Numerical Analysis of a New Mixed Formulation for Eigenvalue Convection-Diffusion Problems

A mixed formulation is proposed and analyzed mathematically for coupled convection-diffusion in heterogeneous medias. Transfer in solid parts driven by pure diffusion is coupled with convection-diffusion transfer in fluid parts. This study is carried out for translation-invariant geometries (general infinite cylinders) and unidirectional flows. This formulation brings to the fore a new convection-diffusion operator, the properties of which are mathematically studied: its symmetry is first shown using a suitable scalar product. It is proved to be self-adjoint with compact resolvent on a simple Hilbert space. Its spectrum is characterized as being composed of a double set of eigenvalues: one converging towards −∞ and the other towards +∞, thus resulting in a nonsectorial operator. The decomposition of the convection-diffusion problem into a generalized eigenvalue problem permits the reduction of the original three-dimensional problem into a two-dimensional one. Despite the operator being nonsectorial, a complete solution on the infinite cylinder, associated to a step change of the wall temperature at the origin, is exhibited with the help of the operator’s two sets of eigenvalues/eigenfunctions. On the computational point of view, a mixed variational formulation is naturally associated to the eigenvalue problem. Numerical illustrations are provided for axisymmetrical situations, the convergence of which is found to be consistent with the numerical discretization

A model for the investigation of the second-order structure of caustic formations in dispersed flows

The formation of caustics by inertial particles is distinctive of dispersed flows. Their pressureless nature allows crossing trajectories resulting in singularities that cannot be captured accurately by standard Lagrangian approaches due to their fine spatial scale. A promising method for the investigation of caustics is the Osiptsov method or fully Lagrangian approach (FLA). The FLA has the advantage of identifying caustics, but its applicability is hindered by the occurrence of singularities. We present an original robust framework based on the FLA that provides an explicit expression of the dispersed phase structure that does not degenerate in the vicinity of caustics, using a single representative particle. The FLA is extended to account for the Hessian of the dispersed continuum (DC). It demonstrates the integrability of the FLA number density and allows for the calculation of the number density on a given length scale, retaining the functionality of the FLA. Number density models based on the second-order representation of the DC and on the one-dimensional structure of the particle distribution, that account for the anisotropy of the DC on caustics, are derived and applied for analytical flows. The number density is linked to a finite length scale, needed for the introduction of the FLA to spatially filtered flow fields. Finally, the method is used for the calculation of the interparticle separation on caustics. The identification of the structure of caustics presented in this work paves the way to a robust understanding of the mechanisms of particle accumulation

Pattern-driven security, privacy, dependability and interoperability management of iot environments

Achieving Security, Privacy, Dependability and Interoperability (SPDI) is of paramount importance for the ubiquitous deployment and impact maximization of Internet of Things (IoT) applications. Nevertheless, said requirements are not only difficult to achieve at system initialization, but also hard to prove and maintain at run-time. This paper highlights an approach to tackling the above challenges, through the definition of pattern language and a framework that can guarantee SPDI in IoT orchestrations. By integrating pattern reasoning engines at the various layers of the IoT infrastructure, and a machine-processable representation of said pattern through Drools rules, the proposed framework can provide ways to fulfill SPDI requirements at design time, and also provide the means to guarantee those SPDI properties and manage the orchestrations accordingly. Moreover, an application example of the framework is presented in an Industrial IoT monitoring environment

A Reference Architecture for Management of Security Operations in Digital Service Chains

Modern computing paradigms (i.e., cloud, edge, Internet of Things) and ubiquitous connectivity have brought the notion of pervasive computing to an unforeseeable level, which boosts service-oriented architectures and microservices patterns to create digital services with data-centric models. However, the resulting agility in service creation and management has not been followed by a similar evolution in cybersecurity patterns, which still largely rest on more conventional device- and infrastructure-centric models. In this Chapter, we describe the implementation of the GUARD Platform, which represents the core element of a modern cybersecurity framework for building detection and analytics services for complex digital service chains. We briefly review the logical components and how they address scientific and technological challenges behind the limitations of existing cybersecurity tools. We also provide validation and performance analysis that show the feasibility and efficiency of our implementation

