2D finite elements for the computational analysis of crack propagation in brittle materials and the handling of double discontinuities

Crack growth simulations by way of the traditional Finite Element Method claim progressive remeshing to fit the geometry of the fracture, severely increasing the computational effort. Methods such as the eXtended Finite Element Method (XFEM) allow to overcome this limitation by means of nodal shape functions multiplied by Heaviside step function to enrich finite element nodes. Through the medium of a discontinuous field, the entire geometry of the discontinuity can be modelled regardless of the mesh, avoiding remeshing. In this paper two shell-type XFEM elements (a three-node triangular element and a four-node quadrangular element) to evaluate crack propagation in brittle materials are presented. These elements have been implemented into the widespread opensource framework OpenSees to evaluate crack propagation into a plane shell subjected to monotonically increasing loads. Moreover, in the perspective of fracture propagation simulations, the problem of managing multiple cracks without remeshing or operating subdivisions on the integration domain has been investigated and a four-node quadrangular finite element for the computational analysis of double crossed discontinuities by the means of equivalent polynomials is presented in this paper. Equivalent polynomials allow to overcome inaccuracies on the results when performing standard numerical integration (e.g. Gauss-Legendre quadrature rule) over the entire domain of XFEM elements, without the need of defining integration subdomains. The presented work and the computational strategy behind it may be extremely useful not only in the field of fracture mechanics, but also to solve complex geometry problems or material discontinuities

Analisi della resistenza a fatica di giunzioni saldate per sospensioni automobilistiche

La presente tesi si inserisce in uno studio sulla resistenza a fatica delle saldature. Lo scopo è quello di identificare un criterio scientifico adatto alla previsione di resistenza a fatica dei giunti saldati, indipendentemente dal giunto e dalla tecnica applicata; questo studio è utile in ambito automobilistico per la progettazione di componenti saldati, senza adottare coefficienti di sicurezza eccessivamente cautelativi a causa di una non completa conoscenza del fenomeno, permettendo una costruzione di componenti più leggera. All’interno dell’elaborato è stata svolta una ricerca bibliografica dove si mettono in evidenza le problematiche che insorgono nella verifica a fatica a causa della tecnica di saldatura. Successivamente è stato fatto un veloce riepilogo delle metodologie di verifica a fatica più frequentemente adoperate. Lo svolgimento della tesi si incentra sullo studio di provini assimilabili a semplici coprigiunti, sono stati applicati due diversi criteri di verifica a fatica tramite la realizzazione di sottomodelli, simulati con l’ausilio del programma agli elementi finiti Ansys. I risultati ottenuti sono stati adoperati per ricavare le curve di regressione S-N. Lo scopo ultimo della tesi è verificare l’affidabilità delle curve di progetto fornite in bibliografia a confronto con le curve di resistenza a fatica ottenute, analizzando eventuali incoerenze

Attention-Based Real-Time Defenses for Physical Adversarial Attacks in Vision Applications

Deep neural networks exhibit excellent performance in computer vision tasks, but their vulnerability to real-world adversarial attacks, achieved through physical objects that can corrupt their predictions, raises serious security concerns for their application in safety-critical domains. Existing defense methods focus on single-frame analysis and are characterized by high computational costs that limit their applicability in multi-frame scenarios, where real-time decisions are crucial. To address this problem, this paper proposes an efficient attention-based defense mechanism that exploits adversarial channel-attention to quickly identify and track malicious objects in shallow network layers and mask their adversarial effects in a multi-frame setting. This work advances the state of the art by enhancing existing over-activation techniques for real-world adversarial attacks to make them usable in real-time applications. It also introduces an efficient multi-frame defense framework, validating its efficacy through extensive experiments aimed at evaluating both defense performance and computational cost

Strategic behaviour of Italian fruit and vegetables importers from South Mediterranean Countries faced with food safety standards

The aim of this study was to analyse the heterogeneity of Italian specialized importers in Southern Mediterranean Countries. We analysed a national representative sample and defined a profile of companies according to the safety of fruit and vegetable im- ports, organization of chain by suppliers and clients and efforts in safety controls. We showed that the type of supply chain affects the importers’ strategies encouraging them to implement stricter standards, such as private standards, with respect to pub- lic law in order to meet customer needs and provide a sufficient degree of differentia- tion. These strategies, however, are not always aimed at obtaining a price premium, but are taken above all to ensure the maintenance of the reputation of the companies towards the most demanding customers and stabilize its market share

Increasing the Confidence of Deep Neural Networks by Coverage Analysis

The great performance of machine learning algorithms and deep neural networks in several perception and control tasks is pushing the industry to adopt such technologies in safety-critical applications, as autonomous robots and self-driving vehicles. At present, however, several issues need to be solved to make deep learning methods more trustworthy, predictable, safe, and secure against adversarial attacks. Although several methods have been proposed to improve the trustworthiness of deep neural networks, most of them are tailored for specific classes of adversarial examples, hence failing to detect other corner cases or unsafe inputs that heavily deviate from the training samples. This paper presents a lightweight monitoring architecture based on coverage paradigms to enhance the model robustness against different unsafe inputs. In particular, four coverage analysis methods are proposed and tested in the architecture for evaluating multiple detection logics. Experimental results show that the proposed approach is effective in detecting both powerful adversarial examples and out-of-distribution inputs, introducing limited extra-execution time and memory requirements

An Approach for Improving Automatic Mouth Emotion Recognition

The study proposes and tests a technique for automated emotion recognition through mouth detection via Convolutional Neural Networks (CNN), meant to be applied for supporting people with health disorders with communication skills issues (e.g. muscle wasting, stroke, autism, or, more simply, pain) in order to recognize emotions and generate real-time feedback, or data feeding supporting systems. The software system starts the computation identifying if a face is present on the acquired image, then it looks for the mouth location and extracts the corresponding features. Both tasks are carried out using Haar Feature-based Classifiers, which guarantee fast execution and promising performance. If our previous works focused on visual micro-expressions for personalized training on a single user, this strategy aims to train the system also on generalized faces data sets

Evaluation and Planning Control of the Ecosystem Fragmentation Due to Urban Development

Different kinds of urban sprawl on the territory cause the ecosystems fragmentation phenomena which the planning tools often are not able to control. It's possible to measure these phenomena through some indicators that consider functional characteristics, shapes and dimensions of the urban objects (road networks and urbanised areas). On the base of these parameters we can obtain the models of different urban fragmentation scenarios, where each model is related to a range of indicator values (fragmentation landscapes). If we consider a set of target animal species linked to local ecosystems we could individuate the changing, in terms of crossing possibilities, that each species has with respect to each fragmentation urban model. When we get the possible relations among the values of fragmentation indicators and the other classic parameters that the planners use to regulate density and distribution of the future urbanised areas on the territory, we?ll can realise the credible scenarios about the environmental fragmentation conditions following the plan tool management. The new framework which the plan draws for the territory will be more or less suitable for the movement of the species that lives around and, analysing this suitability through biopermeability evaluation, will be possible to adjust the impacts of the urban transformation on the ecosystems and natural landscapes. The data and the methods used during the research program that we inserted in the present paper are relative to study area of the Italian Central Apennines, a mountain place where we can find natural areas and complex eco-mosaics, with species of fauna of international importance, and numerous small and middle urban areas ?plunged? in the ecological networks. Corresponding author: Bernardino Roman

Internal jugular vein duplication

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