In response to organic contaminations pollutating water sources of drinking water, domestic water treatment plants (WTP) were transforming from traditional chlorination disinfecton method to advanced ozone-based disinfection processes. However, the effectiveness of water purification procedures n removing AOC (Assimilable Organic Carbon) and DBPsFP (Disinfection By-Products Formation Potential) can be improved. Additionally, the quality of clean water purified at WTP may deteriorate in the water distribution network for various reasons, primarily resulting from the regrowth of microorganisms in the water distribution pipelines. This study investigates and researches the essential water quality items of effluent before and after the advanced water purification treatment plants and water movement to end users through water distribution networks. The investigation proceeded in four directions: (1) the efficiency of removing AOC from raw water using powdered and granular activated carbon biological systems, and the development of an AOC prediction model based on water quality monitoring items using the AutoNet (6.03) method of the artificial neural network system; (2) removal of the byproducts of disinfection from raw water using powdered activated carbon biological systems; (3) examining the relationship between ozone-based and chlorination-based water disinfection methods by comparing the number of coliform bacteria and total bacteria population in traditional and advanced processing units; (4) regarding the water distribution storage facilities for users, water reservoir towers were examined for water quality sampling and analysis and water tower cleaning frequencies. Regression analysis was performed using SPSS ¡]Statistical Product and Service Solutions¡^ statistical software, with the correlation coefficient denoting the closeness of relationships. We anticipate understanding the water quality situation for current users of tap water, and demands for cleaning frequencies, thereby achieving the purpose of improving drinking water safety. Regarding the efficiency of removing AOC from raw water, the results showed powdered and granular activated carbon biological systems performed well, with the AOC removal rate reaching 53% and 54%, respectively, and the SUVA (Specific Ultraviolet Absorbance) value (showed by UV254/DOC) being reduced by 15-18% and 22-23%, respectively. The correlation analysis of the AOC prediction model shows that the GAC (Granular Activated Carbon) had high predictive and actual value R values (R2 = 0.772) after model regressing, and the PAC (Powder Activated Carbon) had higher predictive and actual value R values (R2 = 0.856) after model regressing as well. That the PAC system AOC prediction model has a slightly higher correlation that may be attributed to water contaminations resulting from domestic sewage, agricultural fertilizers, and livestock excretions. In the use of powdered activated carbon biological systems to remove disinfection byproducts, THMsFP (Trihalomethanes Formation Potential) and HAAsFP (Haloacetic acids Formation Potential) functioned with a certain removal efficiency, with the average effluent concentrations being under the regulatory standard of 80£gg/L, respectively, which reduces carcinogenic risks. Correlation analyses conducted using SUVA on the three water quality concentrations (HAA5FP, HAA9FP, and THMsFP) obtained R2 values of 0.805, 0.820, and 0.823, respectively, indicating high levels of correlation. For the results of microbial assessment using ozone and chlorine to process drinking water, the advanced and conventional WTP achieved a removal rate greater than 99% for microbial removal (coliform bacteria and total bacteria population). The correlation analysis between cleaning frequencies and water quality parameters showed the frequency at which the water reservoirs and towers were cleaned has a significant impact on tap water quality in residential compounds and schools that accommodated more than 100 households or less than 99 households. Higher cleaning frequency (more than four cleanings a year) results in better the water quality.

