Lian-Ping Wang Explained

Lian-Ping Wang
Birth Date:1965
Birth Place:Linhai, Zhejiang, China
Nationality:American
Occupation:Mechanical engineer and academic
Education:BS., Applied Mathematics and Engineering Mechanics
PhD., Mechanical Engineering
Alma Mater:Zhejiang University
Washington State University
Thesis Title:On the dispersion of heavy particles by turbulent motion
Doctoral Advisor:David E. Stock
Thesis Year:1990
Workplaces:University of Delaware
Southern University of Science and Technology

Lian-Ping Wang is a mechanical engineer and academic, most known for his work on computational fluid dynamics, turbulence, particle-laden flow, and immiscible multiphase flow, and their applications to industrial and atmospheric processes.[1] He is the Chair Professor of Mechanics and Aerospace Engineering at the Southern University of Science and Technology in China,[2] Professor of Mechanical Engineering, and Joint Professor of Physical Ocean Science and Engineering at University of Delaware.[3]

Wang's research primarily focuses on fundamental physics in turbulent multiphase flows, utilizing computational fluid dynamics (CFD) modeling for intricate flows across various systems, including industrial, natural, and biological contexts. He developed traditional Navier-Stokes-based CFD methods and mesoscopic Boltzmann-equation based methods, like the lattice Boltzmann method and discrete unified gas kinetic scheme, as direct numerical simulation tools for complex turbulent and multiphase flows. He also devised numerical methods for studying complex fluid flow and transport in fuel cells and soil porous media, as well as the transport and retention of colloids and nanoparticles in the subsurface environment.[4]

Wang is an elected Fellow of the American Society of Mechanical Engineers[5] and the American Physical Society.[6] He was named in the World's Top 2% Scientists list by Stanford University in 2023 and in the Most Cited Chinese Researchers list by Elsevier in 2021 and 2022. In addition, he is an Associate Editor of the Journal of Fluid Mechanics[7] and Theoretical and Applied Mechanics Letters,[8] as well as a member of the Editorial Advisory Board for the International Journal of Multiphase Flow.[9]

Education

Wang received a bachelor's degree in Mechanics in 1984 from Zhejiang University, before going to the US for PhD study, and subsequently obtained a PhD in Mechanical Engineering from Washington State University in 1990. During his PhD, he developed a theoretical model predicting the turbulent dispersion of sedimenting inertial particles, concurrently developing an empirical correlation for the integral time scale of fluid velocity observed by such particles, which came to be known as the Wang and Stock correction in multiphase flow literature.[10]

Career and research

During his postdoctoral tenure with Martin Maxey, they authored a paper on particle-laden turbulent flows, utilizing DNS to reveal novel effects of small-scale turbulence structure on particle behavior.[11] At Penn State, he conducted a study on Kolmogorov refined similarity using high-resolution DNS flows, measuring various quantities related to the intermittency and scaling dynamics of fine-scale turbulence.[12]

In 1994, Wang joined the University of Delaware as an assistant professor of Mechanical Engineering, later becoming an associate professor in 2001 and Professor in 2009. He serves as a Chair Professor of Mechanics and Aerospace Engineering and Director of the Center for Computational Science and Engineering at the Southern University of Science and Technology in China,[13] Professor of Mechanical Engineering, and Joint Professor of Physical Ocean Science and Engineering at the University of Delaware.[3]

During the period of 1998 to 2013, Wang's research concentrated on the turbulent collision rate and collision efficiency of inertial particles, where he played a role in establishing a theoretical foundation for the collision kernel, generating rigorous collision rate data from DNS, providing an analytical parameterization of the turbulent collision kernel, and studying the impact of turbulent collision on warm rain initiation.[14] [15] [16] [17] In 2012, he investigated the transport and retention of colloids and nanoparticles in porous media, considering the effects of physicochemical interaction forces. Using the lattice Boltzmann method and Lagrangian particle tracking, he explored multiscale reversible particle retention near grain surfaces, with factors like flow speed, ionic strength, and surface characteristics influencing the retention rate.[18] [19]

