امروز : یکشنبه، 28 مهر 1398

مشخصات : هادی تقوی فر

هادی تقوی فر
  • نام کامل : هادی تقوی فر
  • آخرین مدرک تحصیلی: دکترا
  • مرتبه علمی : استادیار
  • گروه تحصیلی : مکانیک
  • نوع همکاری : مدرس گروه مکانیک
  • ایمیل : h.taghavifar@urmia.ac.ir
  • رزومه :

    Hadi Taghavifar
    Current Position:
    Department of Mechanical Engineering of Urmia University, Iran

    Email: h.taghavifar@urmia.ac.ir, haditaghavifar@yahoo.com
    Curriculum Vitae:
    I graduated from the Ph.D. course in Urmia University under the supervision of Prof. Khalilarya in 2015
    following the research period as M.Sc. in Tabriz University in the Mechanical engineering department
    (Energy conversion branch). The M.Sc. project is centered on the cavitation formation in group-hole
    nozzle and multi-hole nozzle configurations and the quality of spray development from the injectors in
    non-evaporative conditions. The Ph.D. research continued with the investigation of the spray droplet
    evaporation and air-fuel mixing process, which ultimately led to analyze of the combustion phenomena
    and ICE engine-out emissions. My research work has recently been focused on the design, modeling, and
    optimization of internal combustion engines esp. diesel engines (the computational intelligence
    techniques include ANN, ANFIS, ICA, MOGA, NLPQL, Nelder-Mead). My latest field of specialization
    is the use of nanofuels/biofuels in diesel engine, design and optimization of nozzles and diesel engines.
    My subsidiary research interest involves energetic and exergetic evaluation of energy related systems
    such as CHP/CCHP power plants as well as heat exchangers.  
    I have actively contributed in the scientific community by publishing numerous papers. I am chosen as an
    outstanding Reviewer for Energy Conversion and Management with the impact factor of 4.81. 
    Ph.D. Thesis: Combined energetic and exergetic analysis of diesel engine with artificial neural network
    for investigation of fuel air dynamic mixing under parameters of homogeneity factor (HF), injection
    angle, and alternative fuels
    M.Sc. Thesis: Effect of multi hole injectors with different angle of holes on on diesel engine spray
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    Editorial Board:
    Subject editor of the Journal of Advances in Vehicle Engineering (JADVE)
    Guest leading Editor: International Journal of Spray and Combustion Dynamics (SAGE publication)
    www.jadve.com
    Published books:
     Application of artificial intelligence in internal combustion engines, In Persian.
     Fundamentals of combustion processes: Translation
     Green diesel engine: Translation
    Research project: 
     Optimization of the shape of combustion chamber with a parametric study for a submarine
     Benchmarking of water injection in a hydrogen-fueled diesel engine to reduce emissions and
    increase efficiency
     Technical and economical study of the CCHP system in order to generate electricity, heating, and
    cooling simultaneously
    Published peer-reviewed papers:
    1- Taghavifar, H., Taghavifar, H., Mardani, A. and Mohebbi, A., 2014. Exhaust emissions
    prognostication for DI diesel group-hole injectors using a supervised artificial neural network
    approach. Fuel, 125, pp.81-89.
    2- Taghavifar, H., Khalilarya, S. and Jafarmadar, S., 2014. Engine structure modifications effect on the
    flow behavior, combustion, and performance characteristics of DI diesel engine. Energy Conversion and
    Management, 85, pp.20-32.
    3- Taghavifar, H., Khalilarya, S. and Jafarmadar, S., 2014. Diesel engine spray characteristics prediction
    with hybridized artificial neural network optimized by genetic algorithm. Energy, 71, pp.656-664.
    4- Taghavifar, H., Taghavifar, H., Mardani, A. and Mohebbi, A., 2014. Modeling the impact of incylinder

    combustion parameters of DI engines on soot and NOx emissions at rated EGR levels using
    ANN approach. Energy Conversion and Management, 87, pp.1-9.
    5- Taghavifar, H., Taghavifar, H., Mardani, A., Mohebbi, A., Khalilarya, S. and Jafarmadar, S., 2016.
    Appraisal of artificial neural networks to the emission analysis and prediction of CO 2, soot, and NOx of
    n-heptane fueled engine.Journal of Cleaner Production, 112, pp.1729-1739.
    6- Taghavifar, H., Khalilarya, S., Mirhasani, S. and Jafarmadar, S., 2014. Numerical energetic and
    exergetic analysis of CI diesel engine performance for different fuels of hydrogen, dimethyl ether, and
    diesel under various engine speeds. International Journal of Hydrogen Energy, 39(17), pp.9515-9526.
    7- Anvari, S., Taghavifar, H., Saray, R.K., Khalilarya, S. and Jafarmadar, S., 2015. Implementation of
    ANN on CCHP system to predict trigeneration performance with consideration of various operative
    factors. Energy Conversion and Management, 101, pp.503-514.
    8- Taghavifar, H., Taghavifar, H., Mardani, A., Mohebbi, A. and Khalilarya, S., 2015. A numerical
    investigation on the wall heat flux in a DI diesel engine fueled with n-heptane using a coupled CFD and
    ANN approach. Fuel, 140, pp.227-236.
    2
     
