Teoria dei giochi e Multi-criteria decision-making per reti mobili Ad-hoc: un protocollo di routing

Nell'elaborato si analizzano aspetti della teoria dei giochi e della multi-criteria decision-making. La riflessione serve a proporre le basi per un nuovo modello di protocollo di routing in ambito Mobile Ad-hoc Networks. Questo prototipo mira a generare una rete che riesca a gestirsi in maniera ottimale grazie ad un'acuta tecnica di clusterizzazione. Allo stesso tempo si propone come obiettivo il risparmio energetico e la partecipazione collaborativa di tutti i componenti.

Autonomous Pricing using Policy-Gradient Reinforcement Learning

Nella letteratura economica e di teoria dei giochi vi è un dibattito aperto sulla possibilità di emergenza di comportamenti anticompetitivi da parte di algoritmi di determinazione automatica dei prezzi di mercato. L'obiettivo di questa tesi è sviluppare un modello di reinforcement learning di tipo actor-critic con entropy regularization per impostare i prezzi in un gioco dinamico di competizione oligopolistica con prezzi continui. Il modello che propongo esibisce in modo coerente comportamenti cooperativi supportati da meccanismi di punizione che scoraggiano la deviazione dall'equilibrio raggiunto a convergenza. Il comportamento di questo modello durante l'apprendimento e a convergenza avvenuta aiuta inoltre a interpretare le azioni compiute da Q-learning tabellare e altri algoritmi di prezzo in condizioni simili. I risultati sono robusti alla variazione del numero di agenti in competizione e al tipo di deviazione dall'equilibrio ottenuto a convergenza, punendo anche deviazioni a prezzi più alti.

Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

Numerical and experimental investigation of turbulent dissipation

Turbulent energy dissipation is presented in the theoretical context of the famous Kolmogorov theory, formulated in 1941. Some remarks and comments about this theory help the reader understand the approach to turbulence study, as well as give some basic insights to the problem. A clear distinction is made amongst dissipation, pseudo-dissipation and dissipation surrogates. Dissipation regulates how turbulent kinetic energy in a flow gets transformed into internal energy, which makes this quantity a fundamental characteristic to investigate in order to enhance our understanding of turbulence. The dissertation focuses on experimental investigation of the pseudo-dissipation. Indeed this quantity is difficult to measure as it requires the knowledge of all the possible derivatives of the three dimensional velocity field. Once considering an hot-wire technique to measure dissipation we need to deal with surrogates of dissipation, since not all the terms can be measured. The analysis of surrogates is the main topic of this work. In particular two flows, the turbulent channel and the turbulent jet, are considered. These canonic flows, introduced in a brief fashion, are often used as a benchmark for CFD solvers and experimental equipment due to their simple structure. Observations made in the canonic flows are often transferable to more complicated and interesting cases, with many industrial applications. The main tools of investigation are DNS simulations and experimental measures. DNS data are used as a benchmark for the experimental results since all the components of dissipation are known within the numerical simulation. The results of some DNS were already available at the start of this thesis, so the main work consisted in reading and processing the data. Experiments were carried out by means of hot-wire anemometry, described in detail on a theoretical and practical level. The study of DNS data of a turbulent channel at Re=298 reveals that the traditional surrogate can be improved Consequently two new surrogates are proposed and analysed, based on terms of the velocity gradient that are easy to measure experimentally. We manage to find a formulation that improves the accuracy of surrogates by an order of magnitude. For the jet flow results from a DNS at Re=1600 of a temporal jet, and results from our experimental facility CAT at Re=70000, are compared to validate the experiment. It is found that the ratio between components of the dissipation differs between DNS and experimental data. Possible errors in both sets of data are discussed, and some ways to improve the data are proposed.

Planck stars: theory and phenomenology

General Relativity (GR) is one of the greatest scientific achievements of the 20th century along with quantum theory. Despite the elegance and the accordance with experimental tests, these two theories appear to be utterly incompatible at fundamental level. Black holes provide a perfect stage to point out these difficulties. Indeed, classical GR fails to describe Nature at small radii, because nothing prevents quantum mechanics from affecting the high curvature zone, and because classical GR becomes ill-defined at r = 0 anyway. Rovelli and Haggard have recently proposed a scenario where a negative quantum pressure at the Planck scales stops and reverts the gravitational collapse, leading to an effective “bounce” and explosion, thus resolving the central singularity. This scenario, called Black Hole Fireworks, has been proposed in a semiclassical framework. The purpose of this thesis is twofold: - Compute the bouncing time by means of a pure quantum computation based on Loop Quantum Gravity; - Extend the known theory to a more realistic scenario, in which the rotation is taken into account by means of the Newman-Janis Algorithm.

