Fuel cells are electrochemical devices being developed for a variety of consumer applications including homes and vehicles. Before customers will accept this technology fuel cells must demonstrate suitable durability and reliability. One of the most important parts of a fuel cell stack is the polymer electrolyte membrane (PEM). This layer is responsible for conducting protons from anode to cathode and acting as a gas barrier, while operating in a harsh electrochemical environment. In order to develop better and more durable membranes researchers must understand the linkage between the causes of degradation, such as specific material properties and operational conditions. One significant mode of degradation of the electrolyte membrane is through chemical degradation caused by the crossover of reactant gases leading to the formation of peroxide and ultimately radical species. These radicals are able to attack vulnerable groups in the polymer structure of the membrane. The result is membrane thinning, increased gas crossover, fluoride ion release, and voltage degradation. Considerable experimental work has been done to understand these mechanisms, although there has been no attempt to model the connection between the causes of degradation and the physical effects of degradation on the electrolyte membrane. Such a model can be used as a valuable tool when evaluating different degradation mechanisms, developing stronger materials, and enable estimation of the influence of fuel cell operation and system design on degradation. This work presents the development and application of a dynamic semi-mechanistic chemical degradation model for a reinforced membrane in a polymer electrolyte membrane fuel cell. The model was developed using single cell testing with Gore™ PRIMEA® series 5510 catalyst coated membranes under open circuit voltage (OCV) conditions. Such conditions are useful for accelerated testing since they are believed to enhance chemical degradation in membranes since reactant gas partial pressures are at their maximum. It was found that the electrolyte layer closer to the cathode catalyst preferentially degraded. Furthermore, cumulative fluoride release curves for the anode and cathode began to reach plateaus at similar times. The developed model proposes that as the cathode electrolyte layer is degraded, fluoride release slows due to a lack of reactants since the inert reinforcement layer creates a barrier between the cathode and anode electrolyte layers. It is also believed that all fluoride release originates at the degradation site at the cathode. By fitting key parameters, the fluoride release trends were simulated. The proposed model links material properties such as the membrane gas permeability, membrane thickness, and membrane reactivity, as well as operating parameters such as hydrogen partial pressure and relative humidity to fluoride release, thickness change, and crossover. Further investigation into degradation at OCV operation and different relative humidity conditions showed that initial hydrogen crossover measurements were a good indicator of degradation rate over long testing times. The proposed semi-mechanistic model was able to best model the results when using a second order dependence on the hydrogen crossover term. In all cases there was some discrepancy between the model and experimental data after long times. This was attributed to the onset and contribution of anode side degradation. The effect of drawing current on fluoride release was also investigated. Experimental results showed that with increasing current density the fluoride release rate decreased. Using the developed semi-mechanistic model it was proposed that a decrease in hydrogen crossover was primarily responsible for the reduction in chemical degradation of the membrane. A macro-homogeneous model of the anode catalyst layer was used to show that a reduction in hydrogen concentration through the catalyst layer when a current is drawn is a possible reason for the reduction in degradation. Finally the model was applied to three different dynamic drive cycles. The model was able to show that over different drive cycles, the fuel cell will experience different degradation rates. Thus the developed model can be used as a potential tool to evaluate degradation in systems.

