Although a number of definitions of mixing have been proposed in the literature, no single definition accurately and clearly describes the full range of problems in the field of industrial mixing. Based on the review of mixing and segregation characterization techniques in chemical engineering, spatial statistics and population studies, a definition of industrial mixing is proposed in this thesis, based on three separate dimensions of segregation. The first dimension is the intensity of segregation which quantifies the uniformity of concentration; the second dimension is the scale of segregation or clustering; and the last dimension is the exposure or the potential to reduce segregation. The first dimension focuses on the instantaneous concentration variance; the second on the instantaneous length scales in the mixing field; and the third on the driving force for change, i.e. the mixing time scale, or the instantaneous rate of reduction in segregation. The definition is introduced using concepts, theory and mathematical equations. This definition provides a theoretical framework for the rigorous analysis of mixing problems, encompassing all industrial mixing processes and allowing a clear evaluation of experimental methods. In this work, the three dimensions of segregation are presented and defined in the context of previous definitions of mixing, and then applied to a range of industrial mixing problems to test their accuracy and robustness. Suitable quantities for direct measurement of the dimensions of segregation are then investigated in detail. The result is a toolkit of ready-to-use methods for the measurement of the intensity (CoV) and the scale of segregation (maximum striation thickness on a transect, point-to-nearest neighbour distributions and variogram), provided as Matlab codes. The chosen methods are thoroughly investigated by testing their applicability, limitations, sampling strategies and meaningfulness of the results using selected sets of mixing data, resulting in creation of guidelines for the use of each of the provided methods. The developed definition of mixing, together with tools and guidelines for measurement of mixing will help researches to further develop the field of mixing, engineers to solve practical industrial mixing problems, and instructors of chemical engineering courses to introduce mixing concepts more easily. / Chemical Engineering

La circulation atmosphérique en Afrique de l'Ouest est caractérisée par des vents de sud-ouest (mousson) pendant la saison humide et par des vents de nord-est (harmattan) pendant la saison sèche. Cette alternance des saisons est due aux variations de pression liée à l'état des surfaces (rugosité, albédo, végétation) en réaction au forçage solaire. Ces mêmes états de surface génèrent une variabilité de flux turbulents de surface et des circulations secondaires qui rendent complexes les analyses des mesures effectuées sur place en vue de documenter les interactions surface-atmosphère. La modélisation fine échelle (LES) couramment utilisée dans l'étude de la couche limite atmosphérique est requise pour pouvoir palier à ces difficultés en raison de sa capacité à prendre en compte les flux turbulents en 3D et sur topographie complexe. Notre site d'étude est le bassin versant d'ARA située au Nord du Bénin dans un contexte Soudanien avec des propriétés de surface variables. Une analyse climatique est effectuée sur la base des observations de radiosondage, de radar UHF et de stations au sol afin d'extraire des données composites représentatives des saisons sèche et humide. Ces données composites ont servi par la suite à forcer le modèle Méso-NH dans sa version LES. Pour pouvoir caractériser les échelles de longueur des flux turbulents de surface relatives aux saisons sèche et humide, les données standard de forçage de surface de Méso-NH que sont le relief GTOPO30 (1km de résolution) et la végétation ECOCLIMAP (1km de résolution) ont été respectivement remplacer par le SRTM (90m de résolution) et les données de SPOT/HRV (20m de résolution) reéchantillonné à 90m de résolution. A l'aide d'outils statistiques comme la variographie 2D et le suivi Lagrangien, il ressort que la variabilité spatiale de la chaleur sensible H est gouvernée par le couple vent-relief tandis que celle de la chaleur latente E est difficile à mettre en lien sur végétation hétérogène (SPOT/HRV) en saison sèche. En saison humide, la variabilité spatiale du champ H dépend du vent tandis que celle du champ E dépend de la végétation. Cette étude révèle dans tous les cas que les échelles caractéristiques de ces deux champs diffèrent dans les mêmes conditions de forçage de surface et atmosphérique. / West Africa atmosphere circulation is characterized by south-westerly wind (monsoon regime) during the wet season and north-easterly wind (harmattan regime) during the dry season. This alternation of wind regime is due to surface pressure variability linked to surface heterogeneities. Surface heterogeneities generate surface flux variability, secondary circulation and make complex analysis when trying to document surface-atmosphere feedbacks. LES modelling usually used for boundary-layer studies due to its potential to take into account 3D turbulence over complex topography, is used here to overcome these difficulties. Our site of interest is located in north of Benin characterized by Soudanian climate and heterogeneous surface properties. Climate analysis are first performed with radiosoundings, UHF radar, and EC station data in order to extract composite profile representing dry and wet season.. These composite profiles are then used to force atmosphere part of the Méso-NH LES model. To characterize turbulent fluxes length scales relative to dry and wet season, standard surface forcing data with Méso-NH like GTOPO30 orography (1km ) and ECOCLIMAP vegetation (1km) are respectively replaced by SRTM (90m) and SPOT/HRV vegetation data (20m) resampled to 90m. Along with statistical tools like 2D variography and Lagrangian, we notice that during dry season on heterogeneous vegetation, sensible heat flux H is more driven by wind and orography while we not able to discuss the latent heat flux E case. During wet season with the same surface forcing, it appears that H is driven by wind while E is more dependent to vegetation variability. Our study concludes in all case that H and E are not characterized by the same length scale.

