Lian-Ping Wang | |
---|---|
Born | 1965 Linhai, Zhejiang, China |
Nationality | American |
Occupation(s) | Mechanical engineer and academic |
Academic background | |
Education | BS., Applied Mathematics and Engineering Mechanics PhD., Mechanical Engineering |
Alma mater | Zhejiang University Washington State University |
Thesis | On the dispersion of heavy particles by turbulent motion (1990) |
Doctoral advisor | David E. Stock |
Academic work | |
Institutions | 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]
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]
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]
Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perform the calculations required to simulate the free-stream flow of the fluid,and the interaction of the fluid with surfaces defined by boundary conditions. With high-speed supercomputers,better solutions can be achieved,and are often required to solve the largest and most complex problems. Ongoing research yields software that improves the accuracy and speed of complex simulation scenarios such as transonic or turbulent flows. Initial validation of such software is typically performed using experimental apparatus such as wind tunnels. In addition,previously performed analytical or empirical analysis of a particular problem can be used for comparison. A final validation is often performed using full-scale testing,such as flight tests.
The lattice Boltzmann methods (LBM),originated from the lattice gas automata (LGA) method (Hardy-Pomeau-Pazzis and Frisch-Hasslacher-Pomeau models),is a class of computational fluid dynamics (CFD) methods for fluid simulation. Instead of solving the Navier–Stokes equations directly,a fluid density on a lattice is simulated with streaming and collision (relaxation) processes. The method is versatile as the model fluid can straightforwardly be made to mimic common fluid behaviour like vapour/liquid coexistence,and so fluid systems such as liquid droplets can be simulated. Also,fluids in complex environments such as porous media can be straightforwardly simulated,whereas with complex boundaries other CFD methods can be hard to work with.
In fluid mechanics,multiphase flow is the simultaneous flow of materials with two or more thermodynamic phases. Virtually all processing technologies from cavitating pumps and turbines to paper-making and the construction of plastics involve some form of multiphase flow. It is also prevalent in many natural phenomena.
This is an alphabetical list of articles pertaining specifically to Engineering Science and Mechanics (ESM). For a broad overview of engineering,please see Engineering. For biographies please see List of engineers and Mechanicians.
Gretar Tryggvason is Department Head of Mechanical Engineering and Charles A. Miller Jr. Distinguished Professor at Johns Hopkins University. He is known for developing the front tracking method to simulate multiphase flows and free surface flows. Tryggvason was the editor-in-chief of Journal of Computational Physics from 2002–2015.
Hubert Chanson is a professional engineer and academic in hydraulic engineering and environmental fluid mechanics. Since 1990 he has worked at the University of Queensland.
The moving particle semi-implicit (MPS) method is a computational method for the simulation of incompressible free surface flows. It is a macroscopic,deterministic particle method developed by Koshizuka and Oka (1996).
A bubble column reactor is a chemical reactor that belongs to the general class of multiphase reactors,which consists of three main categories:trickle bed reactor,fluidized bed reactor,and bubble column reactor. A bubble column reactor is a very simple device consisting of a vertical vessel filled with water with a gas distributor at the inlet. Due to the ease of design and operation,which does not involve moving parts,they are widely used in the chemical,biochemical,petrochemical,and pharmaceutical industries to generate and control gas-liquid chemical reactions.
Particle-laden flows refers to a class of two-phase fluid flow,in which one of the phases is continuously connected and the other phase is made up of small,immiscible,and typically dilute particles. Fine aerosol particles in air is an example of a particle-laden flow;the aerosols are the dispersed phase,and the air is the carrier phase.
The extended discrete element method (XDEM) is a numerical technique that extends the dynamics of granular material or particles as described through the classical discrete element method (DEM) by additional properties such as the thermodynamic state,stress/strain or electro-magnetic field for each particle. Contrary to a continuum mechanics concept,the XDEM aims at resolving the particulate phase with its various processes attached to the particles. While the discrete element method predicts position and orientation in space and time for each particle,the extended discrete element method additionally estimates properties such as internal temperature and/or species distribution or mechanical impact with structures.
In experimental fluid mechanics,Lagrangian Particle Tracking refers to the process of determining trajectories of small neutrally buoyant particles that are freely suspended within a turbulent flow field. These are usually obtained by 3-D Particle Tracking Velocimetry. A collection of such particle trajectories can be used for analyzing the Lagrangian dynamics of the fluid motion,for performing Lagrangian statistics of various flow quantities etc.
Dimitris Drikakis,PhD,FRAeS,CEng,is a Greek-British applied scientist,engineer and university professor. His research is multidisciplinary. It covers fluid dynamics,computational fluid dynamics,acoustics,heat transfer,computational science from molecular to macro scale,materials,machine learning,and emerging technologies. He has applied his research to diverse fields such as Aerospace &Defence,Biomedical,and Energy and Environment Sectors. He received The William Penney Fellowship Award by the Atomic Weapons Establishment to recognise his contributions to compressible fluid dynamics. He was also the winner of NEF's Innovator of the Year Award by the UK's Institute of Innovation and Knowledge Exchange for a new generation carbon capture nanotechnology that uses carbon nanotubes for filtering out carbon dioxide and other gases.
OpenLB is an object-oriented implementation of the lattice Boltzmann methods (LBM). It is the first implementation of a generic platform for LBM programming,which is shared with the open source community (GPLv2). The code is written in C++ and is used by application programmers as well as developers,with the ability to implement custom models OpenLB supports complex data structures that allow simulations in complex geometries and parallel execution using MPI,OpenMP and CUDA on high-performance computers. The source code uses the concepts of interfaces and templates,so that efficient,direct and intuitive implementations of the LBM become possible. The efficiency and scalability has been checked and proved by code reviews. A user manual and a source code documentation by DoxyGen are available on the project page.
Sivaramakrishnan Balachandar is a professor at the University of Illinois Urbana-Champaign. Sivaramakrishnan is an American physicist,a Distinguished Professor and William F. Powers Professor at University of Florida.
Charles Meneveau is a French-Chilean born American fluid dynamicist,known for his work on turbulence,including turbulence modeling and computational fluid dynamics.
Joseph Katz is an Israel-born American fluid dynamicist,known for his work on experimental fluid mechanics,cavitation phenomena and multiphase flow,turbulence,turbomachinery flows and oceanography flows,flow-induced vibrations and noise,and development of optical flow diagnostics techniques,including Particle Image Velocimetry (PIV) and Holographic Particle Image Velocimetry (HPIV). As of 2005,he is the William F. Ward Sr. Distinguished Professor at the Department of Mechanical Engineering of the Whiting School of Engineering at the Johns Hopkins University.
Yves Pomeau,born in 1942,is a French mathematician and physicist,emeritus research director at the CNRS and corresponding member of the French Academy of sciences. He was one of the founders of the Laboratoire de Physique Statistique,École Normale Supérieure,Paris. He is the son of literature professor RenéPomeau.
Reda R. Mankbadi is the founding Dean of the Engineering College at Embry-Riddle Aeronautical University. He is a former NASA senior scientist at NASA's Glenn Research Center and a Fellow of the NASA Lewis Research Academy. Mankbadi has published over 150 scientific papers.
Christine M. Hrenya is an American chemical engineer and applied mathematician whose research involves computational fluid dynamics,especially of aerosols,multiphase flow,and fluidization of granular materials. She is a professor of chemical and biological engineering at the University of Colorado.
The Lattice Boltzmann methods for solids (LBMS) are a set of methods for solving partial differential equations (PDE) in solid mechanics. The methods use a discretization of the Boltzmann equation(BM),and their use is known as the lattice Boltzmann methods for solids.