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Marco Tognoli
Marco Tognoli
Ph.D. Candidate, Department of Energy Engineering, Politecnico di Milano
Verified email at polimi.it - Homepage
Title
Cited by
Cited by
Year
Dynamic modelling and optimal sizing of industrial fire-tube boilers for various demand profiles
M Tognoli, B Najafi, F Rinaldi
Applied Thermal Engineering 132, 341-351, 2018
242018
Dynamic modelling, experimental validation, and thermo-economic analysis of industrial fire-tube boilers with stagnation point reverse flow combustor
M Tognoli, B Najafi, R Marchesi, F Rinaldi
Applied Thermal Engineering 149, 1394-1407, 2019
172019
Reduced FV modelling based on CFD database and experimental validation for the thermo-fluid dynamic simulation of flue gases in horizontal fire-tubes
A Morelli, M Tognoli, A Ghidoni, B Najafi, F Rinaldi
International Journal of Heat and Mass Transfer 194, 123033, 2022
32022
Implementation of a multi-setpoint strategy for fire-tube boilers utilized in food and beverage industry: Estimating the fuel saving potential
M Tognoli, B Najafi, A Lucchini, LPM Colombo, F Rinaldi
Sustainable Energy Technologies and Assessments 53, 102481, 2022
22022
Reduced Thermal-hydraulic Model of Flue Gases in Horizontal Fire Tubes with Helical Coil Inserts Employing a CFD Simulated Database
M Tognoli, A Morelli, B Najafi, F Rinaldi, A Ghidoni
Available at SSRN 4210318, 2022
12022
Mathematical modelling of proton migration in Earth mantle
V Bobrovskiy, J Galvis, A Kaplin, A Sinitsyn, M Tognoli, P Trucco
Mathematical Modelling of Natural Phenomena 17, 14, 2022
12022
A Machine Learning Model for the Prediction of Building Hourly Heating Demand from CityGML Files: Training Workflow and Deployment as an API
M Tognoli, G Peronato, JH Kaempf
Building Simulation 2023 18, 2932-2939, 2023
2023
Simplified finite volume-based dynamic modeling, experimental validation, and data-driven simulation of a fire-tube hot-water boiler
M Tognoli, S Keyvanmajd, B Najafi, F Rinaldi
Sustainable Energy Technologies and Assessments 58, 103321, 2023
2023
Physical/data-driven dynamic modelling of fire-tube boilers and demand prediction aiming at adaptive optimization of the supply set-point condition
M Tognoli
2022
Machine learning based estimation and measurement anomaly detection of NOx emissions in natural gas fired boilers
GB ZANNINI
Politecnico di Milano, 2018
2018
Deep learning based occupancy prediction and HVAC behavior modeling for improving energy efficiency of commercial buildings
NF MARRUGO CARDENAS
Politecnico di Milano, 2018
2018
Dynamic modelling, experimental validation and optimal sizing of industrial fire-tube boilers for various demand profiles
M TOGNOLI
Politecnico di Milano, 2016
2016
Analisi d'impatto verticale di elicotteri con tecniche numeriche ibride
M TOGNOLI
Politecnico di Milano, 2009
2009
Optimized Thermal-Hydraulic Modeling of Flue Gases in Horizontal Fire Tubes with Helical Coil Inserts: An Approach Using Cfd-Simulated Data
M Tognoli, A Morelli, B Najafi, F Rinaldi, A Ghidoni
Available at SSRN 4590286, 0
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