Stochastic local volatility model for fx markets

Questa tesi verte sullo studio di un modello a volatilità stocastica e locale, utilizzato per valutare opzioni esotiche nei mercati dei cambio. La difficoltà nell'implementare un modello di tal tipo risiede nella calibrazione della leverage surface e uno degli scopi principali di questo lavoro è quello di mostrarne la procedura.

Regularization methods for the solution of a nonlinear least-squares problem in tomography

In this work we study a polyenergetic and multimaterial model for the breast image reconstruction in Digital Tomosynthesis, taking into consideration the variety of the materials forming the object and the polyenergetic nature of the X-rays beam. The modelling of the problem leads to the resolution of a high-dimensional nonlinear least-squares problem that, due to its nature of inverse ill-posed problem, needs some kind of regularization. We test two main classes of methods: the Levenberg-Marquardt method (together with the Conjugate Gradient method for the computation of the descent direction) and two limited-memory BFGS-like methods (L-BFGS). We perform some experiments for different values of the regularization parameter (constant or varying at each iteration), tolerances and stop conditions. Finally, we analyse the performance of the several methods comparing relative errors, iterations number, times and the qualities of the reconstructed images.

Study of a beam-column joint of a precast system by nonlinear numerical analysis

The present work consists of a detailed numerical analysis of a 4-way joint made of a precast column and two partially precast beams. The structure has been previously built and experimentally analyzed through a series of cyclic loads at the Laboratory of Tests on Structures (Laboratorio di Prove su Strutture, La. P. S.) of the University of Bologna. The aim of this work is to design a 3D model of the joint and then apply the techniques of nonlinear finite element analysis (FEA) to computationally reproduce the behavior of the structure under cyclic loads. Once the model has been calibrated to correctly emulate the joint, it is possible to obtain new insights useful to understand and explain the physical phenomena observed in the laboratory and to describe the properties of the structure, such as the cracking patterns, the force-displacement and the moment-curvature relations, as well as the deformations and displacements of the various elements composing the joint.

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

Nonlinear modelling of non-structural masonry walls under a low-intensity earthquake motion: calibration through a parametric study

This thesis aims to understand the behavior of a low-rise unreinforced masonry building (URM), the typical residential house in the Netherlands, when subjected to low-intensity earthquakes. In fact, in the last decades, the Groningen region was hit by several shallow earthquakes caused by the extraction of natural gas. In particular, the focus is addressed to the internal non-structural walls and to their interaction with the structural parts of the building. A simple and cost-efficient 2D FEM model is developed, focused on the interfaces representing mortar layers that are present between the non-structural walls and the rest of the structure. As a reference for geometries and materials, it has been taken into consideration a prototype that was built in full-scale at the EUCENTRE laboratory of Pavia (Italy). Firstly, a quasi-static analysis is performed by gradually applying a prescribed displacement on the roof floor of the structure. Sensitivity analyses are conducted on some key parameters characterizing mortar. This analysis allows for the calibration of their values and the evaluation of the reliability of the model. Successively, a transient analysis is performed to effectively subject the model to a seismic action and hence also evaluate the mechanical response of the building over time. Moreover, it was possible to compare the results of this analysis with the displacements recorded in the experimental tests by creating a model representing the entire considered structure. As a result, some conditions for the model calibration are defined. The reliability of the model is then confirmed by both the reasonable results obtained from the sensitivity analysis and the compatibility of the values obtained for the top displacement of the roof floor of the experimental test, and the same value acquired from the structural model.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Root cause analysis applied to a finite element model's refinement of a negative stiffness structure

Negative Stiffness Structures are mechanical systems that require a decrease in the applied force to generate an increase in displacement. They are structures that possess special characteristics such as snap-through and bi-stability. All of these features make them particularly suitable for different applications, such as shock-absorption, vibration isolation and damping. From this point of view, they have risen awareness of their characteristics and, in order to match them to the application needed, a numerical simulation is of great interest. In this regard, this thesis is a continuation of previous studies in a circular negative stiffness structure and aims at refine the numerical model by presenting a new solution. To that end, an investigation procedure is needed. Amongst all of the methods available, root cause analysis was the chosen one to perform the investigation since it provides a clear view of the problem under analysis and a categorization of all the causes behind it. As a result of the cause-effect analysis, the main causes that have influence on the numerical results were obtained. Once all of the causes were listed, solutions to them were proposed and it led to a new numerical model. The numerical model proposed was of nonlinear type of analysis with hexagonal elements and a hyperelastic material model. The results were analyzed through force-displacement curves, allowing for the visualization of the structure’s energy recovery. When compared to the results obtained from the experimental part, it is evident that the trend is similar and the negative stiffness behaviour is present.