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Inflatable space structures. --- Computerized simulation. --- Sensitivity analysis.
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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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Liquid rocket propellants. --- Sensitivity analysis. --- Propulsion system configurations. --- Mathematical models. --- Mechanical devices. --- Vanes. --- Grid generation (mathematics)
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Aerodynamic noise. --- Sensitivity analysis. --- Noise prediction. --- Supersonic jet flow. --- Mathematical models. --- Probability distribution functions.
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Composite structures. --- Debonding (materials) --- Fracturing. --- Buckling. --- Damage assessment. --- Stringers. --- Sensitivity analysis. --- Fracture strength.
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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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