您的位置:首页 >> 教职员工 >> 陈帜

Updated 2025/July/6   (*Corresponding Author  #Joint First Author)

See latest at Google Scholar 


BOOK CHAPTERS
  1. S. Iavarone, H. Yang, Z. Li, Z. X. Chen, and N. Swaminathan. “On the Use of Machine Learning for Subgrid Scale Filtered Density Function Modelling in Large Eddy Simulations of Combustion Systems”, in Machine Learning and Its Application to Reacting Flows, N. Swaminathan and A. Parente (eds.),  ISBN 978-3-031-16248-0, Springer Nature, Cham, Switzerland (2023). DOI

  2. J. C. Massey*, Z. X. Chen, N. Swaminathan. “Flame Root Dynamics and Their Role in the Stabilisation of Lifted Flames”, in Advances in Energy and Combustion, Green Energy and Technology, A. Gupta et al. (eds.), ISBN 978-981-16-2647-0, Springer Nature, Singapore (2022). DOI
  3. Z. X. Chen*, I. Langella, N. Swaminathan. “The Role of CFD in Modern Jet Engine Combustor Design” in Environmental Impact of Aviation and Sustainable Solutions, R. K. Agarwal (eds.), ISBN 978-1-83962-358-5, Intech Open Ltd., London, UK (2019). DOI


SELECTED JOURNALS
  1. M. Lin, J. Fang*, X. Deng, X. Gu, Z. X. Chen*. "Direct numerical simulation of inflow boundary-layer turbulence effects on cavity flame stabilisation in a model scramjet combustor", Aerosp. Sci. Technol. 165:110463 (2025). DOI
  2. H. Li, R. Yang, Y. Xu, M. Zhang, R. Mao, Z. X. Chen*. "Comprehensive deep learning for combustion chemistry integration: Multi-fuel generalization and a posteriori validation in reacting flow", Phys. Fluids 37:015162 (2025). DOI
  3. R. Mao, X. Dong, X. Bai, Z. Wu, G. Dang, H. Li, Z. X. Chen*. "DeepFlame 2. 0 : A new version for fully GPU-native machine learning accelerated reacting flow simulations under low-Mach conditions", Comput. Phys. Commun. 312:109595 (2025). DOI 
  4. Z. An*, R. Wang, R. Mao*, J. Xing, M. Zhang, Z. X. Chen*, R. Kurose. "Flame stability and emission characteristics of oxygen-enriched ammonia combustion in a swirl combustor", Energy 324:135829 (2025). DOI 
  5. H. Li, K. Xiao, Y. Xu, W. Yuan, F. Qi, Z. X. Chen*. "Detailed simulation of RP-3 kerosene turbulent combustion using reduced chemical mechanisms", Fuel 396:135285 (2025). DOI 
  6. Y. Cai, R. Yang, H. Li, J. Xu, K. Xiao, Z. X. Chen*, H. Wang*. "Efficient machine learning method for supercritical combustion: Predicting real-fluid properties and chemical ODEs", Aerosp. Sci. Technol. 159:110034 (2025). DOI
  7. R. Mao, M. Zhang, Y. Wang, H. Li, J. Xu, X. Dong Y. Zhang, Z. X. Chen*. "An integrated framework for accelerating reactive flow simulation using GPU and machine learning models", Proc. Combust. Inst. 40:105512 (2024). DOI
  8. M. Zhang, R. Mao, H. Li, Z. An, Z. X. Chen*. "Graphics processing unit/artificial neural network-accelerated large-eddy simulation of swirling premixed flames", Phys. Fluids 36:055147 (2024). DOI
  9. R. Mao, M. Lin, Y. Zhang*, T. Zhang, Z.-Q. J. Xu, Z. X. Chen*. "DeepFlame: A deep learning empowered open-source platform for reacting flow simulations", Comput. Phys. Commun. 291:108842 (2023). DOI  arXiv
  10. Y. Xu, Z. X. Chen*. "Direct numerical simulations of the Taylor-Green vortex interacting with a hydrogen diffusion flame: Reynolds number and non-unity-Lewis number effects"Phys. Fluids 35:045128 (2023). [Editor's Pick] DOI  arXiv
  11. H. Yang*, T. Kobayashi, S. Iavarone, J. C. Massey, Z. X. Chen*, Y. Minamoto, N. Swaminathan. "Towards a generalised artificial neural network for sub-grid filtered density function closure in turbulent combustion", Appl. Energy Combust. Sci. 14:100124 (2023). DOI
  12. J. Fang, X. Deng, Z. X. Chen*. "Direct numerical simulation of supersonic internal flow in a model scramjet combustor under a non-reactive condition"Phys. Fluids 35:026103 (2023). [Editor's Pick] DOI
  13. Z. X. Chen*, N. Swaminathan, M. Mazur, N. A. Worth, G. Zhang, L. Li. "Numerical investigation of azimuthal thermoacoustic instability in a gas turbine model combustor", Fuel 339:127405 (2023). DOI  arXiv
  14. J. C. Massey*, Z. Li, Z. X. Chen*, Y. Tanaka, N. Swaminathan. "Large eddy simulation of multi-regime combustion with a two-progress variable approach for carbon monoxide", Proc. Combust. Inst. 39:2117-2127 (2023). DOI
  15. Z. X. Chen*, S. Iavarone, G. Ghiasi, V. Kanan, G. D’Alessio, A. Parente, N. Swaminathan. “Application of machine learning for filtered density function closure in MILD combustion”, Combust. Flame 225:160-179 (2021). DOI