L’os est un matériau vivant avec une structure hiérarchique complexe qui lui confère des propriétés mécaniques remarquables. L’os subit perpétuellement des contraintes mécaniques et physiologiques, ainsi sa qualité et sa résistance à la fracture évoluent constamment au cours du temps à travers le processus de remodelage osseux. La qualité osseuse est non seulement définie par la densité minérale osseuse mais également par les propriétés mécaniques ainsi que la microarchitecture. Dans le cadre de la présente thèse, on a développé une modélisation multiéchelle unifiée couplant à la fois les activités cellulaires au comportement mécanique de l'os tenant compte des différents niveaux hiérarchiques de l'os: de l’ultrastructure au remodelage osseux. Ce modèle permet d’étudier le comportement mécano-bibliologique de l’os et de prédire ses propriétés mécaniques apparentes à différentes échelles allant du nanoscopique au macroscopique en fonction des constituants élémentaires de l'os. Pour atteindre cet objectif, une démarche en quatre phases a été adoptée. La première phase consiste à décrire les constituants élémentaires de l’os. La deuxième phase avait pour objectif la modélisation multiéchelle de l'ultrastructure osseuse constituée de trois échelles nanoscopiques (microfibrille, fibrille et fibre) par la méthode des éléments finis et des réseaux de neurones. La troisième phase correspond à la modélisation des échelles micro-macroscopiques de l’os cortical (lamelle, ostéon, os cortical) en utilisant comme paramètres d’entrée les propriétés de la fibre déterminées dans la deuxième phase. Enfin, dans la dernière phase, on a développé un modèle mécano-biologique du remodelage osseux permettant de simuler le processus d'adaptation osseuse tenant compte explicitement des activités biologiques des cellules osseuses. Les propriétés mécaniques prédites par nos algorithmes multiéchelles ont servi pour alimenter le modèle de remodelage. Ce modèle a été implémenté au code de calcul d’éléments finis ABAQUS/Standard à travers sa routine utilisateur UMAT. Finalement, le modèle EF mécano-biologique multiéchelle du remodelage osseux a été appliqué pour simuler différents scénarii de remodelage sur des fémurs humains (2D et 3D). Différents facteurs ont été ainsi analysés tels que l'âge, le genre, l'amplitude des activités physiques, etc. Les résultats obtenus sont conformes (qualitativement) avec les observations cliniques et cohérents avec les différentes études expérimentales. En conclusion: (i) Les modèles unifiés ainsi développés (modèle multiéchelle, modèle mécano-biologique de remodelage osseux) contribuent à l'analyse fine du comportement de l'os humain. (ii) L'application des algorithmes a permis d'effectuer des essais virtuels pour analyser les effets combinés de nombreux facteurs caractérisant la qualité osseuse. / Bone is a living material with a complex hierarchical structure which entails exceptional mechanical properties. Bone undergoes permanent mechanical and physiological stresses, thus its quality and fracture toughness are constantly evolving over time through the process of bone remodeling. Bone quality is not only defined by bone mineral density but also by the mechanical properties and microarchitecture. The current thesis offers a multiscale modeling approach unifying the cell activity to the mechanical behavior, taking into consideration the hierarchical levels of bone, from the ultrastructure to bone remodeling. This model permits to study the mechanobiological behavior and to predict the mechanical properties of the bone at different scales from nano to macro depending on the elementary constituents of bone. To achieve the objective of the current work, an approach of four phases was adopted. The first phase is to describe the basic components of the bone. The second phase concerns the multiscale modeling of the three nanoscopic levels of bone ultrastructure (microfibril, fibril and fiber) by the finite element method and neural networks. The third phase aims to model the micro-macroscopic structures of cortical bone (lamella, osteon, cortical bone) using the fiber properties predicted from the second phase as input parameters. In the last phase, a mechano-biological model of bone remodeling was achieved to simulate the process of bone adaptation explicitly considering the biological activities of bone cells. Mechanical properties predicted by our multiscale algorithms were used to feed the remodeling model. This model has been implemented into the ABAQUS/Standard finite elements code as a user subroutine. Finally, the finite element mechano-biological multiscale model of bone remodeling was applied to simulate different scenarios on human femurs (2D and 3D). Hence, different factors such as: age, gender, physical activities, etc were analyzed. The obtained results are conformed (qualitatively) to clinical observations and consistent with the various experimental studies. In summary, (i) the models portrayed here (multiscale model, mechanical-biological model of bone remodeling) contribute by their unified approach to the realistic modeling of the response of human bone. (ii) The application of the algorithms permits to perform virtual experiments to scrutinize the combined effects of numerous factors dictating the bone quality.

This diploma thesis deals with the method which are useful for analysis of reliability in specific circuit applications. It also deals with fault analysis in frequency, time and DC domain. Methods for these domains are described in other chapter of this thesis. Finally methods for diagnostics analog circuit are evaluated based on simulation and practical testing of selected methods.