From experimental data,the mechanics relationships describing the behaviour of four different low alloyed steel powders during uniaxial cold compaction

This work aims at determining the constitutive model of four commercial water atomised low alloyed steel powders during cold compaction. Single-action experiments were performed, obtaining cylindrical specimens with different H/D ratios. The distribution of axial and radial stresses was investigated, and the relationships describing both the radial stress transmission coefficient and the flow stress as functions of the relative density were determined. The radial stress transmission coefficient also confirmed the hypothesised value of Poisson’s coefficient. The friction coefficient between the powder column and the die wall was determined, also highlighting the influence of the H/D ratio. Measuring the axial and radial strains due to spring-back, the axial and radial elastic moduli were determined, as functions of the relative density. The results obtained for the four materials were compared, also highlighting both differences and similarities.     

AZ31 magnesium alloy recycling through friction stir extrusion process

Friction Stir Extrusion is a novel technique for direct recycling of metal scrap. In the process, a dedicated tool produces both the heat and the pressure to compact and extrude the original raw material, i.e., machining chip, as a consolidated component. A proper fixture was used to carry out an experimental campaign on Friction Stir Extrusion of AZ31 magnesium alloy. Variable tool rotation and extrusion ratio were considered. Appearance of defects and fractures was related to either too high or too low power input. The extruded rods were investigated both from the metallurgical and mechanical points of view. Tensile strength up to 80 % of the parent material was found for the best combination of process parameters. A peculiar 3D helical material flow was highlighted through metallurgical observation of the specimens.     

Explaining interdependent action delays in multiagent plans execution

In this paper we address the problem of diagnosing the execution of Multiagent Plans with interdependent action delays. To this end, we map our problem to the Model-Based Diagnosis setting, and solve it by devising a novel modeling and reasoning method to infer preferred diagnoses based on partial observation of the start and end times of plan actions. Interestingly, we show that the kind of problem we address can be seen as an extension to the well known disjunctive temporal problem with preferences, augmented with a (qualitative) Bayesian network that models dependencies among action delays. An extensive set of tests performed with a prototype implementation on two different problem domains proves the feasibility of the proposed methodology.     

Beam tests of composite steel-concrete members: A three-dimensional finite element model

Modern construction makes frequent use of composite steel-concrete beams for bridge and building applications. This paper describes a three-dimensional finite element model in which all components forming the composite member are modelled by means of solid elements. The proposed approach is developed using the commercial software Abaqus and is able to model the composite response without requiring information from push-out tests commonly performed to define the constitutive relationship for the shear connectors. All materials are assumed to behave in a nonlinear fashion. Contact between the elements is simulated using surface-to-surface and embedment techniques. The adequacy and accuracy of the proposed modelling approach are validated against experimental results available in the literature on simply-supported and continuous beam tests with both solid and composite slabs.     

Thermodynamic modeling of hydrogen refueling for heavy-duty fuel cell buses and comparison with aggregated real data

The foreseen uptake of hydrogen mobility is a fundamental step towards the decarbonization of the transport sector. Under such premises, both refueling infrastructure and vehicles should be deployed together with improved refueling protocols. Several studies focus on refueling the light-duty vehicles with 10 kg_H2 up to 700 bar, however less known effort is reported for refueling heavy-duty vehicles with 30–40 kg_H2 at 350 bar. The present study illustrates the application of a lumped model to a fuel cell bus tank-to-tank refueling event, tailored upon the real data acquired in the 3Emotion Project. The evolution of the main refueling quantities, such as pressure, temperature, and mass flow, are predicted dynamically throughout the refueling process, as a function of the operating parameters, within the safety limits imposed by SAE J2601/2 technical standard. The results show to refuel the vehicle tank from half to full capacity with an Average Pressure Ramp Rate (APRR) equal to 0.03 MPa/s are needed about 10 min. Furthermore, it is found that the effect of varying the initial vehicle tank pressure is more significant than changing the ambient temperature on the refueling performances. In conclusion, the analysis of the effect of different APRR, from 0.03 to 0.1 MPa/s, indicate that is possible to safely reduce the duration of half-to-full refueling by 62% increasing the APRR value from 0.03 to 0.08 MPa/s.     

