GIANNETTI, Niccolo

写真a

Affiliation

Affiliated organization, Waseda Institute for Advanced Study

Job title

Associate Professor(non-tenure-track)

Concurrent Post 【 display / non-display

  • Faculty of Science and Engineering   School of Fundamental Science and Engineering

Education 【 display / non-display

  • 2013.09
    -
    2016.03

    Waseda University   Department of Applied Mechanics and Aerospace Engineering   Doctoral course  

  • 2012.10
    -
    2013.01

    Association of Professional Engineers of Florence (Italy)   Industrial Engineer (Professional Qualification)  

  • 2010.09
    -
    2012.10

    University of Florence (Italy)   Department of Industrial Engineering, Mechanical Engineering   Graduate school of Engineering (Master program)  

  • 2007.09
    -
    2010.12

    University of Florence (Italy)   Department of Industrial Engineering, Mechanical Engineering   Undergraduate school of Engineering (Bachelor program)  

  • 2002.02
    -
    2007.07

    Niccolo Rodolico high school, Florence (Italy)   Science oriented program  

Degree 【 display / non-display

  • Waseda University   Doctor of Engineering

Research Experience 【 display / non-display

  • 2021.04
    -
    Now

    Waseda University   Waseda Institute for Advanced Study   Associate Professor   Associate Professor (without tenure)

  • 2019.04
    -
    2021.03

    Waseda University   Institue for Advanced Study   Assistant Professor

  • 2017.04
    -
    2019.03

    Waseda University   Department of Applied Mechanics and Aerospace Engineering   Assistant Professor

  • 2014.04
    -
    2017.03

    Waseda University   Department of Applied Mechanics and Aerospace Engineering   Research Associate

  • 2013.03
    -
    2013.08

    University of Florence   Department of Industrial Engineering   Scholarship holder Researcher

Professional Memberships 【 display / non-display

  • 2019.09
    -
    Now

    The Japan Society of Mechanical Engineers

  • 2019.05
    -
    Now

    International Institute of Refrigeration (IIR)

  • 2014.01
    -
    Now

    JAPAN SOCIETY OF REFRIGERATING AND AIR CONDITIONING ENGINEERS

  • 2013.01
    -
    Now

    Association of Professional Engineers of Florence (Italy)

 

Research Areas 【 display / non-display

  • Control and system engineering

  • Thermal engineering   Heat and Mass Transfer

  • Thermal engineering   Thermodynamic Optimization

  • Thermal engineering   Sorption

  • Fluid engineering   Fluid Dynamics

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Research Interests 【 display / non-display

  • Turbomachinery

  • Energy storage

  • Refrigeration and Air-Conditioning

  • Fluid Dynamics

  • Sorption

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Papers 【 display / non-display

  • Variational formulation of stationary two-phase flow distribution

    Niccolo Giannetti, Mark Anthony Redo, Kiyoshi Saito, Hiroaki Yoshimura

    Case Studies in Thermal Engineering   26   101082 - 101082  2021.08  [Refereed]

    Authorship:Lead author, Corresponding author

    DOI

  • Absorption heat transformer - state-of-the-art of industrial applications

    Falk Cudok, Niccolò Giannetti, José L. Corrales Ciganda, Jun Aoyama, P. Babu, Alberto Coronas, Tatsuo Fujii, Naoyuki Inoue, Kiyoshi Saito, Seiichi Yamaguchi, Felix Ziegler

    Renewable and Sustainable Energy Reviews   141   110757 - 110757  2021.05  [Refereed]

    DOI

  • A cost effective and non-intrusive method for performance prediction of air conditioners under fouling and leakage effect

    Sholahudin, Niccolo Giannetti, Seiichi Yamaguchi, Kiyoshi Saito, Katsuhiko Tanaka, Hiroto Ogami

    Sustainable Energy Technologies and Assessments   42   100856 - 100856  2020.12  [Refereed]

     View Summary

    Realistic performance predictions are required for efficient operation strategy of air conditioners. In this study, the application of a cost effective and non-intrusive black box model utilizing artificial neural networks (ANN) to predict the cooling capacity of air conditioning systems is investigated, while considering the effect of fouling and leakage that may occur after prolonged operation. The effect of various leakage and fouling combinations on the output cooling capacity were numerically simulated. The training data set is first generated for a system that is ideally operating without any fouling or leakage. The developed ANN model is tested to predict cooling capacity in "faulty" systems. The results indicated that, as long as leakage and fouling are limited below 10% and 4% respectively, the ANN model trained by the data generated with the ideal system, can predict cooling capacity with a relative averaged cooling capacity difference (Delta(Q) over bar (e,rel)) of approximately 13%. Moreover, the inclusion of data with different leakage and fouling combinations in the training set enables accurate predictions of the cooling capacity of the air conditioning system during the entire timespan of its operation. It suggests that cooling capacity under the fouling and leakage phenomena can be predicted using limited input information.

