Multidisciplinary design optimization (MDO) requires many designs to be evaluated while searching for an optimum. As a result, the calculations done to evaluate the designs must be quick and simple to have a reasonable turn-around time. This makes aerodynamic calculations in the transonic regime difficult. Running computational fluid dynamics (CFD) calculations within the MDO code would be too computationally expensive. Instead, CFD is used outside the MDO to find two-dimensional aerodynamic properties of a chosen airfoil shape, BACJ, at a number of points over a range of thickness-to-chord ratios, free-stream Mach numbers, and lift coefficients. These points are used to generate surrogate models which can be used for the two-dimensional aerodynamic calculations required by the MDO computational design environment. Strip theory is used to relate these two-dimensional results to the three-dimensional wing. Models are developed for the center of pressure location, the lift curve slope, the wave drag, and the maximum allowable lift coefficient before buffet. These models have good agreement with the original CFD results for the airfoil. The models are integrated into the aerodynamic and aeroelastic sections of the MDO code. / Master of Science

It is a well-known fact that a power system contains many sources of uncertainties. These uncertainties coming from the loads, the renewables, the model and the measurement, etc, are influencing the steady state and dynamic response of the power system. Facing this problem, traditional methods, such as the Monte Carlo method and the Perturbation method, are either too time consuming or suffering from the strong nonlinearity in the system. To solve these, this Dissertation will mainly focus on developing the polynomial chaos based method to replace the traditional ones. Using it, the uncertainties from the model and the measurement are propagated through the polynomial chaos bases at a set of collocation points. The approximated polynomial chaos coefficients contain the statistical information. The method can greatly accelerate the calculation efficiency while not losing the accuracy, even when the system is highly stressed. In this dissertation, both the forward problem and the inverse problem of uncertainty quantification will be discussed. The forward problems will include the probabilistic power flow problem and statistical power system dynamic simulations. The generalized polynomial chaos method, the adaptive polynomial chaos-ANOVA method and the multi-element polynomial chaos method will be introduced and compared. The case studies show that the proposed methods have great performances in the statistical analysis of the large-scale power systems. The inverse problems will include the state and parameter estimation problem. A novel polynomial-chaos-based Kalman filter will be proposed. The comparison studies with other traditional Kalman filter demonstrate the good performances of the proposed Kalman filter. We further explored the area dynamic parameter estimation problem under the Bayesian inference framework. The polynomial-chaos-expansions are treated as the response surface of the full dynamic solver. Combing with hybrid Markov chain Monte Carlo method, the proposed method yields very high estimation accuracy while greatly reducing the computing time. For both the forward problem and the inverse problems, the polynomial chaos based methods haven shown great advantages over the traditional methods. These computational techniques can improve the efficiency and accuracy in power system planning, guarantee the rationality and reliability in power system operations, and, finally, speed up the power system dynamic security assessment. / PHD / It is a well-known fact that a power system state is inherently stochastic. Sources of stochasticity include load random variations, renewable energy intermittencies, and random outages of generating units, lines, and transformers, to cite a few. These stochasticities translate into uncertainties in the models that are assumed to describe the steady-sate and dynamic behavior of a power system. Now, these models are themselves approximate since they are based on some assumptions that are typically violated in practice. Therefore, it does not come as a surprise if recent research activities in power systems are focusing on how to cope with uncertainties when dealing with power system planning, monitoring and control. This Dissertation is developing polynomial-chaos-based method in quantifying, and managing these uncertainties. Three major topics, including uncertainty quantification, state estimation and parameter estimation are discussed. The developed method can improve the efficiency and accuracy in power system planning, guarantee the rationality and reliability in power system operations in dealing with the uncertainties, and, finally, enhancing the resilience of the power systems.

