Multi-field and multi-scale modeling of fracture for renewable energy applications

This thesis is mainly focused on the computational model- ing of solar cell cracking, multiphyics phenomena, and re- cycling of photovoltaic (PV) modules through the finite ele- ment method. Specifically, it consists of three parts. In the first part, a comprehensive hygro-thermo-mechanical com- putational framework in the 3D setting is proposed to model the coupled degradation phenomena in the PV modules for the durability analysis, and it is applied to the simulation of three international standard tests of PV modules, namely the damp heat test, the humidity freeze test, and the ther- mal cycling test. The second part is focused on the crack modeling of very thin and brittle silicon solar cells in the PV modules, and a reliable computational framework integrat- ing solid shell element formulation with phase field fracture modeling is developed using the efficient quasi-Newton so- lution scheme and global local approach. The excellent per- formance is showcased through the simulation of different boundary value problems, and then applied to predict the crack growth of silicon solar cells when the PV modules are subjected to different external loadings. The third part ad- dresses the efficient recycling of PV modules through the nu- merical modeling method by the development of 3D interface finite element with humidity-dose enhanced cohesive zone model for the peeling simulation to separate different layers, and diffusion-swelling large deformation continuum theory for the nondestructive recovery of silicon cells in the PV recy- cling using the solvent method. With these tools at hand, it is possible to design suitable virtual testing procedures for PV durability and recyclability analysis

Computational Mechanics Framework for Simulations and Prediction of Wear in Frictional Contacts

A computational fnite element modelling of a mechanical model to predict wear, including friction, is proposed in this work. As an ex- pansion of the interface fnite element with an embedded profle for joint roughness (MPJR interface fnite element), it is designed to solve the frictional contact problem between rigid indenters of any complex shape and elastic bodies. In the formulation, the non-linearity due to contact is considered for predicting contact traction, frictional effects, and wear. This formulation interfaces with FEM software and can em- bed roughness or general deviations from the planarity as a correction to the normal gap function. The model employs a regularized version of the Coulomb friction law for the tangential contact response while introducing a penalty approach in the normal contact direction. The present framework enables the comprehensive investigation of the tan- gential and normal tractions via the computation of displacements and the displacement gaps in the model. These tangential and normal trac- tions can be used to calculate the wear rate via the wear law. The model defnes wear by contact force and gaps. Due to this, contact pressure develops wear and the normal gap changes. Model parameters related to the constitutive equations of the interface where two bodies come in contact: regularized coulomb friction law and Archard’s wear law out- lined. In conclusion, this model predicts the wear and wear rate at the micro-scale level and explains how to formulate and predict wear at the macro-scale level

On the conceptualisation and forecasting of emotion dynamics in healthy and psychiatric individuals

Throughout the day, individuals experience a variety of feelings, such as amusement, relaxation, and envy. By observing the regularities in the stream of affect, individuals learn to predict future emotions from current ones and develop accurate mental models of emotion transitions. This thesis aims to explore the cognitive architecture underlying these affective forecasts. Through a series of experiments involving both healthy and psychiatric individuals, we investigate i) the temporal boundaries of affective predictions and their evolution over time, ii) the influence of the conceptual knowledge about emotions on transition judgements at various timescales, iii) the impact of dysfunctional affective dynamics on the forecast of future emotions. Results indicate that people trust more their predictions in the near future, with confidence dropping after 24 hours. We identified nine prototypes in the temporal profiles of affective forecasts and mapped their trajectories in a two-dimensional space defined by transition plausibility and slope. Also, we characterise emotions as starting states (e.g., surprise) or end-points (e.g., irritation) based on transition judgments, and reveal asymmetry in forecasts for specific transitions (e.g., relief → fear). Analysis of the scaffolding of affective forecasts confirms the relevance of conceptual knowledge about emotions in shaping mental models of emotion transitions. Our findings indicate that similarities between emotions in certain dimensions (e.g., valence) inform predictions regardless of the time interval, while others (e.g., arousal) exert influence only within specific timescales. We demonstrate that psychiatric disorders such as depression and bipolar disorder significantly affect the architecture of affective forecasts, although these adjustments do not undermine the core predictive structure. Findings suggest that patients use their internal emotion dynamics as a reference to construct (or refine) their predictive models of emotion transitions

