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The characterization and reproduction of tyre behaviour for vehicle modelling is a topic of particular interest both for real-time driver in the loop simulations and for offline performance optimization algorithms. Since the accuracy of the tyre forces and moments can be achieved by the accurate physical modelling of all the phenomena concerning the tyre-road interaction, the link between the tyre thermal state and the tyre frictional performance turns into a crucial factor. An integrated numerical methodology, allowing to couple the full 3D CFD (Computational Fluid Dynamics) flux within the internal chamber of the tyre with an equivalent discrete 3D structure model, is proposed with the aim to completely represent the tyre thermodynamic convective behaviour in the steady-state operating conditions. 3D CFD model enables the evaluation of the internal distribution of the gas temperature and of the thermal powers exchanged at each sub-wall in detail. This allows to increase the reliability of the tyre thermodynamic modelling with a particular reference to the proper managing of the aero-thermal flow of the brake disc impact on the rim temperature and therefore on the internal gas dynamics in terms of temperature and pressure, being able to optimize the tyre overall dynamic performance in both warm-up and stabilized thermal conditions. The steady RANS (Reynolds Averaged Navier–Stokes) simulations have been performed employing the 3D CFD model in a wide range of angular velocities with the aim to calculate the convective thermal flux distributions upon rim and inner liner surfaces. The simulation results have been then exploited to derive the convective heat transfer coefficients per each sub domain to be employed within the real-time tyre physical thermal model, with the peculiar advantage of an enhanced model reliability for thermal characteristics. To validate the proposed methodology, the tyre thermal model outputs, in terms of temperatures of internal and external layers, have been validated towards the acquired ones within the specific routine performed on tyre force and moment test bench, confirming an excellent agreement with the experimental data in the entire range of operating conditions explored.

The recent remarkable increase in air passenger traffic has been fostering a considerable congestion of the airport facilities. In this context, traditional procedures employed for check-in operations have been supported by alternative methods, based on the use of self-service options (kiosks, web services, app for mobile phones, etc). However, even if such innovations are contributing to improve the service level provided to passengers, field investigations suggest that traditional procedures will be employed also in the future, especially for medium and long-haul flights, where baggage dropping is required. For this reason, the passengers allocation problem at check-in counters is attracting growing attention by the scientific community and several decision support tools, involving both optimization and simulation methods, have been proposed. Most of the available approaches aim at deciding the optimal number of check-in counters to be activated, in such a way to balance the operative costs and passengers waiting times. Such approaches assume that the service capacity (in terms of available check-in operators and counters) is given and determined on the basis of physical constraints (related to the available space in the terminal) and of staff scheduling decisions made at a tactical level. The present contribution tries to overcome this limitation, by proposing a decision support system, based on a mathematical model, capable of designing optimal check-in policies by also incorporating staff scheduling decisions. The model is tested on some real-world case studies; computational results are evaluated, along with the practical usability of the approach.

Innovation in railway industry points the focus on the production of lightweight vehicles, with high performance, in order to save the energy power and to satisfy the environmental and safety requests. To pursue this aim, innovative materials have been increasingly used for vehicle components and structures. In this paper, the structural behavior of the shock absorber mountings (SAMs) of a novel metro rail vehicle end (RVE) has been analyzed. The innovative RVE integrates aerodynamic, structural and crash functionalities in a single lightweight component. Numerical and experimental activities on a SAM prototype have been performed to validate the innovative component. Both numerical and experimental results underline that the final configuration of the SAM exhibits adequate strength and stiffness under prescribed load.

In this work, we present a mathematical model to support location decisions oriented to rationalize facility systems in non-competitive contexts. In order to test the model, computational results are shown and an application to a real-world case study, concerning the Higher Education system in an Italian region, is discussed.

In recent years, across Europe, the economic crisis has resulted in an increased pressure on education systems. Notably, Italy has been one of the countries that has experienced the most severe reduction in public expenditure in the education sector. In the described conditions, Italian governmental institutions have started to perform rationalisation actions, aimed at modifying the current configuration of the existing facilities offering educational services (either by entirely closing and merging some of them, or by downsizing or transferring capacities), in order to increase the affordability of the system while still providing a required minimum service level. These strategic choices may have a lasting impact; therefore, there is a need for appropriate decision support tools capable of assisting planners. For this reason, after a description of the context and a review of the current literature, this paper presents two novel mathematical models for addressing rationalisation decisions in the Italian education system. The usability of such models is tested by means of real-world case studies, offering interesting insights.