El trabajo presentado en esta Tesis está motivado por la necesidad de los motores de combustión interna alternativos de reducir el consumo de combustible y las emisiones de CO2 mientras se satisfacen las cada vez más restrictivas regulaciones de emisiones contaminantes. Por lo tanto, el objetivo principal de este estudio es optimizar un sistema de combustión de encendido por compresión controlado por mezcla para probar su potencial como motores de futura generación. Con esta meta se ha desarrollado un sistema automático que combina CFD con métodos de optimización avanzados para analizar y entender las configuraciones óptimas. Los resultados presentados en este trabajo se dividen en dos bloques principales. El primero corresponde a la optimización de un sistema de encendido por compresión convencional alimentado con diésel. El segundo se centra en un concepto de combustión avanzado donde se ha sustituido el fuel por Dimetil-eter. En ambos casos, el estudio no sólo halla una configuración óptima sino que también se describen las relaciones causa/efecto entre los parámetros más relevantes del sistema de combustión. El primer bloque aplica métodos de optimización no-evolutivos a un motor medium-duty alimentado por diésel tratando de minimizar consumo a la vez que se mantienen las emisiones contaminantes por debajo de los estándares de emisiones contaminantes impuestos. Una primera parte se centra en la optimización de la geometría de la cámara de combustión y el inyector. Seguidamente se extiende el estudio añadiendo los settings de renovación de la carga de y de inyección al estudio, ampliando el potencial de la optimización. El estudio demuestra el limitado potencial de mejora de consumo que tiene el motor de referencia al mantener los niveles de emisiones contaminantes. Esto demuestra la importancia de incluir parámetros de renovación de la carga e inyección al proceso de optimización. El segundo bloque aplica una metodología basada en algoritmos genéticos al diseño del sistema de combustión de un motor heavy-duty alimentado con Dimetileter. El estudio tiene dos objetivos, primero la optimización de un sistema de combustión convencional controlado por mezcla con el objetivo de lograr mejorar el consumo y reducir las emisiones contaminantes hasta niveles inferiores a los estándares US2010. Segundo la optimización de un sistema de combustión trabajando en condiciones estequiométricas acoplado con un catalizador de tres vías buscando reducir consumo y controlar las emisiones contaminantes por debajo de los estándares 2030. Ambas optimizaciones incluyen tanto la geometría como los parámetros más relevantes de renovación de la carga y de inyección. Los resultados presentan un sistema de combustión convencional óptimo con una notable mejora en rendimiento y un sistema de combustión estequiométrica que es capaz de ofrecer niveles de NOx menores al 1% de los niveles de referencia manteniendo niveles competitivos de rendimiento. Los resultados presentados en esta Tesis ofrecen una visión extendida de las ventajas y limitaciones de los motores MCCI y el camino a seguir para reducir las emisiones de futuros sistemas de combustión por debajo de los estándares establecidos. A su vez, este trabajo también demuestra el gran potencial que tiene el Dimetil-eter como combustible para futuras generaciones de motores. / The work presented in this Thesis was motivated by the needs of internal combustion engines (ICE) to decrease fuel consumption and CO2 emissions, while fulfilling the increasingly stringent pollutant emission regulations. Then, the main objective of this study is to optimize a mixing-controlled compression ignition (MCCI) combustion system to show its potential for future generation engines. For this purpose an automatic system based on CFD coupled with different optimization methods capable of optimizing a complete combustion system with a reasonable time cost was designed together with the methodology to analyze and understand the new optimum systems. The results presented in this work can be divided in two main blocks, firstly an optimization of a conventional diesel combustion system and then an optimization of a MCCI system using an alternative fuel with improved characteristics compared to diesel. Due to the methodologies used in this Thesis, not only the optimum combustion system configurations are described, but also the cause/effect relations between the most relevant inputs and outputs are identified and analyzed. The first optimization block applies non-evolutionary optimization methods in two sequential studies to optimize a medium-duty engine, minimizing the fuel consumption while fulfilling the emission limits in terms of NOx and soot. The first study targeted four optimization parameters related to the engine hardware