Brittle crack propagation simulation based on the Virtual Element Method and J_k-integral fracture criterion

Crack propagation simulation is a challenging topic in computational fracture mechanics, and the main issue is modeling the displacement discontinuity in the existing finite element mesh. The Virtual Element Method (VEM), as an extension of the Finite Element Method (FEM), permits the usage of arbitrarily shaped elements, including non-convex polygons or elements with hanging vertices, and has no distortion sensitivity. These features greatly facilitate VEM in addressing the crack propagation problem. An arbitrary crack propagation path can be achieved during the crack propagation process because the local mesh can be modified by adding or deleting vertices and/or edges, and by splitting one element into two polygons. This study simulates brittle crack propagation by the VEM with an element split strategy. The Jk-integral fracture criterion has been employed to determine the crack initiation and predict the crack propagation direction for mixed-mode loading conditions. The Jk-integral is computed directly by the path integral rather than by the domain integral, and its conservation has been verified. Some numerical applications have been implemented, including a mode-I crack problem test, a shear test of a single-edge notched plate and two different three-point bending tests. The numerical results show good agreement with the experiments, which verify the validity of the proposed simulation method for crack propagation

Leveraging Profiling to Bridge Healthcare Silos for Federated Analyses

Healthcare is more and more relying on digital information, bringing new challenges for its management, exploration, and usage. Healthcare data represents a challenge for information systems because, for privacy regulations, it cannot exit the original silo in which it has been produced (typically owned by hospitals), and may be of various kinds (clinical reports, DNA sequences, MRI scans, etc.). To manage this complexity, it is natural to use Federated Learning to safely analyze the underlying silos’ content. However, designing and running federated algorithms requires to know what the silos contain and how they can be joined (on which common attributes). Existing catalogs provide prelim-inary visualizations, which are hardly generalizable due to their under-lying use-case-tailored data models. To overcome these limitations, we provide a general catalog conceptual model as well as profiling techniques to extract information of interest from silos. Our proposed catalog is gen-eral enough to be used in various healthcare scenarios with diverse kinds of data. It also facilitates experts’ work in creating Federated Learning algorithms running in networks of interoperable healthcare silos

Navigating Twin Transition: Fostering Equitable and Anti-fragile Metropolitan Landscapes Enriching Digital Communities

The upcoming decades will be marked by the transformative dual green and digital transition fundamentally reshaping societies. Ensuring these transitions are equitable requires acknowledging disparities and anticipating socio-economic implications. This chapter underscores the importance of implementing strategies that embrace anti-fragility and de-risking (Taleb in Antifragile: things that gain from disorder. Global Penguin Random House, 2014). It advocates for a shift towards relational, pluriversal (Kothari et al. in Pluriverso. Dizionario del post-sviluppo. Orthotes, Napoli, 2021) modes of inhabiting urban spaces, preparing the context contents for employing digital tools to safeguard natural heritage, preserve local identity, and enhance community well-being (JRC in Understanding and acting on future risks and opportunities, Portfolio 26, 2023). This chapter explores the necessity of alternative dwelling modes that integrate communal existence, regenerative knowledge, and digital tools into metropolitan landscapes by challenging traditional design principles and promoting interconnectedness: a new emerging, nurturing diverse, and resilient ways of living. Our research underscores also the importance of metropolitan cultural heritage (Heritopolis Initiative) as a foundation for digital communities sustainable habitats. We translate these resources into actionable data and methodologies that drive policies that uphold heritage while advancing Twin Transition. A decentralised yet coordinated metropolitan framework is a system in which decision-making and authority are distributed across various entities or levels within a metropolitan area. However, a mechanism is still in place to ensure cooperation and alignment of goals among these entities. It implies a balance between local autonomy and collective coordination to efficiently manage urban development and services in a large city or metropolitan region

Verification-Oriented Specification of Multi-agent Interaction Patterns

Smart cyber agents are pivotal in software-intensive systems such as smart manufacturing, robotics, and the Internet of Things. These agents monitor physical surroundings through sensors and make impactful decisions that influence the environment. Software engineering challenges in this domain include the specification of interactive multi-agent tasks. The general-purpose Domain-Specific Language named LIrAs, Language for Interactive Agents, is a high-level language that allows for unambiguous custom pattern definition. Additionally, LIrAs facilitates interactions with human agents, a safety-critical situation requiring particular attention. This paper lays the foundation for LIrAs specifications translation to Stochastic Hybrid Automaton (SHA). The target SHA model structure follows a three-layer hierarchical structure and makes LIrAs specifications amenable to formal verification, specifically Statistical Model Checking, through the Uppaal tool, capable of including time-dependent ph..

Propulsive landing of launchers’ first stages with Deep Reinforcement Learning

The planetary landing problem is gaining relevance in the space sector, spanning a wide range of applications from unmanned probes landing on other planetary bodies to reusable first and second stages of launcher vehicles. In the existing methodology there is a lack of flexibility in handling complex non-linear dynamics, in particular in the case of non-convexifiable constraints. It is therefore crucial to assess the performance of novel techniques and their advantages and disadvantages. The purpose of this work is the development of an integrated 6-DOF guidance and control approach based on reinforcement learning of deep neural network policies for fuel-optimal planetary landing control, specifically with application to a launcher first-stage terminal landing, and the assessment of its performance and robustness. 3-DOF and 6-DOF simulators are developed and encapsulated in MDP-like (Markov Decision Process) industry-standard compatible environments. Particular care is given in thoroughly shaping reward functions capable of achieving the landing both successfully and in a fuel-optimal manner. A cloud pipeline for effective training of an agent using a PPO reinforcement learning algorithm to successfully achieve the landing goal is developed

Digital supply chains for ecosystem resilience: a framework for the Italian case

Contingency where exogenous and dramatic factors (i.e. Covid) impact not only on political and social life but also on economy is changing the way business is managed. Grounded on recent works studying the relationship between digitalisation and resilience, this work aims to systematize the links between the two dimensions at Supply Chains (SC) and at ecosystem level. A conceptual framework for manufacturing companies and policy makers is proposed to cope with disruptions thanks to digital technology implementation. The work is based on the results of an explorative analysis held with the support of practitioners from the manufacturing sector, IT providers and policy makers in Italy to systematise results and to demonstrate that public–private partnership can help to face disruptions. This paper contributes to the theory of ecosystems to establish a systemic framework to go beyond the border of each SC proposing a cross-collaboration model