Solution of cavitating compressible flows using Discontinuous Galerkin discretisation

A methodology for modelling cavitating flows using a high-order Adaptive Mesh Refinement (AMR) approach based on the Discontinuous Galerkin method (DG) is presented. The AMR implementation used features on-the-fly adaptive mesh refinement for unstructured hybrid meshes. The specific implementation has been developed for the resolution of complex multi-scale phenomena where high accuracy p-adaptive discretisations are combined with an h-adaptive data structure. This approach accommodates the fine spatial resolution for the interface discontinuities and the shock waves observed in compressible cavitating flows. The Tait equation of state is used for the modelling of the liquid phase while an isentropic path is assumed for the liquid/vapour mixture. Second order spatial and a third order non-oscillatory temporal discretisation are used for the integration of the mass and momentum conservation equations, in order to resolve the flow structures responsible for the formation of cavitation bubbles and the resulting compression waves. Assessment of the developed methodology is performed for the one-dimensional advancement of a compressible liquid-vapour interface and the symmetric collapse of a spherical vapour bubble. Following, results obtained with the developed multi-scale modelling AMR approach has revealed a complex bubble collapse mechanism near a rigid wall, providing evidence of processes that have been unknown before due to reduced resolution and dissipative nature of past simulations. The impinging jet accompanying the collapse of a bubble near a wall, was found to induce vortical structures, which result to the formation of a secondary cavitation of a wall-attached bubble at the vicinity of the impingement jet shear layer. At the final stages of the initial bubble collapse, the impinging jet was found to penetrate the centre-line of the wall bubble inducing its partial collapse. This secondary collapse results to a rich spatial structure of shock waves, interacting with the secondary bubbles. Moreover, the calculated pressure level are found to be much higher than those reported from previous methodologies

Droplet nuclei caustic formations in exhaled vortex rings

Vortex ring (VR) structures occur in light or hoarse cough configurations. These instances consist of short impulses of exhaled air resulting to a self-contained structure that can travel large distances. The present study is the first implementation of the second order Fully Lagrangian Approach (FLA) for three-dimensional realistic flow-fields obtained by means of Computational Fluid Dynamics (CFD) and provides a method to calculate the occurrence and the intensity of caustic formations. The carrier phase flow field is resolved by means of second order accurate Direct Numerical Simulation (DNS) based on a Finite Difference approach for the momentum equations, while a spectral approach is followed for the Poisson equation using Fast Fourier Transform (FFT). The effect of the undulations of the carrier phase velocity due to large scale vortical structures and turbulence is investigated. The evaluation of the higher order derivatives needed by the second order FLA is achieved by pre-fabricated least squares second order interpolations in three dimensions. This method allows for the simulation of the clustering of droplets and droplet nuclei exhaled in ambient air in conditions akin to light cough. Given the ambiguous conditions of vortex-ring formation during cough instances, three different exhale (injection) parameters n are assumed, i.e. under-developed ([Formula: see text]), ideal ([Formula: see text]) and over-developed ([Formula: see text]) vortex rings. The formation of clusters results in the spatial variance of the airborne viral load. This un-mixing of exhumed aerosols is related to the formation of localised high viral load distributions that can be linked to super-spreading events