Fuel cells are electrochemical devices being developed for a variety of consumer applications including homes and vehicles. Before customers will accept this technology fuel cells must demonstrate suitable durability and reliability. One of the most important parts of a fuel cell stack is the polymer electrolyte membrane (PEM). This layer is responsible for conducting protons from anode to cathode and acting as a gas barrier, while operating in a harsh electrochemical environment. In order to develop better and more durable membranes researchers must understand the linkage between the causes of degradation, such as specific material properties and operational conditions. One significant mode of degradation of the electrolyte membrane is through chemical degradation caused by the crossover of reactant gases leading to the formation of peroxide and ultimately radical species. These radicals are able to attack vulnerable groups in the polymer structure of the membrane. The result is membrane thinning, increased gas crossover, fluoride ion release, and voltage degradation. Considerable experimental work has been done to understand these mechanisms, although there has been no attempt to model the connection between the causes of degradation and the physical effects of degradation on the electrolyte membrane. Such a model can be used as a valuable tool when evaluating different degradation mechanisms, developing stronger materials, and enable estimation of the influence of fuel cell operation and system design on degradation. This work presents the development and application of a dynamic semi-mechanistic chemical degradation model for a reinforced membrane in a polymer electrolyte membrane fuel cell. The model was developed using single cell testing with Gore™ PRIMEA® series 5510 catalyst coated membranes under open circuit voltage (OCV) conditions. Such conditions are useful for accelerated testing since they are believed to enhance chemical degradation in membranes since reactant gas partial pressures are at their maximum. It was found that the electrolyte layer closer to the cathode catalyst preferentially degraded. Furthermore, cumulative fluoride release curves for the anode and cathode began to reach plateaus at similar times. The developed model proposes that as the cathode electrolyte layer is degraded, fluoride release slows due to a lack of reactants since the inert reinforcement layer creates a barrier between the cathode and anode electrolyte layers. It is also believed that all fluoride release originates at the degradation site at the cathode. By fitting key parameters, the fluoride release trends were simulated. The proposed model links material properties such as the membrane gas permeability, membrane thickness, and membrane reactivity, as well as operating parameters such as hydrogen partial pressure and relative humidity to fluoride release, thickness change, and crossover. Further investigation into degradation at OCV operation and different relative humidity conditions showed that initial hydrogen crossover measurements were a good indicator of degradation rate over long testing times. The proposed semi-mechanistic model was able to best model the results when using a second order dependence on the hydrogen crossover term. In all cases there was some discrepancy between the model and experimental data after long times. This was attributed to the onset and contribution of anode side degradation. The effect of drawing current on fluoride release was also investigated. Experimental results showed that with increasing current density the fluoride release rate decreased. Using the developed semi-mechanistic model it was proposed that a decrease in hydrogen crossover was primarily responsible for the reduction in chemical degradation of the membrane. A macro-homogeneous model of the anode catalyst layer was used to show that a reduction in hydrogen concentration through the catalyst layer when a current is drawn is a possible reason for the reduction in degradation. Finally the model was applied to three different dynamic drive cycles. The model was able to show that over different drive cycles, the fuel cell will experience different degradation rates. Thus the developed model can be used as a potential tool to evaluate degradation in systems.

This dissertation focuses on three research projects: 1) construction of simultaneous prediction intervals/bounds for at least k out of m future observations; 2) semi-parametric degradation model for accelerated destructive degradation test (ADDT) data; and 3) spatial variable selection and application to Lyme disease data in Virginia. Followed by the general introduction in Chapter 1, the rest of the dissertation consists of three main chapters. Chapter 2 presents the construction of two-sided simultaneous prediction intervals (SPIs) or one-sided simultaneous prediction bounds (SPBs) to contain at least k out of m future observations, based on complete or right censored data from (log)-location-scale family of distributions. SPI/SPB calculated by the proposed procedure has exact coverage probability for complete and Type II censored data. In Type I censoring case, it has asymptotically correct coverage probability and reasonably good results for small samples. The proposed procedures can be extended to multiply-censored data or randomly censored data. Chapter 3 focuses on the analysis of ADDT data. We use a general degradation path model with correlated covariance structure to describe ADDT data. Monotone B-splines are used to modeling the underlying degradation process. A likelihood based iterative procedure for parameter estimation is developed. The confidence intervals of parameters are calculated using the nonparametric bootstrap procedure. Both simulated data and real datasets are used to compare the semi-parametric model with the existing parametric models. Chapter 4 studies the Lyme disease emergence in Virginia. The objective is to find important environmental and demographical covariates that are associated with Lyme disease emergence. To address the high-dimentional integral problem in the loglikelihood function, we consider the penalized quasi loglikelihood and the approximated loglikelihood based on Laplace approximation. We impose the adaptive elastic net penalty to obtain sparse estimation of parameters and thus to achieve variable selection of important variables. The proposed methods are investigated in simulation studies. We also apply the proposed methods to Lyme disease data in Virginia. Finally, Chapter 5 contains general conclusions and discussions for future work. / Ph. D.

