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Researcher, Muting Hao

Dr

Muting Hao DPhil BSc MSc

Associate Member of Faculty

Research Fellow at St John's College

TEL: +447536140530
COLLEGE: St John's College

Biography

Dr Muting Hao is a Research Fellow at the Oxford Thermofluid Institute (OTI), and an Associate Member of Faculty at the Department of Engineering, University of Oxford. Her research is focused on advancing fundamental computational fluid dynamics (CFD) and its application across multiple areas, with a particular emphasis on improving the efficiency of aviation technology, a crucial area for addressing current and future energy and pollution challenges worldwide. Dr Muting Hao came to Oxford and joined the CFD Methodology group in 2017. She received her Dphil degree in 2022, in Oxford Thermofluid Institute at the University of Oxford, where she specialised in numerical methods and conjugate heat transfer for film cooling of gas turbine, with sponsorship from Rolls-Royce. After that, she continued as Postdoctoral Researcher at OTI, working on high bypass ratio turbofan design under the UKRI scheme.

Her research has gained significant recognition in both industry and academia, culminating in prestigious awards such as the UKRI Computing Insight UK 2023 Jacky Pallas Award and The Osborne Reynolds 2024 Best Poster Award. Since 2024, she has been awarded a Career Development Research Fellow in Engineering at St John’s College in the University of Oxford. Over the years, her research has spanned a broad range of turbomachinery applications, including gas turbines, compressors, steam turbines, and nuclear reactor coolant pumps. Recently, she has focused on numerical methods for gas turbines, specifically: (1) LES on turbine cooling, (2) conjugate heat transfer, (3) high bypass ratio turbofan modelling and design optimisation, (4) turbulence and heat transfer analysis. (5) Machine learning in fluid dynamics.

Currently, Dr. Hao is engaged in cutting-edge research that integrates machine learning with fundamental fluid dynamics. She also continues research in collaboration with Rolls-Royce, developing solver design tools utilized by the aviation industry for both next-generation aircraft engine design and research.

Research Interests

Muting Hao’s research focuses on numerical methods in fluid dynamics, turbomachinery, turbine cooling, conjugate heat transfer, turbofan design, LES, turbulence, and heat transfer. Muting has so far studied unsteady flows in applications including gas turbines, compressors, stream turbines and nuclear reactor coolant pump. Muting will continue focus on aerospace CFD research and integrating machine learning with fluid dynamics.

Related Academics

Publications

Muting Hao and Luca di Mare, Heat transfer and budgets of turbulent heat flux in film cooling with fan-shaped and cylindrical holes,International Journal of Heat and Mass Transfer, Volume 217,(2023):124687. Muting Hao and Luca di Mare. ”Reynolds stresse

 

Heat transfer and turbulent heat flux budgets in cooling films

Hao M & di Mare L (2023), International Journal of Heat and Mass Transfer, 217

Altmetric score is
BibTeX View PDF
@article{heattransferand-2023/9,
  title={Heat transfer and turbulent heat flux budgets in cooling films},
  author={Hao M & di Mare L},
  journal={International Journal of Heat and Mass Transfer},
  volume={217},
  number={124687},
  publisher={Elsevier},
  year = "2023"
}

Budgets of Reynolds stresses in film cooling with fan-shaped and cylindrical holes

Hao M & di Mare L (2023), Physics of Fluids, 35(8)

Altmetric score is
BibTeX View PDF
@article{budgetsofreynol-2023/8,
  title={Budgets of Reynolds stresses in film cooling with fan-shaped and cylindrical holes},
  author={Hao M & di Mare L},
  journal={Physics of Fluids},
  volume={35},
  number={086103},
  publisher={AIP Publishing},
  year = "2023"
}

Scaling and similarity laws in three-dimensional wall jets

Hao M & di Mare L (2023), Physics of Fluids, 35(7)

Altmetric score is
BibTeX View PDF
@article{scalingandsimil-2023/7,
  title={Scaling and similarity laws in three-dimensional wall jets},
  author={Hao M & di Mare L},
  journal={Physics of Fluids},
  volume={35},
  number={075102},
  publisher={AIP Publishing},
  year = "2023"
}

Reynolds stresses and turbulent heat fluxes in fan-shaped and cylindrical film cooling holes

