Failure due to fatigue in fiber bundles and solids

We consider first a homogeneous fiber bundle model where all the fibers have got the same stress threshold beyond which all fail simultaneously in absence of noise. At finite noise, the bundle acquires a fatigue behavior due to the noise-induced failure probability at any stress. We solve this dynamics of failure analytically and show that the average failure time of the bundle decreases exponentially as the stress increases. We also determine the avalanche size distribution during such failure and find a power law decay. We compare this fatigue behavior with that obtained phenomenologically for the nucleation of Griffith cracks. Next we study numerically the fatigue behavior of random fiber bundles having simple distributions of individual fiber strengths, at stress less than the bundle's strength (beyond which it fails instantly). The average failure time is again seen to decrease exponentially as the stress increases and the avalanche size distribution shows similar power law decay. These results are also in broad agreement with experimental observations on fatigue in solids. We believe, these observations regarding the failure time are useful for quantum breakdown phenomena in disordered systems.Comment: 13 pages, 4 figures, figures added and the text is revise

Medico-legal assessment of personal damage in older people: report from a multidisciplinary consensus conference

Ageing of the global population represents a challenge for national healthcare systems and healthcare professionals, including medico-legal experts, who assess personal damage in an increasing number of older people. Personal damage evaluation in older people is complex, and the scarcity of evidence is hindering the development of formal guidelines on the subject. The main objectives of the first multidisciplinary Consensus Conference on Medico-Legal Assessment of Personal Damage in Older People were to increase knowledge on the subject and establish standard procedures in this field. The conference, organized according to the guidelines issued by the Italian National Institute of Health (ISS), was held in Bologna (Italy) on June 8, 2019 with the support of national scientific societies, professional organizations, and stakeholders. The Scientific Technical Committee prepared 16 questions on 4 thematic areas: (1) differences in injury outcomes in older people compared to younger people and their relevance in personal damage assessment; (2) pre-existing status reconstruction and evaluation; (3) medico-legal examination procedures; (4) multidimensional assessment and scales. The Scientific Secretariat reviewed relevant literature and documents, rated their quality, and summarized evidence. During conference plenary public sessions, 4 pairs of experts reported on each thematic area. After the last session, a multidisciplinary Jury Panel (15 members) drafted the consensus statements. The present report describes Conference methods and results, including a summary of evidence supporting each statement, and areas requiring further investigation. The methodological recommendations issued during the Conference may be useful in several contexts of damage assessment, or to other medico-legal evaluation fields

Deep neural networks for the efficient simulation of macro-scale hysteresis processes with generic excitation waveforms

An effective and performing hysteresis model, based on a deep neural network, with the capability to reproduce the evolution of magnetization processes under arbitrary waveforms of excitation is here presented. The proposed model consists of a standalone multi-layer feed-forward neural network, with reserved input neurons for the past values of both the input (H) and output (M), aiming at the reproduction of the storage mechanism typical of hysteretic systems. The training set has been opportunely prepared starting from a set of simulations, performed by the Preisach hysteresis model. The optimized training procedure, based on multi-stage check of the model performance, will be comprehensively discussed. The comparative analysis between the neural network-based model, implemented at low level of abstraction, and the Preisach model covers additional hysteresis processes, different from those involved in the training. The mild/moderate memory requirement and the significant computational speed make the proposed approach suitable for a future coupling with finite-element analysis

Valutazione dei potenziali fattori di rischio cancerogeno nella popolazione dei Comuni di Popoli e Bussi sul Tirino: indagine preliminare sui casi di tumore, e risultati dell'analisi caso-controllo

No abstract availabl