the intramural periarterial drainage system, glymphatic system and meningeal lymphatic system. Impairment of these systems can potentially contribute to the onset of neurological disorders. The goal of this thesis is to contribute to the understanding of brain fluid dynamics and to the role of vascular pathologies in the context of neurological disorders. To achieve this goal, we designed the first multi-scale, closed-loop mathematical model of the murine fluid system, incorporating: heart dynamics, major arteries and veins, microcirculation, pulmonary circulation, venous valves, cerebrospinal fluid (CSF), brain interstitial fluid (ISF), Starling resistors, Monro-Kellie hypothesis, brain lymphatic drainage and the modern concept of CSF/ISF drainage and absorption based on the {\em Bulat-Klarica-Orešković} hypothesis. The mathematical model relies on one-dimensional Partial Differential Equations (PDEs) for blood vessels and on Ordinary Differential Equations (ODEs) for lumped parameter models. The systems of PDEs and ODEs are solved through a high-order finite volume ADER method and through an implicit Euler method. The computational results are validated against literature values and magnetic resonance flow measurements. Furthermore, the model is validated against {\em in-vivo} intracranial pressure waveforms acquired in healthy mice and in mice with impairment of the intracranial venous outflow. Through a systematic use of our computational model in healthy and pathological cases, we provide a complete and holistic neurovascular view of the main murine fluid dynamics. We propose a hypothesis on the working principles of the glymphatic system, opening a new door towards a comprehensive understanding of the mechanisms which link vascular and neurological disorders. In particular, we show how impairment of the cerebral venous outflow might potentially lead to accumulation of solutes in the parenchyma, by altering CSF and ISF dynamics.
This thesis also concerns the development of a high-order ADER-type numerical method for systems of hyperbolic balance laws in networks, based on a new implicit solver for the junction-generalized Riemann problem. The resulting ADER scheme can deal with stiff source terms and can be applied to non-linear systems of hyperbolic balance laws in domains consisting of networks of one-dimensional sub-domains. Also, we design a novel one-dimensional mathematical model for collecting lymphatics coupled with a Electro-Fluid-Mechanical Contraction (EFMC) model for dynamical contractions. The resulting mathematical model gives each lymphangion the autonomous capability to trigger action potentials based on local fluid-dynamical factors.
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Contarino, Christian. "A holistic multi-scale mathematical model of the murine extracellular fluid systems and study of the brain interactive dynamics." Doctoral thesis, University of Trento, 2018. http://eprints-phd.biblio.unitn.it/2974/1/Thesis.pdf.
Full textAbstract:
Recent advances in medical science regarding the interaction and functional role of fluid compartments in the central nervous system have attracted the attention of many researchers across various disciplines. Neurotoxins are constantly cleared from the brain parenchyma through the intramural periarterial drainage system, glymphatic system and meningeal lymphatic system. Impairment of these systems can potentially contribute to the onset of neurological disorders. The goal of this thesis is to contribute to the understanding of brain fluid dynamics and to the role of vascular pathologies in the context of neurological disorders. To achieve this goal, we designed the first multi-scale, closed-loop mathematical model of the murine fluid system, incorporating: heart dynamics, major arteries and veins, microcirculation, pulmonary circulation, venous valves, cerebrospinal fluid (CSF), brain interstitial fluid (ISF), Starling resistors, Monro-Kellie hypothesis, brain lymphatic drainage and the modern concept of CSF/ISF drainage and absorption based on the {\em Bulat-Klarica-Orešković} hypothesis. The mathematical model relies on one-dimensional Partial Differential Equations (PDEs) for blood vessels and on Ordinary Differential Equations (ODEs) for lumped parameter models. The systems of PDEs and ODEs are solved through a high-order finite volume ADER method and through an implicit Euler method. The computational results are validated against literature values and magnetic resonance flow measurements. Furthermore, the model is validated against {\em in-vivo} intracranial pressure waveforms acquired in healthy mice and in mice with impairment of the intracranial venous outflow. Through a systematic use of our computational model in healthy and pathological cases, we provide a complete and holistic neurovascular view of the main murine fluid dynamics. We propose a hypothesis on the working principles of the glymphatic system, opening a new door towards a comprehensive understanding of the mechanisms which link vascular and neurological disorders. In particular, we show how impairment of the cerebral venous outflow might potentially lead to accumulation of solutes in the parenchyma, by altering CSF and ISF dynamics.
This thesis also concerns the development of a high-order ADER-type numerical method for systems of hyperbolic balance laws in networks, based on a new implicit solver for the junction-generalized Riemann problem. The resulting ADER scheme can deal with stiff source terms and can be applied to non-linear systems of hyperbolic balance laws in domains consisting of networks of one-dimensional sub-domains. Also, we design a novel one-dimensional mathematical model for collecting lymphatics coupled with a Electro-Fluid-Mechanical Contraction (EFMC) model for dynamical contractions. The resulting mathematical model gives each lymphangion the autonomous capability to trigger action potentials based on local fluid-dynamical factors.