Laboratory simulations of local winds in the atmospheric boundary layer via image analysis

In the atmospheric boundary layer, under high pressure conditions and negligible geostrophic winds, problems associated with pollution are the most critical. In this situation local winds play a major role in the evaluation of the atmospheric dynamics at small scales and in dispersion processes. These winds originate as a result of nonuniform heating of the soil, either when it is homogeneous or in discontinuous terrain in the presence of sea and/or slopes. Depending on the source of the thermal gradient, local winds are classified into convective boundary layer, sea and land breezes, urban heat islands, and slope currents. Local winds have been analyzed by (i) simple analytical models; (ii) numerical models; (iii) field measurements; (iv) laboratory measurements through which it is impossible to completely create the necessary similarities, but the parameters that determine the phenomenon can be controlled and each single wind can be separately analyzed. The present paper presents a summary of laboratory simulations of local winds neglecting synoptic winds and the effects of Coriolis force. Image analysis techniques appear suitable to fully describe both the individual phenomenon and the superposition of more than one local wind. Results do agree with other laboratory studies and numerical experiments

A Unified Dissertation on Bearing Rigidity Theory

This work focuses on the bearing rigidity theory, namely the branch of knowledge investigating the structural properties necessary for multi-element systems to preserve the inter-units bearings when exposed to deformations. The original contributions are twofold. The first one consists in the definition of a general framework for the statement of the principal definitions and results that are then particularized by evaluating the most studied metric spaces, providing a complete overview of the existing literature about the bearing rigidity theory. The second one rests on the determination of a necessary and sufficient condition guaranteeing the rigidity properties of a given multi-element system, independently of its metric space

On the estimation of atmospheric turbulence layers for AO systems

In current and next generation of ground telescopes, Adaptive Optics (AO) are employed to overcome the detrimental effects induced by the presence of atmospheric turbulence, that strongly affects the quality of data transmission and therefore limits the actual resolution of the overall system. The analysis as well as the prediction of the turbulent phase affecting the light wavefront is therefore of paramount impor- tance to guarantee the effective performance of the AO solution. In this work, a layered model of turbulence is proposed, based on the definition of a Markov-Random-Field whose parameters are determined according to the turbulence statistics. The problem of turbulence estimation is formalized within the stochastic framework and conditions for the identifiability of the turbulence structure (numbers of layers, energies and velocities) are stated. Finally, an algorithm to allow the layer detection and characterization from measurements is designed. Numerical simulations are used to assess the proposed procedure and validate the results, confirming the validity of the approach and the accuracy of the detection

Three-dimensional structure of the flow inside the left ventricle of the human heart

The laboratory models of the human heart left ventricle developed in the last decades gave a valuable contribution to the comprehension of the role of the fluid dynamics in the cardiac function and to support the interpretation of the data obtained in vivo. Nevertheless, some questions are still open and new ones stem from the continuous improvements in the diagnostic imaging techniques. Many of these unresolved issues are related to the three-dimensional structure of the left-ventricular flow during the cardiac cycle. In this paper we investigated in detail this aspect using a laboratory model. The ventricle was simulated by a flexible sack varying its volume in time according to a physiologically shaped law. Velocities measured during several cycles on series of parallel planes, taken from two orthogonal points of view, were combined together in order to reconstruct the phase averaged, three-dimensional velocity field. During the diastole, three main steps are recognized in the evolution of the vortical structures: i) straight propagation in the direction of the long axis of a vortex-ring originated from the mitral orifice; ii) asymmetric development of the vortex-ring on an inclined plane; iii) single vortex formation. The analysis of three-dimensional data gives the experimental evidence of the reorganization of the flow in a single vortex persisting until the end of the diastole. This flow pattern seems to optimize the cardiac function since it directs velocity towards the aortic valve just before the systole and minimizes the fraction of blood residing within the ventricle for more cycles

