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The researchers Siddharth Pitta, Jose I. Rojas, Francesc Roure, Daniel Crespo, and Magd Abdel Wahab, from the Group of Materials Characterization of the UPC, the Materials Strength Laboratory of the UPC, and the Ghent University, have made new progresses in the characterization of the fatigue response of aircraft repair patches made of carbon fiber reinforced epoxy (CFRE) and aluminum alloy on aircraft airframe substrates made as well of CFRE and aluminum alloy

Researchers Y. J. Duan, E. Pineda and D. Crespo, from the Group of Materials Characterization of the UPC, have made new progress to understand the mechanical properties of high-entropy metallic glasses. The work clarifies the correlation between the fraction of liquid-like zones, i.e. the fraction of atoms that can easily rearrange under the effect of external forces, and the secondary or β relaxation observed in these materials. Besides, the work reveals the high-entropy effect on the supercooled liquid dynamics of the metallic melt.

Nikolai Kvashin defended his thesis co-directed by Napoleón Anento and Dmitry Terentyev on 16th of November 2022 at Campus Nord. Titled “Atomistic Study of Slip Transfer in BCC Metals “, the thesis presents an atomistic computer simulation study on the interaction between dislocations (single and pile-up cases) and a set of grain boundaries with the purpose to investigate the role played by the grain boundary atomic structure

Xiao Liu defended his thesis co-supervised by Jaume Sanz Subirana and Adria Rovira Garcia on November 10th 2022 at Campus Nord. Entitled "Contributions to High Accuracy Snapshot GNSS Positioning", the thesis presents a novel method for high accuracy GNSS positioning using only a very short interval of the GNSS satellite signal.

Max Casamor defended his thesis co-supervised by professors Jordi Freixa and Francesc Reventós on October 10 at the Escola Técnica Superior d'Engineria Industrial de Barcelona. Entitled "Evaluation of TH Multi-Scale Coupling Methods in BEPU Analysis", the thesis presents the application of advanced methodologies in safety analysis for nuclear reactors.

Manuel Mateos Villar defended his doctoral thesis, with industrial doctorate mention, co-supervised by Xavier Prats (UPC) and Oliva Garcia (Nommon Solutions and Technologies), entitled "Machine Learning for Aircraft Trajectory Prediction: a Solution for Pre-tactical Air Traffic Flow Management". The thesis presents a solution for traffic prediction in the pre-tactical phase that improves the predictive exercise of the current tool (PREDICT) and is able to deal with the entire set of flights in the ECAC network in a way computationally efficient. To do this, different trajectory prediction approaches based on machine learning models trained on historical data have been explored.