The Representation of Visual Naturalistic Stimuli in Resting State Activity: An Investigation in the Visual and Motor Areas Representations at Rest

Resting state is characterized as an offline period, during which the eyes may be either open or closed. In this disengaged state, one’s system operates independently of external input or feedback, and by definition, relies on an internalized model of the world. Literature shows that resting state activity may reflect the statistics of the natural environment, but also the unique individual biases, and is possible to be reshaped over time. This is highlighted by studies that show that resting state fluctuations maintain traces of everyday activity; but how are these representations extracted, how stable are they, and to what extent are they malleable? To answer that we need to understand: 1) How is our system structured to maintain regularities? 2) How are they integrated in an internalized model? 3) How do low frequencies fluctuate when detecting an error? The main aim of this thesis is to understand how natural information is represented in resting state. The working model is that (1) naturalistic information is processed along a hierarchy in time and space to code higher level information that is low dimensional and sparse (chapter 2). 2) This information is then maintained in resting state in a generic form (chapter 3). 3) This is achieved because low frequency fluctuations are adapted to naturalistic statics, and hence are altered in otherwise unexpected situations (chapter 4). We examined the functional connectivity (FC) of MEG signal changes in the visual (VIS) and dorsal attention (DAN) networks during the observation of naturalistic videos, by comparing them to a pretrained convolutional network. We reveal distinct temporal dynamics in processing low and high-level features. Low-level features are immediately and abundantly represented, while high-level features exhibit a delayed and scarce representation, potentially storing information in a generic form (chapter 2). For instance, we find that the BOLD multivoxel spatial representation of a still hand, controlled for low-level features, is coherent with the spatial representation of the resting somatomotor area, as opposed to another object such as a food item (chapter 3). We suggest that the representations during resting states may contribute to the goal of interacting with the environment. This is enriched by our final findings; the multivoxel spatial representation of observing common movements aligns more coherently with resting somatomotor patterns as opposed to uncommon (chapter 4)

Gravity Models of Networks

Trade networks are mathematical representations of the ex- changes established by countries, industries, firms or individ- uals. The present thesis collects works aimed at overcoming the limitations characterizing the econometric recipes tradi- tionally employed to study the aforementioned systems, by introducing a novel framework, based upon the maximum- entropy formalism. In chapter 2 we develop a novel class of models to study networks with discrete weights, capable of accommodating both structural and econometric parameters, finding that they outperform standard, econometric models [1]. In chapter 3 we extend the aforementioned set of models to study networks with continuous weights [2]. In chapter 4 we go beyond the ‘deterministic’ optimization procedure pre- scribed by econometrics to specify conditional models, con- sidering two, alternative estimation recipes characterized by different ways of averaging over the topological randomness: what we find is that the ‘annealed’ recipe, prescribing to max- imize a generalized likelihood function, is to be preferred, re- gardless of the heterogeneity of weights [3]. Finally, in Chap- ter 5, we delve into the extent to which the triadic structures embedded within the Dutch multi-commodity production net- work align with maximum-entropy conditional models [4]. Our findings reveal that for the vast majority of commodities, these models effectively replicate the observed triadic struc- tures, exhibiting minimal deviations

Perception, Cognition and Ayahuasca A Multidimensional Analysis of Alter States of Consciousness