    DOI

  • Semitheoretical formulation of annular flow void fraction using the principle of minimum entropy production

    Niccolò Giannetti, Seiichi Yamaguchi, Kiyoshi Saito, Hiroaki Yoshimura

    International Journal of Thermal Sciences   158  2020.12  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    © 2020 Elsevier Masson SAS The two-phase flow void fraction is a critical parameter for characterising the pressure drop as well as heat and mass transfer capability of the working fluid within thermal systems, the accurate estimation of which drives heat exchanger design and control optimisation. A semitheoretical expression for the void fraction of two-phase flows, also applicable to small-sized channels, is obtained from an analytical study based on the principle of minimum entropy production and the introduction of empirical coefficients to be fitted to experimental data available in the open literature. These coefficients embody the importance of the simplified physical terms of this formulation while recovering the accuracy loss owing to nonlinear phenomena, heat and mass transfer, and three-dimensional effects. By accounting for surface tension, this model generalises previous theories and describes the influence of smaller-sized channels in terms of the stable void fraction. This mathematical framework can be used to summarise data covering different refrigerants, channel diameters, and operating conditions.

    DOI

  • Experimental implementation of artificial neural network for cost effective and non-intrusive performance estimation of air conditioning systems

    Sholahudin, Niccolo Giannetti, Seiichi Yamaguchi, Kiyoshi Saito, Yoichi Miyaoka, Katsuhiko Tanaka, Hiroto Ogami

    Applied Thermal Engineering   181   115985 - 115985  2020.11  [Refereed]

     View Summary

    Owing to the high variability of operating conditions and the complexity of dynamic phenomena occurring within air conditioning cycles, the realistic performance estimation of these systems remains an open question in this field. This paper demonstrates the applicability of a cost-effective estimation method based on an artificial neural network exclusively using four refrigerant temperatures as the network input. The experimental datasets are collected from a reference experimental facility. The system is operated with variable cooling load, outdoor temperature, and indoor temperature settings, as representative of the actual operation. The artificial neural network structure was optimized by considering the effect of previous time step inputs, number of neurons, sampling time, and number of training data. The results reveal that the developed model can successfully estimate the cooling capacity of an air conditioning system during on-off, continuous unsteady, and steady operation, using four temperature inputs with relative averaged error below 5%.

    DOI

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Awards 【 display / non-display

  • Outstanding contribution in Reviewing

    2018.06   Elsevier, Applied Energy  

    Winner: Niccolo Giannetti

  • Outstanding contribution in Reviewing

    2018.02   Elsevier, International Journal of Refrigeration  

    Winner: Niccolo Giannetti

  • ISHPC2017, Young Researcher Award

    2017.08   2017 International Sorption Heat Pump Conference Organizing Committee   Simplified expressions of the transfer coefficients on a partially wet absorber tube

    Winner: Niccolo Giannetti

  • Japan Refrigeration and Air Conditioning Association Award

    2016.09   Japan Refrigeration and Air Conditioning Association   Thermo-fluid dynamics of falling film type vapour absorption process

    Winner: Niccolo Giannetti

Research Projects 【 display / non-display

  • Lagrange-Dirac Systems and Applications

    Project Year :

    2019.04
    -
    2024.03
     

    Authorship: Coinvestigator(s)

  • Development of Assessment Techniques for Next-Generation Refrigerants with Low GWP Values

    Project Year :

    2018.04
    -
    2023.03
     

    Authorship: Coinvestigator(s)

  • Study on Unsteady Analysis of Two-Stage Turbo Chiller

    Project Year :

    2021.04
    -
    2022.03
     

    Authorship: Principal investigator

  • Research on Capacity Estimation Method of Multi-Air Conditioners for Buildings by Machine Learning

    Project Year :

    2020.04
    -
    2022.03
     

    Authorship: Coinvestigator(s)

  • Research and development of technology for innovative use of unused heat energy / Research and development of technology for innovative use of unused heat energy

    Project Year :

    2015.04
    -
    2021.03
     

    Authorship: Coinvestigator(s)

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Presentations 【 display / non-display

  • Assessment of surfactant-induced Marangoni convection within high-temperature aqueous Lithium-Bromide solution

    N. Giannetti

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants 

    Presentation date: 2020.12

    Event date:
    2020.12
     
     
  • Numerical Investigation of CO2 Heat Pump Water Heater Performance

    M. Yulianto, N. Giannetti, co-auth

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants 

    Event date:
    2020.12
     
     
  • Experimental performance analysis and simulation of an internally cooled liquid desiccant air conditioning system using a novel ionic liquid

    R.J. Varela, N. Giannetti (co-author)

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants 

    Event date:
    2020.12
     
     
  • Thermodynamic investigation of asynchronous open inverse air cycle integrated with compressed air energy storage