including piston bowl geometry, injector nozzle configuration and mean swirl number. After the analysis of the results, the second study extended to six parameters, limiting the optimization of the engine hardware to the bowl geometry, but including the key air management and injection settings. The results confirmed the limited benefits, in terms of fuel consumption, with constant NOx emission achieved when optimizing the engine hardware, while keeping air management and injection settings. Thus, including air management and injection settings in the optimization is mandatory to significantly decrease the fuel consumption while keeping the emission limits. The second optimization block applies a genetic algorithm optimization methodology to the design of the combustion system of a heavy-duty Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional mixing-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric mixing-controlled combustion system coupled with a three way catalyst to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The target of the optimizations is to improve net indicated efficiency while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels. Compared to the baseline engine fueled with DME, the results of the study provide an optimum conventional combustion system with a noticeable NIE improvement and an optimum stoichiometric combustion system that offers a limited NIE improvement keeping tailpipe NOx values below 1% of the original levels. The results presented in this Thesis provide an extended view of the advantages and limitations of MCCI engines and the optimization path required to achieve future emission standards with these engines. Additionally, this work showed how DME is a promising fuel for future generation engines since it is able to achieve future emission standards while maintaining diesel-like efficiency / El treball presentat en esta Tesi està motivat per la necessitat dels motors de combustió interna alternatius de reduir el consum de combustible i les emissions de CO2 mentres se satisfan les cada vegada mes restrictives regulacions d'emissions contaminants. Per tant, l'objectiu principal d'este estudi es optimitzar un sistema de combustió d'encesa per compressió controlat per mescla per a provar el seu potencial com a motors de futura generació. Amb esta meta s'ha desenrotllat un sistema automàtic que combina CFD amb mètodes d'optimització avançats per a analitzar i entendre les configuracions òptimes. Els resultats presentats en este treball es dividixen en dos blocs principals. El primer correspon a l'optimització d'un sistema d'encesa per compressió convencional alimentat amb dièsel. El segon se centra en un concepte de combustió avançat on s'ha substituït el fuel per Dimetil-eter. En ambdós casos, l'estudi no sols troba una configuració òptima sinó que també es descriuen les relacions causa/efecte entre els paràmetres més rellevants del sistema de combustió. El primer bloc aplica mètodes d'optimització no-evolutius a un motor mediumduty alimentat per dièsel tractant de minimitzar consum al mateix temps que es mantenen les emissions contaminants per davall dels estàndards d'emissions contaminants impostos. Una primera part se centra en l'optimització de la geometria de la cambra de combustió i l'injector. A continuació s'estén l'estudi afegint els settings de renovació de la càrrega de i d'injecció a l'estudi, ampliant el potencial de l'optimització. L'estudi demostra el limitat potencial de millora de consum que té el motor de referència al mantindre els nivells d'emissions contaminants. Açò demostra la importància d'incloure paràmetres de renovació de la càrrega i injecció al procés d'optimització. El segon bloc aplica una metodologia basada en algoritmes genètics al disseny del sistema de combustió d'un motor heavy-duty alimentat amb Dimetil-eter. L'estudi té dos objectius, primer l'optimització d'un sistema de combustió convencional controlat per mescla amb l'objectiu d'aconseguir millorar el consum i reduir les emissions contaminants fins nivells inferiors als estàndards US2010. Segon l'optimització d'un sistema de combustió treballant en condicions estequiomètriques acoblat amb un catalitzador de tres vies buscant reduir consum i controlar les emissions contaminants per davall dels estàndards 2030. Ambdós optimitzacions inclouen tant la geometria com els paràmetres més rellevants de renovació de la càrrega i d'injecció. Els resultats presenten un sistema de combustió convencional òptim amb una notable millora en rendiment i un sistema de combustió estequiomètrica que és capaç d'oferir nivells de NOx menors al 1% dels nivells de referència mantenint nivells competitius de rendiment. Els resultats presentats en esta Tesi oferixen una visió estesa dels avantatges i limitacions dels motors MCCI i el camï que s'ha de seguir per a reduir les emissions de futurs sistemes de combustió per davall dels estàndards establits. Al seu torn, este treball també demostra el gran potencial que té el Dimetil-eter com a combustible per a futures generacions de motors. / Hernández López, A. (2018). Optimization and analysis by CFD of mixing-controlled combustion concepts in compression ignition engines [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/103826

