A5053243136- Building Energy and Comfort Optimization
- Advanced Control Systems Optimization
- Extremum Seeking Control Systems
- Fault Detection and Control Systems
- Particle Detector Development and Performance
- Refrigeration and Air Conditioning Technologies
- Heat Transfer and Optimization
- Smart Grid Energy Management
- Anomaly Detection Techniques and Applications
- Smart Grid Security and Resilience
- Particle physics theoretical and experimental studies
- Heat Transfer and Boiling Studies
- Combustion and flame dynamics
- Neutrino Physics Research
- Energy Efficiency and Management
- Nuclear physics research studies
- Adsorption and Cooling Systems
- Microgrid Control and Optimization
- Reservoir Engineering and Simulation Methods
- Nuclear Physics and Applications
- Advanced Control Systems Design
- Engineering Education and Pedagogy
- Electrostatic Discharge in Electronics
- Control Systems and Identification
- Radiation Detection and Scintillator Technologies
University of Padua
2015-2024
Istituto Nazionale di Fisica Nucleare, Sezione di Padova
2017-2023
University of Milan
2020-2021
Istituto Nazionale di Fisica Nucleare, Sezione di Milano
2020-2021
Unidades Centrales Científico-Técnicas
2020
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
2020
San Jose State University
2020
Instituto de Física de Cantabria
2016-2018
Universidad de Cantabria
2016-2018
Petroleum of Venezuela (Venezuela)
1999
The design of micro-finned tube heat exchangers is a complex task due to intricate geometry, transfer goals, material selection, and manufacturing challenges. Nowadays, mathematical models provide valuable insights, aid in optimization, allow us explore various parameters efficiently. However, existing empirical often fall short facilitating an optimal because their limited accuracy, sensitivity assumption, context dependency. In this scenario, the use Machine Deep Learning (ML DL) methods...
Smart grids are critical for addressing the growing energy demand due to global population growth and urbanization. They enhance efficiency, reliability, sustainability by integrating renewable energy. Ensuring their availability safety requires advanced operational control measures. Researchers employ AI machine learning assess grid stability, but challenges like lack of datasets cybersecurity threats, including adversarial attacks, persist. In particular, data scarcity is a key issue:...
Data centers are facilities hosting a large number of servers dedicated to data storage and management. In recent years, their power consumption has increased significantly due the density IT equipment. particular, cooling represents approximately one third total electricity consumption, therefore efficiently become challenging problem it an opportunity reduce both energy costs emissions environmental impact. The efficiency computers room air conditioning (CRAC) systems can be using advanced...
The electromagnetic structure of $^{66}\mathrm{Zn}$ at low excitation energy was investigated via low-energy Coulomb INFN Legnaro National Laboratories, using the Gamma Array Infn Laboratories for nuclEar spectrOscopy (GALILEO) $\ensuremath{\gamma}$-ray spectrometer coupled to SPIDER (Silicon PIe DEtectoR). A set reduced $E2, E3$, and $M1$ matrix elements extracted from collected data gosia code, yielding 12 transition probabilities between low-spin states spectroscopic quadrupole moment...
Several faults affect heating, ventilation, and air conditioning (HVAC) chiller systems, leading to energy wastage, discomfort for the users, shorter equipment life, system unreliability. Early detection of anomalies can prevent further deterioration wastage. In this work, a data-driven approach is used in order detect that usually plague systems. particular, proposed employs kernel principal component analysis (KPCA) capture normal operative conditions system; learning method turns out be...
Predicting and classifying faults in electricity networks is crucial for uninterrupted provision keeping maintenance costs at a minimum. Thanks to the advancements field provided by smart grid, several data-driven approaches have been proposed literature tackle fault prediction tasks. Implementing these systems brought improvements, such as optimal energy consumption quick restoration. Thus, they become an essential component of grid. However, robustness security against adversarial attacks...
Faulty operation of HVAC systems can lead to discomfort for the occupants, energy wastage, unreliability and shorter equipment life. Cost-effective Fault Detection Diagnosis (FDD) methods therefore ensure an increase in system uptime, reliability, overall efficiency. In this paper, order evaluate compare FDD systems, we resort a particular case Variable Air Volume models, that are capable describing response control both normal fault operating conditions. The is tested by performing...
Faulty operations of Heating, Ventilation and Air Conditioning (HVAC) chiller systems can lead to discomfort for the users, energy wastage, system unreliability shorter equipment life. Faults need be early diagnosed prevent further deterioration behaviour losses. In this paper a model-based approach is used in order detect important faults. First, linear dynamic black-box model identified each relevant characteristic features during normal functioning chiller. Then, an on-line correlogram...