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Poster presented at SETAC Europe's 33rd Annual Meeting held in Dublin Ireland..

This work presents and investigates a novel high-performance antenna design for remote sensing and satellite communications applications that is compact and lightweight. The performance requirements include dual-polarization, wide impedance bandwidth, low cross-polarization, high gain, and high aperture efficiency. To simultaneously achieve all these qualities is challenging and a combination of compatible performance enhancement techniques was selected and derived. A new antenna design, namely an octagonal cavity-backed radiating open prism (OCROP) antenna, was first introduced. The antenna is orthogonally and differentially fed to provide dual-polarization and low cross-polarization. The impedance bandwidth is increased by combining the resonances from the radiating feedlines and the open prism. The corner truncated octagonal ground cavity, instead of a more commonly seen square ground plane or square ground cavity, is used to further suppress the cross-polarization and enhance the gain and aperture efficiency. To show the superiority of the octagonal design, it was compared with a square ground cavity backed antenna. To further improve the gain of this novel antenna, its array and flared configurations are considered, investigated, and compared. The array design offers higher gain and aperture efficiency, while the flared design can provide lower cross-polarization. To achieve higher gain with the flared design, a larger flare angle was chosen which increased cross-polarization. To remedy the problem of the increased cross-polarization, a new iris design concept is proposed and investigated. It shows that this method can successfully suppress the cross-polarization of the flared design. This concept is general and has the potential to be applied to other types of aperture antennas. The design concepts and the simulation results are verified by fabricating and testing two prototypes, i.e., with and without a flare.

Les gens consacrent une importante part de leur existence à prendre diverses décisions, pouvant affecter leur demande en transport, par exemple les choix de lieux d'habitation et de travail, les modes de transport, les heures de départ, le nombre et type de voitures dans le ménage, les itinéraires ... Les choix liés au transport sont généralement fonction du temps et caractérisés par un grand nombre de solutions alternatives qui peuvent être spatialement corrélées. Cette thèse traite de modèles pouvant être utilisés pour analyser et prédire les choix discrets dans les applications liées aux réseaux de grandes tailles. Les modèles et méthodes proposées sont particulièrement pertinents pour les applications en transport, sans toutefois s'y limiter. Nous modélisons les décisions comme des séquences de choix, dans le cadre des choix discrets dynamiques, aussi connus comme processus de décision de Markov paramétriques. Ces modèles sont réputés difficiles à estimer et à appliquer en prédiction, puisque le calcul des probabilités de choix requiert la résolution de problèmes de programmation dynamique. Nous montrons dans cette thèse qu'il est possible d'exploiter la structure du réseau et la flexibilité de la programmation dynamique afin de rendre l'approche de modélisation dynamique en choix discrets non seulement utile pour représenter les choix dépendant du temps, mais également pour modéliser plus facilement des choix statiques au sein d'ensembles de choix de très grande taille. La thèse se compose de sept articles, présentant divers modèles et méthodes d'estimation, leur application ainsi que des expériences numériques sur des modèles de choix discrets de grande taille. Nous regroupons les contributions en trois principales thématiques: modélisation du choix de route, estimation de modèles en valeur extrême multivariée (MEV) de grande taille et algorithmes d'optimisation non-linéaire. Cinq articles sont associés à la modélisation de choix de route. Nous proposons différents modèles de choix discrets dynamiques permettant aux utilités des chemins d'être corrélées, sur base de formulations MEV et logit mixte. Les modèles résultants devenant coûteux à estimer, nous présentons de nouvelles approches permettant de diminuer les efforts de calcul. Nous proposons par exemple une méthode de décomposition qui non seulement ouvre la possibilité d'estimer efficacement des modèles logit mixte, mais également d'accélérer l'estimation de modèles simples comme les modèles logit multinomiaux, ce qui a également des implications en simulation de trafic. De plus, nous comparons les règles de décision basées sur le principe de maximisation d'utilité de celles sur la minimisation du regret pour ce type de modèles. Nous proposons finalement un test statistique sur les erreurs de spécification pour les modèles de choix de route basés sur le logit multinomial. Le second thème porte sur l'estimation de modèles de choix discrets statiques avec de grands ensembles de choix. Nous établissons que certains types de modèles MEV peuvent être reformulés comme des modèles de choix discrets dynamiques, construits sur des réseaux de structure de corrélation. Ces modèles peuvent alors être estimées rapidement en utilisant des techniques de programmation dynamique en combinaison avec un algorithme efficace d'optimisation non-linéaire. La troisième et dernière thématique concerne les algorithmes d'optimisation non-linéaires dans le cadre de l'estimation de modèles complexes de choix discrets par maximum de vraisemblance. Nous examinons et adaptons des méthodes quasi-Newton structurées qui peuvent être facilement intégrées dans des algorithmes d'optimisation usuels (recherche linéaire et région de confiance) afin d'accélérer le processus d'estimation. Les modèles de choix discrets dynamiques et les méthodes d'optimisation proposés peuvent être employés dans diverses applications de choix discrets. Dans le domaine des sciences de données, des modèles qui peuvent traiter de grands ensembles de choix et des ensembles de choix séquentiels sont importants. Nos recherches peuvent dès lors être d'intérêt dans diverses applications d'analyse de la demande (analyse prédictive) ou peuvent être intégrées à des modèles d'optimisation (analyse prescriptive). De plus, nos études mettent en évidence le potentiel des techniques de programmation dynamique dans ce contexte, y compris pour des modèles statiques, ouvrant la voie à de multiples directions de recherche future. People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

