- Finite Elements and Numerical Linear Algebra for PDE constrained Optimization in Fluid-Dynamics applications. Visiting Scientist: John W. Pearson, Department of Maths, University of Edinburgh (UK).
The research/educational collaboration project focuses on aspects of the solution of PDEs and optimization problems for realistic fluid dynamics and infiltration problems in porous media. Seminars on the discretization of PDEs for fluid dynamics problems and seminars on constrained optimization problems with PDE constraints arising from environmental engineering problems are planned. In addition to research in the field of mathematical-numerical modeling, the topics potentially affected by the project refer to problems of subsurface flow, rock and soil mechanics and the sectors of environmental engineering. In the SEI project, the collaboration focuses on the Smart Data line, with the development of computational tools for advanced numerical simulations. The project is oriented to the PhD course and students of the LM course in Mathematical Engineering.
- Early Warning Systems for Vector- and Water-borne Diseases. Visiting scientist: William Pan, Duke University (USA).
The collaborative research/teaching project focuses on the issues related to the use of ground-based epidemiological data together with remote sensing data (Synthetic aperture radar / SAR) for the prediction and monitoring of epidemics of diseases regulated by the availability of water, such as malaria, dengue and enteric diseases. The initiative will consist of a series of seminars and, subsequently, a workshop for the construction of a mathematical model that, using daily community-level disease surveillance combined with Sentinel-1 SAR data, can allow to monitor and estimate in advance the number of infected people in countries trying to eliminate malaria and other water-sensitive diseases. In the SEI project, the collaboration focuses on the Smart Lab line. The activity is of interest mainly to students of the LM in WGRE and Environmental Engineering, but also to PhD students interested in water-related topics.
- Smart and Sustainable Engineering Structures. Visiting scientist: Vanesa Ortega Lopez, Civil Engineering Department, University of Burgos (E).
The research/educational collaboration project focuses on the topic of smart engineering construction practices, through the use of new equipment acquired in the SEI project (additive manufacturing tools), to design sustainable and innovative construction materials. The project includes seminars for PhD students on the topics of recycling and circular economy in the field of construction and pavement engineering. Seminars are also planned for master’s students of the Recycling and reuse of raw materials course, within the LM Environmental Engineering. In the SEI project, the collaboration focuses on the Smart Lab line.
- Nonlinear techniques for data analysis (genetic algorithms, artificial neural networks) focusing on the prediction of coastal flooding hazards. Visiting Scientist: Giovanni Coco, University of Auckland (NZ).
The research/education collaboration project focuses on topics related to nonlinear techniques for data analysis (genetic algorithms, artificial neural networks) focused on the prediction of coastal flooding hazards. A series of seminars on machine learning and coastal hazards is planned, as well as collaborations on research related to: bank erosion in river and tidal channels; application of machine learning to local datasets; role of ecology on estuarine morphodynamics. In the SEI project, the collaboration focuses on the Smart Data line. The project includes seminars aimed at students of the Civil Engineering, Environmental Engineering, Mathematical Engineering and PhD courses.
- Valuing the potential of a chatbot to generate a digital bridge twin for maintenance. Visiting Scientist: Bernd Domer, Univerity HES-SO (Haute Ecole spécilisèe de Swiss Occidentale – Ecole Polytecnique de Lausanne.
The research/education collaboration project focuses on the topics of Digital Twins and Building Information Modeling (BIM), a digital methodology for managing a project throughout its life cycle. The initiative aims to demonstrate the possibilities of virtually connecting digital tools for measurement and design with the 3D model of a building or an engineering project. It shows how to use a chatbot to analyze existing documents (descriptions, inspection reports, plans) and generate an abstract digital twin for maintenance purposes. In the SEI project, the collaboration focuses on the Smart Lab and Smart Living lines. The Project includes seminars and laboratories for PhD students and students of the Building Engineering and Architecture and Civil Engineering courses.
