Methodology for Detecting Progressive Damage in Structures Using Ultrasound-Guided Waves.

Damage detection in structural health monitoring of metallic or composite structures depends on several factors, including the sensor technology and the type of defect that is under the spotlight. Commercial devices generally used to obtain these data neither allow for their installation on board nor permit their scalability when several structures or sensors need to be monitored. This paper introduces self-developed equipment designed to create ultrasonic guided waves and a methodology for the detection of progressive damage, such as corrosion damage in aircraft structures, i.e., algorithms for monitoring such damage. To create slowly changing conditions, aluminum- and carbon-reinforced polymer plates were placed together with seawater to speed up the corrosion process. The setup was completed by an array of 10 piezoelectric transducers driven and sensed by a structural health monitoring ultrasonic system, which generated 100 waveforms per test. The hardware was able to pre-process the raw acquisition to minimize the transmitted data. The experiment was conducted over eight weeks. Three different processing stages were followed to extract information on the degree of corrosion: hardware algorithm, pattern matching, and pattern recognition. The proposed methodology allows for the detection of trends in the progressive degradation of structures.

Study to find out the perception that first year students in engineering have about the Computational Thinking skills, and to identify possible factors related to the ability of Abstraction.

Since the end of the 20th century, the digitalization of society, including the educational systems, has been growing exponentially. At the same time, education systems have been evolving towards competency-based assessment. Likewise, at the beginning of this century, the idea of Computational Thinking was resurrected by J. Wing, for solving problems and designing systems using concepts of computer science. Today, we can see how all these questions are taking shape in a new competence, called Computational Thinking, related to others that already exist. In this paper, we have studied the skills of Computational Thinking in university students, focusing on abstraction and its possible relationship with other factors. Results conclude that the students fail in relation to abstraction and in algorithmic thinking. Although the ability of abstraction is not easy to measure, a linear regression analysis has been carried out in order to determine its possible study.

Skills in computational thinking of engineering students of the first school year.

In this world of the digital era, in which we are living, one of the fundamental competences that students must acquire is the competence in Computational Thinking (CT). Although there is no general consensus on a formal definition, there is a general understanding of it as a set of skills and attitudes necessary for the resolution, with or without a computer, of problems that may arise in any area of life. Measuring and evaluating which of the CT skills students have acquired is fundamental, and for this purpose, previously validated measuring instruments must be used. In this study, a previously validated instrument is applied to know if the new students in the Engineering Degrees of the University of the Basque Country have the following skills in CT: Critical Thinking, Algorithmic Thinking, Problem Solving, Cooperativity and Creativity.