In recent years, Wang developed a lattice Boltzmann-based particle-resolving simulation tool to study turbulence modulation by finite-size solid particles, revealing size-dependent characteristics.[20] [21] His group improved lattice Boltzmann method implementation for moving boundaries, enhancing numerical stability and computational efficiency, including the first DNS of turbulent pipe flow using the lattice Boltzmann method.[22] [23] [24] He also developed lattice-Boltzmann models fully consistent with Navier-Stokes equations, such as the use of 2D rectangular or 3D cuboid lattices,[25] [26] and introduced a new D3Q27 lattice Boltzmann model enabling mesoscopic computation of local fluid vorticity, derived through an inverse design approach using hydrodynamic equations.[27] Wang further applied the particle-resolving simulation tool to study the enhancement of particle drag in a turbulent background flow[28] and dynamics of non-spherical particles.[29]

Awards and honors

Selected articles

External links

Notes and References

  1. Web site: WANG Lianping - Faculty Profiles - SUSTech. faculty.sustech.edu.cn.
  2. Web site: WANG Lianping - Faculty - SUSTech. www.sustech.edu.cn.
  3. Web site: Home Page for Lian-Ping (Huanlin) Wang. research.me.udel.edu.
  4. Web site: Lian-Ping Wang. scholar.google.com.
  5. Web site: ASME Fellow. Vicky. Tosh-Morelli. November 3, 2016.
  6. Web site: APS Fellow Archive. aps.org.
  7. Web site: Editorial board. Cambridge Core.
  8. Web site: Editorial board - Theoretical and Applied Mechanics Letters | ScienceDirect.com by Elsevier. www.sciencedirect.com.
  9. Web site: Editorial board - International Journal of Multiphase Flow | ScienceDirect.com by Elsevier. www.sciencedirect.com.
  10. Dispersion of Heavy Particles by Turbulent Motion. Lian-Ping. Wang. Davd E.. Stock. July 1, 1993. Journal of the Atmospheric Sciences. 50. 13. 1897–1913. journals.ametsoc.org. 10.1175/1520-0469(1993)050<1897:DOHPBT>2.0.CO;2.
  11. Settling velocity and concentration distribution of heavy particles in homogeneous isotropic turbulence. Lian-Ping. Wang. Martin R.. Maxey. November 29, 1993. Journal of Fluid Mechanics. 256. 27–68. Cambridge University Press. 10.1017/S0022112093002708.
  12. Examination of hypotheses in the Kolmogorov refined turbulence theory through high-resolution simulations. Part 1. Velocity field. Lian-Ping. Wang. Shiyi. Chen. James G.. Brasseur. John C.. Wyngaard. February 29, 1996. Journal of Fluid Mechanics. 309. 113–156. Cambridge University Press. 10.1017/S0022112096001589.
  13. Web site: Center for Computational Science and Engineering enhances user experience. newshub.sustech.edu.cn.
  14. Statistical mechanical description and modelling of turbulent collision of inertial particles. Lian-Ping. Wang. Anthony S.. Wexler. Yong. Zhou. July 29, 2000. Journal of Fluid Mechanics. 415. 117–153. Cambridge University Press. 10.1017/S0022112000008661.
  15. Modelling turbulent collision of bidisperse inertial particles. Yong. Zhou. Anthony S.. Wexler. Lian-Ping. Wang. April 29, 2001. Journal of Fluid Mechanics. 433. 77–104. Cambridge University Press. 10.1017/S0022112000003372.
  16. Theoretical Formulation of Collision Rate and Collision Efficiency of Hydrodynamically Interacting Cloud Droplets in Turbulent Atmosphere. Lian-Ping. Wang. Orlando. Ayala. Scott E.. Kasprzak. Wojciech W.. Grabowski. July 1, 2005. Journal of the Atmospheric Sciences. 62. 7. 2433–2450. journals.ametsoc.org. 10.1175/JAS3492.1.