Kriging techniques are regression methods used for evaluation of continuous spatial processes. If the covariance structure of process is unknown, then it's necessary to estimate it from the data. The first part of this Master's thesis is devoted to description the kriging method and to estimate of a variogram fuction, which describes the covariance structure of considered process. The second part includes the implementation of kriging method in MATLAB for simulated and real data.

No description available.

If mitigation measures are not made to prevent global warming the consequences of a continued global climate change, caused by the use of fossil fuels, may be severe. Carbon Capture and Storage (CCS) has been suggested as a way of decreasing the global atmospheric emission of CO2. In the realms of MUSTANG, a four year (2009-2013) large-scale integrating European project funded by the EU FP7, the objective is to gain understanding of the performance as well as to develop improved methods and models for characterizing so- called saline aquifers for geological storage of CO2. In this context a number of sites of different geological settings and geographical locations in Europe are also analyzed and modeled in order to gain a wide understanding of CO2 storage relevant site characteristics. The south Scania site is included into the study as one example site with data coming from previous geothermal and other investigations. The objective of the Master's thesis work presented herein was to construct a 3D model for the south Scania site by using modeling/simulation software Petrel, evaluate well log data as well as carry out stochastic simulations by using different geostatistical algorithms and evaluate the benefits in this. The aim was to produce a 3D model to be used for CO2 injection simulation purposes in the continuing work of the MUSTANG project. The sequential Gaussian simulation algorithm was used in the porosity modeling process of the Arnager greensand aquifer with porosity data determined from neutron and gamma ray measurements. Five hundred realizations were averaged and an increasing porosity with depth was observed.   Two different algorithms were used for the facies modeling of the alternative multilayered trap, the truncated Gaussian simulation algorithm and the sequential indicator simulation algorithm. It was seen that realistic geological models were given when the truncated Gaussian simulation algorithm was used with a low-nugget variogram and a relatively large range. / Den antropogena globala uppvärmningen orsakad av användandet av fossila bränslen kan få förödande konsekvenser om ingenting görs. Koldioxidavskiljning och lagring är en åtgärd som föreslagits för att minska de globala CO2-utsläppen. Inom ramarna för MUSTANG, ett fyra år långt (2009-2013) integrerande projekt finansierat av EU FP7 (www.co2mustang.eu), utvecklas metoder, modeller och förståelse angående så kallade saltvattenakviferers lämplighet för geologisk koldioxidlagring. En del av projektet är att analysera ett antal representativa formationer i olika delar av Europa för att få kunskap angående förekommande koldioxidlagringsspecifika egenskaper hos saltvattenakviferer. Ett av områdena som har inkluderats är i sydvästra Skåne. Syftet med detta examensarbete var att konstruera en 3D modell över detta område med hjälp av modellerings/simuleringsprogrammet Petrel, utvärdera borrhålsdata samt genomföra stokastiska simuleringar med olika geostatistiska algoritmer och utvärdera dem. Målsättningen var att konstruera en modell för CO2 injiceringssimuleringar i det forstsatta arbetet inom MUSTANG-projektet. En algoritm av sekventiell Gaussisk typ användes vid porositetsmodelleringen av Arnager Grönsandsakviferen med porositetsdata erhållen från neutron- och gammastrålningsmätningar. Ett genomsnitt av femhundra realisationer gjordes och en porositetstrend som visade en ökning med djupet kunde åskådligöras. Två olika algoritmer användes vid faciesmodelleringen av den alternativa flerlagrade fällan: en algoritm av trunkerade Gaussisk typ och en sekventiell indikatorsimuleringsalgoritm. Resultaten tyder på att en realistisk geologisk modell kan erhållas vid användandet av den trunkerande algoritmen med ett låg-nugget variogram samt en förhållandevis lång range.

