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.     

Effect of crystal habit and superstructure on modulus of elasticity of isotactic polypropylene by AFM nanoindentation

In this study the effects of crystal habit, crystallinity and superstructure on the modulus of elasticity of isotactic polypropylene films were analyzed by atomic force microscope (AFM) nanoindentation. The modulus of elasticity, evaluated on the nanometer scale by AFM, showed a qualitatively similar dependence on the crystal habit, crystallinity and superstructure as the modulus of elasticity measured by dynamic-mechanical analysis and tensile testing. The observed values of both the surface stiffness measured by AFM and the macroscopic/bulk stiffness were distinctly larger in the presence of non-isometric lamellae organized in spherulite than in the presence of isometric nodular crystals, not organized in a spherulitic superstructure. The experimental data showed that the modulus of elasticity is not primarily influenced by the presence or absence of spherulite but by the molecular-deformation constraint associated to the crystal habit.     

A method for the determination of turbulence intensity by means of a fast response pressure probe and its application in a LP turbine

This paper describes the measurements and the post-processing procedure adopted for the determination of the turbulence intensity in a low pressure turbine (LPT) by means of a single sensor fast response aerodynamic pressure probe. The rig was designed in cooperation with MTU Aero Engines and considerable efforts were put into the adjustment of all relevant model parameters. Blade count ratio, airfoil aspect ratio, reduced massflow, reduced speed, inlet turbulence intensity and Reynolds numbers were chosen to reproduce the full scale LP turbine. Measurements were performed adopting a phase-locked acquisition technique in order to provide the time resolved flow field downstream of the turbine rotor. The total pressure random fluctuations are obtained by selectively filtering, in the frequency domain, the deterministic unsteadiness due to the rotor blades and coherent structures. The turbulence intensity is derived from the inverse Fourier transform and the correlations between total pressure and velocity fluctuations. The determination of the turbulence intensity allows the discussion of the interaction processes between the stator and rotor for engine-representative operating conditions of the turbine.     

Linear optimal control strategies for production systems with a discrete-event demand pattern

A class of production systems are considered in this paper with the aim of determining closed-loop strategies providing the production effort as functions of the system state. The key feature of the considered class of systems is that the demand and the way it is satisfied are asynchronous sequences of part requests and instantaneous withdrawals, respectively, generated by discrete-event processes, whereas the production process has continuous-time dynamics. The optimization problem, whose objective is to minimize inventory and lateness costs, is restated as an optimal control problem by exploiting some structural properties of the optimal solution. Then, optimal closed-loop strategies are found with dynamic programming techniques.     

A framework for home energy management and its experimental validation

With the Smart Grid revolution and the increasing interest in renewable energy sources, the management of the electricity consumption and production of individual households and small residential communities is becoming an essential element of new power systems. The electric energy chain can greatly benefit from a flexible interaction with end-users based on the optimization of load profiles and the exploitation of local generation and energy storage. This paper proposes a framework for the development of a complete energy management system for individual residential units and small communities of domestic users, taking into account both the power system and the final users’ perspectives. All the main elements of the framework are considered, and contributions are provided on the users’ habits profiling, electricity generation forecast, energy load, and storage optimization. Specifically, we propose a linear regression model to predict the photovoltaic panels production, a stochastic method to forecast the home appliances usage, and two optimization models to optimize the electricity management of residential users with the goal of minimizing their bills. The study shows that it is possible to reduce the energy bill of residential users through the electricity optimization driven by dynamic energy prices. Moreover, remarkable improvements of the electric grid efficiency can be achieved with the cooperation among users, confirming that services for the coordination of the demand of groups of users allow huge benefits on the power system performance.