Hao M & di Mare L (2023), International Journal of Heat and Mass Transfer, 214

Altmetric score is
BibTeX View PDF
@article{reynoldsstresse-2023/6,
  title={Reynolds stresses and turbulent heat fluxes in fan-shaped and cylindrical film cooling holes},
  author={Hao M & di Mare L},
  journal={International Journal of Heat and Mass Transfer},
  volume={214},
  number={124324},
  publisher={Elsevier},
  year = "2023"
}

Divergence-free turbulent inflow data from realistic covariance tensor

Dreze Y, Hao M & di Mare L (2023), Physics of Fluids, 35(2)

Altmetric score is
BibTeX View PDF
@article{divergencefreet-2023/2,
  title={Divergence-free turbulent inflow data from realistic covariance tensor},
  author={Dreze Y, Hao M & di Mare L},
  journal={Physics of Fluids},
  volume={35},
  number={025120},
  publisher={AIP Publishing},
  year = "2023"
}

Generation of turbulent in???ow data from realistic approximations of the covariance tensor

Hao M, Hope-Collins J & di Mare L (2022), Physics of Fluids, 34

Altmetric score is
BibTeX View PDF
@article{generationoftur-2022/10,
  title={Generation of turbulent in???ow data from realistic approximations of the covariance tensor},
  author={Hao M, Hope-Collins J & di Mare L},
  journal={Physics of Fluids},
  volume={34},
  number={115140 },
  publisher={AIP Publishing},
  year = "2022"
}

Template-Based Hexahedral Mesh Generation for Turbine Cooling Geometries

Hao M, Wang F, Hope-Collins J, Rife ME & di Mare L (2020)

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BibTeX View PDF
@inproceedings{templatebasedhe-2020/9,
  title={Template-Based Hexahedral Mesh Generation for Turbine Cooling Geometries},
  author={Hao M, Wang F, Hope-Collins J, Rife ME & di Mare L},
  booktitle={Volume 2C: Turbomachinery},
  year = "2020"
}

Off-design performance comparative analysis of a transcritical CO2 power cycle using a radial turbine by different operation methods

Du Y, Chen H, Hao M, Qiang X, Wang J et al. (2018), Energy Conversion and Management, 168, 529-544

Altmetric score is
BibTeX View PDF
@article{offdesignperfor-2018/7,
  title={Off-design performance comparative analysis of a transcritical CO2 power cycle using a radial turbine by different operation methods},
  author={Du Y, Chen H, Hao M, Qiang X, Wang J et al.},
  journal={Energy Conversion and Management},
  volume={168},
  pages={529-544},
  publisher={Elsevier},
  year = "2018"
}

Off-design performance comparative analysis between basic and parallel dual-pressure organic Rankine cycles using radial inflow turbines

Du Y, Yang Y, Hu D, Hao M, Wang J et al. (2018), Applied Thermal Engineering, 138, 18-34

Altmetric score is
BibTeX View PDF
@article{offdesignperfor-2018/6,
  title={Off-design performance comparative analysis between basic and parallel dual-pressure organic Rankine cycles using radial inflow turbines},
  author={Du Y, Yang Y, Hu D, Hao M, Wang J et al.},
  journal={Applied Thermal Engineering},
  volume={138},
  pages={18-34},
  publisher={Elsevier},
  year = "2018"
}

Off-Design Performance Comparative Analysis Between Dual-Pressure Organic Rankine Cycles Using Pure and Mixture Working Fluids

Du Y, Long Y, Hao M, Huo Y, Zhao P et al. (2018), v003t28a003-v003t28a003

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BibTeX View PDF
@inproceedings{offdesignperfor-2018/6,
  title={Off-Design Performance Comparative Analysis Between Dual-Pressure Organic Rankine Cycles Using Pure and Mixture Working Fluids},
  author={Du Y, Long Y, Hao M, Huo Y, Zhao P et al.},
  booktitle={Volume 3: Coal, Biomass, and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration; Organic Rankine Cycle Power Systems},
  pages={v003t28a003-v003t28a003},
  year = "2018"
}
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DPhil Opportunities

I am interested to hear from potential students who have interests in research areas spanning from fundamental fluid dynamics/aerodynamics/high order scheme/machine learning in CFD.