Near-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices.

Cette thèse est une contribution à la construction de l’Approche Locale de la rupture à l’échelle microscopique à l’aide de la modélisation d’agrégats polycristallins. Elle consiste à prendre en compte la variabilité spatiale de la microstructure du matériau. Pour ce faire, la modélisation micromécanique du matériau est réalisée par la simulation d’agrégats polycristallins par éléments finis. Les champs aléatoires de contrainte (principale maximale et de clivage) dans le matériau qui représentent la variabilité spatiale de la microstructure sont ensuite modélisés par un champ aléatoire gaussien stationnaire ergodique. Les propriétés de variabilité spatiale de ces champs sont identifiés par une méthode d’identification, e.g. méthode du périodogramme, méthode du variogramme, méthode du maximum de vraisemblance. Des réalisations synthétiques des champs de contraintes sont ensuite simulées par une méthode de simulation, e.g. méthode Karhunen-Loève discrète, méthode “Circulant Embedding”, méthode spectrale, sans nouveau calcul aux éléments finis. Enfin, le modèle d’Approche Locale de la rupture par simulation de champ de contrainte de clivage permettant d’y intégrer les réalisations simulées du champ est construit pour estimer la probabilité de rupture du matériau. / This thesis is a contribution to the construction of the Local Approach to fracture at the microscopic scale using polycrystalline aggregate modeling. It consists in taking into account the spatial variability of the microstructure of the material. To do this, the micromechanical modeling is carried out by finite element analysis of polycrystalline aggregates. The random stress fields (maximum principal et cleavage stress) in the material representing the spatial variability of the microstructure are then modeled by a stationary ergodic Gaussian random field. The properties of the spatial variability of these fields are identified by an identification method, e.g. periodogram method, variogram method, maximum likelihood method. The synthetic realizations of the stress fields are then simulated by a simulation method, e.g. discrete Karhunen-Loève method, circulant embedding method, spectral method, without additional finite element calculations. Finally, a Local Approach to fracture by simulation of the cleavage stress field using the simulated realizations is constructed to estimate the rupture probability of the material.

Within the context of the assessment of laryngeal function, acoustic analysis has an important place because the speech signal may be recorded non-invasively and it forms the base on which the perceptual assessment of voice is founded. Given the limitations of perceptual ratings, one has investigated vocal cues of disordered voices that are clinically relevant, summarize properties of speech signals and report on a speaker's phonation in general and voice in particular. Ideally, the acoustic descriptors should also be correlates of auditory-perceptual ratings of voice. Generally speaking, the goal of acoustic analysis is to document quantitatively the degree of severity of a voice disorder and monitor the evolution of the voice of dysphonic speakers.<p><p><p>The first part of this thesis is devoted to the analysis of disordered connected speech. The aim is to investigate vocal cues that are clinically relevant and correlated with auditory-perceptual ratings. Two approaches are investigated. The variogram-based method in the temporal domain is addressed first. The second approach is in the cepstral domain. In particular, the first rahmonic amplitude is used as an acoustic cue to describe voice quality. A multi-dimensional approach combining temporal and spectral aspects is also investigated. The goal is to check whether acoustic cues in both domains report complementary information when predicting perceptual scores.<p><p><p>Both methods are tested first on a corpus of synthetic sound stimuli that has been obtained by means of a synthesizer of disordered voices. The purpose is to learn about the link between the signal properties (fixed by the synthesis parameters) and acoustic cues.<p>In this study, we had the opportunity to use two large natural speech corpora. One of them has been perceptually rated. <p><p><p>The final part of the text is devoted to the automatic classification of voice with regard to perceived voice quality. Many studies have proposed a binary (normal/pathological) classification of voice samples. An automatic categorization according to perceived degrees of hoarseness appears, however, to be more attractive to both clinicians and technologists and more likely to be clinically relevant. Indeed, one way to reduce inter-rater variability of an auditory-perceptual evaluation is to ask several experts to participate and then to average the perceptual scores. However, auditory-perceptual evaluation of a corpus by several judges is a very laborious, time-consuming and costly task. Making this perceptual evaluation task automatic is therefore desirable. <p>The aim of this study is to exploit the support vector machine classifier that has become, over the last years, a popular tool for classification, to carry out categorization of voices according to perceived degrees of hoarseness. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished