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Sensitivity analysis --- Programming(Linear-) --- Mathematical optimization
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research design --- causal model --- target parameter specification --- identifiability --- statistical estimation --- sensitivity analysis
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This work will study the characterization of crude oil. Will be used suitable methods in particular as regard to heavy fractions. The aim is to integrate the study within VALI, owned by BELSIM SA company, and improve the software in the Data Validation and Reconciliation process where is one of the leaders in this field.
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Inside a galvanization line, a thin layer of zinc is applied on a steel strip. The thickness of this deposit depends on the galvanized steel's application and must thus be controlled precisely. This master thesis studies and predicts the resulting zinc coating weight given the set of the line's parameters. Based on real data, multiple models using machine learning and deep learning algorithms were designed to infer the deposit. The best results were obtained with the Extremely Randomized Trees regressor and this model achieves to reach less than 1\% of relative error in its predictions. After that, the trained model was used to create a tool to study the sensitivity of the zinc coating weight when the parameters of the line are modified. A static and a dynamic analysis were implemented. The last one allows an operator to enter the different values of each parameter and receive the predicted coating weight associated to them. Along this work, this master thesis also presents another problem which is the surface prediction. In this case, only the coating weight measures and their positions are given to the model. This one must then infer the profile of the deposit, the surface of the steel strip.
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The management of irrigation districts is becoming laborious in some regions of Colombia. In the Tolima region, the bimodal climate is present in hot and semi-arid areas that are vulnerable due to the increasing impact of climatic phenomena that cause an intensification of droughts, but also of rainfall. The systems in place sometimes require more water than is needed, in a context of increasing producer density. Agricultural yields, particularly for rice, which is very present in the region, can sometimes decrease in an unprecedented way in the event of insufficient water supply. Moreover, the experiments to be carried out to put an end to these problems are sometimes costly in terms of time and money. In this study, trials of irrigation systems and scheduling were tried, and the use of a calibrated crop simulation model to assess the possibility of predicting the behaviour of these experiments on a variety of Oriza sativa L. from the region. The calibration shows simulations of the evolution of plant parameters, such as canopy cover with an average RMSE of about 2.60 % and correlated for the first cycle and a much poorer simulation for the second cycle, but also a simulated dry yield with an overall MBE of 0.621t/ha that is rather accurate and can differ from the observed evolution of the different treatments to some extent. Further simulations were carried out to assess the importance of the parameters on these outputs. The sensitivity analysis shows 7 parameters explaining 95 % of the total sensitivity of the evolution during a fictitious cycle of different soil water content, biomass, canopy cover and dry yield. These results will allow future evaluation of irrigation schedules in order to optimise yields according to local water consumption. Based on the results of the sensitivity analysis, further analyses can be done in the region to facilitate and plan future calibrations in a local environment. Thanks to the processed and modelled local climate data, it will also be possible to carry out irrigation schedules according to extreme weather events.
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In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria.
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As a part of the New Space development in industry, this research pursues the development of an end-to-end performance modeling interface for optical systems (EMIOS). The interest of managing performance prediction with computer-aided technologies for space instrument are huge. It is primordial for companies to supply reliable instrument to customers and to be compliant with standards. This study demonstrates the robustness of this kind of software by giving a detailed analysis of the sensitivity of optical instruments, especially hyperspectral instruments. This work is based on a deep understanding of different theoretical and practical concepts happening along the design lifetime of hyperspectral instruments. By managing the optical design processes, engineers can have an overview of the future operation of hyperspectral instruments. The thermo-elastic perturbations have to be evaluated and the resulting image deformations too. Therefore, it is important to define the different quality criteria that will be used to sense the optical aberrations coming from these deformations. Naturally, an enhancement of the end-to-end performance tools is performed beforehand in order to upgrade the software and achieve the sensitivity analysis afterwards. Finally, this sensitivity study gives the main tendencies in terms of mirrors deformations and motions that will allow engineers to better understand the behavior of hyperspectral instruments in operation. Several recommendations about the future reliability of the developed optics are also provided. Dans le cadre du développement du New Space en industrie, cette recherche poursuit le développement d'une interface de modélisation des performances de bout en bout pour les systèmes optiques (EMIOS). L'intérêt de gérer la prévision des performances avec des technologies assistées par ordinateur pour les instruments spatiaux est énorme. Il est primordial pour les entreprises de fournir des instruments fiables aux clients et de se conformer aux normes. Cette étude démontre la robustesse de ce type de logiciel en donnant une analyse détaillée de la sensibilité des instruments optiques, en particulier des instruments hyperspectraux. Ce travail est basé sur une compréhension approfondie des différents concepts théoriques et pratiques qui se produisent tout au long de la durée de vie de conception des instruments hyperspectraux. En gérant les processus de conception optique, les ingénieurs peuvent avoir une vue d'ensemble du fonctionnement futur des instruments hyperspectraux. Les perturbations thermo-élastiques doivent être évaluées et les déformations d'image qui en résultent également. Il est donc important de définir les différents critères de qualité qui seront utilisés pour détecter les aberrations optiques provenant de ces déformations. Naturellement, une amélioration des outils de performance de bout en bout est effectuée au préalable afin de mettre à niveau le logiciel et de réaliser l'analyse de sensibilité par la suite. Enfin, cette étude de sensibilité donne les principales tendances en termes de déformations et de mouvements des miroirs qui permettront aux ingénieurs de mieux comprendre le comportement des instruments hyperspectraux durant leur fonctionnement. Plusieurs recommandations sur la fiabilité future des optiques développées sont également fournies.
Optical performances --- Sensitivity analysis --- Hyperspectral --- EMIOS --- Performances optiques --- Analyse de sensibilité --- Hyperspectral --- EMIOS --- Ingénierie, informatique & technologie > Ingénierie aérospatiale
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Sponsored by the Ocean and Offshore Engineering Committee of the Coasts, Oceans, Ports, and Rivers Institute of ASCE. Spar Platforms: Technology and Analysis Methods examines the design, analysis, and use of spar platforms for offshore oil production. Since the first spar platform, the Oryx Neptune, was installed in the Gulf of Mexico in 1996, spars have evolved into a proven, reliable technology for oil drilling and production in deep and remote areas. Three spar concepts are in use today: the classic spar, the truss spar, and the cell spar. Although the technology and analysis methods are considered mature, technical challenges remain, including understanding and suppressing vortex-induced motion and improving survivability in category 4 and 5 hurricanes. This volume surveys the history of spar development and presents detailed design modeling aspects of spar hull, mooring, and anchoring systems. Two methodologies—the diffraction method and the Morrison formula—that can be used to analyze spar motions are demonstrated and assessed. Design considerations for vortex-induced motion of spars are weighed, along with possible remedies. In addition, testing methods for spar models in wave basins are considered, and full-scale field data is compared with the results of several numerical analysis tools. Ocean and coastal engineers, those involved in the design and construction of offshore structures, and petroleum engineers will find the book a useful supplement to existing specifications for spar platforms.
Drilling platforms. --- Offshore oil well drilling. --- Underwater drilling. --- Data analysis --- Offshore platforms --- Sensitivity analysis --- Numerical models --- Dynamic analysis --- Motion (dynamics) --- Scale models --- Field tests --- Gulf of Mexico
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Recent studies have shown that not only exporters but also importers perform better than firms that do not trade. Using a detailed firm level dataset from 43 developing countries, I show that there are persistent differences in evolution of firms when they are grouped according to their trade orientation as: two-way traders (both importing and exporting), only exporters, only importers, and non-traders. Extending the existing models of firm evolution in open economies by incorporating importing decision, I show that: i) globally engaged firms are larger, more productive, and grow faster than non-traders; ii) two-way traders are the fastest growing and most innovative group who are followed by only-exporters; iii) estimating export premium without controlling for import status is likely to overestimate the actual value by capturing the import premium; and iv) R&D investment contributes to growth of traders significantly more than to non-traders. Finally I show the robustness of the findings by providing evidence from the panel data constructed from the original dataset and controlling for variables that are likely to affect firm growth.
Certificate --- E-Business --- Economic Theory & Research --- Emerging Markets --- Enterprise surveys --- Finance and Financial Sector Development --- Fixed cost --- Foreign inputs --- Globalization --- Innovation --- International trade --- Labor Policies --- Macroeconomics and Economic Growth --- Manufacturing --- Microfinance --- Performance measures --- Private sector --- Private sector development --- Productivity --- R&d --- Result --- Results --- Sensitivity analysis --- Social Protections and Labor --- Technological innovation --- Technological innovations --- Technology transfer --- Web
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