size effect on fracture toughness of snow

Abstract: Depending on the scale of observation, many engineered and natural materials show different mechanical behaviour. Thus, size effect theories, based on a multiscale approach, analyse the intrinsic (due to microstructural constraints, e.g., grain size) and extrinsic effects (caused by dimensional constraints), in order to improve the knowledge in materials science and applied mechanics. Nevertheless, several problems regarding Solid Mechanics and Materials Science cannot be solved by conventional approaches, because of the complexity and uncertainty of materials proprieties, especially at different scales. For this reason, a simple model, capable of predicting a fracture toughness at different scale, has been developed and presented in this paper. This model is based on the Golden Ratio, which was firstly defined by Euclide as: "A straight line is said to have been cut in extreme and mean ratio when, as the whole line is to the greater segment, so is the greater to the less". Intimately interconnected with the Fibonacci sequence (1, 2, 3, 5, 8, 13, …), this number controls growth in Nature and recurs in many disciplines, such as art, architecture, design, medicine, etc.., and for man-made and natural brittle materials, the Golden Ratio permits to define the relationship between the average crack spacing and the thickness of quasi-brittle materials. In these cases, the theoretical results provided by the Golden Ratio, used to calibrate a size-effect law of fracture toughness, are in accordance with the experimental measurements taken in several test campaigns carried on different materials (i.e., rocks, ice, and concrete). This paper presents the case of fracture toughness of snow, in which the irrational number 1.61803 recurs when the geometrical dimensions vary. This aspect is confirmed by the results of experimental campaigns performed on snow samples. Thus, we reveals the existence of the size-effect law of fracture toughness of snow and we argue that the centrality of the Golden Ratio in the fracture properties of quasi-brittle materials. Consequently, by means of the proposed model, the Kic of large samples can be simply and rapidly predicted, without knowing the material performances but by testing prototypes of the lower dimensions

Fiber volume fraction and ductility index in fiber-reinforced concrete round determined panels

Abstract Due to the high scatter affecting the post-cracking response of Fiber-Reinforced Concrete Beams (FRC-B) in bending, new Fiber-Reinforced Concrete Round Determined Panels (FRC-RDP) are tested. Accordingly, the introduction of a model to predict the flexural response of FRC-RDP is of practical interest. Similarly to FRC-B, the response of centrally loaded FRC-RDP can be described by the Ductility Index ( DI ), which defines the deflection-softening or the deflection-hardening behavior. Since DI is proportional to the difference between ultimate and effective cracking loads, the brittle/ductile transition corresponds to DI equal to zero. Moreover, a linear increment of DI with the amount of fibers can be theoretically and experimentally found for both beams and panels. Through this general relationship, the minimum amount of fibers for ductile response can be determined

Object segmentation in depth maps with one user click and a synthetically trained fully convolutional network

With more and more household objects built on planned obsolescence and consumed by a fast-growing population, hazardous waste recycling has become a critical challenge. Given the large variability of household waste, current recycling platforms mostly rely on human operators to analyze the scene, typically composed of many object instances piled up in bulk. Helping them by robotizing the unitary extraction is a key challenge to speed up this tedious process. Whereas supervised deep learning has proven very efficient for such object-level scene understanding, e.g., generic object detection and segmentation in everyday scenes, it however requires large sets of per-pixel labeled images, that are hardly available for numerous application contexts, including industrial robotics. We thus propose a step towards a practical interactive application for generating an object-oriented robotic grasp, requiring as inputs only one depth map of the scene and one user click on the next object to extract. More precisely, we address in this paper the middle issue of object seg-mentation in top views of piles of bulk objects given a pixel location, namely seed, provided interactively by a human operator. We propose a twofold framework for generating edge-driven instance segments. First, we repurpose a state-of-the-art fully convolutional object contour detector for seed-based instance segmentation by introducing the notion of edge-mask duality with a novel patch-free and contour-oriented loss function. Second, we train one model using only synthetic scenes, instead of manually labeled training data. Our experimental results show that considering edge-mask duality for training an encoder-decoder network, as we suggest, outperforms a state-of-the-art patch-based network in the present application context.Comment: This is a pre-print of an article published in Human Friendly Robotics, 10th International Workshop, Springer Proceedings in Advanced Robotics, vol 7. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-89327-3\_16, Springer Proceedings in Advanced Robotics, Siciliano Bruno, Khatib Oussama, In press, Human Friendly Robotics, 10th International Workshop,