  17. Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization. Orlando. Ayala. Bogdan. Rosa. Lian-Ping. Wang. September 29, 2008. New Journal of Physics. 10. 9. 099802. Institute of Physics. 10.1088/1367-2630/10/9/099802. free.
  18. Role of Mixed Boundaries on Flow in Open Capillary Channels with Curved Air–Water Interfaces. Wenjuan. Zheng. Lian-Ping. Wang. Dani. Or. Volha. Lazouskaya. Yan. Jin. September 4, 2012. Langmuir. 28. 35. 12753–12761. CrossRef. 10.1021/la302833p.
  19. Application of DLVO Energy Map To Evaluate Interactions between Spherical Colloids and Rough Surfaces. Chongyang. Shen. Feng. Wang. Baoguo. Li. Yan. Jin. Lian-Ping. Wang. Yuanfang. Huang. October 16, 2012. Langmuir. 28. 41. 14681–14692. CrossRef. 10.1021/la303163c.
  20. Lattice Boltzmann simulation of turbulent flow laden with finite-size particles. Hui. Gao. Hui. Li. Lian-Ping. Wang. January 1, 2013. Computers & Mathematics with Applications. 65. 2. 194–210. ScienceDirect. 10.1016/j.camwa.2011.06.028. free.
  21. Study of forced turbulence and its modulation by finite-size solid particles using the lattice Boltzmann approach. Lian-Ping. Wang. Orlando. Ayala. Hui. Gao. Charles. Andersen. Kevin L.. Mathews. February 1, 2014. Computers & Mathematics with Applications. 67. 2. 363–380. ScienceDirect. 10.1016/j.camwa.2013.04.001. free.
  22. Implementation issues and benchmarking of lattice Boltzmann method for moving rigid particle simulations in a viscous flow. Cheng. Peng. Yihua. Teng. Brian. Hwang. Zhaoli. Guo. Lian-Ping. Wang. July 1, 2016. Computers & Mathematics with Applications. 72. 2. 349–374. ScienceDirect. 10.1016/j.camwa.2015.08.027. free.
  23. Issues associated with Galilean invariance on a moving solid boundary in the lattice Boltzmann method. Cheng. Peng. Nicholas. Geneva. Zhaoli. Guo. Lian-Ping. Wang. January 3, 2017. Physical Review E. 95. 1. 013301. APS. 10.1103/PhysRevE.95.013301. free.
  24. A scalable interface-resolved simulation of particle-laden flow using the lattice Boltzmann method. Nicholas. Geneva. Cheng. Peng. Xiaoming. Li. Lian-Ping. Wang. September 1, 2017. Parallel Computing. 67. 20–37. ScienceDirect. 10.1016/j.parco.2017.07.005. free.
  25. Designing correct fluid hydrodynamics on a rectangular grid using MRT lattice Boltzmann approach. Yuan. Zong. Cheng. Peng. Zhaoli. Guo. Lian-Ping. Wang. July 1, 2016. Computers & Mathematics with Applications. 72. 2. 288–310. ScienceDirect. 10.1016/j.camwa.2015.05.021.
  26. A hydrodynamically-consistent MRT lattice Boltzmann model on a 2D rectangular grid. Cheng. Peng. Haoda. Min. Zhaoli. Guo. Lian-Ping. Wang. December 1, 2016. Journal of Computational Physics. 326. 893–912. ScienceDirect. 10.1016/j.jcp.2016.09.031.
  27. Lattice Boltzmann model capable of mesoscopic vorticity computation. Cheng. Peng. Zhaoli. Guo. Lian-Ping. Wang. November 6, 2017. Physical Review E. 96. 5. 053304. APS. 10.1103/PhysRevE.96.053304. free.
  28. Mechanisms and models of particle drag enhancements in turbulent environments. Cheng. Peng. Lian-Ping. Wang. March 22, 2023. Journal of Fluid Mechanics. 959. A30. Cambridge University Press. 10.1017/jfm.2023.152.
  29. Three-dimensional sedimentation patterns of two interacting disks in a viscous fluid. Yi. Liu. Yu. Guo. Bo. Yang. Dingyi. Pan. Zhenhua. Xia. Zhaosheng. Yu. Lian-Ping. Wang. April 10, 2023. Journal of Fluid Mechanics. 960. A25. arXiv.org. 10.1017/jfm.2023.186. 2301.06338.
  30. Web site: World's Best Mechanical and Aerospace Engineering Scientists: H-Index Mechanical and Aerospace Engineering Science Ranking in China 2023 | Research.com.

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