Large scale, multidisciplinary, engineering designs are always difficult due to the complexity and dimensionality of these problems. Direct coupling between the analysis codes and the optimization routines can be prohibitively time consuming. One way of tackling this problem is by constructing computationally cheap(er) approximations of the expensive simulations, that mimic the behavior of the simulation model as closely as possible. This paper presents a data driven, surrogate based optimization algorithm that uses a trust region based sequential approximate optimization (SAO) framework and a statistical sampling approach based on design of experiment (DOE) arrays. The algorithm is implemented using techniques from the two packages SURFPACK and SHEPPACK that provide a collection of approximation algorithms to build the surrogates and three different DOE techniques: full factorial (FF), Latin hypercube sampling (LHS), and central composite design (CCD) are used to train the surrogates. The biggest concern in using the proposed methodology is the generation of the required database. This thesis proposes a data driven approach where an expensive simulation run is required if and only if a nearby data point does not exist in the cumulatively growing database. Over time the database matures and is enriched as more and more optimizations are performed. Results show that the response surface approximations constructed using design of experiments can be effectively managed by a SAO framework based on a trust region strategy. An interesting result is the significant reduction in the number of simulations for the subsequent runs of the optimization algorithm with a cumulatively growing simulation database. / Master of Science

Der Small-Punch-Test (SPT) ist eine vielversprechende minimalinvasive mechanische Prüfmethode, wenn nur sehr wenig Material für Proben zur Verfügung steht. Die vorliegende Arbeit hat das Ziel, aus Small-Punch-Kleinstproben wahre Materialparameter der elastisch-plastischen Verformung und des spröden Versagens zu bestimmen. Die Kraft-Verschiebungs-Kurve des Versuchs stellt die nichtlineare Materialantwort der inhomogen beanspruchten Probe dar. Das inverse Problem der Identifikation konstitutiver Materialparameter wird numerisch mit Hilfe von Finite-Elemente-Simulationen in Verbindung mit einem Response-Surface-Modell und nichtlinearer Optimierungsverfahren gelöst, indem die Abweichung zwischen gemessener und simulierter Kurve minimiert wird. Mit Hilfe einer eigens entwickelten Kühlapparatur wurden Versuche mit ferritischen Stählen von Raumtemperatur bis hinunter zu -191°C durchgeführt und die temperaturabhängigen Fließkurven identifiziert. Bei tiefen Temperaturen wurden die Weibull-Parameter der zufällig streuenden Sprödbruchfestigkeit bestimmt und die Bruchzähigkeitsverteilung durch Simulation einer CT-Probe vorhergesagt. Für eine Aluminiumoxidkeramik wurden ebenfalls die Weibull-Parameter bestimmt sowie mit Indenterrissen versehene Proben zur Abschätzung der Bruchzähigkeit verwendet. / The small punch test (SPT) is a promising minimally invasive material testing method, especially in cases where only small amounts of material are available. This thesis is aimed at identifying true material parameters of elastic-plastic deformation and brittle fracture. The load-displacement curve of the test represents the non-linear material response of the nonuniformly stressed specimen. The identification of material parameters of constitutive laws is an inverse problem, which is solved numerically. Finite element simulations together with a response surface model and nonlinear optimization techniques are applied to minimize the error between measured and simulated curves. A specially developed cooling apparatus was used to perform tests with ferritic steels from room temperature down to -191°C. The temperature dependent yield stresses and hardening curves were identified. At low temperatures the Weibull parameters of randomly distributed cleavage fracture strength were estimated. The fracture toughness distribution was then predicted by the help of a finite element simulation of a CT specimen. Furthermore the Weibull parameters of an alumina ceramic were determined and its fracture toughness was predicted using specimens prepared with indentation cracks.