La cosmologie a atteint une ère passionnante. Pour la première fois dans l’histoire humaine, un modèle quantitatif pour la formation et l’évolution de l’Univers existe,expliquant une gamme très variée de phénomènes et ayant été testé avec une impressionnante. De plus, nous sommes à l’aube d’une époque dans laquelle nous aurons à notre disposition une abondance de données de grande qualité, ce qui nous permettra d’utiliser la cosmologie comme un outil pour tester la physique fondamentale.En particulier, comme les structures de grandes échelles de l’Univers sont gouvernées par la force de gravité, la cosmologie peut être utilisée pour tester la théorie de la relativité générale d’Einstein. Cette idée a inspiré la plupart des travaux décrits dans ce manuscrit, dans lequel j’ai étudié des théories alternatives au modèle standard de la cosmologie et des tests à grandes échelles pour la relativité générale.Dans la première partie de ma thèse, je me suis concentré sur les “théories tenseur-scalaire” de la gravité. Ce sont des théories alternatives de la gravité, dans lesquelles un champ scalaire, qui est responsable de l’accélération de l’expansion de l’Univers, est ajouté à l’action de Einstein-Hilbert. Dans le deuxième chapitre, j’ai décrit le modèle de K-mouflage, une “théorie tenseur scalaire”dans laquelle le champ scalaire possède un terme cinétique non-standard, en montrant son effet non négligeable sur la dynamique des amas des galaxies. J’ai aussi montré comment cet effet peut être utilisé pour contraindre le modèle de “K-mouflage” en utilisant des observations en rayon X.En particulier, j’ai montré que le cisaillement cosmique a un pouvoir assez limité actuellement pour contraindre ces théories, à cause de la faible précision des observations actuelles et des dégénérescences avec les processus baryoniques.Dans le cinquième chapitre, j’ai donné une description de mon étude des relations de cohérence. Ce sont des relations entreles fonctions de corrélation des champs cosmiques à (n + 1) et n points, valables aussi dans le régime non-linéaire.Leur intérêt vient du fait que leur dérivation dépend seulement du Principe d’Équivalence et de l’hypothèse de conditions initiales Gaussiennes, et donc elles peuvent être utilisées pour tester ces hypothèses fondamentales du modèle standard de la cosmologie.Des relations similaires ont été étudiées auparavant, mais j’ai montré comment il est possible d’obtenir des relations qui ne s’annulent pas lorsque tous les champs sont considérés au même instant. J’ai utilisé ce résultat pour obtenir des relations de cohérence entre fonctions de corrélation de quantités observables, notamment le champ de densité des galaxies et la fluctuation de température du fond diffus cosmologie donnée par l’effet Sachs-Wolfe. Ces relations peuvent être utilisées pour des tests de la relativité générale,reposant sur des observations par satellites, sans avoir besoin de modéliser la physique des baryons aux petites échelles.Enfin, j’ai donné un aperçu des quelques perspectives possibles pour poursuivre le travail décrit dans ce manuscrit.En particulier, j’ai souligné comment des simulations numérique sont nécessaires pourmieux comprendre la formation des structuresdans le contexte des modèles “K-mouflage” et“ultra-local”. En outre, elles peuvent être aussiutilisées pour tester les hypothèses sous-tendantl’analyse des lentilles gravitationnelles faiblesprésentée dans ce manuscrit, surtout pourdistinguer l’effet de la physique des baryons etdes neutrinos de l’effet des théories de gravitémodifiée sur le cisaillement cosmique. En cequi concerne les relations de cohérence, uneétude de faisabilité de leur mesure avec les“surveys” cosmologiques est nécessaire, pourcomprendre si elles peuvent donner descontraintes compétitives sur les théoriesalternatives de la gravité. The study of physical cosmology has reached an exciting era. For the first time in human history, a quantitative model for the formation and the evolution of the Universe exists, which explains a wide range of phenomena and has been tested with incredible accuracy during the last century. Moreover, weare approaching a time when a bounty of high quality cosmological data will be available,allowing us to use cosmology as a tool to test fundamental physics.In particular, as the large-scale structures of the Universe are governed by gravity, cosmology can help us to asses the correctness of Albert Einstein’s general relativity. This idea fueledmost of the work described in this manuscript,in which we study alternative theories to the standard cosmological model and large-scale structure tests for general relativity.In particular, we focus on two scalar-tensor theories of gravity, the K-mouflage models described in Chapter 2 and the ultra-localmodels of gravity presented in Chapter 3. The K-mouflage theories are k-essence models with a non-standard kinetic term that were already studied at the linear and background levels. In this manuscript, we extend this description showing how the scalar field, which is responsible for the late time acceleration of the Universe, has a non-negligible impact on cluster dynamics, arguing that future surveysmay have the power of constraining K-mouflage models via X-ray observations. Next,we study the ultra-local models of gravity,where a scalar field with a negligible kinetic term is added to the Einstein-Hilbert action,investigating how the latter modifiescosmological structure formation and howthese models can be related to super-chameleonmodels.In Chapter 4, we present a cosmic shear data analysis in the context of f (R) and Dilaton models, and we show how current data canaccommodate most of the theories considered,once baryonic and neutrino physicsdegeneracies are taken into account. Finally, in Chapter 5 we present an analysis of consistency relations for large-scale structures,which are non-perturbative relations among correlations of cosmic fields. They are alsovalid in the non-linear regime, where very few analytical results are known, and only rely on the Equivalence Principle and primordial Gaussian initial conditions. This makes them a powerful tool to test general relativity and inflationary models using the cosmologic allarge-scale structures.We provide here the first non-vanishing equaltime consistency relations, which we use to obtain consistency relations involving observational quantities.In this Thesis manuscript, we highlight the major results of the full analysis done in the articles that are appended to the main text,where the reader can quench any thirst for technical details.

