Un modello spazialmente distribuito per la modellazione fisicamente basata del contributo locale al trasporto solido in sospensione in alvei fluviali

La presente tesi di dottorato si propone lo sviluppo di un modello spazialmente distribuito per produrre una stima dell'erosione superficiale in bacini appenninici. Il modello è stato progettato per simulare in maniera fisicamente basata il distacco di suolo e di sedimento depositato ad opera delle precipitazioni e del deflusso superficiale, e si propone come utile strumento per lo studio della vulnerabilità del territorio collinare e montano. Si è scelto un bacino collinare dell'Appennino bolognese per testare le capacità del modello e verificarne la robustezza. Dopo una breve introduzione per esporre il contesto in cui si opera, nel primo capitolo sono presentate le principali forme di erosione e una loro descrizione fisico-matematica, nel secondo capitolo verranno introdotti i principali prodotti della modellistica di erosione del suolo, spiegando quale interpretazione dei fenomeni fisici è stata data. Nel terzo capitolo verrà descritto il modello oggetto della tesi di dottorando, con una prima breve descrizione della componente afflussi-deflussi ed una seconda descrizione della componente di erosione del suolo. Nel quarto capitolo verrà descritto il bacino di applicazione del modello, i risultati della calibrazione ed un'analisi di sensitività. Infine si presenteranno le conclusioni sullo studio.

Ricostruzione degli sforzi in elementi finiti di piastra

Nell’ambito dell’analisi computazionale delle strutture il metodo degli elementi finiti è probabilmente uno dei metodi numerici più efficaci ed impiegati. La semplicità dell’idea di base del metodo e la relativa facilità con cui può essere implementato in codici di calcolo hanno reso possibile l’applicazione di questa tecnica computazionale in diversi settori, non solo dell’ingegneria strutturale, ma in generale della matematica applicata. Ma, nonostante il livello raggiunto dalle tecnologie ad elementi finiti sia già abbastanza elevato, per alcune applicazioni tipiche dell’ingegneria strutturale (problemi bidimensionali, analisi di lastre inflesse) le prestazioni fornite dagli elementi usualmente utilizzati, ovvero gli elementi di tipo compatibile, sono in effetti poco soddisfacenti. Vengono in aiuto perciò gli elementi finiti basati su formulazioni miste che da un lato presentano una più complessa formulazione, ma dall’altro consentono di prevenire alcuni problemi ricorrenti quali per esempio il fenomeno dello shear locking. Indipendentemente dai tipi di elementi finiti utilizzati, le quantità di interesse nell’ambito dell’ingegneria non sono gli spostamenti ma gli sforzi o più in generale le quantità derivate dagli spostamenti. Mentre i primi sono molto accurati, i secondi risultano discontinui e di qualità scadente. A valle di un calcolo FEM, negli ultimi anni, hanno preso piede procedure di post-processing in grado, partendo dalla soluzione agli elementi finiti, di ricostruire lo sforzo all’interno di patch di elementi rendendo quest’ultimo più accurato. Tali procedure prendono il nome di Procedure di Ricostruzione (Recovery Based Approaches). Le procedure di ricostruzione qui utilizzate risultano essere la REP (Recovery by Equilibrium in Patches) e la RCP (Recovery by Compatibility in Patches). L’obbiettivo che ci si prefigge in questo lavoro è quello di applicare le procedure di ricostruzione ad un esempio di piastra, discretizzato con vari tipi di elementi finiti, mettendone in luce i vantaggi in termini di migliore accurattezza e di maggiore convergenza.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Maximum principle, mean value operators and quasi boundedness in non-euclidean settings

This work deals with some classes of linear second order partial differential operators with non-negative characteristic form and underlying non- Euclidean structures. These structures are determined by families of locally Lipschitz-continuous vector fields in RN, generating metric spaces of Carnot- Carath´eodory type. The Carnot-Carath´eodory metric related to a family {Xj}j=1,...,m is the control distance obtained by minimizing the time needed to go from two points along piecewise trajectories of vector fields. We are mainly interested in the causes in which a Sobolev-type inequality holds with respect to the X-gradient, and/or the X-control distance is Doubling with respect to the Lebesgue measure in RN. This study is divided into three parts (each corresponding to a chapter), and the subject of each one is a class of operators that includes the class of the subsequent one. In the first chapter, after recalling “X-ellipticity” and related concepts introduced by Kogoj and Lanconelli in [KL00], we show a Maximum Principle for linear second order differential operators for which we only assume a Sobolev-type inequality together with a lower terms summability. Adding some crucial hypotheses on measure and on vector fields (Doubling property and Poincar´e inequality), we will be able to obtain some Liouville-type results. This chapter is based on the paper [GL03] by Guti´errez and Lanconelli. In the second chapter we treat some ultraparabolic equations on Lie groups. In this case RN is the support of a Lie group, and moreover we require that vector fields satisfy left invariance. After recalling some results of Cinti [Cin07] about this class of operators and associated potential theory, we prove a scalar convexity for mean-value operators of L-subharmonic functions, where L is our differential operator. In the third chapter we prove a necessary and sufficient condition of regularity, for boundary points, for Dirichlet problem on an open subset of RN related to sub-Laplacian. On a Carnot group we give the essential background for this type of operator, and introduce the notion of “quasi-boundedness”. Then we show the strict relationship between this notion, the fundamental solution of the given operator, and the regularity of the boundary points.