Durability of carbon-supported platinum nanoparticle is one of the limiting factors for PEM fuel cell commercial applications. In our research work, we applied both experimental and mathematical simulative tools to study the mechanisms of Pt/C catalyst degradation. An accelerated catalyst degradation protocol by cycling the cathode potential in a square-wave profile was applied to study the losses of cell performances, catalyst ORR activity, and Pt active surface areas. Post-mortem analyses of cathode Pt particle size by X-ray diffraction and platinum distributions in CCMs by SEM/EDS were also conducted. Increased cell temperature and relative humidity was found to accelerate the cathode catalyst degradation. High membrane water contents or abundant water/ionic channels within the polymer electrolyte were believed to accelerate Pt ion transport and cathode degradation. After degradation tests, significant amount of Pt loss into the membrane forming a Pt "band" was observed through cathode platinum dissolution and chemical reduction of soluble Pt ions by permeated hydrogen from the anode. Platinum deposition was confirmed at a location where the permeated hydrogen and oxygen had the complete catalytic combustion over the deposited Pt clusters/particles as the catalyst. A cathode degradation model was built including the processes of platinum oxidation, dissolution/replating, diffusion of Pt ions and Pt band formation in electrolyte. A simplified bi-modal particle size distribution was applied with equal numbers of small and large type particles uniformly distributed in the cathode initially. Processes of Pt mass exchange between two types of particles were demonstrated to cause the overall particle growth. This was due to the particle size effect that platinum dissolution from the small type particles and replating of Pt ions onto the large particles was favored. Parametric study found the increased upper cycling potential was the dominated factor to accelerate the catalyst degradation. Also high frequency of potential cycle and low surface oxide coverage accelerated the degradation rate. Pt dissolution and oxidation processes in perchloric acid were preliminary investigated, and both chemical and electrochemical processes of oxidation and dissolution were believed to be involved under closed-circuit fuel cell conditions with oxygen presence at cathode.

Avec la miniaturisation continue des circuits intégrés et le remplacement de l’oxydede silicium par des diélectriques low-κ poreux à base de SiOCH, la fiabilité des circuitsmicroélectroniques a été fortement compromise. Il est aujourd’hui extrêmement importantde mieux appréhender les mécanismes de dégradation au sein de ces matériaux afin deréaliser une estimation précise de leur durée de vie.Dans ce contexte, ces travaux de thèse ont consisté à étudier les mécanismes de dégradationau sein du diélectrique afin de proposer un modèle de durée de vie plus pertinent.Par une étude statistique du temps à la défaillance sous différents types de stress électrique,un mécanisme de génération des défauts par impact est mis en évidence. En l’associantau mécanisme de conduction au sein du diélectrique, il a été possible de développer unmodèle de durée de vie cohérent pour les interconnexions permettant une estimation de ladurée de vie plus fiable que les modèles de la littérature. L’impact du piégeage de chargesdans le diélectrique a ensuite été analysé grâce à ce modèle. / With the constant size reduction of integrated circuits and the replacement of silicon dioxide with porous SiOCH, the reliability of interconnects has been sharply reduced. A better understanding of degradation mechanisms is now required in order to have a precise estimation of product lifetime. In this work, degradation mechanisms have been studied in order to propose a more accurate lifetime model. A statistical study of times to failure under various electrical stresses is used to explain the physical mechanisms involved in defect creation. Combining these degradation mechanisms and Poole-Frenkel conduction mechanism enables the use of a new lifetime model. This model leads to a better estimation of the lifetime than existing models. Finally, the effects of charge trapping on lifetime in these materials have been studied.