My Ph.D. thesis comprises a series of experiments aimed at investigating the impact of a novel ayahuasca analog, pharmahuasca (PHA), on face perception and creative cognition. These studies were executed with a within-subject, double-blind, placebo-controlled design involving 30 healthy male participants. Chapter 2 centers on the effects of psychedelics on face perception, utilizing electroencephalography (EEG) during a visual oddball task with self, familiar, and unknown faces as stimuli. Notable changes induced by PHA in early visual processing, such as increased P1 and reduced N170 across all face categories, were observed. In late visual processing, a decrease in neural activation in response to the self-face, as indicated by the P300 wave, highlights the significance of psychedelics in altering self-referential information processing. Additionally, the impact of psychedelics on face discrimination was explored through a two-alternative forced choice (2-AFC) task, where faces are incrementally morphed to each other, revealing a decreased sensitivity for discrimination during psychedelic experiences across all face categories. Chapter 3 shifts focus to understanding how psychedelics influence creative cognition. Through task-based methodologies, the findings unveil a reduction in convergent thinking without affecting on divergent thinking. Next, we investigate how utilization of different thinking modes during the artistic creation, specifically in the domain of painting, under the influence of psychedelics. Importantly, there was a significant reduction in transitions between different creative thinking modes during the psychedelic-induced creative process, particularly affecting stages traditionally requiring convergent thinking, offered valuable insights into the phenomenological nuances of the interplay between psychedelics and the dynamics of creative thinking

Spectral signature of Breaking of ensemble equivalence

In this thesis we explore the concept of Breaking of Ensem- ble Equivalence (BEE) within the context of random graph models, focusing on spectral properties of adjacency matri- ces. Our research aims to identify spectral quantities that can distinguish between different random graph ensembles, thereby providing new insights into the structure and behav- ior of complex networks. We cover both theoretical aspects and practical implications, including simulations and sam- pling methods for random graph models. In Chapter 1 we introduce some basic notions of random graph theory, and discuss how maximum entropy graph models are fundamental in modeling real-world networks. We explain what BEE is, what is its characterization in the context of sta- tistical mechanics, and how it is intimately connected to dif- ferences that arise naturally between the canonical versus the microcanonical description of random graph ensembles. In order to do so, we delve into the spectral theory of random graphs and use it to investigate BEE. In Chapter 2 we formulate a conjecture on the equivalence of measure-BEE and the presence of a gap between the largest non-centered and non-scaled largest eigenvalues of the adja- cency matrix in the canonical and the microcanonical ensem- ble. We prove this conjecture in the setting of homogeneous graphs. In Chapter 3 we study the same question for Chung-Lu ran- dom graphs. In particular, we prove central limit theorems for the largest eigenvalue and its associated eigenvector. In Chapter 4 we compute the expectation of the largest eigen- value for the configuration model, which verifies our conjec- ture in the setting of inhomogeneous graphs as well. In Chapter 5 we provide numerical evidence for our findings through simulation, after a brief introduction to graph sam- pling. We formulate the main conclusions of our work and indicate possible further directions of research

Understanding Emotions: The Evolution of Affective Neuroscience and a Network-Based Taxonomy of Emotion

Emotion, as a field of study, has evolved significantly over the centuries, encompassing various perspectives from theology, philosophy, medicine, psychology, and neuroscience. Historically, terms like 'passions,' 'affections,' and 'emotions' have carried different connotations and have been studied through different lenses, influenced by societal norms and scientific advancements. The affective lexicon has seen a transition across different languages and cultural contexts, contributing to the development of a global scientific community and a more nuanced understanding of emotional phenomena. The first part provides a comprehensive overview of the evolution of affective neuroscience, highlighting the historical path, emotional models and theories, and methodological advancements. A thorough qualitative look at the sharp increase in affective studies provides a beter understanding of where emotion research has focused. An extensive literature review across PubMed was conducted to gather relevant studies focusing on affective topics, neuroimaging techniques, and emotional categories. The findings demonstrated the trends in the publications of the affective neuroscience field over time. The analysis revealed a significant shift in research focus over the years, a specific focus on neuroimaging techniques and certain emotion categories The second part presents an innovative approach to understanding emotions through language. This section delves into the semantic structures underlying affective terms and explores how linguistic and cultural nuances could shape emotional experiences. It examines the challenges in achieving a scientific consensus on the nature of emotions due to their conceptual complexity. This complexity is further compounded by the variety of models proposed to categorize emotions, stemming from basic emotion theories, which suggest a limited number of universal emotions, to dimensional and constructionist theories, which argue for a more fluid and context-dependent understanding of emotional experiences. Through the experimental procedure, participants were instructed to define emotional terms based on the subjective experience. The results demonstrate that emotions are intricately linked within a network-based hierarchical taxonomy based on language, offering a more detailed and systematic classification of emotions than traditional emotion models. This network-based approach elucidates the relationships between various affective terms and their semantic structures, highlighting the complex interplay between language and emotion