L’objectif de la thèse est une mise au point des espèces de Stephania répertoriées au Cambodge par l’étude systématique, phytochimique et pharmacologique. Du point de vue systématique, les travaux ont permis de répertorier sept espèces et deux variétés de Stephania au Cambodge : S. cambodica, S. japonica var. discolor et var. timoriensis, S. oblata, S. pierrei, S. rotunda (espèce-type), S. suberosa, et S. venosa. La clef de détermination établie lors de ce travail de thèse permet d’identifier ces espèces. D’après les résultats phylogénétiques, seul S. pierrei est monophylétique, ce qui représente moins de 10% des espèces de Stephania. L’étude chimique de cinq espèces a été réalisée par des méthodes chromatographiques (CLHP, UCLHP) et des méthodes spectroscopiques. Différents alcaloïdes ont été proposés comme marqueurs : la palmatine, la roémérine et la tétrahydropalmatine pour S. cambodica et S. rotunda, la cépharanthine, la tétrahydropalmatine et la xylopinine pour S. suberosa, la cépharanthine pour S. pierrei, la crébanine, et la tétrahydropalmatine pour S. venosa. Neuf alcaloïdes ont été isolés à partir du tubercule de S. cambodica, dont un nouveau composé dénommé «angkorwatine ». Une méthode d’éco-extraction des alcaloïdes assistée par ultrasons a été mise au point et optimisée par un plan d’expérience pour cette espèce. Une méthode analytique par UCLHP a été développée et validée pour le contrôle qualité de S. cambodica. Les résultats montrent que les extraits hydroéthanoliques obtenus par macération à partir du tubercule de S. suberosa, S. venosa et S. rotunda présentent une activité anti-inflammatoire importante (in vitro) avec un ratio anti-inflammatoire élevé. / The thesis aims to provide update on species of the genus Stephania recorded in Cambodia by systematic, phytochemical and pharmacological studies.The systematic study allowed to list seven species and two varieties of Stephania in Cambodia: S. cambodica, S. japonica var. discolor and var. timoriensis, S. oblata, S. pierrei, S. rotunda (type species), S. suberosa and S. venosa. The presence of S. japonica var. timoriensis and S. oblata is reported for the first time in Cambodia. According to the phylogenetic results, only S. pierrei is monophyletic, which represents less than 10% of species in the genus Stephania. Chemical studies on the tubers of five species were carried out using chromatographic methods (HPLC, UHPLC) and spectroscopic methods. Different isolated alkaloids have been proposed as markers: palmatine, roemerine and tetrahydropalmatine for S. cambodica and S. rotunda, cepharanthine, tetrahydropalmatine, and xylopinine for S. suberosa, cepharanthine for S. pierrei, crebanine, and tetrahydropalmatine for S. venosa. Nine alkaloids belonging to five classes were isolated from the tuber of S. cambodica and a new compound namely "angkorwatine" was described. Ultrasound assisted extraction of alkaloids was developed and optimized by Design of Experiment for this species. This innovative extraction is a good alternative to conventional methods. An analytical UHPLC method was developed and validated for the quality control of S. cambodica. Results show that hydroethanolic extracts obtained by maceration of S. suberosa, S. rotunda and S. venosa exhibit significant anti-inflammatory activity with high anti-inflammatory ratio (selectivity index).

