Analyse de sensibilité d’un multimodèle hydrologique

Les enjeux hydrologiques modernes, de prévisions ou liés aux changements climatiques, forcent l’exploration de nouvelles approches en modélisation afin de combler les lacunes actuelles et d’améliorer l’évaluation des incertitudes. L’approche abordée dans ce mémoire est celle du multimodèle (MM). L’innovation se trouve dans la construction du multimodèle présenté dans cette étude : plutôt que de caler individuellement des modèles et d’utiliser leur combinaison, un calage collectif est réalisé sur la moyenne des 12 modèles globaux conceptuels sélectionnés. Un des défis soulevés par cette approche novatrice est le grand nombre de paramètres (82) qui complexifie le calage et l’utilisation, en plus d’entraîner des problèmes potentiels d’équifinalité. La solution proposée dans ce mémoire est une analyse de sensibilité qui permettra de fixer les paramètres peu influents et d’ainsi réduire le nombre de paramètres total à caler. Une procédure d’optimisation avec calage et validation permet ensuite d’évaluer les performances du multimodèle et de sa version réduite en plus d’en améliorer la compréhension. L’analyse de sensibilité est réalisée avec la méthode de Morris, qui permet de présenter une version du MM à 51 paramètres (MM51) tout aussi performante que le MM original à 82 paramètres et présentant une diminution des problèmes potentiels d’équifinalité. Les résultats du calage et de la validation avec le « Split-Sample Test » (SST) du MM sont comparés avec les 12 modèles calés individuellement. Il ressort de cette analyse que les modèles individuels, composant le MM, présentent de moins bonnes performances que ceux calés indépendamment. Cette baisse de performances individuelles, nécessaire pour obtenir de bonnes performances globales du MM, s’accompagne d’une hausse de la diversité des sorties des modèles du MM. Cette dernière est particulièrement requise pour les applications hydrologiques nécessitant une évaluation des incertitudes. Tous ces résultats mènent à une amélioration de la compréhension du multimodèle et à son optimisation, ce qui facilite non seulement son calage, mais également son utilisation potentielle en contexte opérationnel.

Managing and utilizing information flow for new products’ periodic account sales process

The goal was to understand, document and module how information is currently flown internally in the largest dairy organization in Finland. The organization has undergone radical changes in the past years due to economic sanctions between European Union and Russia. Therefore, organization’s ultimate goal would be to continue its growth through managing its sales process more efficiently. The thesis consists of a literature review and an empirical part. The literature review consists of knowledge management and process modeling theories. First, the knowledge management discusses how data, information and knowledge are exchanged in the process. Knowledge management models and processes are describing how knowledge is created, exchanged and can be managed in an organization. Secondly, the process modeling is responsible for visualizing information flow through discussion of modeling approaches and presenting different methods and techniques. Finally, process’ documentation procedure was presented. In the end, a constructive research approach was used in order to identify process’ related problems and bottlenecks. Therefore, possible solutions were presented based on this approach. The empirical part of the study is based on 37 interviews, organization’s internal data sources and theoretical framework. The acquired data and information were used to document and to module the sales process in question with a flowchart diagram. Results are conducted through construction of the flowchart diagram and analysis of the documentation. In fact, answers to research questions are derived from empirical and theoretical parts. In the end, 14 problems and two bottlenecks were identified in the process. The most important problems are related to approach and/or standardization for information sharing, insufficient information technology tool utilization and lack of systematization of documentation. The bottlenecks are caused by the alarming amount of changes to files after their deadlines.

Quantifying the impacts of urban wind sheltering on the building energy consumption

Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.

