ジャンネッティ ニコロ (ジャンネッティ ニコロ)

写真a

所属

附属機関・学校 高等研究所

職名

准教授(任期付)

兼担 【 表示 / 非表示

  • 理工学術院   基幹理工学部

学歴 【 表示 / 非表示

  • 2013年09月
    -
    2016年03月

    早稲田大学   機械科学・航空学科   博士課程  

  • 2012年10月
    -
    2013年01月

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

  • 2010年09月
    -
    2012年10月

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

  • 2007年09月
    -
    2010年12月

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

  • 2002年02月
    -
    2007年07月

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

学位 【 表示 / 非表示

  • 早稲田大学   博士(工学)

経歴 【 表示 / 非表示

  • 2021年04月
    -
    継続中

    早稲田大学   早稲田高等研究所   准教授   准教授(任期付)

  • 2019年04月
    -
    2021年03月

    早稲田大学   高等研究所   講師

  • 2017年04月
    -
    2019年03月

    早稲田大学   機械科学・航空学科   講師

  • 2014年04月
    -
    2017年03月

    早稲田大学   機械科学・航空学科   助手

  • 2013年03月
    -
    2013年08月

    University of Florence   Department of Industrial Engineering   Scholarship holder Researcher

所属学協会 【 表示 / 非表示

  • 2019年09月
    -
    継続中

    日本機械学会

  • 2019年05月
    -
    継続中

    International Institute of Refrigeration (IIR)

  • 2014年01月
    -
    継続中

    公益社団法人日本冷凍空調学会

  • 2013年01月
    -
    継続中

    Association of Professional Engineers of Florence (Italy)

 

研究分野 【 表示 / 非表示

  • 制御、システム工学

  • 熱工学   熱・物質移動

  • 熱工学   熱力学的な最適化

  • 熱工学   吸収・吸着

  • 流体工学   流体力学

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研究キーワード 【 表示 / 非表示

  • ターボ機械

  • エネルギーストレージ

  • 冷凍空調

  • 流体力学

  • 吸収・吸着

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論文 【 表示 / 非表示

  • 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年08月  [査読有り]

    担当区分:筆頭著者, 責任著者

    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年05月  [査読有り]

    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年12月  [査読有り]

     概要を見る

    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年12月  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    © 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年11月  [査読有り]

     概要を見る

    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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Misc 【 表示 / 非表示

受賞 【 表示 / 非表示

  • Outstanding contribution in Reviewing

    2018年06月   Elsevier, Applied Energy  

    受賞者: ジャンネッティ ニコロ

  • Outstanding contribution in Reviewing

    2018年02月   Elsevier, International Journal of Refrigeration  

    受賞者: ジャンネッティ ニコロ

  • ISHPC2017, Young Researcher Award

    2017年08月   2017 International Sorption Heat Pump Conference Organizing Committee   Simplified expressions of the transfer coefficients on a partially wet absorber tube  

    受賞者: ジャンネッティ ニコロ

  • 日本冷凍空調学会賞・会長奨励賞

    2016年09月   公益社団法人日本冷凍空調学会   流下液膜式冷媒吸収プロセスの熱流体力学的挙動に関する研究  

    受賞者: ジャンネッティ ニコロ

共同研究・競争的資金等の研究課題 【 表示 / 非表示

  • JST・ラグランジュ・ディラック力学の展開とその応用

    研究期間:

    2019年04月
    -
    2024年03月
     

    担当区分: 研究分担者

  • 省エネ化・低温室効果を達成できる次世代冷凍空調技術の最適化及び評価手法の開発/低GWP冷媒を採用した次世代冷凍空調技術の実用化評価に関する研究開発

    研究期間:

    2018年04月
    -
    2023年03月
     

    担当区分: 研究分担者

  • 2段ターボ冷凍機の非定常解析に関する研究

    研究期間:

    2021年04月
    -
    2022年03月
     

    担当区分: 研究代表者

  • 機械学習によるビル用マルチエアコンの能力推定手法の研究

    研究期間:

    2020年04月
    -
    2022年03月
     

    担当区分: 研究分担者

  • 未利用熱エネルギーの革新的活用技術研究開発/未利用熱エネルギーの革新的活用技術研究開発

    研究期間:

    2015年04月
    -
    2021年03月
     

    担当区分: 研究分担者

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講演・口頭発表等 【 表示 / 非表示

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

    N. Giannetti

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants  

    発表年月: 2020年12月

    開催年月:
    2020年12月
     
     
  • Numerical Investigation of CO2 Heat Pump Water Heater Performance

    M. Yulianto, N. Giannetti, co-auth

    The 14th IIR Gustav Lorentzen Conference on Natural refrigerants  

    開催年月:
    2020年12月
     
     
  • 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  

    開催年月:
    2020年12月
     
     
  • 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  

    開催年月:
    2020年12月
     
     
  • Semi-Theoretical Formulation of Annular Flow Void-Fraction

    Niccolo Giannetti

    The 11th International Meeting on Advances in Thermofluids  

    発表年月: 2019年11月

    開催年月:
    2019年11月
     
     

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特定課題研究 【 表示 / 非表示

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

    2020年  

     概要を見る

    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年  

     概要を見る

    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年  

     概要を見る

    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.

 

現在担当している科目 【 表示 / 非表示

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担当経験のある科目(授業) 【 表示 / 非表示

  • ダイナミクス B

    早稲田大学  

    2020年04月
    -
    継続中
     

  • ダイナミクス A

    早稲田大学  

    2020年04月
    -
    継続中
     

  • 熱力学 B

    早稲田大学  

    2019年09月
    -
    継続中
     

  • 熱力学 A

    早稲田大学  

    2019年09月
    -
    継続中
     

  • Heat Transfer (伝熱工学)

    School of Fundamental Science and Engineering  

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委員歴 【 表示 / 非表示

  • 2019年07月
    -
    継続中

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

  • 2014年08月
    -
    継続中

    Waseda University, International Institute of Refrigeration  ISHPC Organizing Committee