Der Small-Punch-Test (SPT) ist eine vielversprechende minimalinvasive mechanische Prüfmethode, wenn nur sehr wenig Material für Proben zur Verfügung steht. Die vorliegende Arbeit hat das Ziel, aus Small-Punch-Kleinstproben wahre Materialparameter der elastisch-plastischen Verformung und des spröden Versagens zu bestimmen. Die Kraft-Verschiebungs-Kurve des Versuchs stellt die nichtlineare Materialantwort der inhomogen beanspruchten Probe dar. Das inverse Problem der Identifikation konstitutiver Materialparameter wird numerisch mit Hilfe von Finite-Elemente-Simulationen in Verbindung mit einem Response-Surface-Modell und nichtlinearer Optimierungsverfahren gelöst, indem die Abweichung zwischen gemessener und simulierter Kurve minimiert wird. Mit Hilfe einer eigens entwickelten Kühlapparatur wurden Versuche mit ferritischen Stählen von Raumtemperatur bis hinunter zu -191°C durchgeführt und die temperaturabhängigen Fließkurven identifiziert. Bei tiefen Temperaturen wurden die Weibull-Parameter der zufällig streuenden Sprödbruchfestigkeit bestimmt und die Bruchzähigkeitsverteilung durch Simulation einer CT-Probe vorhergesagt. Für eine Aluminiumoxidkeramik wurden ebenfalls die Weibull-Parameter bestimmt sowie mit Indenterrissen versehene Proben zur Abschätzung der Bruchzähigkeit verwendet. / The small punch test (SPT) is a promising minimally invasive material testing method, especially in cases where only small amounts of material are available. This thesis is aimed at identifying true material parameters of elastic-plastic deformation and brittle fracture. The load-displacement curve of the test represents the non-linear material response of the nonuniformly stressed specimen. The identification of material parameters of constitutive laws is an inverse problem, which is solved numerically. Finite element simulations together with a response surface model and nonlinear optimization techniques are applied to minimize the error between measured and simulated curves. A specially developed cooling apparatus was used to perform tests with ferritic steels from room temperature down to -191°C. The temperature dependent yield stresses and hardening curves were identified. At low temperatures the Weibull parameters of randomly distributed cleavage fracture strength were estimated. The fracture toughness distribution was then predicted by the help of a finite element simulation of a CT specimen. Furthermore the Weibull parameters of an alumina ceramic were determined and its fracture toughness was predicted using specimens prepared with indentation cracks.

Hochtemperatur-Konversionsprozesse sind ein wesentlicher Bestandteil von industriellen Produktionsprozessen, die maßgeblich den Prozesswirkungsgrad und die Produktionskosten beeinflussen. Die modellgestützte Optimierung ermöglicht eine gezielte Verbesserung verschiedener Parameter unter Berücksichtigung von prozesstechnischen, ökonomischen und ökologischen Aspekten. Bisher existiert in der Literatur kein Vergleich der Einsatzmöglichkeiten verschiedener Modellierungsmethoden zur modellgestützten, multikriteriellen Optimierung von Hochtemperatur-Konversionsprozessen. Daher werden in dieser Arbeit drei exemplarische Konversionsprozesse mit unterschiedlichen Modellierungsmethoden optimiert und anhand der Ergebnisse die Potenziale und Einsatzgrenzen für die modellgestützte Optimierung bewertet. Die Modellierung eines Wirbelschichtvergasers zeigt, dass detaillierte CFD-Modelle für komplexe mehrphasige Prozesse zu rechenaufwändig sind. Hingegen ist für einfache einphasige Prozesse wie ein Quench-Reaktor die Optimierung mit reduzierten CFD-Modellen realisierbar. Die Integration von Ersatzmodellen beschleunigt das Optimierungskonzept bei gleicher Ergebnisqualität, was die Optimierung von komplexen Prozessen für einfache Optimierungsprobleme ermöglicht. Die Optimierung der Partialoxidation von flüssigen Einsatzstoffen zur Methanolproduktion zeigt, dass sich Fließbildmodelle gut zur Optimierung von vollständigen Produktionsprozessen und komplexen Optimierungsproblemen eignen. Die Ergebnisse dieser Arbeit können als Basis für die Erstellung von Modellierungs- und Optimierungskonzepten für weitere Hochtemperatur-Konversionsprozesse genutzt werden.

