Area of research
Mechanics of Materials · Control and Systems Engineering
Research interest
Research interests include Computer science, Gas turbines, Fault (geology), Reliability (semiconductor), Artificial intelligence, and Renewable energy.
Optimization of sizing and operation of pumped hydro storage plants under current and future economic scenarios
Gas Turbine Diagnostics by Means of Convolutional Neural Networks Fed With Time Series Data Encoded as Images
Hydraulic and electrical regulations of pumps as turbines for energy recovery in water distribution networks: Energy and economic analysis
Gas Turbine Diagnostics by Means of Convolutional Neural Networks Fed With Time Series Data Encoded As Images
Encoding Multivariate Time Series of Gas Turbine Data as Images to Improve Fault Detection Reliability
Data-driven approach for the detection of faults in district heating networks
Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation
Machine Learning Approaches for the Prediction of Gas Turbine Transients
Unsupervised Methodology for the Prognostics of Gas Turbine Abrupt Faults
Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation
Energy and Economic Optimization of the Design and Operation of Hybrid Energy Plants Under Current and Future Economic Scenarios
Analysis of Pumped Hydro Storage Using Mines As Hydro Reservoirs
Pressure Management in Water Distribution Networks by Means of Pumps as Turbines: A Case Study in Northern Italy
Author comment: Hydraulic and electrical regulations of pumps as turbines for energy recovery in water distribution networks: Energy and economic analysis — R2/PR1
Development and validation of a comprehensive methodology for predicting PAT performance curves
Optimal Selection and Operation of Pumps as Turbines for Maximizing Energy Recovery
Methodology to Monitor Early Warnings Before Gas Turbine Trip
Hybrid diagnostic approach for the diagnosis of district heating networks
Methodology to Monitor Early Warnings Before Gas Turbine Trip
Concurrent Design and Operation Optimization of a Multi-Generation Energy System by Using a SMO-MILP Hybrid Algorithm
Application of Transfer Learning for the Prediction of Gas Turbine Trip
Prediction of Gas Turbine Trip by Combining Gas Path Measurements and Vibration Signals
Detection and identification of faults in a District Heating Network
Optimal management with demand response program for a multi-generation energy system
A diagnostic approach for fault detection and identification in district heating networks
Optimization of a renewable energy plant with seasonal energy storage for the transition towards 100% renewable energy supply
Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data
Analysis of a Multi-Generation Renewable Energy System With Hydrogen-Fueled Gas Turbine
Ensemble Learning Approach to the Prediction of Gas Turbine Trip
Optimal Classifier to Detect Unit of Measure Inconsistency in Gas Turbine Sensors