Le nombre important de campagnes de numérisation mises en place ces deux dernières décennies a entraîné une effervescence scientifique ayant mené à la création de nombreuses méthodes pour traiter et/ou analyser ces images de documents (reconnaissance d’écriture, analyse de la structure de documents, détection/indexation et recherche d’éléments graphiques, etc.). Un bon nombre de ces approches est basé sur un apprentissage (supervisé, semi supervisé ou non supervisé). Afin de pouvoir entraîner les algorithmes correspondants et en comparer les performances, la communauté scientifique a un fort besoin de bases publiques d’images de documents avec la vérité-terrain correspondante, et suffisamment exhaustive pour contenir des exemples représentatifs du contenu des documents à traiter ou analyser. La constitution de bases d’images de documents réels nécessite d’annoter les données (constituer la vérité terrain). Les performances des approches récentes d’annotation automatique étant très liées à la qualité et à l’exhaustivité des données d’apprentissage, ce processus d’annotation reste très largement manuel. Ce processus peut s’avérer complexe, subjectif et fastidieux. Afin de tenter de pallier à ces difficultés, plusieurs initiatives de crowdsourcing ont vu le jour ces dernières années, certaines sous la forme de jeux pour les rendre plus attractives. Si ce type d’initiatives permet effectivement de réduire le coût et la subjectivité des annotations, reste un certain nombre de difficultés techniques difficiles à résoudre de manière complètement automatique, par exemple l’alignement de la transcription et des lignes de texte automatiquement extraites des images. Une alternative à la création systématique de bases d’images de documents étiquetées manuellement a été imaginée dès le début des années 90. Cette alternative consiste à générer des images semi-synthétiques imitant les images réelles. La génération d’images de documents semi-synthétiques permet de constituer rapidement un volume de données important et varié, répondant ainsi aux besoins de la communauté pour l’apprentissage et l’évaluation de performances de leurs algorithmes. Dans la cadre du projet DIGIDOC (Document Image diGitisation with Interactive DescriptiOn Capability) financé par l’ANR (Agence Nationale de la Recherche), nous avons mené des travaux de recherche relatifs à la génération d’images de documents anciens semi-synthétiques. Le premier apport majeur de nos travaux réside dans la création de plusieurs modèles de dégradation permettant de reproduire de manière synthétique des déformations couramment rencontrées dans les images de documents anciens (dégradation de l’encre, déformation du papier, apparition de la transparence, etc.). Le second apport majeur de ces travaux de recherche est la mise en place de plusieurs bases d’images semi-synthétiques utilisées dans des campagnes de test (compétition ICDAR2013, GREC2013) ou pour améliorer par ré-apprentissage les résultats de méthodes de reconnaissance de caractères, de segmentation ou de binarisation. Ces travaux ont abouti sur plusieurs collaborations nationales et internationales, qui se sont soldées en particulier par plusieurs publications communes. Notre but est de valider de manière la plus objective possible, et en collaboration avec la communauté scientifique concernée, l’intérêt des images de documents anciens semi-synthétiques générées pour l’évaluation de performances et le ré-apprentissage. / In the last two decades, the increase in document image digitization projects results in scientific effervescence for conceiving document image processing and analysis algorithms (handwritten recognition, structure document analysis, spotting and indexing / retrieval graphical elements, etc.). A number of successful algorithms are based on learning (supervised, semi-supervised or unsupervised). In order to train such algorithms and to compare their performances, the scientific community on document image analysis needs many publicly available annotated document image databases. Their contents must be exhaustive enough to be representative of the possible variations in the documents to process / analyze. To create real document image databases, one needs an automatic or a manual annotation process. The performance of an automatic annotation process is proportional to the quality and completeness of these databases, and therefore annotation remains largely manual. Regarding the manual process, it is complicated, subjective, and tedious. To overcome such difficulties, several crowd-sourcing initiatives have been proposed, and some of them being modelled as a game to be more attractive. Such processes reduce significantly the price andsubjectivity of annotation, but difficulties still exist. For example, transcription and textline alignment have to be carried out manually. Since the 1990s, alternative document image generation approaches have been proposed including in generating semi-synthetic document images mimicking real ones. Semi-synthetic document image generation allows creating rapidly and cheaply benchmarking databases for evaluating the performances and trainingdocument processing and analysis algorithms. In the context of the project DIGIDOC (Document Image diGitisation with Interactive DescriptiOn Capability) funded by ANR (Agence Nationale de la Recherche), we focus on semi-synthetic document image generation adapted to ancient documents. First, we investigate new degradation models or adapt existing degradation models to ancient documents such as bleed-through model, distortion model, character degradation model, etc. Second, we apply such degradation models to generate semi-synthetic document image databases for performance evaluation (e.g the competition ICDAR2013, GREC2013) or for performance improvement (by re-training a handwritten recognition system, a segmentation system, and a binarisation system). This research work raises many collaboration opportunities with other researchers to share our experimental results with our scientific community. This collaborative work also helps us to validate our degradation models and to prove the efficiency of semi-synthetic document images for performance evaluation and re-training.