A framework for formal analysis and simulative evaluation of security attacks in wireless sensor networks

Journal of Computer Virology and Hacking Techniques - When designing Wireless Sensor Networks it is important to analyze their security risks and provide adequate solutions for protecting them from...     

A methodological approach to fully automated highly accelerated life tests

Microsystem Technologies - Highly accelerated life test (HALT) is a test methodology to evaluate reliability of mechanical and electromechanical devices. HALT is often used on devices that must be...     

Hardware architecture of the Protein Processing Associative Memory and the effects of dimensionality and quantisation on performance

The Protein Processor Associative Memory (PPAM) is a novel hardware architecture for a distributed, decentralised, robust and scalable, bidirectional, hetero-associative memory, that can adapt online to changes in the training data. The PPAM uses the location of data in memory to identify relationships and is therefore fundamentally different from traditional processing methods that tend to use arithmetic operations to perform computation. This paper presents the hardware architecture and details a sample digital logic implementation with an analysis of the implications of using existing techniques for such hardware architectures. It also presents the results of implementing the PPAM for a robotic application that involves learning the forward and inverse kinematics. The results show that, contrary to most other techniques, the PPAM benefits from higher dimensionality of data, and that quantisation intervals are crucial to the performance of the PPAM.     

Molecularly imprinted polymers by phase inversion technique for the selective recognition of saccharides of biomedical interest in aqueous solutions

The purpose of this work was the preparation and characterization of polymeric membranes for the selective recognition of saccharides using molecular imprinting technology associated with phase inversion. A system able to bind saccharides with high selectivity is particularly important in the pharmaceutical sector, since some of these compounds are constituents of molecules which can exert serious toxic effects even at very low concentrations. Two polymeric matrices were prepared using poly(ethylene‐co‐vinyl alcohol) copolymers, with an ethylene molar content of 32% and 44%, and were imprinted with two different saccharide molecules: maltose and 2‐keto‐3‐deoxy‐d ‐manno‐octulosonate (KDO). Matrices imprinted against maltose and KDO showed an easy template extraction, high binding capability and satisfactory selectivity, particularly for the matrix with an ethylene molar content of 44%. © 2017 Society of Chemical Industry     

Conjugation of amino-bioactive glasses with 5-aminofluorescein as probe molecule for the development of pH sensitive stimuli-responsive biomaterials

Bioceramics, such as silica-based glasses, are widely used in bone and teeth restoration. Nowadays, the association between nanotechnology and pharmacology is one of the most promising research fields in cancer therapy. The advanced processing methods and new chemical strategies allow the incorporation of drugs within them or on their functionalized surfaces. Bioceramics can act as local drug delivery systems to treat bone and teeth diseases. The present paper reports data related to the development of a pH-stimuli responsive bioactive glass. The glass conjugation with 5-aminofluorescein (5-AF), through a pH-sensitive organic spacer, allows to produce a pH-responsive bioactive biomaterial: when it is exposed to specific pH changes, it can favour the release of 5-AF directly at the target site. 5-AF has been chosen as a simple, low cost, non toxic model to simulate doxorubicin, an anticancer drug. As doxorubicin, 5-AF contains an amino group in its structure in order to form an amide bond with the carboxylic functionalities of the glass. Raman spectroscopy and thermal analysis confirm the glass conjugation of 5-AF by means of an amide bond; the amount of 5-AF loaded was very high (≈65 and 44 wt%). The release tests at two different pH (4.2 and 7.4) show that the amount of released 5-AF is higher at acid pH with respect to physiological one. This preliminary datum evidenced that a pH-sensitive drug delivery system has been developed. The low amount of 5-AF released (<1 wt% of the total 5-AF) is due to the very low solubility of 5-AF in aqueous medium. This disadvantage, may be overcome in a dynamic environment (physiological conditions), where it is possible to obtain a drug release system ensuring an effective therapeutic dose for long times and, at the same time, avoiding the drug toxicity.