<p align="justify">The conservation of structures of the historical heritage is an increasing concern nowadays for public authorities. The technical design phase of repair operations for these structures is of prime importance. Such operations usually require an estimation of the residual strength and of the potential structural failure modes of structures to optimize the choice of the repairing techniques.</p> <p align="justify">Although rules of thumb and codes are widely used, numerical simulations now start to emerge as valuable tools. Such alternative methods may be useful in this respect only if they are able to account realistically for the possibly complex failure modes of masonry in structural applications.</p> <p align="justify">The mechanical behaviour of masonry is characterized by the properties of its constituents (bricks and mortar joints) and their stacking mode. Structural failure mechanisms are strongly connected to the mesostructure of the material, with strong localization and damage-induced anisotropy.</p> <p align="justify">The currently available numerical tools for this material are mostly based on approaches incorporating only one scale of representation. Mesoscopic models are used in order to study structural details with an explicit representation of the constituents and of their behaviour. The range of applicability of these descriptions is however restricted by computational costs. At the other end of the spectrum, macroscopic descriptions used in structural computations rely on phenomenological constitutive laws representing the collective behaviour of the constituents. As a result, these macroscopic models are difficult to identify and sometimes lead to wrong failure mode predictions.</p> <p align="justify">The purpose of this study is to bridge the gap between mesoscopic and macroscopic representations and to propose a computational methodology for the analysis of plane masonry walls. To overcome the drawbacks of existing approaches, a multi-scale framework is used which allows to include mesoscopic behaviour features in macroscopic descriptions, without the need for an a priori postulated macroscopic constitutive law. First, a mesoscopic constitutive description is defined for the quasi-brittle constituents of the masonry material, the failure of which mainly occurs through stiffness degradation. The mesoscopic description is therefore based on a scalar damage model. Plane stress and generalized plane state assumptions are used at the mesoscopic scale, leading to two-dimensional macroscopic continuum descriptions. Based on periodic homogenization techniques and unit cell computations, it is shown that the identified mesoscopic constitutive setting allows to reproduce the characteristic shape of (anisotropic) failure envelopes observed experimentally. The failure modes corresponding to various macroscopic loading directions are also shown to be correctly captured. The in-plane failure mechanisms are correctly represented by a plane stress description, while the generalized plane state assumption, introducing simplified three-dimensional effects, is shown to be needed to represent out-of-plane failure under biaxial compressive loading. Macroscopic damage-induced anisotropy resulting from the constituents' stacking mode in the material, which is complex to represent properly using macroscopic phenomenological constitutive equations, is here obtained in a natural fashion. The identified mesoscopic description is introduced in a scale transition procedure to infer the macroscopic response of the material. The first-order computational homogenization technique is used for this purpose to extract this response from unit cells. Damage localization eventually appears as a natural outcome of the quasi-brittle nature of the constituents. The onset of macroscopic localization is treated as a material bifurcation phenomenon and is detected from an eigenvalue analysis of the homogenized acoustic tensor obtained from the scale transition procedure together with a limit point criterion. The macroscopic localization orientations obtained with this type of detection are shown to be strongly related to the underlying mesostructural failure modes in the unit cells.</p> <p align="justify">A well-posed macroscopic description is preserved by embedding localization bands at the macroscopic localization onset, with a width directly deduced from the initial periodicity of the mesostructure of the material. This allows to take into account the finite size of the fracturing zone in the macroscopic description. As a result of mesoscopic damage localization in narrow zones of the order of a mortar joint, the material response computationally deduced from unit cells may exhibit a snap-back behaviour. This precludes the use of such a response in the standard strain-driven multi-scale scheme.</p> <p align="justify">Adaptations of the multi-scale framework required to treat the mesostructural response snap-back are proposed. This multi-scale framework is finally applied for a typical confined shear wall problem, which allows to verify its ability to represent complex structural failure modes.</p>

