Link Travel Time Estimation in Double-Queue-Based Traffic Models

Double queue concept has gained its popularity in dynamic user equilibrium (DUE) modeling because it can properly model real traffic dynamics. While directly solving such double-queue-based DUE problems is extremely challenging, an approximation scheme called first-order approximation was proposed to simplify the link travel time estimation of DUE problems in a recent study without evaluating its properties and performance. This paper focuses on directly investigating the First-In-First-Out property and the performance of the first-order approximation in link travel time estimation by designing and modeling dynamic network loading (DNL) on single-line stretch networks. After model formulation, we analyze the First-In-First-Out (FIFO) property of the first-order approximation. Then a series of numerical experiments is conducted to demonstrate the FIFO property of the first-order approximation, and to compare its performance with those using the second-order approximation, a point queue model, and the cumulative inflow and exit flow curves. The numerical results show that the first-order approximation does not guarantee FIFO and also suggest that the second-order approximation is recommended especially when the link exit flow is increasing. The study provides guidance for further study on proposing new methods to better estimate link travel times

Characterisation and modelling of natural fracture networks: geometry, geomechanics and fluid flow

Natural fractures are ubiquitous in crustal rocks and often dominate the bulk properties of geological formations. The development of numerical tools to model the geometry, geomechanics and fluid flow behaviour of natural fracture networks is a challenging issue which is relevant to many rock engineering applications. The thesis first presents a study of the statistics and tectonism of a multiscale fracture system in limestone, from which the complexity of natural fractures is illustrated with respect to hierarchical topologies and underlying mechanisms. To simulate the geomechanical behaviour of rock masses embedded with natural fractures, the finite-discrete element method (FEMDEM) is integrated with a joint constitutive model (JCM) to solve the solid mechanics problems of such intricate discontinuity systems explicitly represented by discrete fracture network (DFN) models. This computational formulation can calculate the stress/strain fields of the rock matrix, capture the mechanical interactions of discrete rock blocks, characterise the non-linear deformation of rough fractures and mimic the propagation of new cracks driven by stress concentrations. The developed simulation tool is used to derive the aperture distribution of various fracture networks under different geomechanical conditions, based on which the stress-dependent fluid flow is further analysed. A novel upscaling approach to fracture network models is developed to evaluate the scaling of the equivalent permeability of fractured rocks under in-situ stresses. The combined JCM-FEMDEM model is further applied to simulate the progressive rock mass failure around an underground excavation in a crystalline rock with pre-existing discontinuities. The scope of this thesis covers the scenarios of both two-dimensional (2D) and three-dimensional (3D) fracture networks with pre-existing natural fractures and stress-induced new cracks. The research findings demonstrate the importance of integrating explicit DFN representations and conducting geomechanical computations for more meaningful assessments of the hydromechanical behaviour of naturally fractured rocks.Open Acces

Lattice Element Method and its application to Multiphysics

In this thesis, a Lattice element modelling method is developed and is applied to model the loose and cemented, natural and artificial, granular matters subject to thermo-hydro-mechanical coupled loading conditions. In lattice element method, the lattice nodes which can be considered as the centres of the unit cells, are connected by cohesive links, such as spring beams that can carry normal and shear forces, bending and torsion moment. For the heat transfer due to conduction, the cohesive links are also used to carry heat as 1D pipes, and the physical properties of these rods are computed based on the Hertz contact model. The hydro part is included with the pore network modelling scheme. The voids are inscribed with the pore nodes and connected with throats, and then the meso level flow equation is solved. The Euler-Bernoulli and Timoshenko beams are chosen as the cohesive links or the lattice elements, while the latter should be used when beam elements are short and deep. This property becomes interesting in modelling auxetic materials. The model is applied to study benchmarks in geotechnical engineering. For heat transfer in the dry and full range of saturation, and fractures in the cemented granular media.How through porous media failure behaviours of rocks at high temperature and pressure and granular composites subjected to coupled Thermo hydro Mechanical loads. The model is further extended to capture the wave motion in the heterogeneous granular matter, and a few case studies for the wavefield modification with existing cracks are presented. The developed method is capable of capturing the complex interaction of crack wave interaction with relative ease and at a substantially less computational cost

A multi-scale homogenization scheme for modeling anisotropic material’s elastic and failure response