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment with a primary physics goal of observing neutrino and antineutrino oscillation patterns to precisely measure the parameters governing long-baseline neutrino oscillation in a single experiment, and to test the three-flavor paradigm. DUNE's design has been developed by a large, international collaboration of scientists and engineers to have unique capability to measure neutrino oscillation as a function of energy in a broadband beam, to resolve degeneracy among oscillation parameters, and to control systematic uncertainty using the exquisite imaging capability of massive LArTPC far detector modules and an argon-based near detector. DUNE's neutrino oscillation measurements will unambiguously resolve the neutrino mass ordering and provide the sensitivity to discover CP violation in neutrinos for a wide range of possible values of $\delta_{CP}$. DUNE is also uniquely sensitive to electron neutrinos from a galactic supernova burst, and to a broad range of physics beyond the Standard Model (BSM), including nucleon decays. DUNE is anticipated to begin collecting physics data with Phase I, an initial experiment configuration consisting of two far detector modules and a minimal suite of near detector components, with a 1.2 MW proton beam. To realize its extensive, world-leading physics potential requires the full scope of DUNE be completed in Phase II. The three Phase II upgrades are all necessary to achieve DUNE's physics goals: (1) addition of far detector modules three and four for a total FD fiducial mass of at least 40 kt, (2) upgrade of the proton beam power from 1.2 MW to 2.4 MW, and (3) replacement of the near detector's temporary muon spectrometer with a magnetized, high-pressure gaseous argon TPC and calorimeter.

Transmission line (TL) structure failures caused by tornadoes have been observed in multiple countries around the globe. The objective of this study is to develop an accurate load case that can simulate the critical tornado forces transmitted from the TL conductors to the towers. In order to achieve the goal, three different tornado wind fields, which were previously developed using computational fluid dynamic simulations, are considered. The tornado wind field provides the most critical forces on the TL conductors is determined and considered to obtain the critical load cases. Using the critical wind field, parametric studies are conducted to identify the tornado position that generates peak longitudinal forces. A parametric study is conducted on two different transmission line systems to assess the influence of conductor parameters on the longitudinal forces. Results of the parametric study are used to develop charts, which together with a three-dimensional interpolation procedure can estimate the critical conductor longitudinal forces on the towers.