Produced water is the largest waste product by volume in the oil industry and its treatment in onshore or offshore fields poses bigger and different challenges than what water engineers are used to encounter. Process to achieve reuse quality of this water is very expensive with many technical hurdles to overcome making the optimization of the treatment steps necessary. Electrocoagulation (EC) generates coagulants in-situ responsible for destabilizing oil droplets, suspended particles, and common pollutant in produced water. Furthermore, EC is a very efficient technology compared with traditional primary treatments used in the oil & gas industry and has several advantages such as: no hazardous chemical handling (which diminishes the risk of accident and logistic costs), high efficiency potential concerning boron removal, potential small footprint and less sludge generation. In this research, the treatment of produced water using EC was investigated in a practical manner for the oilfield to aim for a cleaner effluent for further processing and help to achieve a reuse quality. For this, an EC cell was designed using different parameters normally used in the literature to fit this scenario. After preliminary tests, the treatment time was set to 3 seconds. Response surface method (RSM) was employed to optimize the operating conditions for TOC removal on a broad quality of synthetic produced water while varying: salinity, initial oil concentration and initial pH. TOC was chosen to be the main response because of its importance in legislation and sensibility on the method. Furthermore, turbidity removal, change of pH value after EC in water with lack of buffer capacity, aluminum concentration and preliminary tests involving boron removal and influence of hydrogen carbonate were also studied. Real produced water was treated with EC to assess the optimum conditions obtained by the RSM showing the results were closely related. Finally, an estimation of volume required and operating cost for EC in the different types of produced water was made to assess how realistic it is for onshore and offshore applications.:ERKLÄRUNG DES PROMOVENDEN I ACKNOLEDGEMENT III ABSTRACT V TABLE OF CONTENT VII LIST OF FIGURES IX LIST OF TABLES X LIST OF EQUATIONS XII ABBREVIATIONS XIV 1. INTRODUCTION 1 2. PRODUCED WATER 6 2.1 Characterization of Oilfield Produced Water 6 2.2 Produced Water Management 10 2.2.1 Discharge and Regulations 10 2.2.2 Efforts on Reuse 11 2.2.3 Cost 14 3. PRODUCED WATER TREATMENT 17 3.1 Most Common Primary Treatment 17 3.1.1 Hydrocyclones 17 3.1.2 Flotation unit 18 3.2 Further Water Treatment Technologies 19 3.2.1 Membrane Process 19 3.2.1.1 Microfiltration 19 3.2.1.2 Ultrafiltration 21 3.2.1.3 Nanofiltration 23 3.2.1.4 Reverse Osmosis 24 3.2.1.5 Forward osmosis 24 3.2.2 Electrodialysis 25 3.2.3 Biological treatment 28 3.2.3.1 Aerobic and anaerobic process 28 3.2.3.2 Combining membrane and bio-reactor 29 3.2.4 Oxidative process 30 3.2.4.1 Oxidation process 30 3.2.4.2 Anodic oxidation 32 3.2.5 Thermal technology 34 3.2.5.1 Evaporation 34 3.2.5.2 Eutectic freeze crystallization 35 3.2.6 Adsorption and ion-exchange 36 3.3 Electrocoagulation 39 3.3.1 Colloidal Stability Theory 39 3.3.2 Theory of Electrocoagulation 40 3.3.3 Mechanism of Abatement of Impurities 44 3.3.4 Operational parameters and efficiency 49 4. MATERIALS AND METHODS 51 4.1 Analytical Techniques and Synthetic Solutions 51 4.1.1 Analytical Techniques 51 4.1.2 Synthetic Produced Water 51 4.2 Design of Experiment and Models 54 4.3 Experimental Protocol for EC 56 4 .4 Development of the new Electrocoagulation cell 57 4.5 Real Produced water 58 5. RESULTS AND DISCUSSION 59 5.1 Designing EC Cell Process 59 5.1.1 Computational Fluid Dynamics for EC manufacturing 59 5.2 Preliminary Experiments 61 5.2.1 TOC Removal and Residence Time Determination 61 5.2.2 Aluminum Concentration 64 5.3 Models Quality and Range of Validity 66 5.3.1 TOC Removal 66 5.3.2 Turbidity Removal 69 5.3.3 Final pH value 71 5.3.4 Ionic Strength and Interpolation for Different Salinities 73 5.3.5 Partial Conclusions 76 5.4 Evolution of the Final pH Value 78 5.5 Operation Region for