Exploring redox-driven self-assembly of mixed metal polyoxometalates

How can we control the experimental conditions towards the isolation of specific structures? Why do particular architectures form? These are some challenging questions that synthetic chemists try to answer, specifically within polyoxometalate (POM) chemistry, where there is still much unknown regarding the synthesis of novel molecular structures in a controlled and predictive manner. This work covers a wide range of POM chemistry, exploring the redox self-assembly of polyoxometalate clusters, using both “one-pot”, flow and hydrothermal conditions. For this purpose, different vanadium, molybdenum and tungsten reagents, heteroatoms, inorganic salts and reducing agents have been used. The template effect of lone-pair containing pyramidal heteroatoms has been investigated. Efforts to synthesize new POM clusters displaying pyramidal heteroanions (XO32-, where X= S, Se, Te, P) are reported. The reaction of molybdenum with vanadium in the presence of XO32- heteroatoms is explored, showing how via the cation and experimental control it is possible to direct the self-assembly process and to isolate isostructural compounds. A series of four isostructural (two new, namely {Mo11V7P} and {Mo11V7Te} and two already known, namely {Mo11V7Se} and {Mo11V7S} disordered egg-shaped Polyoxometalates have been reported. The compounds were characterized by X-ray structural analysis, TGA, UV-Vis, FT-IR, Elemental and Flame Atomic Absorption Spectroscopy (FAAS) analysis and Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Cyclic Voltammetry measurements have been carried out in all four compounds showing the effect of the ionic density of the heteroatom on the potential. High-Resolution ESI-MS studies have revealed that the structures retain their integrity in solution. Efforts to synthesize new mixed-metal compounds led to isolation, structural, and electronic characterization of the theoretically predicted, but experimentally elusive δ-isomer of the Keggin polyoxometalate cluster anion, {H2W4V9O33(C6H13NO3)}, by the reaction of tungstate(VI) and vanadium(V) with triethanolammonium ions (TEAH), acting as a tripodal ligand grafted to the surface of the cluster. Control experiments (in the absence of the organic compound) have proven that the tripodal ligand plays crucial role on the formation of the isomer. The six vanadium metal centres, which consist the upper part of the cluster, are bonded to the “capping” TEA tripodal ligand. This metal-ligand bonding directs and stabilises the formation of the final product. The δ-Keggin species was characterized by single-crystal X-ray diffraction, FT-IR, UV-vis, NMR and ESI-MS spectrometry. Electronic structure and structure-stability correlations were evaluated by means of DFT calculations. The compounds exhibited photochromic properties by undergoing single-crystal-to-single-crystal (SC-SC) transformations and changing colour under light. Non-conventional synthetic approaches are also used for the synthesis of the POM clusters comparing the classical “one-pot” reaction conditions and exploring the synthetic parameters of the synthesis of POM compounds. Reactions under hydrothermal and flow conditions, where single crystals that depend on the solubility of the minerals under hot water and high pressure can be synthesized, resulted in the isolation of two isostructural compounds, namely, {Mo12V3Te5}. The compound isolated from a continuous processing method, crystallizes in a hexagonal crystal system, forming a 2D porous plane net, while the compound isolated using hard experimental conditions (high temperature and pressure) crystallizes in monoclinic system, resulting in a different packing configuration. Utilizing these alternative synthetic approaches, the most kinetically and thermodynamically compounds would possibly be isolated. These compounds were characterised by single-crystal X-ray diffraction, FT-IR and UV-vis spectroscopy. Finally, the redox-controlled driven oscillatory template exchange between phosphate (P) and vanadate (V) anions enclosed in an {M18O54(XO4)2} cluster is further investigated using UV-vis spectroscopy as a function of reaction time, showed that more than six complete oscillations interconverting the capsule species present in solution from {P2M18} to {V2M18} were possible, provided that a sufficient concentration of the TEA reducing agent was present in solution. In an effort to investigate the periodicity of the exchange of the phosphate and vanadate anions, time dependent Uv-vis measurements were performed for a period at a range of 170-550 hours. Different experimental conditions were also applied in order to investigate the role of the reducing agent, as well as the effect of other experimental variables on the oscillatory system.

Estudo do genoma do vírus causador da mionecrose infecciosa em camarões e desenvolvimento de métodos para detecção de polimorfismos

Shrimp farming is one of the activities that contribute most to the growth of global aquaculture. However, this business has undergone significant economic losses due to the onset of viral diseases such as Infectious Myonecrosis (IMN). The IMN is already widespread throughout Northeastern Brazil and affects other countries such as Indonesia, Thailand and China. The main symptom of disease is myonecrosis, which consists of necrosis of striated muscles of the abdomen and cephalothorax of shrimp. The IMN is caused by infectious myonecrosis virus (IMNV), a non-enveloped virus which has protrusions along its capsid. The viral genome consists of a single molecule of double-stranded RNA and has two Open Reading Frames (ORFs). The ORF1 encodes the major capsid protein (MCP) and a potential RNA binding protein (RBP). ORF2 encodes a probable RNA-dependent RNA polymerase (RdRp) and classifies IMNV in Totiviridae family. Thus, the objective of this research was study the IMNV complete genome and encoded proteins in order to develop a system differentiate virus isolates based on polymorphisms presence. The phylogenetic relationship among some totivirus was investigated and showed a new group to IMNV within Totiviridae family. Two new genomes were sequenced, analyzed and compared to two other genomes already deposited in GenBank. The new genomes were more similar to each other than those already described. Conserved and variable regions of the genome were identified through similarity graphs and alignments using the four IMNV sequences. This analyze allowed mapping of polymorphic sites and revealed that the most variable region of the genome is in the first half of ORF1, which coincides with the regions that possibly encode the viral protrusion, while the most stable regions of the genome were found in conserved domains of proteins that interact with RNA. Moreover, secondary structures were predicted for all proteins using various softwares and protein structural models were calculated using threading and ab initio modeling approaches. From these analyses was possible to observe that the IMNV proteins have motifs and shapes similar to proteins of other totiviruses and new possible protein functions have been proposed. The genome and proteins study was essential for development of a PCR-based detection system able to discriminate the four IMNV isolates based on the presence of polymorphic sites

