University of Salento (Unisalento)
From law to science, economics to engineering, humanities to media studies, provides academic pathways to a range of professions as well as post-graduate and specialist courses. Open and reliant on international cooperation, the Dept. of Engineering for Innovation (DefI) offers several education and exchange opportunities for study, traineeship and research, in virtual and blended modality. DEfI research and labs cover the following fields:
Renewable Energies, Materials Science & Technologies, ICTs, Internet of Things, High- Performance Computing, Virtual & Augmented Reality, Nanotechnologies, Automation & Robotics, Machine Processing Systems & Technologies, Mechanical & Aerospace Design, Intelligent & Clean Manufacturing Technologies, Management Engineering, Design and Testing in Mechanical & Civil Engineering, Fluid Dynamics & Machinery, Bio-applications.
HEALTH MONITORING AND FLEET MANGEMENT
The research activities focus on the service support process. The information obtained through Health Monitoring and Fleet Mangement activities will be used together with data from logistical data (lead time supplies and repair work), engineering data (modifications and manuals) to develop a maintenance strategy that has the least impact on fleet operation, reduce supply lead times, and optimize warehouse management. A new methodology approach to the process of maintenance outside the factory is intended to provide operators who are directly involved in the maintenance process, new Internet-based tools for Internet Things, with the aim of maximizing the efficiency of the systems and make full use of the information available in the different areas of the manufacturing process.
HYBRID-ELECTRIC PROPULSION TECHNOLOGIES
Hybrid-electric propulsion technologies for different applications, particularly for new integrated concepts for general aviation, immune system control systems based on distributed architectures, systems based on distributed architectures, multi-core controllers, propulsion system sensors for weight reduction, increased security, and the implementation of advanced diagnostic and prognostic capabilities. The development of all these solutions requires the definition of electric machines and the resolution of integration issues with thermal motors, with distribution lines, gearboxes for motor and generator connection, design of engine architectures adapted the use of the electrical system and the simulation and evaluation of the implementations of integrated systems during the mission with the use of developed software tools and models.
INTELLIGENT AUTONOMOUS SPACE DEBRIS REMOVAL BASED ON HIGHLY EXPANDABLE, TOUGH, STICKY, BIO-INSPIRED UNDERACTUATED STRUCTURES
The research project aims at finding nature-inspired passive/active underactuated structures, and their capturing/ removal maneuver control algorithms, to mitigate the proliferation of space debris. Space debris poses many threats to human safety and infrastructure, both in space and on ground, ranging from space weather and Near Earth Objects to threats from uncontrolled objects and fragments thereof. This project tackles some of the aspects of this issue by developing novel AI-controlled strategies and nature-inspired highlycompliant tacky (strongly adhesive) structures for the on-flight capturing and removal of multiscale space debris. Keywords: space debris removal, AI, bio-inspired adhesion, tribology, space debris mechanics.
The lifetime and performance of vaporizing liquid microthrusters (VLMs) are dramatically reduced by the occurrence of flow boiling instabilities. Our project concerns with the development of a sensed VLM equipped with actively controlled heating characterized by:
- decoupling of liquid vaporization from gas superheating using two heating steps, enabling for Isp maximization with device temperature reduction.
- Fast pulsed actively controlled heating to maximize the thermal efficiency and stabilize the boiling flow. This control is based on inchannel heaters and sensors (temperature, void fraction), real-time management electronics, and control algorithms built on machine learning techniques. Further performance enhancement will be achieved via the optimization study of channel geometries, in combination with the assessment of alternative green propellants.
Via per Arnesano
73100, Lecce (LE), Italy
Head of the Dept. of Engineering for Innovation