In this thesis, we present a new procedure for mesh adaptation for wakes. The approach starts by tracking the wake centerline with an initial isotropic unstructured mesh. A vertex-centered finite volume method is used, and the velocity field is obtained from solution reconstruction. The velocity data is integrated numerically using an adaptive fourth-order Runge-Kutta method. We insert the wake centerline into the existing unstructured mesh as an internal boundary and use a metric-based anisotropic mesh adaptation to generate anisotropic cells in regions with large second derivatives of flow variables. In the second step, the problem is solved on adapted mesh and a new wake centerline is tracked. We then move the previous wake centerline (which is now a part of adapted mesh) to match the centerline obtained from the adapted mesh. To move the wake centerline, a solid mechanics analogy is used and the linear elasticity equation is solved on the adapted mesh. As a result, the displacement is propagated throughout the mesh and the already adapted regions along the wake centerline are preserved. The process is then followed for subsequent cycles of anisotropic mesh adaptation to obtain a more accurate approximation of the wake centerline. As an alternate strategy for obtaining an anisotropic mesh in the wake, we take the first geometry, together with the captured wake centerline from an unstructured triangular mesh, as an initial geometry to produce a quad dominant mesh, using an advancing layer method. The correctness of the streamline tracking algorithm is verified using an analytical velocity field. The mesh morphing approach is tested using the method of manufactured solutions, demonstrating that the linear finite element solution is second-order accurate. The results of laminar flow test cases for the attached and separated flow are presented and compared with some well-established numerical results in the literature. Our results show that the advancing layer mesh is more efficient in resolving the wake. In the end, one case for turbulent subsonic flow is considered. For turbulent flow, a cell-centered finite volume method is used and we only track the wake centerline at different angles of attack.

The beam-helicity asymmetry was measured, for the first time, in photoproduction of $\pi^{0}\eta$ pairs on carbon, aluminum, and lead, with the A2 experimental setup at MAMI. The results are compared to an earlier measurement on a free proton and to the corresponding theoretical calculations. The Mainz model is used to predict the beam-helicity asymmetry for the nuclear targets. The present results indicate that the photoproduction mechanism for $\pi^{0}\eta$ pairs on nuclei is similar to photoproduction on a free nucleon. This process is dominated by the $D_{33}$ partial wave with the $\eta\Delta(1232)$ intermediate state.

In Ontario, 7 of the 8 native species of freshwater turtles are listed as at-risk. Protection of species-at-risk requires delineation and identification of their critical habitat to enable the proposal of conservation strategies. Because of pre-existing development and limited resources for conservation, it is difficult to protect land required for species’ survival especially when faced with multiple threats such as habitat loss, degradation, and fragmentation, invasive species, and a changing climate. To improve conservation strategies, we must understand how turtle populations use a variety of different landscapes at a range of spatial scales. The goals of this thesis were to develop and assess landscape-level conservation strategies for imperiled freshwater turtles. I first determined that Blanding's turtles (Emydoidea blandingii) require inland and coastal wetlands, a suitable upland matrix and connecting corridors. Since turtles overwinter for majority of the year, I determined suitable thermal parameters of occupied sites, revealing suitable water temperatures range from 0.44° C to 3.68° C and slowly decline throughout the overwintering period. Using a landscape-level approach, my models support that habitat in Georgian Bay is in good condition; 64% of evaluated islands support habitat for Blanding’s turtles and majority of surveyed coastal wetlands support eastern musk turtles (Sternotherus odoratus). In particular, coastal wetlands with higher proportions of forest cover, lower densities of roads, buildings, and docks, and more variable bathymetric slopes provide more suitable habitat. In addition to anthropogenic stressors, invasive species pose a threat to turtles and their habitat. I provided the first quantitative evidence of the negative consequences of Phragmites australis invasion on availability of habitat for turtles. Since roads are a ubiquitous feature in our landscape, I evaluated strategies aimed at limiting their negative effects on at-risk reptiles. A decade-long dataset of road mortality reveals the ineffectiveness of partial fencing as a mitigation strategy. I recommend emphasis on fence integrity and continuity, limiting impact of edge effects, and conducting a comprehensive monitoring program. Finally, long-term changes in a protected landscape are evaluated and results indicate habitat succession and invasive species can negatively affect habitat suitability, and protection of land alone does not necessarily equate to protection of sensitive herpetofauna. My research integrates geographic information systems and remote sensing to advance our understanding of landscape requirements for turtles and will inform future conservation strategies aimed at mitigating threats to imperiled freshwater turtles. Turtles are one of the most endangered taxonomic groups, with as many as 1 in 2 species at risk of extinction. Although turtles are one of the oldest groups of animals in the world, anthropogenic impacts causing habitat loss and degradation have led to population declines. The goals of this thesis were to develop and assess landscape-level conservation strategies for imperiled freshwater turtles. I analyzed habitat selection by an imperiled freshwater turtle and determined suitable thermal characteristics of critical overwintering habitat. At the landscape-scale, I modeled habitat suitability and occupancy for at-risk turtles. My research reveals the negative effects of invasive species and the ineffectiveness of partial fencing as a strategy to mitigate reptile road mortality. Lastly, I discuss the implications of habitat succession on reptile habitat and the need for management when protection of land alone does not equate to protection of sensitive species. My research advances our understanding of landscape requirements for turtles and will inform future conservation strategies for imperiled freshwater turtles. Doctor of Philosophy (PhD) Thesis