This dissertation focuses on the introduction and development of an integrated model-based design and optimization platform to solve the optimal design and optimal control, or hardware and software co-design, problem for hybrid electric propulsion systems. Specifically, the hybrid and plug-in hybrid electric powertrain systems with diesel and natural gas (NG) fueled compression ignition (CI) engines and large Li-ion battery energy storage system (ESS) for propelling a hybrid electric marine vessel are investigated. The combined design and control optimization of the hybrid propulsion system is formulated as a bi-level, nested optimization problem. The lower-level optimization applies dynamic programming (DP) to ensure optimal energy management for each feasible powertrain system design, and the upper-level global optimization aims at identifying the optimal sizes of key powertrain components for the powertrain system with optimized control. Recently, Li-ion batteries became a promising ESS technology for electrified transportation applications. However, these costly Li-ion battery ESSs contribute to a large portion of the powertrain electrification and hybridization costs and suffer a much shorter lifetime compared to other key powertrain components. Different battery performance modelling methods are reviewed to identify the appropriate degradation prediction approach. Using this approach and a large set of experimental data, the performance degradation and life prediction model of LiFePO4 type battery has been developed and validated. This model serves as the foundation for determining the optimal size of battery ESS and for optimal energy management in powertrain system control to achieve balanced reduction of fuel consumption and the extension of battery lifetime. In modelling and design of different hybrid electric marine propulsion systems, the life cycle cost (LCC) model of the cleaner, hybrid propulsion systems is introduced, considering the investment, replacement and operational costs of their major contributors. The costs of liquefied NG (LNG), diesel and electricity in the LCC model are collected from various sources, with a focus on present industrial price in British Columbia, Canada. The greenhouse gas (GHG) and criteria air pollutant (CAP) emissions from traditional diesel and cleaner NG-fueled engines with conventional and optimized hybrid electric powertrains are also evaluated. To solve the computational expensive nested optimization problem, a surrogate model-based (or metamodel-based) global optimization method is used. This advanced global optimization search algorithm uses the optimized Latin hypercube sampling (OLHS) to form the Kriging model and uses expected improvement (EI) online sampling criterion to refine the model to guide the search of global optimum through a much-reduced number of sample data points from the computationally intensive objective function. Solutions from the combined hybrid propulsion system design and control optimization are presented and discussed. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. The resulting hybrid propulsion system with NG engine and Li-ion battery ESS presents a more economical and environmentally friendly propulsion system design of the tugboat. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. Other main contributions include incorporating the battery performance degradation model to the powertrain size optimization and optimal energy management; performing a systematic design and optimization considering LCC of diesel and NG engines in the hybrid electric powertrains; and developing an effective method for the computational intensive powertrain co-design problem. / Graduate