Inhalable antitubercular therapy mediated by locust bean gum microparticles

Tuberculosis remains a major global health problem and alternative therapeutic approaches are needed. Considering the high prevalence of lung tuberculosis (80% of cases), the pulmonary delivery of antitubercular drugs in a carrier system capable of reaching the alveoli, being recognised and phagocytosed by alveolar macrophages (mycobacterium hosts), would be a significant improvement to current oral drug regimens. Locust bean gum (LBG) is a polysaccharide composed of galactose and mannose residues, which may favour specific recognition by macrophages and potentiate phagocytosis. LBG microparticles produced by spray-drying are reported herein for the first time, incorporating either isoniazid or rifabutin, first-line antitubercular drugs (association efficiencies >82%). Microparticles have adequate theoretical properties for deep lung delivery (aerodynamic diameters between 1.15 and 1.67 μm). The cytotoxic evaluation in lung epithelial cells (A549 cells) and macrophages (THP-1 cells) revealed a toxic effect from rifabutin-loaded microparticles at the highest concentrations, but we may consider that these were very high comparing with in vivo conditions. LBG microparticles further evidenced strong ability to be captured by macrophages (percentage of phagocytosis >94%). Overall, the obtained data indicated the potential of the proposed system for tuberculosis therapy.

AN ASSESSMENT OF FLOW REGIME MAPS AND A NUMERICAL HEAT TRANSFER CORRELATION FOR THE STRATIFIED/ANNULAR REGIME OF SHEAR-DRIVEN INTERNAL CONDENSING FLOWS

Several modern-day cooling applications require the incorporation of mini/micro-channel shear-driven flow condensers. There are several design challenges that need to be overcome in order to meet those requirements. The difficulty in developing effective design tools for shear-driven flow condensers is exacerbated due to the lack of a bridge between the physics-based modelling of condensing flows and the current, popular approach based on semi-empirical heat transfer correlations. One of the primary contributors of this disconnect is a lack of understanding caused by the fact that typical heat transfer correlations eliminate the dependence of the heat transfer coefficient on the method of cooling employed on the condenser surface when it may very well not be the case. This is in direct contrast to direct physics-based modeling approaches where the thermal boundary conditions have a direct and huge impact on the heat transfer coefficient values. Typical heat transfer correlations instead introduce vapor quality as one of the variables on which the value of the heat transfer coefficient depends. This study shows how, under certain conditions, a heat transfer correlation from direct physics-based modeling can be equivalent to typical engineering heat transfer correlations without making the same apriori assumptions. Another huge factor that raises doubts on the validity of the heat-transfer correlations is the opacity associated with the application of flow regime maps for internal condensing flows. It is well known that flow regimes influence heat transfer rates strongly. However, several heat transfer correlations ignore flow regimes entirely and present a single heat transfer correlation for all flow regimes. This is believed to be inaccurate since one would expect significant differences in the heat transfer correlations for different flow regimes. Several other studies present a heat transfer correlation for a particular flow regime - however, they ignore the method by which extents of the flow regime is established. This thesis provides a definitive answer (in the context of stratified/annular flows) to: (i) whether a heat transfer correlation can always be independent of the thermal boundary condition and represented as a function of vapor quality, and (ii) whether a heat transfer correlation can be independently obtained for a flow regime without knowing the flow regime boundary (even if the flow regime boundary is represented through a separate and independent correlation). To obtain the results required to arrive at an answer to these questions, this study uses two numerical simulation tools - the approximate but highly efficient Quasi-1D simulation tool and the exact but more expensive 2D Steady Simulation tool. Using these tools and the approximate values of flow regime transitions, a deeper understanding of the current state of knowledge in flow regime maps and heat transfer correlations in shear-driven internal condensing flows is obtained. The ideas presented here can be extended for other flow regimes of shear-driven flows as well. Analogous correlations can also be obtained for internal condensers in the gravity-driven and mixed-driven configuration.

Geographic Provenancing of Unprocessed Cotton Using Elemental Analysis and Stable Isotope Ratios

Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the “useful ablation efficiency” for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A comparative study of alternative approaches for common factors identification

Preliminary version

Alternative harvest strategies to alleviate predation bottlenecks: a bioeconomic modeling approach to inform adaptive management

Thesis (Ph.D.)--University of Washington, 2016-06

Computational approaches and tools for modeling biomass pyrolysis

Thesis (Ph.D.)--University of Washington, 2016-08

The Swiss heroin trials: testing alternative approaches

Over half a million heroin misusers receive oral methadone maintenance treatment world-wide1 but the maintenance prescription of injectable opioid drugs, like heroin, remains controversial. In 1992 Switzerland began a large scale evaluation of heroin and other injectable opiate prescribing that eventually involved 1035 misusers. 2 3 The results of the evaluation have recently been reported.4 These show that it was feasible to provide heroin by intravenous injection at a clinic, up to three times a day, for seven days a week. This was done while maintaining good drug control, good order, client safety, and staff morale. Patients were stabilised on 500 to 600 mg heroin daily without evidence of increasing tolerance. Retention in treatment was 89% at six months and 69% at 18 months.4 The self reported use of non-prescribed heroin fell signifianctly, but other drug use was minimally affected. The death rate was 1% per year, and there were no deaths from overdose among participants . . . [Full text of this article]

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.