    9- Taghavifar, H., Mardani, A., Mohebbi, A. and Taghavifar, H., 2014. Investigating the effect of
    combustion properties on the accumulated heat release of DI engines at rated EGR levels using the ANN
    approach. Fuel,137, pp.1-10.
    10- Taghavifar, H., Shervani-Tabar, M.T. and Abbasalizadeh, M., 2015. Numerical study of the effects of
    injector needle movement and the nozzle inclination angle on the internal fluid flow and spray structure of
    a group-hole nozzle layout. Applied Mathematical Modelling, 39(23), pp.7718-7733.
    11- Taghavifar, H., 2015. Numerical study on the influence of group-hole nozzle injectors on flow
    domain of diesel spray. Journal of Advances in Vehicle Engineering, 1(2).
    12- Taghavifar, H., Khalilarya, S. and Jafarmadar, S., 2015. Exergy analysis of combustion in VGTmodified
    diesel
    engine
    with
    detailed
    chemical
    kinetics
    mechanism.
    Energy,
    93,
    pp.740-748.

    13- Taghavifar, H. and Shabahangnia, E., 2014. Prediction of thermal gradient in an air channel with
    presence of electrostatic field using artificial neural network. Heat and Mass Transfer, 50(11), pp.15151524.

    14- Taghavifar, H., Khalilarya, S. and Jafarmadar, S., 2015. Adaptive neuro-fuzzy system (ANFIS) based
    appraisal of accumulated heat from hydrogen-fueled engine. International Journal of Hydrogen
    Energy, 40(25), pp.8206-8218.
    15- Taghavifar, H., Khalilarya, S. and Jafarmadar, S., 2015. Three‐dimensional energetic and exergetic
    analysis of the injection orientation of DI diesel engine under different engine speeds. Energy Science &
    Engineering, 3(4), pp.360-370.
    16- Taghavifar, H., Khalilarya, S., Jafarmadar, S. and Taghavifar, H., 2016. A RANS simulation toward
    the effect of turbulence and cavitation on spray propagation and combustion characteristics. Theoretical
    and Computational Fluid Dynamics, pp.1-14.
    17- Taghavifar, H., Khalilarya, S., Jafarmadar, S. and Baghery, F., 2016. 3-D numerical consideration of
    nozzle structure on combustion and emission characteristics of DI diesel injector. Applied Mathematical
    Modelling.
    18- Anvari, S., Taghavifar, H., Khalilarya, S., Jafarmadar, S. and Shervani-Tabar, M.T., 2016. Numerical
    simulation of diesel injector nozzle flow and in-cylinder spray evolution. Applied Mathematical
    Modelling.
    19- Taghavifar, H., Jafarmadar, S., Taghavifar, H. and Navid, A., 2016. Application of DoE evaluation to
    introduce the optimum injection strategy-chamber geometry of diesel engine using surrogate epsilonSVR.
    Applied
    Thermal
    Engineering,
    106,
    pp.56-66.

    20- Jafarmadar, S., Taghavifar, H., Taghavifar, H. and Navid, A., 2016. Numerical assessment of flow
    dynamics for various DI diesel engine designs considering swirl number and uniformity index. Energy
    Conversion and Management, 110, pp.347-355.
    21- Taghavifar, H., Taghavifar, H., Mardani, A., Mohebbi, A., Khalilarya, S. and Jafarmadar, S., 2015.
    On the modeling of convective heat transfer coefficient of hydrogen fueled diesel engine as affected by
    3
     