Walking a mile in another’s shoes. The use of naturalistic stimulation to study emotional processing and empathy

The present dissertation delves into the cutting-edge field of naturalistic stimulation to investigate the multifaceted nature of emotional experiences and the mechanisms underlying empathic responses. Through a series of behavioral studies, we explored 1) whether the emotional experience elicited by a movie can be embedded by a limited set of descriptors conventionally referred to as genres; 2) the affective unfolding of narratives, and the emotional transitions dynamics underlying individual experience; 3) the contribution of visual, acoustic, and semantic properties of the stimulus in predicting the subjective emotional experience. Our results show that the unfolding of emotions plays a crucial role in shaping how audiences perceive and categorize movies. Then, we confirm the existence of six archetypal patterns that shape the emotional trajectories of narratives, and we demonstrate that certain emotions may serve as triggers, others act as catalysts for subsequent reactions, or emerge as outcomes of appraised states. The same emotion may behave as both starting and landing state, suggesting the crucial role of context in shaping the inner emotional experience. Also, we find that, although we can predict a consistent amount of the audience's emotional states, the physical properties of the stimulus may not be entirely sufficient to reconstruct the subjective affective experience. Lastly, we assess the psychometric properties of two recently developed questionnaires measuring empathic abilities in the Italian populatio

Circumventing Plague: The Spatial Experience of Women and Men during the Outbreak of 1630-31 Bologna

Though managing early modern plague in northern Italy necessitated regulations and restrictions of movement in order to combat outbreaks, the factors resulting in immobility at the same time created opportunities for mobility. The ability to move and interact within the urban environment was contingent on social factors such as age, gender, class and occupational status and remained essential in the shaping of the spatial experience. Moreover, the ability to move across barriers, such as crossing the threshold of the home, formulated possibilities for social life to flourish during plague. This study investigates the relationships between early modern people and places during the period of plague in Bologna from 1630-31 through the lens of the new mobilities paradigm. This model interrogates how places are continuously shaped and reshaped by way of human and non-human interaction. Adopting approaches emerging from the mobility turn, this research places emphasis on the social drivers that contributed to movement and asks: how did mobility inform the various experiences of the plague of 1630-31 in Bologna? Building on the extensive studies on seventeenth-century plague for the cities of Milan, Venice and Florence, this study offers new insights into the early modern experience and approaches to plague from the perspective of the significant northern Italian centre of Bologna. This study draws on a broad array of primary documents including handwritten and printed records, encompassing contemporary chronicles, manuscripts and egal decrees. Historical sources including plague tracts reveal contemporary understanding of combatting plague. Visual sources, such as early modern paintings and architectural plans, alongside digital maps of Bologna’s network of plague hospitals, similarly play a crucial role in uncovering the spatial experience during plague. The research presented in this study contends that the urban experience and the public health management of early modern plague was informed by mobility. Architecture, in combination with regulations and disciplinary punishment, were used to contain, control and limit the movement of people. Despite immobility, men and women found ways to circumvent restrictions. They crossed architectural divides by way of health passes or illicit activities and traversed physical but also social boundaries through professional opportunities. Bolognese citizens continued to move by way of engaging with devotional performances, such as processions. Ritualised performance was enacted to counteract the moral causes of the illness and ultimately served the social life of the community. Mobility was also considered an asset for plague management according to seventeenth-century practice as demonstrated in the creation and employment of a network of plague hospitals in Bologna. Moreover, this study reveals how social dimensions contributed to varying degrees of mobility as women, men, the nobility and the poor each had diverse experiences of plague