The effect of small-scale random defects such as microcracks or inclusions are critical to the prediction of material failure, yet including these in a fracture simulation can be difficult to perform efficiently. Typically, work has focused on implementing these through a statistical characterization of the micro- or meso-scales. This characterization has traditionally focused on the spatial distribution of faults, assuming the material is purely isotropic. At the macro-scale, many materials can be assumed to be fully isotropic and homogeneous, but at the small scale may show significant anisotropy or heterogeneity. Other materials may be effectively anisotropic in bulk, such as rock bedding planes. Statistical volume elements (SVE) are one homogenization methodology used to retain this heterogeneity or anisotropy when characterizing a material. Unlike a Representative Volume Element (RVE), the choice of SVE including size, boundary conditions applied, shape, and type, may affect the given material properties. In addition, the size which an RVE exists is well-studied for homogeneity, but there is less study of the isotropic limit. This work introduces a multi-scale methodology using SVEs to study material heterogeneity and anisotropy. Results are given for macroscopic fracture simulations using this SVE-based homogenization scheme. In addition, the rate of convergence to the RVE limit for both the homogeneous and isotropic limit of two types of SVE, Regular Square and Voronoi Square, are shown. This methodology shows promise for characterization of both isotropic and anisotropic materials

A statistical approach for fracture property realization and macroscopic failure analysis of brittle materials

Lacking the energy dissipative mechanics such as plastic deformation to rebalance localized stresses, similar to their ductile counterparts, brittle material fracture mechanics is associated with catastrophic failure of purely brittle and quasi-brittle materials at immeasurable and measurable deformation scales respectively. This failure, in the form macroscale sharp cracks, is highly dependent on the composition of the material microstructure. Further, the complexity of this relationship and the resulting crack patterns is exacerbated under highly dynamic loading conditions. A robust brittle material model must account for the multiscale inhomogeneity as well as the probabilistic distribution of the constituents which cause material heterogeneity and influence the complex mechanisms of dynamic fracture responses of the material. Continuum-based homogenization is carried out via finite element-based micromechanical analysis of a material neighbor which gives is geometrically described as a sampling windows (i.e., statistical volume elements). These volume elements are well-defined such that they are representative of the material while propagating material randomness from the inherent microscale defects. Homogenization yields spatially defined elastic and fracture related effective properties, utilized to statistically characterize the material in terms of these properties. This spatial characterization is made possible by performing homogenization at prescribed spatial locations which collectively comprise a non-uniform spatial grid which allows the mapping of each effective material properties to an associated spatial location. Through stochastic decomposition of the derived empirical covariance of the sampled effective material property, the Karhunen-Loeve method is used to generate realizations of a continuous and spatially-correlated random field approximation that preserve the statistics of the material from which it is derived. Aspects of modeling both isotropic and anisotropic brittle materials, from a statistical viewpoint, are investigated to determine how each influences the macroscale fracture response of these materials under highly dynamic conditions. The effects of modeling a material both explicitly by representations of discrete multiscale constituents and/or implicitly by continuum representation of material properties is studies to determine how each model influences the resulting material fracture response. For the implicit material representations, both a statistical white noise (i.e., Weibull-based spatially-uncorrelated) and colored noise (i.e., Karhunen-Loeve spatially-correlated model) random fields are employed herein

Scalable visual analytics over voluminous spatiotemporal data

2018 Fall.Includes bibliographical references.Visualization is a critical part of modern data analytics. This is especially true of interactive and exploratory visual analytics, which encourages speedy discovery of trends, patterns, and connections in data by allowing analysts to rapidly change what data is displayed and how it is displayed. Unfortunately, the explosion of data production in recent years has led to problems of scale as storage, processing, querying, and visualization have struggled to keep pace with data volumes. Visualization of spatiotemporal data pose unique challenges, thanks in part to high-dimensionality in the input feature space, interactions between features, and the production of voluminous, high-resolution outputs. In this dissertation, we address challenges associated with supporting interactive, exploratory visualization of voluminous spatiotemporal datasets and underlying phenomena. This requires the visualization of millions of entities and changes to these entities as the spatiotemporal phenomena unfolds. The rendering and propagation of spatiotemporal phenomena must be both accurate and timely. Key contributions of this dissertation include: 1) the temporal and spatial coupling of spatially localized models to enable the visualization of phenomena at far greater geospatial scales; 2) the ability to directly compare and contrast diverging spatiotemporal outcomes that arise from multiple exploratory "what-if" queries; and 3) the computational framework required to support an interactive user experience in a heavily resource-constrained environment. We additionally provide support for collaborative and competitive exploration with multiple synchronized clients