    combustion parameters using a coupled numerical-artificial neural network approach.international
    journal of hydrogen energy, 40(12), pp.4370-4381.
    22- Taghavifar, H., Anvari, S., Saray, R.K., Khalilarya, S., Jafarmadar, S. and Taghavifar, H., 2015.
    Towards modeling of combined cooling, heating and power system with artificial neural network for
    exergy destruction and exergy efficiency prognostication of tri-generation components. Applied Thermal
    Engineering, 89, pp.156-168.
    23-Jalilpour, B., Jafarmadar, S., Ganji, D.D., Shotorban, A.B. and Taghavifar, H., 2014. Heat
    generation/absorption on MHD stagnation flow of nanofluid towards a porous stretching sheet with
    prescribed surface heat flux. Journal of Molecular Liquids, 195, pp.194-204.
    24-Jafarmadar, S., Jalilpour, B., Ganji, D.D. and Taghavifar, H., 2014. A Unified Model Considering
    Effects of Droplet Break-Up and Air Entrainment at the Initial Stage of Fuel Spray
    Penetration. Mathematical Problems in Engineering, 2014.
    25- Saraee, H.S., Jafarmadar, S., Taghavifar, H. and Ashrafi, S.J., 2015. Reduction of emissions and fuel
    consumption in a compression ignition engine using nanoparticles. International Journal of
    Environmental Science and Technology, 12(7), pp.2245-2252.
    26-Saraee H.S., Taghavifar H, Jafarmadar S. Experimental and numerical consideration of the effect of
    CeO2 nanoparticles on diesel engine performance and exhaust emission with the aid of artificial neural
    network. Applied Thermal Engineering 2016 (Accepted manuscript).
    27- Navid A, Khalilarya Sh, Taghavifar H. Comparing multi-objective non-evolutionary NLPQL and
    evolutionary genetic algorithm optimization of a DI diesel engine: DoE estimation and creating surrogate
    model. Energy Conversion and Management 2016 (Accepted manuscript).
    28- Haghighi, E.A., Jafarmadar, S. and Taghavifar, H., 2013. Application of ANN-ICA Hybrid Algorithm
    toward Prediction of Engine Power and Exhaust Emissions. Int J Automot Eng, 3, pp.602-608.
    29- Taghavifar, H., 2017. On the optimization of a HSDI diesel engine by genetic algorithm: Nu-SVR
    modeling. International Journal of Heavy Vehicle Systems: Under review
    30- Taghavifar, H., 2017. Application of divergent split injection in a CIDI diesel engine to reduce
    emissions and boost the efficiency. Transport: Under review
    31- Taghavifar H, Anvari S, Parvishi A,. 2017. Benchmarking of water injection in a hydrogen-fueled
    diesel engine to reduce emissions and increase efficiency. International Journal of Hydrogen Energy:
    (Accepted Manuscript: In press)
    32- Taghavifar, H., 2017. Towards multiobjective Nelder-Mead optimization of a HSDI diesel engine:
    Application of Latin hypercube design-explorer with SVM modeling approach. Energy Conversion and
    Management (Under Review)
    33- Anvari S, Taghavifar H, Parvishi A., Thermo - economical consideration of RORC coupling with the
    absorption chiller systems incorporated in the CCHP system. Energy Conversion and Management
    (Under Review)
    4
     
    Conference proceedings:
    1-Taghavifar H, Khalilarya Sh. The effect of injector structure in terms of inlet nozzle curvature and
    nozzle angles on combustion and emission. 5
    5
     
    th
     National Conference of Fuel and Combustion, March
    2014, Tehran, Iran.
    2- Taghavifar H, Khalilarya Sh, Jafarmadar S. Wall heat flux ealuation of a DI diesel engine with the aid
    of ANN and CFD. The 8
    th
     Student Conference on Mechanical Engineering, 8-10 October 2014,
    University of Guilan, Iran.
    3- Navid A, Khalilarya Sh, Taghavifar H. Muti-objective optimization of combustion chamber of DI
    diesel engine using NLPQL algorithm. International Congress on Engineering & Technology
    Development, May 2016, Tabriz, Iran.
    Awards and Achievements:
    1- Outstanding Reviewer, Energy Conversion and Management, Elsevier 2015
    2- First Rank student of Ph.D. period in Urmia University
    3- The best researcher award of the year (2015) from Azma-Tech Company: The most profitable research
    project
    4- MSRT language certificate (English): 87/100
    Patents:
    Design and manufacture of hinged rotary cylinder of engines: In progress
    Reviewer:
     Energy (Elsevier)
     Energy conversion and management (Elsevier)
     International Journal of Hydrogen Energy (Elsevier)
     Applied Thermal Engineering (Elsevier)
     Engineering Applications of Computational Fluid Mechanics (Taylor and Francis)
     Alexandria Engineering Journal (Elsevier)
     Fuel processing technology (Elsevier)
     Journal of Intelligent systems (De Gruyter)
     Journal of Electrostatics (Elsevier)
     Journal of the Brazilian Society of Mechanical Sciences and Engineering (Springer)
     Fuel (Elsevier)
     European Journal of Sustainable Development Research
    Research interests:
     CFD simulation of combustion process, multiphase flow and cavitation formation in
    injectors
     Modeling of combustion chamber, group-hole and multi-hole injectors 
     Nano particle effect on fuel and combustion properties
     Prediction and optimization of spray and combustion with the aid of ANN, ICA, GA
     Investigation of spray characteristics on combustion and emission process
     Free convective heat transfer from air channel
     Exergy and energy analysis
     Design of CHP, and CCHP power plants
    Skills:
     Proficiency in AVL-Fire, and Fluent software
     Nano-fuel experimental research
     Design and analysis of engine by NLPQL, MOGA, and Nelder-Mead Algorithms
     Familiar with Catia, and 3D max
     EES and MATLAB code development for energy and exergy analysis of power plants
     Strong mathematical and analytical ability
     
     
     
     

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