  16. M. Zhao#Z. X. Chen#, H. Zhang*, N. Swaminathan. “Large Eddy simulation of a supersonic lifted hydrogen flame with perfectly stirred reactor model”. Combust. Flame 230:111441 (2021). DOI  arXiv
  17. Z. Li*, S. Tomasch, Z. X. Chen*, A. Parente, I. S. Ertesvåg, N. Swaminathan. “Study of MILD combustion using LES and advanced analysis tools”. Proc. Combust. Inst. 38:5423-5432 (2021). DOI
  18. S. Iavarone*, A. Péquin, Z. X. Chen*, N. A. D. Doan, N. Swaminathan, A. Parente*. “An a-priori assessment of the Partially Stirred Reactor (PaSR) model for MILD combustion”. Proc. Combust. Inst. 38:5403-5414 (2021). DOI
  19. Z. X. Chen*, N. Swaminathan. “Influence of fuel plenum on thermoacoustic oscillations inside a swirl combustor”. Fuel 275:117868 (2020). DOI
  20. Z. X. Chen*#, I. Langella*#, R. S. Barlow*, N. Swaminathan. “Prediction of local extinctions in piloted jet flames with inhomogeneous inlets using unstrained flamelets”. Combust. Flame 212:415-423 (2020). DOI
  21. Z. X. Chen*, I. Langella, N. Swaminathan, M. Stöhr, W. Meier, H. Kolla. “Large Eddy Simulation of a dual swirl gas turbine combustor: Flame/flow structures and stabilisation under thermoacoustically stable and unstable conditions”. Combust. Flame 203:279-300 (2019). DOI
  22. Z. X. Chen*, N. Swaminathan, M. Stöhr, W. Meier. “Interaction between self-excited oscillations and fuel-air mixing in a dual swirl combustor”, Proc. Combust. Inst. 37:2325-2333 (2019). DOI
  23. J. C. Massey, Z. X. Chen*, N. Swaminathan. “Lean flame root dynamics inside a model gas turbine combustor”. Combust. Sci. Technol. 191:1019-1042 (2019). DOI
  24. Z. X. Chen*, N. A. K. Doan, X. J. Lv, N. Swaminathan, G. Ceriello, G. Sorrentino, A. Cavaliere. “A numerical study of a cyclonic combustor under MILD conditions using non-adiabatic tabulated chemistry”, Energy Fuels 32:10256-10265 (2018). DOI
  25. Z. X. Chen*, N. A. K. Doan, S. Ruan, I. Langella, N. Swaminathan. “A priori investigation of subgrid correlation of mixture fraction and progress variable in partially premixed flames”. Combust. Theory Model. 22:862-882 (2018). DOI
  26. Z. Chen, V. M. Reddy, S. Ruan, N. A. K. Doan, W. L. Roberts*, N. Swaminathan. “Simulation of MILD combustion using Perfectly Stirred Reactor model”. Proc. Combust. Inst. 36:4279-4286 (2017). DOI
  27. Z. Chen*, S. Ruan, N. Swaminathan. “Large Eddy Simulation of flame edge evolution in a spark-ignited methane-air jet”. Proc. Combust. Inst. 36:1645-1652 (2017). DOI
  28. Z. Chen*, S. Ruan, N. Swaminathan. “Numerical study of transient evolution of lifted jet flames: partially premixed flame propagation and influence of physical dimensions”. Combust. Theory Model. 20:592-612 (2016). DOI
  29. Z. Chen, S. Ruan, N. Swaminathan*. “Simulation of turbulent lifted methane jet flames: Effects of air-dilution and transient flame propagation”. Combust. Flame 162:703-716 (2015). DOI