Optimization of an innovative T6 heat treatment for the AlSi10Mg alloy processed by Laser-based Powder Bed Fusion: effect on microstructure, mechanical properties, and tribological behavior

Laser-based Powder Bed Fusion (L-PBF) technology is one of the most commonly used metal Additive Manufacturing (AM) techniques to produce highly customized and value-added parts. The AlSi10Mg alloy has received more attention in the L-PBF process due to its good printability, high strength/weight ratio, corrosion resistance, and relatively low cost. However, a deep understanding of the effect of heat treatments on this alloy's metastable microstructure is still required for developing tailored heat treatments for the L-PBF AlSi10Mg alloy to overcome the limits of the as-built condition. Several authors have already investigated the effects of conventional heat treatment on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy but often overlooked the peculiarities of the starting supersatured and ultrafine microstructure induced by rapid solidification. For this reason, the effects of innovative T6 heat treatment (T6R) on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy were assessed. The short solution soaking time (10 min) and the relatively low temperature (510 °C) reduced the typical porosity growth at high temperatures and led to a homogeneous distribution of fine globular Si particles in the Al matrix. In addition, it increased the amount of Mg and Si in the solid solution available for precipitation hardening during the aging step. The mechanical (at room temperature and 200 °C) and tribological properties of the T6R alloy were evaluated and compared with other solutions, especially with an optimized direct-aged alloy (T5 alloy). Results showed that the innovative T6R alloy exhibits the best mechanical trade-off between strength and ductility, the highest fatigue strength among the analyzed conditions, and interesting tribological behavior. Furthermore, the high-temperature mechanical performances of the heat-treated L-PBF AlSi10Mg alloy make it suitable for structural components operating in mild service conditions at 200 °C.

Adjustable robust optimization with nonlinear recourses

Over the last century, mathematical optimization has become a prominent tool for decision making. Its systematic application in practical fields such as economics, logistics or defense led to the development of algorithmic methods with ever increasing efficiency. Indeed, for a variety of real-world problems, finding an optimal decision among a set of (implicitly or explicitly) predefined alternatives has become conceivable in reasonable time. In the last decades, however, the research community raised more and more attention to the role of uncertainty in the optimization process. In particular, one may question the notion of optimality, and even feasibility, when studying decision problems with unknown or imprecise input parameters. This concern is even more critical in a world becoming more and more complex —by which we intend, interconnected —where each individual variation inside a system inevitably causes other variations in the system itself. In this dissertation, we study a class of optimization problems which suffer from imprecise input data and feature a two-stage decision process, i.e., where decisions are made in a sequential order —called stages —and where unknown parameters are revealed throughout the stages. The applications of such problems are plethora in practical fields such as, e.g., facility location problems with uncertain demands, transportation problems with uncertain costs or scheduling under uncertain processing times. The uncertainty is dealt with a robust optimization (RO) viewpoint (also known as "worst-case perspective") and we present original contributions to the RO literature on both the theoretical and practical side.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.