The hydraulic and removal efficiencies of a Horizontal Flow Treatment Wetlands (HF TW) were investigated through an internal three dimensional grid of sampling ports. Tracer tests and regular monitoring of water quality parameters were performed. Results demonstrated that the HF TW has generally good hydraulic and volumetric efficiencies, with relatively low dead zones. The application of models developed by chemical engineering provided the number of tanks in series and the calculated detention times which were input as parameters in the multi flow with dispersion hydraulic model. This second model identified that water fluxes were not homogeneous with depth inside the TW and 60% of the flow was along the bottom layer of the bed. It also indicated the water flow velocities, which were faster on the bottom of the bed, and the axial dispersion, which was higher where flow velocity was lower. The reviewed inflow rate distribution allowed review for all layers of the nominal detention time and of the hydraulic indexes, which are developed by the chemical engineering theory, and based on the incorrect assumption of homogeneous systems. The P-k-C* degradation model was applied in order to define degradation k-rate values of BOD and COD and the frequency distribution profiles were developed. The degradation rate coefficients for BOD ranked from less than 10 m/yr to more than 300 m/yr. Significant higher degradation rates were observed for all the bottom layers and for the closest sampling line from the inlet. The results of COD were similar to those observed for BOD. Finally, the specific pollutants of nitrogen and phosphorus were analysed for total nitrogen (TN) and total phosphorus (TP). The global trend of the TN degradation coefficient values was a slow and regular decrease over length, having systematically higher degradation coefficients for the bottom layers. The saturation of the media sites for sorption capacity of TP was demonstrated being in progress. Les efficacités hydraulique et épuratoire du filtre planté à écoulement horizontal ont été mesurées grâce à un dispositif de prélèvement tridimensionnel dans un filtre en fonctionnement. Des essais de traçage ont été réalisés ainsi que des analyses régulières de la qualité de leau en tous les points déchantillonnage. Les résultats ont démontré que le filtre présente des efficacités hydraulique et volumétrique généralement bonnes, avec relativement peu de zones mortes. Lapplication des modèles mathématiques issus du génie chimique ont permis la détermination du nombre N de réservoirs en série et de calculer les temps de séjour ; ceux-ci ont ensuite été introduit dans le modèle hydraulique de dispersion multi-couches. Ce second modèle a identifié que les flux en eau nétaient pas homogènes avec la profondeur à lintérieur du système et que 60 % de lécoulement se concentraient dans la couche de fond du filtre. Il a également fournit les vitesses découlement par couche, qui se présentent comme plus rapides dans le fond du filtre, et la dispersion axiale, dont la valeur augmente en corrélation avec une diminution de la vitesse. La distribution du débit par horizon a pu être revue comme non homogène avec la profondeur et a permis de recalculer les index hydrauliques et les temps de séjour par horizon en évitant lhypothèse erronée des modèles du génie chimique de lhomogénéité du système. Le modèle de dégradation des polluants P-k-C* a été appliqué pour définir les valeurs des coefficients de dégradation de la DBO, la DCO et lazote total. Les profils de distribution de fréquence ont été dressés. Les différences de coefficients de dégradation de la DBO sont très hautement significatives avec la profondeur et la longueur, en ayant des valeurs plus importantes pour la couche de fond et pour la première ligne de prélèvement la plus proche de la zone de distribution de leffluent dans le filtre. Les résultats obtenus pour la DCO ont été semblables. Les coefficients de dégradation de lazote total ont montré une décroissance lente et régulière avec la longueur, et des valeurs systématiquement plus importantes avec la profondeur. Finalement, il a été démontré que les sites dadsorption du phosphore total sont en cours de saturation.

