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In this article, the Resource Constrained Clustered Shortest Path Tree Problem is defined. It generalizes the classic Resource Constrained Shortest Path Tree Problem since it is defined on an undirected, complete and weighted graph whose set of nodes is partitioned into clusters. The aim is then to find a shortest path tree respecting some resource consumption constraints and inducing a connected subgraph within each cluster. The main support and motivation for studying this problem are related, among the others, to the design of telecommunication networks, and to Disaster Operations Management. In this work, we present a path-based formulation for the problem, addressing the case of local resource constraints, that is, resource constraints on single paths. For its resolution, a Branch&Price algorithm featuring a Column Generation approach with Multiple Pricing Scheme is devised. A comprehensive computational study is conducted, comparing the proposed method with the results achieved by the CPLEX solver, adopted to solve the mathematical model. The numerical results underline that the Branch&Price algorithm outperforms CPLEX, both in terms of solution cost and time.

Damage detection and assessment are key objectives of structural health monitoring. Inspections timing and results accuracy represent crucial aspects to properly assess the integrity of a structural system over time. The goal of this work consists in the development of an automated damage classification methodology based on machine learning, that is able to process sampled measurements of the dynamic structural response as input and provide a quantitative health assessment of the structure as output. The methodology is validated on a broad set of examples, including both numerical simulations and data recorded on real structures, evidencing high accuracy across all instances. Moreover, the computational experiments show consistency in the assessment of location and severity of the damages even in presence of additive white Gaussian noise.

The paper deals with the effect of pressure, temperature and time on corrosion rate of pipeline steels in CO2saturated water and in humid saturated CO2 gas in the range from 25 to 60°C and pressure from 20 to 145 bar,up to 400 hours of exposure. The results of weight loss tests show very high rates in the aqueous phase, oneor two order of magnitude higher than the values obtained in CO2 saturated with water, but remaining in anycase much lower than values extrapolated by De Waard and Milliams model at high partial pressure. Dependingon temperature and pressure, cementite and iron carbonate scales can grow on metallic surface reducingcorrosion rate. SEM and metallographic analysis evidenced the evolution of scale from defective cementitebasedlayer to protective compact carbonate scale.