Computational study of the structural, thermodynamic and transport properties of polymeric materials at equilibrium requires multi-scale modeling techniques due to processes occurring across a broad spectrum of time and length scales. Classical molecular-level simulation, such as Molecular Dynamics (MD), has proved very useful in the study of polymeric oligomers or short chains. However, there is a strong, nonlinear dependence of relaxation time with respect to chain length that requires the use of less computationally demanding techniques to describe the behavior of longer chains. As one of the mesoscale modeling techniques, Coarse-grained (CG) procedure has been developed recently to extend the molecular simulation to larger time and length scales. With a CG model, structural and dynamics of long chain polymeric systems can be directly studied though CG level simulation. In the CG simulations, the generation of the CG potential is an area of current research activity. The work in this dissertation focused on both the development of techniques for generating CG potentials as well as the application of CG potentials in Coarse-grained Molecular Dynamics (CGMD) simulations to describe structural, thermodynamic and transport properties of various polymer systems. First, an improved procedure for generated CG potentials from structural data obtained from atomistic simulation of short chains was developed. The Ornstein-Zernike integral equation with the Percus Yevick approximation was invoked to solve this inverse problem (OZPY-1). Then the OZPY-1 method was applied to CG modeling of polyethylene terephthalate (PET) and polyethylene glycol (PEG). Finally, CG procedure was applied to a model of sulfonated and cross-linked Poly (1, 3-cyclohexadiene) (sxPCHD) polymer that is designed for future application as a proton exchange membrane material used in fuel cell. Through above efforts, we developed an understanding of the strengths and limitations of various procedures for generating CG potentials. We were able to simulate entangled polymer chains for PET and study the structure and dynamics as a function of chain length. The work here also provides the first glimpses of the nanoscale morphology of the hydrated sxPCHD membrane. An understanding of this structure is important in the prediction of proton conductivity in the membrane.

Iterative competition between organisms for limited resources gives rise to different social strategies including cooperation. One specific problem in the cooperating but competing species in that cost associated in exhibiting cooperative traits provokes "cheating". Cheaters acquire relatively higher fitness by reaping the benefits of cooperation without contributing towards community beneficial goods. While the relatively fit cheaters can drive the contributors to extinction, the contributors exhibit different strategies to gain preferential benefits of cooperation. The facultative benefit of cooperation to cheaters drives the population to an equilibrium frequency of cooperators and cheaters. Here we develop a multi-scale modeling approach to simulate the dynamics of such cooperation within mixed population of contributors and cheaters. We recursively use genome-scale metabolic models to estimate the fitness of the organism based on the current ecological state. In addition, a series of ordinary differential equations estimate the dynamics of the population and ecological conditions. We use our approach to investigate alternative strategies whereby the cooperating strain may improve its fitness and find that regulation of gene expression is superior to modulation of enzyme activity in our system.

In recent years, the prevalence and application of composite materials has exploded. Due to the demands of commercial transportation, the aviation industry has taken a leading role in the integration of composite structures. Among the leading concepts to develop lighter, more fuel-efficient commercial transport is the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept. The highly integrated structure of PRSEUS allows pressurized, non-circular fuselage designs to be implemented, enabling the feasibility of Hybrid Wing Body (HWB) aircraft. In addition to its unique fabrication process, the through-thickness stitching utilized by PRSEUS overcomes the low post-damage strength present in typical composites. Although many proof-of-concept tests have been performed that demonstrate the potential for PRSEUS, efficient computational tools must be developed before the concept can be commercially certified and implemented. In an attempt to address this need, a comprehensive modeling approach is developed that investigates PRSEUS at multiple scales. The majority of available experiments for comparison have been conducted at the coupon level. Therefore, a computational methodology is progressively developed based on physically realistic concepts without the use of tuning parameters. A thorough verification study is performed to identify the most effective approach to model PRSEUS, including the effect of element type, boundary conditions, bonding properties, and model fidelity. Using the results of this baseline study, a high fidelity stringer model is created at the component scale and validated against the existing experiments. Finally, the validated model is extended to larger scales to compare PRSEUS to the current state-of-the-art. Throughout the current work, the developed methodology is demonstrated to make accurate predictions that are well beyond the capability of existing predictive models. While using commercially available predictive tools, the methodology developed herein can accurately predict local behavior up to and beyond failure for stitched structures such as PRSEUS for the first time. Additionally, by extending the methodology to a large scale fuselage section drop scenario, the dynamic behavior of PRSEUS was investigated for the first time. With the predictive capabilities and unique insight provided, the work herein may serve to benefit future iteration of PRSEUS as well as certification by analysis efforts for future airframe development. / PHD

