Books:
1. “Emulation of Complex Fluid Flows: Projection-Based Reduced-Order Modeling and Machine Learning,” De Gruyter publishing, Authors: Xingjian Wang and Vigor Yang
2. “Liquid Rocket Injectors” coauthored with Profs. Vigor Yang and Xiaodong Chen, to be published by AIAA
Journal Articles:
1. R Zuo, L Wang, X Wang*, ”Differential diffusion effect on near-field characteristics of hydrogen-enriched oxy-methane flames,” International Journal of Hydrogen Energy 144 (2025), p. 445-457
2. T Wan, L. Chen, X. Wang*, “Assessment and data-driven modeling of subgrid-scale thermophysical properties in supercritical channel flows,” International Journal of Heat and Mass Transfer, 247 (2025): 127184
3. M. Zhou, R. Zuo, C.-L. Sung, Y. Tong, X. Wang*, “Region-optimal Gaussian process surrogate model via Dirichlet process for cold-flow and combustion emulations,” Computer Methods in Applied Mechanics and Engineering 439 (2025): 117894
4. T. Wan, X. Wang*, Y. Jin, P. Zhao*, “Effects of large density variations on near-wall turbulence and heat transfer in channel flow at supercritical pressure,” Journal of Fluid Mechanics, 1007 (2025): A68
5. S. Ding, C. Ni, X. Chu, Q. Lu, X. Wang*, “Reduced-order modeling via convolutional autoencoder for combustion of hydrogen/methane fuel blends,” Combustion and Flame, 274 (2025): 113981
6. T. Wan, P. Zhao, X. Wang*, “Turbulence anisotropy in fully developed channel flow at supercritical pressure,” International Journal of Heat and Mass Transfer, 241 (2025): 126734
7. S. Ding, W. Wang, X. Wang*, “Spray characteristics of axial-vaned slinger atomizer in air crossflow,” Applied Thermal Engineering, 261 (2025): 125107
8. T Wan, M Zhou, P Zhao, X Wang*, “Challenges in the modeling and simulation of turbulent supercritical fluid flows and heat transfer,” Propulsion and Energy, 1 (2025):6
9. L Zhang, X Chu, S Ding, M Zhou, C Ni, X Wang*, “Surrogate Modeling of Hydrogen-Enriched Combustion Using Autoencoder-Based Dimensionality Reduction,” Processes 13 (4) (2025): 1093
10. J. Geng, H. Qi, J. Li, X. Wang*, “Local surrogate modeling for spatial emulation of gas-turbine combustion via similarity-based sample processing,” Journal of Engineering for Gas Turbines and Power, 146(10) (2024): 101019
11. C. Ni, S. Ding, J. Li, X. Chu, Z. Ren, X. Wang*, “Projection-based reduced order modeling of multi-species mixing and combustion,” Physics of Fluids 36 (2024): 077168
12. S. Ding, L. Wang, Q. Lu, X. Wang*, “Data-driven surrogate modeling and optimization of supercritical jet into supersonic crossflow,” Chinese Journal of Aeronautics, 2024, 37(12): 139-155
13. S. Ding, J. Li, X. Wang*, “Dynamics of elevated dodecane jets in crossflow at supercritical pressure,” Physics of Fluids, 36 (2024), 075135
14. C.L. Sung, W. Wang, L. Ding, X Wang, “Mesh-clustered Gaussian process emulator for partial differential equation boundary value problems,” Technometrics, Vol. 66:3(2024), p. 406-421
15. L. Wang , H. Xiao , B. Yang , X. Wang*, “Steam dilution effect on laminar flame characteristics of hydrogen-enriched oxy-combustion,” International Journal of Hydrogen Energy, Vol. 71 (2024), p. 375–386