Theoretical and experimental studies of gold catalysts for glucose oxidation

The glucaric acid (GLA) has been identified as a “top value-added chemical from biomass” that can be employed for many uses; for instance, it could be a precursor of adipic acid, a monomer of Nylon-6,6. GLA can be synthetized by the oxidation of glucose (GLU), passing through the intermediate gluconic acid (GLO). In recent years, a new process has been sought to obtain GLA in an economic and environmental sustainable way, in order to replace the current use of HNO3 as a stoichiometric oxidant, or electrocatalysis and biochemical synthesis, which show several disadvantages. Thereby, this work is focused on the study of catalysts based on gold nanoparticles supported on activated carbon for the oxidation reaction of GLU to GLA using O2 as an oxidant agent and NaOH as base. The sol-immobilization method leads us to obtain small and well dispersed nanoparticles, characterized by UV-Vis, XRD and TEM techniques. Repeating the reaction on different batches of catalyst, both the synthesis and the reaction were confirmed to be reproducible. The effect of the reaction time feeding GLO as reagent was studied: the results show that the conversion of GLO increases as the reaction time increases; however, the yields of GLA and others increase up to 1 hour, and then they remain constant. In order to obtain information on the catalytic mechanism at the atomistic level, a computational study based on density functional theory and atomistic modeling of the gold nano-catalyst were performed. Highly symmetric (icosahedral and cubo-octahedral) and distorted Au55 nanoparticles have been optimized along with Au(111) and Au(100) surfaces. Distorted structures were found to be more stable than symmetrical ones due to relativistic effects. On these various models the adsorptions of various species involved in the catalysis have been studied, including OH- species, GLU and GLO. The study carried out aims to provide a method for approaching to the study of nanoparticellary catalytic systems.

Theoretical and experimental investigations on homologation of ethanol to butanol using a ruthenium-based catalyst

The mechanism of homologation of bioethanol to butanol and higher alcohols via the Guerbet reaction was computationally and experimentally investigated. The catalytic pathway involves a ruthenium-based complex and a base co-catalyst which work simultaneously. Due to selectivity issues, secondary products were formed and high competition between main pathway and side reactions was recorded. Herein, the overall catalytic mechanism for all the processes involved in was investigated, also considering the principal side reactions, using density functional theory (DFT) methods and experiments to confirm theoretical outcomes. Due to the complexity of the reaction network, kinetic simulations were established from DFT results, confirming experimental products distribution and giving insights into the factors governing the reaction mechanism.

Numerical study on viscoelastic behavior of polypropylene fiber reinforced concrete subjected to temperature variations using LDPM theory

This thesis is focused on the viscoelastic behavior of macro-synthetic fiber-reinforced concrete (MSFRC) with polypropylene studied numerically when subjected to temperature variations (-30 oC to +60 oC). LDPM (lattice discrete particle model), a meso-scale model for heterogeneous composites, is used. To reproduce the MSFRC structural behavior, an extended version of LDPM that includes fiber effects through fiber-concrete interface micromechanics, called LDPM-F, is applied. Model calibration is performed based on three-point bending, cube, and cylinder test for plain concrete and MSFRC. This is followed by a comprehensive literature study on the variation of mechanical properties with temperature for individual fibers and plain concrete. This literature study and past experimental test results constitute inputs for final numerical simulations. The numerical response of MSFRC three-point bending test is replicated and compared with the previously conducted experimental test results; finally, the conclusions were drawn. LDPM numerical model is successfully calibrated using experimental responses on plain concrete. Fiber-concrete interface micro-mechanical parameters are subsequently fixed and LDPM-F models are calibrated based on MSFRC three-point bending test at room temperature. Number of fibers contributing crack bridging mechanism is computed and found to be in good agreement with experimental counts. Temperature variations model for individual constituents of MSFRC, fibers and plain concrete, are implemented in LDPM-F. The model is validated for MSFRC three-point bending stress-CMOD (crack mouth opening) response reproduced at -30 oC, -15 oC, 0 oC, +20 oC, +40 oC and +60 oC. It is found that the model can well describe the temperature variation behavior of MSFRC. At positive temperatures, simulated responses are in good agreement. Slight disagreement in negative regimes suggests an in-depth study on fiber-matrix interface bond behavior with varying temperatures.