Inflatable Aerodynamic Decelerators (IADs) are a candidate technology NASA began investigating in the late 1960’s. Compared to supersonic parachutes, IADs represent a decelerator option capable of operating at higher Mach numbers and dynamic pressures. IADs have seen a resurgence in interest from the Entry, Descent, and Landing (EDL) community in recent years. The NASA Space Technology Roadmap (STR) highlights EDL systems, as well as, Materials, Structures, Mechanical Systems, and Manufacturing (MSMM) as key Technology Areas for development in the future; recognizing deployable decelerators, flexible material systems, and computational design of materials as essential disciplines for development. This investigation develops a multi-scale flexible material modeling approach that enables efficient high-fidelity IAD design and a critical understanding of the new materials required for robust and cost effective qualification methods. The approach combines understanding of the fabric architecture, analytical modeling, numerical simulations, and experimental data. This work identifies an efficient method that is as simple and as fast as possible for determining IAD material characteristics while not utilizing complicated or expensive research equipment. This investigation also recontextualizes an existing mesomechanical model through validation for structures pertaining to the analysis of IADs. In addition, corroboration and elaboration of this model is carried out by evaluating the effects of varying input parameters. Finally, the present investigation presents a novel method for numerically determining mechanical properties. A sub-scale section that captures the periodic pattern in the material (unit cell) is built. With the unit cell, various numerical tests are performed. The effective nonlinear mechanical stiffness matrix is obtained as a function of elemental strains through correlating the unit cell force-displacement results with a four node membrane element of the same size. Numerically determined properties are validated for relevant structures. Optical microscopy is used to capture the undeformed geometry of the individual yarns.

Embryonic development depends on the precise coordination of cell fate specification, patterning and morphogenesis. Although great strides have been made in the molecular understanding of each of these processes, how their interplay governs the formation of complex tissues remains poorly understood. New techniques for experimental manipulation and image quantification enable the study of development in unprecedented detail, resulting in new hypotheses on the interactions between known components. By expressing these hypotheses in terms of rules and equations, computational modeling and simulation allows one to test their consistency against experimental data. However, new computational methods are required to represent and integrate the network of interactions between gene regulation, signaling and biomechanics that extend over the molecular, cellular and tissue scales. In this thesis, I present a framework that facilitates computational modeling of multiscale multicellular systems and apply it to investigate pancreatic development and the formation of vascular networks. This framework is based on the integration of discrete cell-based models with continuous models for intracellular regulation and intercellular signaling. Specifically, gene regulatory networks are represented by differential equations to analyze cell fate regulation; interactions and distributions of signaling molecules are modeled by reaction-diffusion systems to study pattern formation; and cell-cell interactions are represented in cell-based models to investigate morphogenetic processes. A cell-centered approach is adopted that facilitates the integration of processes across the scales and simultaneously constrains model complexity. The computational methods that are required for this modeling framework have been implemented in the software platform Morpheus. This modeling and simulation environment enables the development, execution and analysis of multi-scale models of multicellular systems. These models are represented in a new domain-specific markup language that separates the biological model from the computational methods and facilitates model storage and exchange. Together with a user-friendly graphical interface, Morpheus enables computational modeling of complex developmental processes without programming and thereby widens its accessibility for biologists. To demonstrate the applicability of the framework to problems in developmental biology, two case studies are presented that address different aspects of the interplay between cell fate specification, patterning and morphogenesis. In the first, I focus on the interplay between cell fate stability and intercellular signaling. Specifically, two studies are presented that investigate how mechanisms of cell-cell communication affect cell fate regulation and spatial patterning in the pancreatic epithelium. Using bifurcation analysis and simulations of spatially coupled differential equations, it is shown that intercellular communication results in a multistability of gene expression states that can explain the scattered spatial distribution and low cell type ratio of nascent islet cells. Moreover, model analysis shows that disruption of intercellular communication induces a transition between gene expression states that can explain observations of in vitro transdifferentiation from adult acinar cells into new islet cells. These results emphasize the role of the multicellular context in cell fate regulation during development and may be used to optimize protocols for cellular reprogramming. The second case study focuses on the feedback between patterning and morphogenesis in the context of the formation of vascular networks. Integrating a cell-based model of endothelial chemotaxis with a reaction-diffusion model representing signaling molecules and extracellular matrix, it is shown that vascular network patterns with realistic morphometry can arise when signaling factors are retained by cell-modified matrix molecules. Through the validation of this model using in vitro assays, quantitative estimates are obtained for kinetic parameters that, when used in quantitative model simulations, confirm the formation of vascular networks under measured biophysical conditions. These results demonstrate the key role of the extracellular matrix in providing spatial guidance cues, a fact that may be exploited to enhance vascularization of engineered tissues. Together, the modeling framework, software platform and case studies presented in this thesis demonstrate how cell-centered computational modeling of multi-scale and multicellular systems provide powerful tools to help disentangle the complex interplay between cell fate specification, patterning and morphogenesis during embryonic development.

