今晚7点直播|The International Multiphase Flow Technology Forum

IMFTF Keynote Meeting (13) Schedule

Date & Time: Fri, 28 Oct. 2022, 19:00

Chair:   

Professor Kun Luo, Zhejiang University 

Opening:

(19:00 - 19:05 Beijing Time)

Programme:

Keynote Speech-1

(19:05  –  19:45  Beijing  Time)

Postdoc researcher 

Kai Liu

Zhejiang University

Q&A 

(19:45 – 20:00 Beijing Time)

Keynote Speech-2

(20:00  –  20:40  Beijing  Time)

Distinguished Professor  

Sivaramakrishnan Balachandar

University of Florida

Q&A 

(20:40 – 20:55 Beijing Time)

Discussions, closing

(20:55  –  21:00  Beijing  Time)

Platform:  Zoom

https://us02web.zoom.us/j/87036567996?pwd=bjVxL0hTSWNFSTc5Z3RZaUw2UWdpUT09

Meeting ID:  870 3656 7996

Passcode:  1028

Organizers

  International Multiphase Flow Technology Forum

Shanghai Institute For Advanced Study, Zhejiang University  

China University of Petroleum-Beijing

  Chinese Society of Particuology

Keynote Speech-1

Two-way Coupled Euler-Lagrange Simulations of Mid-field Spray: Droplet Inflow and Dynamics Modeling

Sprays widely exist, from aero-engine injectors to pandemic contagion. Investigating the background physics and developing reliable models are necessary to better predict and control spray systems. In order to produce highly consistent simulation results with the experiment, a series of droplet inflow and dynamic models have been developed and rigorously validated. This presentation will focus on the two-way coupled Euler-Lagrange simulations of the mesoscopic mid-field spray, where all droplets are fully-disperse. A stochastic particle injection model fitted from experimental data is developed to substitute massive interface-resolved simulation in the near field. The result shows that the position, diameter, and velocity distributions of droplet clouds throughout the simulation domain faithfully agree with experimental measurements. Considering the poly-disperse characteristic of droplet cloud, in which large-size droplets may violate the small particle approximation of most Euler-Lagrange point-particle models, self-induced velocity and temperature correction models are correspondingly developed to further improve the drag and heat transfer prediction accuracy of individual droplets. Finally, two applications of acoustic spray control and human sneeze will be introduced to highlight the application potential of Euler-Lagrange spray simulation in analyzing practical problems.

Speaker Information

Education：

B.S., Energy Power System and Automation, Xi’an Jiaotong University, China, 2014

M.S., Mechanical Engineering, University of Florida, US, 2016

Ph.D., Mechanical Engineering, University of Florida, US, 2020

Awards：

Dissertation Award Thermal Sciences and   Fluid Dynamics 2020-2021, University of Florida, US

2020 Chinese Government Award for Outstanding Self-financed   Students Abroad, China Scholarship Council

Work Experience:

Postdoc, College of Energy Engineering, Zhejiang University, China, 2022-present

Selected Publications:

1. K. Liu K ; P.D. Huck; A.Aliseda; S. Balachandar ; Investigation   of turbulent inflow specification in Euler-Lagrange simulations of mid-field   spray, Physics of Fluids, 2021, 33(3)

2. K. Liu K ; M. Allahyari; J. Salinas; N. Zgheib; S. Balachandar   ; Investigation of theoretical scaling laws using large eddy simulations for   airborne spreading of viral contagion from sneezing and coughing, Physics of   Fluids, 2021, 33(6)

3. Kai Liu K ; Mandar Lakhote; S. Balachandar ; Self-induced   temperature correction for inter-phase heat transfer in Euler-Lagrange   point-particle simulation, Journal of Computational Physics, 2019, 396:   596-615

Email:

1240270754@qq.com

Keynote Speech-2

Physics-Inspired Machine Learning for Multiphase Flow Modeling

Euler-Lagrange (EL) and Euler-Euler (EE) techniques have been widely employed for solving particle, droplet, and bubble-laden flows. Since flow around the individual particles is not resolved, the accuracy of the technique depends on the fidelity of the point-particle force laws used. The main focus of this talk is the use of emerging machine learning techniques along with physical insight into the averaging processes involved in the EL and EE techniques can yield closures that recover fully-resolved-like accuracy at orders of magnitude lower cost.

Speaker Information

Education：

B. Tech. Mechanical Engineering Indian Institute of Technology 1983

Sc.M. Engineering Brown University 1985

Sc.M. Applied Mathematics Brown University 1986

Ph.D. Engineering Brown University 1988

Awards：

Gad Hetsroni Senior Award, International Conference on Multiphase Flow, Rio De Janeiro, Brazil, May 2019

Outstanding Alumnus Award, Indian Institute of Technology, Madras, March 2020

Doctoral Dissertation Advisor/Mentoring Award, University of Florida, April 2020

Thermal Fluids Engineering Award, American Society of Thermal Fluids Engineer, May 2022

Work Experience:

Distinguished Professor, University of Florida,   Gainesville, FL, June 2016 – Present

Director, Institute for Computational   Engineering, University of Florida, June 2011 – Present

Affiliate Professor, Dept of Civil and Costal   Engineering, UF, Gainesville, FL, 2010 – Present

Chair, William F. Powers Professor of MAE, UF,   Gainesville, FL, December 2005 - June 2011

Associate Head, Department of Theoretical &   Applied Mechanics, University of Illinois, Urbana, IL, 2004 - April 2005

Professor,   Department of Theoretical & Applied Mechanics, University of Illinois,   1990 - 2005

Selected Publications:

Ouellet, F., Rollin, B., Durant, B., Koneru, R. B., & Balachandar, S. Shock-driven dispersal of a corrugated finite-thickness particle layer. Physics of Fluids, 34(8), 083301 (2022).

Farzaneh, M., Zgheib, N., Sherif, S. A., & Balachandar, S. Sensitivity Analysis of Frost Deposition in Turbulent Flow over a Cold Plate using Direct Numerical Simulation. International Journal of Heat and Mass Transfer, 196, 123233 (2022).

Siddani, B., & Balachandar, S. Point-particle drag, lift, and torque closure models using machine learning: hierarchical approach and interpretability. arXiv preprint arXiv:2207.08888 (2022).

Yu, M., Yu, X., Balachandar, S., & Manning, A. J. (2022). Floc Size Distributions of Cohesive Sediment in Homogeneous Isotropic Turbulence. Frontiers of Earth Science, 10, 815652 (2022)

Email:

Bala1s@ufl.edu

Website:

https://www.eng.ufl.edu/ice/about/leadership/

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