Effective Treatment of Produced Water with EC 80 5.5.1 Produced Water with Low Salinity 80 Organic Compounds Removal 80 Turbidity Removal 83 5.5.2 Produced Water with Medium Salinity 84 Organic Compounds Removal 84 Turbidity Removal 86 5.5.3 Produced Water with High Salinity 87 Organic Compounds Removal 87 5.6 Influence of Hydrogen Carbonate 90 5.7 Real Produced water 91 5.8 Boron Removal 93 5.9 Estimation of the Size for EC in Full scale 94 5.10 Produced Water with Very Low Salinity and EC 95 5.11 Estimation of Operation Cost 96 6. CONCLUSION AND RECOMMENDATIONS 98 6.1 Conclusion 98 6.2 Recommendations for Future Work 101 Scale up on EC for upstream 101 Further processing and reuse 101 Online optimization for EC 101 Recommendations for any research related to upstream produced water 101 BIBLIOGRAPHY 102 APPENDIX A 117 APPENDIX B 120

Cette thèse propose une méthodologie pour des études en simulation numérique en grande dimension. Elle se décline en différentes étapes : construction de plan d'expériences approprié, analyse de sensibilité et modélisation par surface de réponse. Les plans d'expériences adaptés à la simulation numérique sont les "Space Filling Designs", qui visent à répartir uniformément les points dans l'espace des variables d'entrée. Nous proposons l'algorithme WSP pour construire ces plans, rapidement, avec de bons critères d'uniformité, même en grande dimension. Ces travaux proposent la construction d'un plan polyvalent, qui sera utilisé pour les différentes étapes de l'étude : de l'analyse de sensibilité aux surfaces de réponse. L'analyse de sensibilité sera réalisée avec une approche innovante sur les points de ce plan, pour détecter le sous-ensemble de variables d'entrée réellement influentes. Basée sur le principe de la méthode de Morris, cette approche permet de hiérarchiser les variables d'entrée selon leurs effets. Le plan initial est ensuite "replié" dans le sous-espace des variables d'entrée les plus influentes, ce qui nécessite au préalable une étude pour vérifier l'uniformité de la répartition des points dans l'espace réduit et ainsi détecter d'éventuels amas et/ou lacunes. Ainsi, après réparation, ce plan est utilisé pour l'étape ultime : étude de surfaces de réponse. Nous avons alors choisi d'utiliser l'approche des Support Vector Regression, indépendante de la dimension et rapide dans sa mise en place. Obtenant des résultats comparables à l'approche classique (Krigeage), cette technique semble prometteuse pour étudier des phénomènes complexes en grande dimension. / This thesis proposes a methodology of study in numeric simulation for high dimensions. There are several steps in this methodology : setting up an experimental design, performing sensitivity analysis, then using response surface for modelling. In numeric simulation, we use a Space Filling Design that scatters the points in the entire domain. The construction of an experimental design in high dimensions must be efficient, with good uniformity properties. Moreover, this construction must be fast. We propose using the WSP algorithm to construct such an experimental design. This design is then used in all steps of the methodology, making it a versatile design, from sensitivity analysis to modelling. A sensitivity analysis allows identifying the influent factors. Adapting the Morris method principle, this approach classifies the inputs into three groups according to their effects. Then, the experimental design is folded over in the subspace of the influent inputs. This action can modify the uniformity properties of the experimental design by creating possible gaps and clusters. So, it is necessary to repair it by removing clusters and filling gaps. We propose a step-by-step approach to offer suitable repairing for each experimental design. Then, the repaired design is used for the final step: modelling from the response surface. We consider a Support Vector Machines method because dimension does not affect the construction. Easy to construct and with good results, similar to the results obtained by Kriging, the Support Vector Regression method is an alternative method for the study of complex phenomena in high dimensions.