Les propriétés effectives mécaniques et physiques des matériaux hétérogènes dépendent d'une part de leurs constituants, mais peuvent également être fortement modifiées par leur répartition géométrique à l'échelle de la microstructure. L'optimisation topologique a pour but de définir la répartition optimale de matière dans une structure en vue de maximiser un ou plusieurs objectifs tels que les propriétés mécaniques sous des contraintes telles que la masse de matière. Récemment, les développements rapides de l'impression 3D ou d'autres techniques de fabrication additive ont rendu possible la fabrication de matériaux avec des microstructures "à la demande", ouvrant de nouvelles perspectives inédites pour la conception de matériaux. Dans ce contexte, les objectifs de cette thèse sont de développer des outils de modélisation et de simulation numériques pour concevoir des matériaux et des structures hétérogènes ayant des propriétés optimisées basés sur l'optimisation topologique. Plus précisément, nous nous intéressons aux points suivants. Premièrement, nous proposons des contributions à l'optimisation topologique à une seule échelle. Nous présentons tout d'abord une nouvelle méthode d'optimisation topologique avec évolution pour la conception de structures continues par description lisse de bords. Nous introduisons également deux techniques d'homogénéisation topologique pour la conception de microstructures possédant des propriétés effectives extrêmes et des « méta propriétés » (coefficient de Poisson négatif).Dans une seconde partie, des techniques multi échelle basées sur l'optimisation topologique sont développées. Nous proposons d'une part une approche concourante de structures hétérogènes dont les microstructures peuvent posséder plus de deux matériaux. Nous développons ensuite une approche d'optimisation topologique dans un cadre d'homogénéisation pour des échelles faiblement séparées, induisant des effets de gradient. Enfin dans une troisième partie, nous développons l'optimisation topologique pour maximiser la résistance à la fracture de structures ou de matériaux hétérogènes. La méthode de champs de phase pour la fracture est combinée à la méthode BESO pour concevoir des microstructures permettant d'augmenter fortement la résistance à la rupture. La technique prend en compte l'initiation, la propagation et la rupture complète de la structure / Mechanical and physical properties of complex heterogeneous materials are determined on one hand by the composition of their constituents, but can on the other hand be drastically modified by their microstructural geometrical shape. Topology optimization aims at defining the optimal structural or material geometry with regards to specific objectives under mechanical constraints like equilibrium and boundary conditions. Recently, the development of 3D printing techniques and other additive manufacturing processes have made possible to manufacture directly the designed materials from a numerical file, opening routes for totally new designs. The main objectives of this thesis are to develop modeling and numerical tools to design new materials using topology optimization. More specifically, the following aspects are investigated. First, topology optimization in mono-scale structures is developed. We primarily present a new evolutionary topology optimization method for design of continuum structures with smoothed boundary representation and high robustness. In addition, we propose two topology optimization frameworks in design of material microstructures for extreme effective elastic modulus or negative Poisson's ratio. Next, multiscale topology optimization of heterogeneous materials is investigated. We firstly present a concurrent topological design framework of 2D and 3D macroscopic structures and the underlying three or more phases material microstructures. Then, multiscale topology optimization procedures are conducted not only for heterogeneous materials but also for mesoscopic structures in the context of non-separated scales. A filter-based nonlocal homogenization framework is adopted to take into account strain gradient. Finally, we investigate the use of topology optimization in the context of fracture resistance of heterogeneous structures and materials. We propose a first attempt for the extension of the phase field method to viscoelastic materials. In addition, Phase field methods for fracture able to take into account initiation, propagation and interactions of complex both matrix and interfacial micro cracks networks are adopted to optimally design the microstructures to improve the fracture resistance

