A5033358562- Water Systems and Optimization
- Gas Dynamics and Kinetic Theory
- Machine Fault Diagnosis Techniques
- Cavitation Phenomena in Pumps
- Rocket and propulsion systems research
- Maritime Transport Emissions and Efficiency
- Fault Detection and Control Systems
- Spacecraft and Cryogenic Technologies
- Underwater Acoustics Research
- Image and Signal Denoising Methods
- Space Satellite Systems and Control
- Industrial Vision Systems and Defect Detection
- Advanced Aircraft Design and Technologies
- Radiative Heat Transfer Studies
- Hydraulic and Pneumatic Systems
- Maritime Navigation and Safety
- Structural Integrity and Reliability Analysis
- Gear and Bearing Dynamics Analysis
- Ship Hydrodynamics and Maneuverability
- Aerospace and Aviation Technology
- Marine Ecology and Invasive Species
- Energy Load and Power Forecasting
- Machine Learning and Algorithms
- Flow Measurement and Analysis
- Internet of Things and Social Network Interactions
FIT Consulting (Italy)
2023
University of Genoa
2017-2021
European Space Research Institute
2019
Fondazione Vincenzo Pansadoro
2019
European Space Research and Technology Centre
2003-2006
Japan External Trade Organization
2002-2003
Fast diesel engine models for real-time prediction in dynamic conditions are required to predict performance parameters, identify emerging failures early on and establish trends reduction. In order address these issues, two main alternatives exist: one is exploit the physical knowledge of problem, other historical data produced by modern automation system. Unfortunately, first approach often results hard-to-tune very computationally demanding that not suited prediction, while second trusted...
Abstract Recent advances in machine learning research, combined with the reduced sequencing costs enabled by modern next-generation sequencing, paved way to implementation of precision medicine through routine multi-omics molecular profiling tumours. Thus, there is an emerging need reliable models exploiting such data retrieve clinically useful information. Here, we introduce original consensus clustering approach, overcoming intrinsic instability common methods based on data. This approach...
Induction motors are fundamental components of several modern automation system, and they one the central pivot developing e-mobility era. The most vulnerable parts an induction motor bearings, stator winding rotor bars. Consequently, monitoring maintaining them during operations is vital. In this work, authors propose Motors bearings tool which leverages on currents signals processed with a Deep Learning architecture. Differently from state-of-the-art approaches exploit vibration signals,...
*† During the last years, Europe has dedicated significant efforts to improve quality and reliability of aerothermodynamic predictions, due their key importance in design development any hypersonic aerospace vehicle. In particular, invested a lot during decade construction, commissioning improvement ground based facilities as well validation advanced numerical tools for space vehicles purposes. In-flight experimentation constitutes this frame necessary step fully validate fluid dynamic...
[Abstract] This paper reports on the aerothermodynamic (ATD) environment of EXPERT configuration associated with planned first flight (5km/sec trajectory). A status report is given embarked measurement technique developments and qualification emphasis thermal protection system (TPS) integration issues. Special attention to design sensors themselves, their into TPS as well free stream parameters during re-entry using an Air Data System (ADS). The will address numerical work optimise location...
In the latest years, models combining physical knowledge of a phenomenon and statistical inference are becoming much interest in many real world applications. this context, ship propeller underwater radiated noise is an interesting field application for these so-called hybrid models, especially when cavitates. Nowadays, model scale tests considered state-of-the-art technique to predict cavitation spectra. Unfortunately, they negatively affected by effects which could alter onset some...
Reducing the noise impact of ships on marine environment is one objectives new propellers designs, since they represent dominant source underwater radiated noise, especially when cavitation occurs. Consequently, ship designers require predictive tools able to verify compliance with requirements and compare effectiveness different design solutions. In this context, provide a reliable estimate propeller spectra based just information available at stage fundamental tool speed up process...
Accurate energy consumption forecasting has become pivotal for many companies as a way to tailor the budget dedicated purchase on their actual power demand, thus sustainably minimizing waste and expenses. For these companies, both short-term long-term forecasts are matter of interest since they would like program last-minute buy sell also plan future investments optimization. this purpose, in paper, different Deep Neural Networks techniques will be tested perform supervised an unsupervised...