    A. Milazzo, N. Giannetti, K. Saito

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants 

    Event date:
    2020.12
     
     
  • Semi-Theoretical Formulation of Annular Flow Void-Fraction

    Niccolo Giannetti

    The 11th International Meeting on Advances in Thermofluids 

    Presentation date: 2019.11

    Event date:
    2019.11
     
     

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Specific Research 【 display / non-display

  • Modelling thermal engineering processes with variational principle of non equilibrium thermodynamics

    2020  

     View Summary

    A generalizable understanding of the fundamental transportphenomena occurring within thermal systems is necessary to keep up with theirfast-paced technological progress, which is evolving towards advancedconfigurations and new working substances. Accordingly, this research targetsthe generalized modeling of interfacial multiphase processes for thermalsystems optimization and control through an interdisciplinary effort clusteringengineering experiments, artificial intelligence AI, and physical modeling. Research outcomes resulted into general formulations ofinterfacial multiphase processes (surface wetting, flow pattern transition,void fraction arrangement of two-phase flows, and two-phase flow separation) atsteady-state within the theory of nonequilibrium thermodynamics while providingcorresponding experimental validations. The above-mentioned formulation is thenused as the basis for a variational representation which extends the classicalLagrangian formulation in mechanics to nonequilibrium thermodynamic systemsincluding irreversible processes.The theoretical framework consequently obtained is combinedto corrective coefficients from computational fluid dynamics and experimentaldata to achieve phenomenon representations with higher accuracy. The use of machine learning tools is then guided by thegained theoretical understanding of the process to select the essentialtraining parameters for generalizing the applicability of such tool, whiletaking advantage of the powerful ability of AI to reconstruct complexintercorrelations between input and output quantities.

  • Interdisciplinary Theory of Interfacial Multiphase Processes for Advanced Modelling and Control of Engineering Thermal Systems

    2019  

     View Summary

    The first outcomes of this research project cover the application of variational principle for the mathematical formulations ofengineering phenomena recurrent in thermal systems, development of semi-theoretical phenomena combining the above-said mathematical formulations with collected experimental data, in parallel to the investigation of Artificial Intelligence approach for device optimisation procedures . Specifically, the Principleof minimum energy and Prigogine’s Theorem of minimum entropy generation have been applied tofalling-film wetting and two-phase refrigerant distribution in microchannelheat exchangers, respectively, along with the construction of a Lagrangian formulation able to include time evolution and unify different variational approaches.  A simplified formulation through Taylor series approximation was implemented as the mathematical framework for modelling open refrigerated display cabinets in combination with the representation given by collected experimental data. Other semi-theoretical models were obtained for desiccant wetting and two-phase flow void fraction. Genetic Algorithm has beenimplemented for circuitry optimisation in finned-tube heat exchangers andsystem-scale optimal operation. 

  • Study on Marangoni convection within high temperature absorbers for heat transformer applications

    2017  

     View Summary

    Absorption heat pumps and low exergy heat recovery have been named as keytechnologies for contributing to the solution of energy provision problems andrelated environmental issues. In order to achieve a better understanding and predictive models for thephenomena occurring in high temperature absorption heat transformers thisproject focus on Marangoni convection and high temperature absorption phenomenaas critical aspects yet to be clarified.To achieve this goal, experimental investigations at high temperatureoperability and direct visualization of falling film absorbers have beencarried out as terms of comparison for refining and validate the developednumerical models. Preliminary results have been summarized into papers,presented to domestic and international conferences and submitted tointernational journals.Finally, the equipment for the fundamental characterization and PIVmeasurement of Marangoni convection in a nearly-bi-dimensional space wasdesigned, constructed and instrumented for investigating the driving force ofthis phenomenon, the most suitable surfactant characteristics and theabsorption performance enhancement with respect to pure aqueous Lithium-Bromidemixtures.

 

Syllabus 【 display / non-display

  • Heat Transfer

    School of Fundamental Science and Engineering

    2021   spring semester

  • Control Engineering [S Grade]

    School of Fundamental Science and Engineering

    2021   fall semester

  • Control Engineering

    School of Fundamental Science and Engineering

    2021   fall semester

  • Dynamics [S Grade]

    School of Fundamental Science and Engineering

    2021   fall semester

  • Dynamics

    School of Fundamental Science and Engineering

    2021   fall semester

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Teaching Experience 【 display / non-display

  • Dynamics B

    Waseda University  

    2020.04
    -
    Now
     

  • Dynamics A

    Waseda University  

    2020.04
    -
    Now
     

  • Thermodynamics B

    Waseda University  

    2019.09
    -
    Now
     

  • Thermodynamics A

    Waseda University  

    2019.09
    -
    Now
     

  • Heat Transfer (伝熱工学)

    School of Fundamental Science and Engineering  

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Committee Memberships 【 display / non-display

  • 2019.07
    -
    Now

    14th IIR-Gustav Lorentzen Conference on Natural Refrigerants - GL2020  Organizing Committee, Secretary General

  • 2014.08
    -
    Now

    Waseda University, International Institute of Refrigeration  ISHPC Organizing Committee