Parking Policy and Urban Mobility Level of Service – System Dynamics as a Modelling Tool for Decision Making

Parking policy is still the most directly available instrument for managing traffic demand in many cities. But policy design is subject to difficulties resulting from the complexity of the urban mobility system. This article presents a model framework, based on a system dynamics approach, aimed at assessing the effectiveness of parking policy and quantitatively identifying optimal design at an aggregate spatial level under a level of service maximization objective. An application to a city is developed and the results are discussed in view of their qualitative outcomes and quantitative validity and robustness. It is argued that system dynamics addresses several needs of modellers and decision makers regarding urban parking policy assessment, particularly if parking is used as a traffic management tool. The qualitative results of the model coincide with the prescriptions that would come from the economic theory, even with an objective function based on level of service instead of a broader indicator of efficiency. At the quantitative level, the validation testing of the model application with the available data provided positive indications and no case to reject that a quantitative accurateness useful for policy prescription could be attained provided that some data gaps are fulfilled. The necessary data for calibration seems to be possible to obtain by feasible local empirical observations

Sismabeton: a new frontier for ductile concrete

The high ductility of Fiber Reinforced Self-consolidating concrete (called Sismabeton) can be developed not only in tension but also in compression. This aspect is evidenced in the present paper by measuring the mechanical response of normal concrete (NC), plain self-compacting concrete (SC) and Sismabeton cylindrical specimens under uniaxial and triaxial compression. The post-peak behaviour of these specimens is defined by a non-dimensional function that relates the inelastic displacement and the relative stress during softening. Both for NC and SC, the increase of the fracture toughness with the confinement stress is observed. Conversely, Sismabeton shows, even in absence of confinement, practically the same ductility measured in normal and self-compacting concretes with a confining pressure. Thus, the presence of Sismabeton in compressed columns is itself sufficient to create a sort of active distributed confinement

Eulerian and Lagrangian time scales of the turbulence above staggered arrays of cubical obstacles

We present results from water-channel experiments on neutrally-stable turbulent flows over staggered arrays of cubical obstacles modelling idealised urban canopies. Attention is concentrated on the vertical profiles of the Eulerian (TE) and Lagrangian (TL) time scales of the turbulence above three canopies with different plan area fractions (λP = 0.1, 0.25 and 0.4). The results show that both the streamwise and vertical components of TL increase approximately linearly with height above the obstacles, supporting Raupach’s linear law. The comparisons with the Lagrangian time scales over canyon-type canopies in the skimming flow and wake interference regimes show that the staggered configuration of cubical obstacles increases the streamwise TL, while decreasing its vertical counterpart. A good agreement has also been found between the eddy viscosities (KT) estimated by applying Taylor’s theory and the classical first order closure relating the momentum flux to the velocity gradient. The results show that KT obeys Prandtl’s theory, particularly for λP = 0.25 and 0.4

Successful inoculation of Artemia and production of cysts in man-made salterns in the Philippines

The authors report on inoculation experiments of Artemia nauplii and young adults of the San Francisco Bay strains in earthen fish ponds. The test inoculated proved successful where water salinity ranges from 20 to 32 o/oo during the start of the rainy season in the Philippines

A Soft Tactile Sensor Based on Magnetics and Hybrid Flexible-Rigid Electronics

Tactile sensing is crucial for robots to manipulate objects successfully. However, integrating tactile sensors into robotic hands is still challenging, mainly due to the need to cover small multi-curved surfaces with several components that must be miniaturized. In this paper, we report the design of a novel magnetic-based tactile sensor to be integrated into the robotic hand of the humanoid robot Vizzy. We designed and fabricated a flexible 4 × 2 matrix of Si chips of magnetoresistive spin valve sensors that, coupled with a single small magnet, can measure contact forces from 0.1 to 5 N on multiple locations over the surface of a robotic fingertip; this design is innovative with respect to previous works in the literature, and it is made possible by careful engineering and miniaturization of the custom-made electronic components that we employ. In addition, we characterize the behavior of the sensor through a COMSOL simulation, which can be used to generate optimized designs for sensors with different geometries