The discovery of antibiotics is considered as one of the most significant scientific achievements of the 20th century – lives of millions of people and animals have been saved. Thenceforth, substantial amounts of administered antibiotics and their metabo-lites have been excreted into waste stream via urine and faeces. In this dissertation, primary focus is the qualitative balance of 14 antibiotics and one metabolite in urban water management and in urban waters, respectively. In particular, antibiotics pre-scribed to human beings are drained in the urban sewer system and finally enter the environment: (i) Continuously via the effluent of the wastewater treatment plant after a partially effective removal or degradation or (ii) Intermittent via combined sewer overflow structures due to capacity limitations of the urban drainage system. The fate and the potential effects and risks of these substances on ecosystems and hu-man health are of major concern – their direct toxic effect to all trophic levels as well as the global spread of antibiotic resistance genes are challenging. Hence, an assessment of microbial community activity due to antibiotic exposure is presented. In particular, systematic work has been carried out to study the presence and character-istics of 14 antibiotics in urban waters. In detail, investigations were conducted to gain scientific knowledge with respect to adsorption, desorption, abiotic, biotic and photolyt-ic degradation as well as activity-inhibition of microorganism communities in sewage and of natural freshwater biofilm communities, respectively, due to inevitable urban drainage overflows. In order to provide information to assist potential management strategies, which miti-gate surface water pollution and minimize the adverse impacts of antibiotics on activity of microorganism communities, the following specific topics were addressed: ⑴ The occurrence of 14 antibiotics and one metabolite were determined in sewag-es at three sampling sites in the city of Dresden, Germany. ⑵ The adsorption affinities of 14 antibiotics and one metabolite to size dependent sewer sediments were determined in experimental investigations, three sam-pling campaigns and subsequently an antibiotic-specific adsorption coefficient, normalized to organic content, was quantified. ⑶ The desorption affinity and -dynamics of 14 antibiotics and one metabolite were quantified in size dependent sewer sediments in experimental investigation and with statistical analysis. ⑷ The abiotic, biotic and photolytic degradation affinity of 14 antibiotics and one metabolite were quantified based on batch experiments with three different sewages at 7°C and 22°C, with artificial irradiation and different dilution ratios of the sewage at 30°C and subsequently a model framework decrypted ranges of abiotic, biotic and photolytic degradation coefficients. ⑸ The occurrence of three antibiotics, namely ciprofloxacin, clarithromycin and doxycycline was determined in sewage sampled during dry weather conditions in a small catchment of Dresden, which spills intermittently combined sewage (a mixture of sewage and storm water) to an adjacent brook in the case of capacity limitations of the urban drainage system during periods of intense rainfall and subsequently the three antibiotics were determined in the adjacent brook water. ⑹ Then, the activity-inhibition of microorganism community in sewage of this small catchment was quantified due to an exposition with three different antibiotics and three different antibiotic concentrations. ⑺ Last but not least, the activity-inhibition of natural freshwater biofilm communities in the adjacent brook was quantified via exposure to three antibiotics, which were individually dosed in three different concentrations, and also in mixture. ⑻ Finally, a two-dimensional hierarchical cluster analysis with dendrogram and heat map based on before mentioned activity inhibition of natural freshwater biofilm communities were conducted to identify hot spots of antibiotic tolerant and resistant bacterial subpopulations due to inevitable urban drainage system overflows.:List of Figures IV List of Tables VIII Symbols and Abbreviations XII List of Publications on the Ph.D. topic XIX 1 General Introduction 2 1.1 Background 2 1.2 Aims and Objectives 3 1.3 Innovation and Contribution to the Knowledge 4 1.4 Outline of this Thesis 4 1.5 References 6 2 Adsorption and Desorption Affinity of 14 Antibiotics and One Metabolite for particulate components in urban drainage systems 10 2.1 Introduction 11 2.2 Materials and Methods 12 2.2.1 Study area 12 2.2.2 Sewer sediment and sewage sample collection 12 2.2.3 Sediment fractionation 13 2.2.4 Antibiotic determination in sewage and sediment 13 2.3 Results and Discussion 18 2.3.1 Antibiotics in composite sewage samples 18 2.3.2 Antibiotics adsorbed to sewer sediments 19 2.3.3 Organic-bound antibiotic load as a linear function of liquid concentration 20 2.3.4 Adsorption