Towards time-varying proximal dynamics in Multi-Agent Network Games

Distributed decision making in multi-agent networks has recently attracted significant research attention thanks to its wide applicability, e.g. in the management and optimization of computer networks, power systems, robotic teams, sensor networks and consumer markets. Distributed decision-making problems can be modeled as inter-dependent optimization problems, i.e., multi-agent game-equilibrium seeking problems, where noncooperative agents seek an equilibrium by communicating over a network. To achieve a network equilibrium, the agents may decide to update their decision variables via proximal dynamics, driven by the decision variables of the neighboring agents. In this paper, we provide an operator-theoretic characterization of convergence with a time-invariant communication network. For the time-varying case, we consider adjacency matrices that may switch subject to a dwell time. We illustrate our investigations using a distributed robotic exploration example.Comment: 6 pages, 3 figure

Multi-agent network games with applications in smart electric mobility

The growing complexity and globalization of modern society brought to light novel problems and challenges for researchers that aim to model real-life phenomena. Nowadays communities and even single individuals cannot be considered as a closed system, since one's actions create a ripple effect that ends up influencing the action of others. Therefore, the study of decision-making processes over networks became a pivotal topic in the research community. The possible applications are virtually endless and span into many different fields. Two of the most relevant examples are smart mobility and energy management in highly populated cities, where a collection of (partially) noncooperative individuals interact over a network trying to reach an efficient equilibrium point, in the sense of Nash, and share limited resources due to the environment in which they operate. In this work, we approach these problems through the lens of game theory. We use different declinations of this powerful mathematical tool to study several aspects of these themes. We design decentralized iterative algorithms solving generalized network games that generate behavioral rules for the players that, if followed, ensure global convergence. Then, we question the classical assumption of perfect players’ rationality by introducing novel dynamics to model partial rationality and analyzing their properties. We conclude by focusing on the design of optimal policies to regulate smart mobility and energy management. In this case, we create a detailed and more realistic description of the problem and use a nudging mechanism, implemented by means of a semi-decentralized algorithm, to align the users' behavior with the one desired by the policymaker

Newton-Raphson Consensus for Distributed Convex Optimization

We address the problem of distributed uncon- strained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local private multidimensional convex cost, is subject to communication constraints, and wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proved, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents distributedly compute and sequentially update an approximated Newton- Raphson direction by means of suitable average consensus ratios. We show with numerical simulations that the speed of convergence of this strategy is comparable with alternative optimization strategies such as the Alternating Direction Method of Multipliers. Finally, we propose some alternative strategies which trade-off communication and computational requirements with convergence speed.Comment: 18 pages, preprint with proof

Essays in international finance

This thesis consists of three essays in international finance, with a focus on the foreign exchange market. The first chapter provides an empirical investigation of the predictive ability of average variance and average correlation on the return to carry trades. Using quantile regressions, we find that higher average variance is significantly related to large future carry trade losses, whereas lower average correlation is significantly related to large gains. This is consistent with the carry trade unwinding in times of high volatility and the good performance of the carry trade when asset correlations are low. Finally, a new version of the carry trade that conditions on average variance and average correlation generates considerable performance gains net of transaction costs. In the second chapter I study the evolution over time of the response of exchange rates to fundamental shocks. Using Bayesian time-varying-parameters VARs with stochastic volatility, I provide empirical evidence that the transmission of these shocks has changed over time. Specifically, currency excess returns tend to initially underreact to interest rate differential shocks for the whole sample considered, undershooting the level implied by uncovered interest rate parity and long-run purchasing power parity. In contrast, at longer horizons the previously documented evidence of overshooting tends to disappear in recent years in the case of the euro, the British pound and the Canadian dollar. Instead, overreaction at long horizons is a persistent feature of the excess returns on the Japanese yen and the Swiss franc throughout the whole sample. In the third chapter we provide a comprehensive review of models that are used by policymakers and international investors to assess exchange rate misalignments from their fair value. We survey the literature and illustrate a number of models by means of examples and by evaluating their strengths and weaknesses. We analyse the sensitivity of underlying balance (UB) models with respect to estimated trade elasticities. We also illustrate a fair value concept extensively used by financial markets practitioners but not previously formalised in the academic literature, and dub it the indirect fair value (IFV). As case studies, we analyse the models used by Goldman Sachs and by the International Monetary Fund’s Consultative Group on Exchange Rate Issues (CGER)