La corrosion des aciers est l’une des principales causes de dégradation des ouvrages en béton armé, notamment en façade maritime. Cette dégradation est due à la diffusion d’ions chlorures qui peut se produire dans les ouvrages immergés dans l’eau de mer, ceux subissant des cycles de marnage et également ceux soumis aux embruns marins. La corrosion peut être également due au processus de carbonatation du béton, responsable de la baisse du pH et par conséquent de la dépassivation des aciers. Cette thèse propose un modèle physico-chimique pour décrire la penetration des agents agressifs dans la première phase de la corrosion des aciers. Cette phase dite « incubation » correspond à la phase pendant laquelle le transfert des espèces agressives se produit dans le béton. Afin d’identifier clairement les paramètres de transport de ce modèle macroscopique une démarche multi-échelle est mise en oeuvre pour rendre compte de la diffusion dans les bétons. Cette démarche repose sur une description détaillée de la microstructure du béton (constituants et morphologie) par des méthodes de changement d’échelle. Cette approche se veut la plus exhaustive possible avec la prise en compte explicite de l’influence du rapport eau sur liant de la pâte de ciment, des propriétés des granulats et de la zone de transition entre la pâte et les granulats. Après identification de tous les paramètres d’entrée, le modèle physico-chimique macroscopique est utilisé pour évaluer la durée de vie d’un béton soumis au couplage carbonatation -chlorures en milieu insaturé. Suite à une validation du modèle par comparaison à des résultats expérimentaux, plusieurs applications de ce modèle sont présentées. / The corrosion of steels is one of the principal causes of degradation of reinforced concrete structures, especially in front of the sea. This degradation is due to the diffusion of chloride ions that can occur in the structures immersed in the seawater, those undergoing tidal cycles and also those subjected to the sea spray. The corrosion can also be due to the carbonation process of the concrete, which is responsible for decreasing of the pH and consequently the depassivation of the steels. This thesis proposes a physicochemical model to describe the penetration of aggressive agents in the first period of steel corrosion. This so-called « incubation » period corresponds to the period during which the transfer of aggressive species occurs in the concrete. In order to clearly identify the transport parameters of thismacroscopic model, a multi-scale approach is implemented to consider the diffusion in concretes. This approach is based on taking into account the detailed description of the microstructure of the concrete (constituents and morphology) by upscaling methods. This multi-scale approach is intended to be the most comprehensive with the consideration of the influence of the water-to-binder ratio of the cement paste, the properties of the aggregates and the transition zone between the cement paste and the aggregates. After identifying all the input parameters, the macroscopic physico-chemical model is used to evaluate the service life of a concrete subjected to coupling carbonation -chlorides in unsaturated medium. Following a validation of the model compared to experimental results, several applications of this model are presented.

Remote sensors and unmanned aerial vehicles (UAVs) have the potential to dramatically improve infrastructure health monitoring in terms of accuracy of the information and frequency of data collection. UAV automation has made significant progress but that automation is also creating vast amounts of data that needs to be processed into actionable information. A key aspect of this work is the optimization (not just automation) of data collection from UAVs for targeted planning of mission objectives. This work investigates the use of camera planning for Structure from Motion for 3D modeling of infrastructure. Included in this thesis is a novel multi-scale view-planning algorithm for autonomous targeted inspection. The method presented reduced the number of photos needed and therefore reduced the processing time while maintaining desired accuracies across the test site. A second focus in this work investigates various set covering problem algorithms to use for selecting the optimal camera set. The trade-offs between solve time and quality of results are explored. The Carousel Greedy algorithm is found to be the best method for solving the problem due to its relatively fast solve speeds and the high quality of the solutions found. Finally, physical flight tests are used to demonstrate the quality of the method for determining coverage. Each of the set covering problem algorithms are used to create a camera set that achieves 95% coverage. The models from the different camera sets are comparable despite having a large amount of variability in the camera sets chosen. While this study focuses on multi-scale view planning for optical sensors, the methods could be extended to other remote sensors, such as aerial LiDAR.

Remote sensors and unmanned aerial vehicles (UAVs) have the potential to dramatically improve infrastructure health monitoring in terms of accuracy of the information and frequency of data collection. UAV automation has made significant progress but that automation is also creating vast amounts of data that needs to be processed into actionable information. A key aspect of this work is the optimization (not just automation) of data collection from UAVs for targeted planning of mission objectives. This work investigates the use of camera planning for Structure from Motion for 3D modeling of infrastructure. Included in this thesis is a novel multi-scale view-planning algorithm for autonomous targeted inspection. The method presented reduced the number of photos needed and therefore reduced the processing time while maintaining desired accuracies across the test site. A second focus in this work investigates various set covering problem algorithms to use for selecting the optimal camera set. The trade-offs between solve time and quality of results are explored. The Carousel Greedy algorithm is found to be the best method for solving the problem due to its relatively fast solve speeds and the high quality of the solutions found. Finally, physical flight tests are used to demonstrate the quality of the method for determining coverage. Each of the set covering problem algorithms are used to create a camera set that achieves 95% coverage. The models from the different camera sets are comparable despite having a large amount of variability in the camera sets chosen. While this study focuses on multi-scale view planning for optical sensors, the methods could be extended to other remote sensors, such as aerial LiDAR.