dynamics and adsorption coefficient determined by bath experiments 20 2.3.5 Mineral composition of sewer sediment SED#1B 23 2.3.6 Initial characteristics of sediment SED#1B 23 2.3.7 Desorption dynamics and desorption coefficient of SED#1B 24 2.4 Conclusions 25 2.5 References 26 3 Abiotic, Biotic and Photolytic Degradation Coefficients of 14 Antibiotics and One Metabolite 32 3.1 Introduction 34 3.2 Materials and Methods 35 3.2.1 Study area and sample collection 35 3.2.2 Experimental set up 35 3.2.3 Modelling framework 38 3.2.4 Procedure of model calibration 40 3.3 Results and Discussion 43 3.3.1 Primary metabolic parameter 43 3.3.2 Secondary metabolic parameter 44 3.4 Conclusions 50 3.5 References 50 4 Activity-Inhibition of Microorganisms due to an Exposition with different Antibiotics and Concentrations 56 4.1 Assessing Antibiotic Resistance of Microorganisms in Sanitary Sewage 56 4.1.1 Introduction 57 4.1.2 Material and Methods 58 4.1.2.1 Sampling Site and Antibiotic Agents 58 4.1.2.2 Analyzing Antibiotics 60 4.1.2.3 Respiration Rate 60 4.1.3 Results and Discussion 60 4.1.3.1 Concentration Range of Antibiotics and Typical Sewage Parameters 60 4.1.3.2 Oxygen Uptake Rate 62 4.1.4 Summary and Conclusions 63 4.1.5 References 64 4.2 Hot Spots of Antibiotic Tolerant and Resistant Bacterial Subpopulations in Natural Freshwater Biofilm Communities due to Inevitable Urban Drainage System Overflows 66 4.2.1 Introduction 68 4.2.2 Material and Methods 69 4.2.3 Results and Discussion 72 4.2.4 Conclusions 76 4.2.5 References 76 5 Summery and General Coclusions 82 5.1 Adsorption and Desorption Affinity 82 5.2 Abiotic, Biotic and Photolytic Degradation 83 5.3 Activity-Inhibition of Microorganism Communities due to Antibiotic Exposure 84 5.4 Enhancement of the Stockholm County Council (2014) assessment of antibiotics 84 5.5 References 87 6 Proposed Directions of Future Research 90 7 Appendixes 94 7.1 Chapters 94 7.2 Figures 95 7.3 Tables 115 7.4 References 139

Cette thèse développe des approches pour le diagnostic et le pronostic de systèmes dynamiques incertains en utilisant la technique de modélisation Bond Graph (BG). Tout d'abord, une représentation par intervalles des incertitudes paramétriques et de mesures est intégrée à un modèle BG-LFT (Linear Fractional Transformation). Une méthode de détection robuste de défaut est développée en utilisant les règles de l'arithmétique d'intervalle pour la génération de seuils robustes et adaptatifs sur les résidus nominaux. La méthode est validée en temps réel sur un système de générateur de vapeur.Deuxièmement, une nouvelle méthodologie de pronostic hybride est développée en utilisant les Relations de Redondance Analytique déduites d'un modèle BG et les Filtres Particulaires. Une estimation de l'état courant du paramètre candidat pour le pronostic est obtenue en termes probabilistes. La prédiction de la durée de vie résiduelle est atteinte en termes probabilistes. Les incertitudes associées aux mesures bruitées, les conditions environnementales, etc. sont gérées efficacement. La méthode est validée en temps réel sur un système mécatronique incertain.Enfin, la méthodologie de pronostic développée est mise en œuvre et validée pour le suivi efficace de la santé d'un sous-système électrochimique d’une pile à combustible à membrane échangeuse de protons (PEMFC) industrielle à l’aide de données de dégradation réelles. / This thesis develops the approaches for diagnostics and prognostics of uncertain dynamic systems in Bond Graph (BG) modeling framework. Firstly, properties of Interval Arithmetic (IA) and BG in Linear Fractional Transformation, are integrated for representation of parametric and measurement uncertainties on an uncertain BG model. Robust fault detection methodology is developed by utilizing the rules of IA for the generation of adaptive interval valued thresholds over the nominal residuals. The method is validated in real time on an uncertain and highly complex steam generator system.Secondly, a novel hybrid prognostic methodology is developed using BG derived Analytical Redundancy Relationships and Particle Filtering algorithms. Estimations of the current state of health of a system parameter and the associated hidden parameters are achieved in probabilistic terms. Prediction of the Remaining Useful Life (RUL) of the system parameter is also achieved in probabilistic terms. The associated uncertainties arising out of noisy measurements, environmental conditions etc. are effectively managed to produce a reliable prediction of RUL with suitable confidence bounds. The method is validated in real time on an uncertain mechatronic system.Thirdly, the prognostic methodology is validated and implemented on the electrical electro-chemical subsystem of an industrial Proton Exchange Membrane Fuel Cell. A BG of the latter is utilized which is suited for diagnostics and prognostics. The hybrid prognostic methodology is validated, involving real degradation data sets.