Catenary–pantograph contact force is generally used for assessment of the current collection quality. A good current collection quality not only increases catenary lifetime but also keeps a stable electric supply and helps to avoid accidents. Low contact forces lead to electric arcs that degrade the catenary, and high contact forces generate excessive wear on the sliding surfaces. Railway track operators require track tests to ensure that catenary–pantograph force remains between safe values. However, a direct measure of the contact force requires an instrumented pantograph which is generally costly and complicated. This paper presents a test bench that allows testing virtual catenaries over real pantographs. Therefore, the contact point force behavior can be tested before the track test to guarantee that the test is passed. Moreover, due to its flexibility, the system can be used for model identification and validation, catenary testing, or contact loss simulation. The test bench also explores using computer vision as an additional sensor for each application. Results show that the system has high precision and flexibility in the available tests.

The pantograph-catenary dynamic interaction problem is addressed by Hardware-in-the-Loop (HIL) tests to simulate the dynamic interaction between a numerical model (the catenary) and a physical device (the pantograph). The real-time simulation requires a computationally efficient numerical model and an on time and accurate transference of the response to the pantograph, for which a Periodic Finite Element Model (PFEM) of the catenary is considered. Firstly because of the acceptable computation time required to solve it, makes it suitable for real-time simulations and, secondly, its ability to allow for the delay caused by the transfer of the numerical model response. The catenary PFEM we used considers the non-linear behaviour of the dropper slackening, leading to highly accurate HIL test results, which were validated up to a frequency of 25 Hz.

With the emergence of the fourth technological revolution, smart devices and generative AI have become central to innovation. Universities are not exempt from this shift, as stakeholders urge them to stay up to date with these advancements. This paper examines the current use of generative AI in higher education and gathers stakeholder perspectives, including their expectations, concerns, and aspirations, illustrating its applications with examples and highlighting the benefits for both students and lecturers. Additionally, the study examines the roles that the AI can assume in university courses. Finally, it outlines potential future directions for the development and integration of this technology considering an appropriate balance between the risks and benefits of this new tools. The research began with a literature review to examine existing approaches to generative AI in education and to establish a solid knowledge base. The study concludes that while AI is already present in universities, its primary use remains limited. Within academic programs, lecturers strive to adapt rapidly to the integration of AI while upholding teaching quality. At the same time, students increasingly perceive AI as a valuable resource for personalized learning. However, despite its potential benefits, ethical concerns surrounding its use remain a major issue among stakeholders.

As wind turbine power requirements have evolved from the order of kilowatts (kWs) to the order of several megawatts (MWs), wind turbine components have been subjected to more demanding and critical operating conditions. The wind turbine must cope with higher wind loads due to larger blade sizes, which are also time-varying, and, ultimately, higher power levels. One of the challenges in the manufacture of high-power wind turbines lies in the gearbox and consists of achieving ever-greater power density without compromising efficiency, i.e., greater load capacity with lower weight (and production cost) and reduced power losses. Epicyclic geartrains are used to build the gearbox due to various advantages in relation to conventional gear systems, such as higher feasible gear ratios, higher efficiency, compactnesss, and lower weight. In this paper, several epicyclic geartrains with different structures will be analysed to reveal the influence that certain design parameters have on the size and weight of the gearbox components in the selected model and, therefore, of the gearbox itself. For this purpose, the theoretical model of the gearbox will be planned and the influence of the calculation parameters on the gearbox design will be analyzed following ISO 6336. Special emphasis is placed on the influence of the material used; the modulus and tooth width on the size and weight of the gearbox will be observed. Critical stresses are also calculated. The goal is to prepare the theoretical basis for an optimization process subject to geometric, kinematic, and dynamic constraints that will result in a gearbox as compact, energy-dense, and light as possible without compromising the service life of the components.

Universities play a key role in transforming society, which necessarily leads them to promote the Sustainable Development Goals (SDG) laid down in the UN’s 2030 Agenda. The Escuela Técnica Superior de Ingeniería Industrial (ETSII) of the Universitat Politècnica de València (UPV) is working on a project to design and develop strategies and interventions to include the SDGs in their degree courses. For this, the present paper proposes a map of the industrial subjects in both the BSc in Engineering in Industrial Technologies and the MSc in Industrial Engineering to determine how far the SDGs have been incorporated into these courses. An exhaustive review of the syllabus of the related subjects was carried out, together with a diagnosis of the current status of the SDG concepts so far included. The subsequent analysis of the data identified the possibilities of each subject to develop a sense of responsibility for educating students in the SDGs.