Flexible barriers are increasingly used for the protection from debris flow in mountainous terrain due to their low cost and environmental impact. However, a numerical tool for rational design of such structures is still missing. In this work, a hybrid computational framework is presented, using a total Lagrangian formulation of the Finite Element Method (FEM) to represent a flexible barrier. The actions exerted on the structure by a debris flow are obtained from simultaneous simulations of the flow of a fluid-grain mixture, using two conveniently coupled solvers: the Discrete Element Method (DEM) governs the motion of the grains, while the freesurface non-Newtonian fluid phase is solved using the Lattice-Boltzmann Method (LBM). Simulations on realistic geometries show the dependence of the momentum transfer on the barrier on the composition of the debris flow, challenging typical assumptions made during the design process today. In particular, we demonstrate that both grains and fluid contribute in a non-negligible way to the momentum transfer. Moreover, we show how the flexibility of the barrier reduces its vulnerability to structural collapse, and how the stress is distributed on its fabric, highlighting potential weak points.

Cohesive zone models are explored in order to study cleavage fracture in adhesive bonded joints. A mode I cohesive model is defined which correlates the tensile traction and the displacement jump (crack faces opening) along the fracture process zone. In order to determine the traction-separation relation, the main fracture parameters, namely the cohesive strength and the fracture energy, as well as its shape, must be specified. However, owing to the difficulties associated to the direct measurement of the fracture parameters, very often they are obtained by comparing a measured fracture property with numerical predictions based on an idealized traction separation relation. Likewise in this paper the cohesive strength of an adhesive layer sandwiched between elastic substrates is adjusted to achieve a match between simulations and experiments. To this aim, the fracture energy and the load-displacement curve are adopted as input in the simulations. In order to assess whether or not the shape of the cohesive model may have an influence on the results, three representative cohesive zone models have been investigated, i.e. exponential, bilinear and trapezoidal. A good agreement between experiments and simulations has been generally observed. However, a slight difference in predicting the loads for damage onset has been found using the different cohesive models.

Sensor networks are characterized by limited battery supplies. Due to this feature, communication protocols specifically designed for these networks should be aimed a t minimizing energy consumption. To this purpose, the sensor's capability of transmitting with different power levels can be exploited. With this in mind, in this paper an integrated MAC/Routing protocol, called MACRO, which exploits the capability of sensor devices to tune their transmission power is introduced. The proposed protocol requires that each node only knows its own coordinates and the coordinates of the destination, but does not require any exchange of location information. In order to select the next relay node, a competition is triggered at each bop, so that the most energy efficient r e b y node is chosen. This is achieved through maximization of a newly introduced parameter, called weighted progress factor, which represents the progress towards the destination per unit of transmitted power. To this aim, an analytical framework which guarantees that MACRO performs the best choice is derived. MACRO performance is evaluated through n s -2 simulation and compared to other relevant routing schemes. Performance results show that the proposed protocol outperforms other solutions in terms of energy efficiency and boosts data aggregation.

The complexity of the interactions between the constituent granular and liquid phases of a suspension requires an adequate treatment of the constituents themselves. A promising way for numerical simulations of such systems is given by hybrid computational frameworks. This is naturally done, when the Lagrangian description of particle dynamics of the granular phase finds a correspondence in the fluid description. In this work we employ extensions of the Lattice-Boltzmann Method for non-Newtonian rheology, free surfaces, and moving boundaries. The models allows for a full coupling of the phases, but in a simplified way. An experimental validation is given by an example of gravity driven flow of a particle suspension.

The number of smart things is growing exponentially. By 2020, tens of billions of things will be deployed worldwide, collecting a wealth of diverse data. Traditional computing models collect in-field data and then transmit it to a central data center where analytics are applied to it, but this is no longer a sustainable model. New approaches and new technologies are required to transform enormous amounts of collected data into meaningful information. Technology also will enable the interconnection around things in the IoT ecosystem but further research is required in the development, convergence and interoperability of the different IoT elements. In this paper, we provide a picture of the main technological components needed to enable the interconnection among things in order to realize IoT concepts and applications.978-1-4799-5344-8/15/$31.00 ©2015 IEEE

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A granular front emerges whenever the free-surface flow of a concentrated suspension spontaneously alters its internal structure, exhibiting a higher concentration of particles close to its front. This is a common and yet unexplained phenomenon, which is usually believed to be the result of fluid convection in combination with particle size segregation. However, suspensions composed of uniformly sized particles also develop a granular front. Within a large rotating drum, a stationary recirculating avalanche is generated. The flowing material is a mixture of a viscoplastic fluid obtained from a kaolin-water dispersion with spherical ceramic particles denser than the fluid. The goal is to mimic the composition of many common granular-fluid materials, such as fresh concrete or debris flow. In these materials, granular and fluid phases have the natural tendency to separate due to particle settling. However, through the shearing caused by the rotation of the drum, a reorganization of the phases is induced, leading to the formation of a granular front. By tuning the particle concentration and the drum velocity, it is possible to control this phenomenon. The setting is reproduced in a numerical environment, where the fluid is solved by a lattice-Boltzmann method, and the particles are explicitly represented using the discrete element method. The simulations confirm the findings of the experiments, and provide insight into the internal mechanisms. Comparing the time scale of particle settling with the one of particle recirculation, a nondimensional number is defined, and is found to be effective in predicting the formation of a granular front.

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