Diffusion wearTi555.3 alloy Ti6Al4V alloy a b s t r a c t Near-beta titanium alloys like Ti555.3 are increasingly being used in aeronautics replacing in some critical applications the most common Ti6Al4V. However, these near-beta titanium alloys have a poor machinability rating which needs to be overcome so as to maintain at least the same productivity levels as in Ti6Al4V.This paper presents the machinability results carried out for Ti555.3 compared with the commonly used Ti6Al4V. The aim of this research work is to understand tool wear mechanisms when machining Ti555.3. Analysis of variables such as cutting forces, chip geometry and tool wear shows that: (I) greater difficulty is encounterd when machining Ti555.3 alloy compared with Ti6Al4V alloy which can be machined at higher speeds up to 90 m min −1 ; (II) there was a correlation between the mechanical properties of work material, tool wear, and component forces; (III) the occurrence of the diffusion process leads to the formation of a layer of adhered material composed of Ti and TiC on the tool's rake face for both Ti alloys.

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Orthogonal cutting force measurements and single-point tool life tests were conducted in order to analyze the sensitivity to heat treatment on the machinability of three titanium alloys: Ti6Al4V, Ti-5Al-4V-0.6Mo-0.4Fe (TIMETAL 1 54M), and Ti6246. The Ti6246 alloy showed the highest tool wear rates and the higher cutting forces in all the heat treatment conditions which could be related to its higher mechanical properties. TIMETAL 1 54M alloy, a newly developed alloy with similar mechanical properties to the more commonly used Ti6Al4V, showed the lowest wear rates. Microstructural changes due to heat treatment have some influence in the machinability of the alloys. The b annealed samples of the Ti6Al4V and TIMETAL 1 54M alloys, with a very coarse lamellar microstructure, showed considerably shorter tool life and higher cutting forces. The rest of the heat treatments showed no significant influence in the machining behavior of the analyzed alloys as they do not cause important microstructural changes.

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Considering the increasing integration of renewable energies into the power grid, batteries are expected to play a key role in the challenge of compensating the stochastic and intermittent nature of these energy sources. Besides, the deployment of batteries can increase the benefits of a renewable power plant. One way to increase the profits with batteries studied in this paper is performing energy arbitrage. This strategy is based on storing energy at low electricity price moments and selling it when electricity price is high. In this paper, a hybrid renewable energy system consisting of wind and solar power with batteries is studied, and an optimization process is conducted in order to maximize the benefits regarding the dayahead production scheduling of the plant. A multi-objective cost function is proposed, which, on the one hand, maximizes the obtained profit, and, on the other hand, reduces the loss of value of the battery. A particle swarm optimization algorithm is developed and fitted in order to solve this non-linear multi-objective function. With the aim of analyzing the importance of considering both the energy efficiency of the battery and its loss of value, two more simplified cost functions are proposed. Results show the importance of including the energy efficiency in the cost function to optimize. Besides, it is proven that the battery lifetime increases substantially by using the multi-objective cost function, whereas the profitability is similar to the one obtained in case the loss of value is not considered. Finally, due to the small difference in price among hours in the analyzed Iberian electricity market, it is observed that low profits can be provided to the plant by using batteries just for arbitrage purposes in the day-ahead market.