Towards a Collection of Security and Privacy Patterns

Security and privacy (SP)-related challenges constitute a significant barrier to the wider adoption of Internet of Things (IoT)/Industrial IoT (IIoT) devices and the associated novel applications and services. In this context, patterns, which are constructs encoding re-usable solutions to common problems and building blocks to architectures, can be an asset in alleviating said barrier. More specifically, patterns can be used to encode dependencies between SP properties of individual smart objects and corresponding properties of orchestrations (compositions) involving them, facilitating the design of IoT solutions that are secure and privacy-aware by design. Motivated by the above, this work presents a survey and taxonomy of SP patterns towards the creation of a usable pattern collection. The aim is to enable decomposition of higher-level properties to more specific ones, matching them to relevant patterns, while also creating a comprehensive overview of security- and privacy-related properties and sub-properties that are of interest in IoT/IIoT environments. To this end, the identified patterns are organized using a hierarchical taxonomy that allows their classification based on provided property, context, and generality, while also showing the relationships between them. The two high-level properties, Security and Privacy, are decomposed to a first layer of lower-level sub-properties such as confidentiality and anonymity. The lower layers of the taxonomy, then, include implementation-level enablers. The coverage that these patterns offer in terms of the considered properties, data states (data in transit, at rest, and in process), and platform connectivity cases (within the same IoT platform and across different IoT platforms) is also highlighted. Furthermore, pointers to extensions of the pattern collection to include additional patterns and properties, including Dependability and Interoperability, are given. Finally, to showcase the use of the presented pattern collection, a practical application is detailed, involving the pattern-driven composition of IoT/IIoT orchestrations with SP property guarantees

Numerical study of real gas effects during bubble collapse using a disequilibrium multiphase model

An explicit density-based solver of the Euler equations for inviscid and immiscible gas-liquid flow media is coupled with real-fluid thermodynamic equations of state supporting mild dissociation and calibrated with shock tube data up to 5000 K and 28 GPa. The present work expands the original 6-equation disequilibrium method by generalising the numerical approach required for estimating the equilibrium pressure in computational cells where both gas and liquid phases co-exist while enforcing energy conservation for all media. An iterative numerical procedure is suggested for taking into account the properties of the gas content as derived from highly non-linear real gas equations of state and implemented in a tabulated form during the numerical solution. The developed method is subsequently used to investigate gaseous bubble collapse cases considering both spherical and 2D asymmetric arrangements as induced by the presence of a rigid wall. It is demonstrated that the predicted maximum temperatures are strongly influenced by the equations of state used; the real gas model predicts a temperature reduction in the bubble interior up to 41% space-averaged and 50% locally during the collapse phase compared to the predictions obtained with the aid of the widely used ideal gas approximation

CIRCE: Architectural Patterns for Circular and Trustworthy By-Design IoT Orchestrations

The adoption of Internet of Things (IoT) devices, applications and services gradually transform our everyday lives. In parallel, the transition from linear to circular economic (CE) models provide an even more fertile ground for novel types of services, and the update and enrichment of legacy ones. To fully realize the potential of the interplay between IoT and CE, the design-time definition of IoT orchestrations with proven circularity properties, and the run-time management of these orchestrations based on said properties, is of paramount importance. Nevertheless, the circularity requirements and associated properties are not only difficult to achieve at the IoT orchestration design and deployment initialization phases, but also hard to prove and maintain at run-time. Motivated by this, this paper presents the CIRCE framework for circular and trustworthy by-design IoT orchestrations. The CIRCE approach leverages concepts from pattern-driven engineering, whereby patterns are used to encode proven dependencies between the Location, Condition, and Availability (LCA) properties of individual smart objects and corresponding properties of orchestrations (compositions) involving them. These are augmented by patterns encoding trustworthiness-related properties, namely Connectivity, Security, Privacy, Dependability, and Interoperability (CSPDI). Thereby, these patterns are used to generate IoT orchestrations with proven LCA and CSPDI properties, as needed, at design time. At runtime, these properties are monitored in real-time, leveraging reasoning engines deployed across system layers, triggering adaptations to return the deployed orchestration to the desired LCA and CSPDI states, when required. Details are provided on the above novel combination of IoT, CE and pattern-based engineering, along with a proposed architecture and implementation approach. Furthermore, an assessment of a proof-of-concept implementation is provided, validating the feasibility of the proposed approach