16. M. Zhou, C. Ni, and X. Wang*, “Modeling of thermophysical properties and vapor-liquid equilibrium using Gaussian process regression,” International Journal of Heat and Mass Transfer, 219 (2024) 124888
17. S. Ding, J. Li, L. Wang, and X. Wang*, “Flow Dynamics of a Dodecane Jet in Oxygen Crossflow at Supercritical Pressures,” AIAA Journal, Vol. 62 No. 5 (2024), p. 1840-1853
18. J. Geng, X. Wang, J. Liu, F. Teng, and H. Qi, “Surrogate model of combustor flow mixing process,” Journal of Tsinghua University, Vol. 63, No. 4 (2023), p. 633-641
19. M. Zhou, S. Ding, and X. Wang*, “Review of subgrid models of equation of state in the large eddy simulation of transcritical and supercritical flows andcombustion,” Journal of Tsinghua University, Vol. 63, No. 4 (2023), p. 473-486
20. M. Zhou, W. Chen, X. Su, C.-L. Sung, X. Wang*, and Z. Ren, “Data-Driven Modeling of General Fluid Density Under Subcritical and Supercritical Conditions,”, AIAA Journal, 2023, Vol. 61, No. 4 (2023), p. 1519-1531
21. C. Ni, X. Wang*, H. Liu, K. Zhang, X. Zheng, and Y. Duan, “Physics-informed deep learning for thermophysical properties of carbon dioxide,” Journal of Thermophysics and Heat Transfer, Vol. 37, No. 2 (2023), p. 382-393
22. S. Ding, C. Ni, W. Wang*, “Nearfield flow characteristics of kerosene injection at supercritical pressures,” Journal of Propulsion Technology, 2022
23. X. Wang*, T. Liu, D. Ma, and V. Yang, “Linear stability of real-fluid mixing layers at supercritical pressures,” Physics of Fluids, Vol. 34 (2022), 084106
24. L. Zhang, Y. Li, X. Wang, and V. Yang, “Effect of Recess Length on Flow Dynamics in Gas-Centered Liquid-Swirl Coaxial Injectors under Supercritical Conditions,” Aerospace Science and Technology, Vol. 128 (2022), 107757
25. P. Milan, J.-P. Hickey, X. Wang, and V. Yang, “Deep-learning accelerated calculation of real-fluid properties in numerical simulation of complex flowfields,” Journal of Computational Physics, Vol. 444 (2021), 110567
26. Y.H. Chang, X. Wang, L. Zhang, Y. Li, S. Mak, C.F.J. Wu, and V. Yang, “An efficient reduced-order model CKSPOD for emulation of spatiotemporally evolving flows,”, AIAA Journal, Vol.59, No. 9 (2021), pp. 3291–3303
27. T. Liu, X. Wang*, and V. Yang*, “Flow dynamics of shear-coaxial cryogenic nitrogen jets under supercritical conditions with and without acoustic excitations,” Physics of Fluids, Vol. 33, No. 7, (2021), pp. 076111
28. U. Unnikrishnan, H. Huo, X. Wang, and V. Yang, “Subgrid scale modeling considerations for large eddy simulation of supercritical turbulent mixing and combustion,”. Physics of Fluids, Vol. 33, No. 7, (2021), pp. 075112.
29. X. Wang, Y.H. Chang, Y. Li, V. Yang, and Y.H. Su, “Surrogate-based modeling for emulation of supercritical injector flow and combustion,” Proceedings of the Combustion Institute, Vol.38, No. 4 (2021) pp. 6393-6401
30. X. Wang, P. Lafon, D. Sundaram, and V. Yang, “Liquid vaporization under thermodynamic phase non-equilibrium condition at the gas-liquid interface,” Science China Technological Sciences, Vol. 63, No. 12 (2020) pp. 2649-2656.
31. S. Yang, X. Wang, W. Sun, and V. Yang, “Comparison of Finite Rate Chemistry and Flamelet/Progress-Variable Models: Sandia Flames and the Effect of Differential Diffusion,” Combustion Science and Technology, Vol. 192, No. 7 (2020), pp. 1137-1159.
