Valutazione del comportamento differito di una trave inflessa realizzata in due fasi

La presente tesi analizza il comportamento differito in una prova di flessione su quattro punti su una trave prefabbricata con getto di soletta integrativa in opera. Sono riportati i risultati della prova di carico e di rottura sulla trave. Le prove sono state eseguite presso il Laboratorio di Prove Strutture (DISTART) dell'Università di Bologna. La trave è composta di due tipi di calcestreuzzo, realizzati in tempi diversi e con proprietà meccaniche diverse. L'obiettivo della campagna sperimentale è studiare l'effetto delle fasi di costruzione sull'evoluzione delle tensioni e delle deformazioni nel tempo e sulla resistenza ultima della trave. Il comportamento sperimentale è stato confrontato con i risultati numerici ottenuti con un modello a fibre in grado di cogliere anche i fenomeni legati al creep.

A maximum entropy approach to disturbed ecosystems

The current climate crisis requires a comprehensive understanding of biodiversity to acknowledge how ecosystems’ responses to anthropogenic disturbances may result in feedback that can either mitigate or exacerbate global warming. Although ecosystems are dynamic and macroecological patterns change drastically in response to disturbance, dynamic macroecology has received insufficient attention and theoretical formalisation. In this context, the maximum entropy principle (MaxEnt) could provide an effective inference procedure to study ecosystems. Since the improper usage of entropy outside its scope often leads to misconceptions, the opening chapter will clarify its meaning by following its evolution from classical thermodynamics to information theory. The second chapter introduces the study of ecosystems from a physicist’s viewpoint. In particular, the MaxEnt Theory of Ecology (METE) will be the cornerstone of the discussion. METE predicts the shapes of macroecological metrics in relatively static ecosystems using constraints imposed by static state variables. However, in disturbed ecosystems with macroscale state variables that change rapidly over time, its predictions tend to fail. In the final chapter, DynaMETE is therefore presented as an extension of METE from static to dynamic. By predicting how macroecological patterns are likely to change in response to perturbations, DynaMETE can contribute to a better understanding of disturbed ecosystems’ fate and the improvement of conservation and management of carbon sinks, like forests. Targeted strategies in ecosystem management are now indispensable to enhance the interdependence of human well-being and the health of ecosystems, thus avoiding climate change tipping points.