This paper investigates the use of a controlled tethered wing, or kite, for naval transportation. Linked to a boat by light composite-fiber lines, the kite is able to fly between 200 and 600 m above the sea and to generate high traction forces. A mechatronic system named Kite Steering Unit (KSU) that is installed on the boat controls the kite and converts the line speed and force into electricity. Different from previous works, the boat is also equipped with electric propellers so that naval propulsion can be achieved both directly, i.e., through the towing forces exerted by the lines, and indirectly, i.e., through the electricity generated by the KSU that is fed to the electric propellers via a battery pack. The optimal system operating conditions that maximize the boat speed for the given wind characteristics are computed. Then, a model predictive controller is designed, and numerical simulations with a realistic model are carried out to assess the performance of the control system against the optimal operating conditions. The results indicate that, with this system, a completely green naval transportation system can be obtained, regardless of the wind direction.

Resistance spot welding (RSW) is considered a preferred technique for joining metal parts in various industries, mainly for its efficiency and cost-effectiveness. The mechanical properties of spot welds are pivotal in ensuring structural integrity and overall assembly performance. In this work, the quality attributes of resistance spot welding, such as both nugget and corona bond sizes, are assessed by analyzing the thermal behavior of the joint using a physical information neural network (PINN). Starting from the thermal signal phase gradient and amplitude gradient maps, a convolutional neural network (CNN) estimates the size of nuggets and corona bonds. The CNN architecture is based on the Inception V3 architecture, a state-of-the-art neural network that excels in image recognition tasks. This study suggests adopting a new methodology for automatic RSW quality control based on thermal signal analysis.

Performance and functionality are two key factors in designing advanced components. One promising approach in manufacturing design is the fabrication of multi-material structures by joining dissimilar materials. Steels, known for their outstanding properties and cost-effective production, are widely used across several industries. However, their high density presents challenges when designing lightweight components. A solution lies in combining steels with lightweight, non-ferrous alloys to develop cost-effective multi-material parts. However, joining different materials is generally complex due to their different properties, making it sometimes challenging or even unfeasible. Resistance element welding (REW) offers a high-performance alternative to traditional methods, such as resistance spot welding, with a high potential in mass production industries like automotive manufacturing. This article comprehensively reviews the latest research on REW for dissimilar joining of steels and non-ferrous alloys. It focuses on the microstructural and mechanical properties of joints, innovations in the REW process, the influence of process parameters on joint quality, as well as simulation and numerical studies. In addition, REW is compared with traditional joining methods.

This project aims to implement a Remote European Asian Lab, an Automatic Control remote laboratory, in the joint academic cooperation framework between two universities located in Europe and Central Asia. Emphasis is given to the inclusive solution of a shared teaching facility and its learning achievements into a bachelor course (Uzbekistan) and a master course (Italy) to foresee a better education quality. The different cultural and social contexts allow (a) the evaluation of the effect obtained by introducing a remote laboratory experience in a course entirely theoretical, and (b) the shift from a physical laboratories experience to a remote one. Students are first introduced to this laboratory by the lecturer in dedicated classes. Then students can independently access it 24/7 by simply booking a specific station for a time slot. From the analysis comes out that remote laboratory experiences positively impact learning achievements. The benefits of the remote environment are perfectly comparable with the ones obtained from the physical laboratory activities.