32. S. Yang, X. Wang, H. Huo, W. Sun, and V. Yang, “An Efficient Finite-Rate Chemistry Model for a Preconditioned Compressible Flow Solver and its Comparison with the Flamelet/Progress-Variable Model,” Combustion and Flame, Vol. 210 (2019), pp. 172-182
33. Y.-H. Chang, L. Zhang, X. Wang, S.-T. Yeh, S. Mak, C.L. Sung, C.F.J. Wu, and V. Yang, “Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for spatiotemporally evolving flow dynamics prediction,” AIAA Journal, AIAA Journal, Vol. 57 No. 12 (2019), 5269-5280
34. X. Wang, Y. Wang, and V. Yang, “Three-dimensional flow dynamics and mixing in a gas-centered liquid-swirl coaxial injector at supercritical pressure,” Physics of Fluids, Vol. 31, (2019) 065109. (FRONT COVER)
35. Y. Wang, X. Chen, X. Wang, and V. Yang, “Vaporization of liquid droplet with large deformation and high mass transfer rate, II: variable-density, variable-property case,” Journal of Computational Physics, Vol. 394 (2019), pp. 1-17
36. X. Wang, S.-T. Yeh, Y.-H. Chang, and V. Yang, “A high-fidelity design methodology using LES-based simulation and POD-based emulation: a case study of swirl injectors,” Chinese Journal of Aeronautics, Vol. 31 No. 9 (2018), pp. 1855-1869.
37. X. Wang, L. Zhang, Y. Li, S.-T. Yeh, and V. Yang, "Supercritical combustion of gas-centered liquid-swirl coaxial injectors for staged-combustion engines," Combustion and Flame, Vol. 197 (2018), pp. 204-214.
38. L. Zhang, X. Wang, Y. Li, S.-T. Yeh, and V. Yang, "Supercritical flow dynamics in a gas-centered liquid-swirl coaxial injector," Physics of Fluid, Vol. 30 (2018) 075106 (Editor’s Pick)
39. X. Wang, H. Huo, U. Unnikrishnan, and V. Yang, “A systematic approach to high-fidelity modeling and efficient simulation of supercritical fluid mixing and combustion,” Combustion and Flame, Vol. 195 (2018), pp. 203-215.
40. S.-T. Yeh, X. Wang*, C. Sung, S. Mak, Y. Chang, V. R. Joseph, V. Yang, and C.F. Wu, "Common proper orthogonal decomposition-based spatiotemporal emulator for design exploration," AIAA Journal, Vol. 56, No. 6 (2018), pp. 2429-2442.
41. S. Mak, C. Sung, X Wang, S. Yeh, Y. Chang, R. Joseph, V. Yang, C.F. Wu, “An efficient surrogate model for emulation and physics extraction of large eddy simulations,” Journal of the American Statistical Association, 113 No. 524 (2018), 1443-1456. (SPES Award)
42. Y. Wang, X. Wang, V. Yang, “Evolution and transition mechanisms of internal swirling flows with tangential entry,” Physics of Fluids Vol. 30, No. 1 (2018), pp. 013601 (Editor’s Pick)
43. X. Wang, Y. Li, Y. Wang, and V. Yang, "Near-field flame dynamics of liquid oxygen/kerosene bi-swirl injectors at supercritical conditions," Combustion and Flame, Vol.190 (2018), pp. 1-11.
44. X. Wang, Y. Wang, and V. Yang, "Geometric effects on liquid oxygen/kerosene bi-swirl injector flow dynamics at supercritical conditions," AIAA Journal, Vol. 55, No. 10 (2017), pp. 3467-3475.
45. X. Wang, H. Huo, Y. Wang, and V. Yang, “Comprehensive study of cryogenic fluid dynamics of swirl injectors at supercritical conditions,” AIAA Journal, Vol. 55, No. 9 (2017), pp. 3109-3119.
46. X. Wang and V. Yang, "Supercritical mixing and combustion of liquid-oxygen /kerosene bi-swirl injectors ," Journal of Propulsion and Power, 33(2) (2017), p. 316-322.
47. X. Wang, H. Huo, and V. Yang, "Counterflow diffusion flames of oxygen and n-alkane hydrocarbons (CH4-C16H34) at subcritical and supercritical conditions," Combustion Science and Technology, 187(1-2) (2015), p. 60-82.
48. H. Huo, X. Wang, and V. Yang, "A general study of counterflow diffusion flames at subcritical and supercritical conditions: Oxygen/hydrogen mixtures," Combustion and Flame, 161(12) (2014), p. 3040-3050.