Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Page not in menu
This is a page not in th emain menu
Posts
Join PNNL
Published:
Zirui Mao will leave from TAMU in the end of 2021. Next, he will join Pacific Northwest National Library and start new research with Dr. Shenyang Hu being the direct mentor.
A talk is invited at University of Cincinnati
Published:
A talk named as ‘Solutions to solving and controlling Phase-Field models: from numerical methods to machine learning algorithms’ is distributed on the seminar of Department of Aerospace Engineering and Engineerng Mechanics at University of Cincinnati.
A new journal paper is accepted
Published:
Our paper entitled ‘Mobility inference of the Cahn–Hilliard equation from a model experiment’ was accepted by JMR.
A talk is invited at Texas A&M University
Published:
A talk named as ‘Control algorithms for microstructure evolution’ is distributed on the postdoc research seminar of Department of Materials Science and Engineering at Texas A&M University.
Our work was presented on the TMS2021 conference
Published:
A talk named as ‘Mobility inference of the Cahn-Hilliard equation from a model experiment’ was presented by Zirui Mao on the TMS 2021 online.
A new book chapter is published
Published:
Our book chapter entitled ‘Chapter 12 - SPH modeling for soil mechanics with application to landslides’ was published online.
A talk was given on the NME 2020
Published:
A talk named as ‘Lagrangian Gradient Smoothing Method (L-GSM): A novel meshfree method for large deformation problems simulation’ is given by Zirui Mao on the 3th International Conference on Numerical Modeling in Engineering (NME 2020). Please find the ‘online record’ of presentation.
A slides show on SC20 Virtual Exhibit Event
Published:
A slide show named as ‘‘High Performance Computation-based Phase Field Simulation of Metal Layer Retraction’ is given by Zirui Mao on the International Conference for High Performance Computing, Networking, Storage and Analysis (SC20), November 17-19, 2020.
A 3-min flash talk was given on the Postdoc Research Symposium held at TAMU
Published:
A flash talk named as ‘Optimal Control of Microstructure Evolution’ (#13) is given by Zirui Mao on the ‘2020 Postdoc Research Symposium’ held at Texas A&M University.
A new paper is accepted by ASA
Published:
Our paper entitled ‘Perfectly matched layer absorbing boundary conditions for Euler equations with oblique mean flows modeled with smoothed particle hydrodynamics’ was accepted by The Journal of the Acoustical Society of America.
A new paper is accepted by IJNME
Published:
Our paper entitled ‘A 3D Lagrangian gradient smoothing method framework with an adaptable gradient smoothing domain‐constructing algorithm for simulating large deformation free surface flows’ was accepted by International Journal for Numerical Method in Engineering.
A new paper is accepted by EG
Published:
Our paper entitled ‘A conservative and consistent Lagrangian gradient smoothing method for earthquake-induced landslide simulation’ was accepted by Engineering Geology.
A new paper is accepted by EABE
Published:
Our paper entitled ‘A local Lagrangian gradient smoothing method for fluids and fluid-like solids: A novel particle-like method’ was accepted by Engineering Analysis with Boundary Elements.
A new paper is accepted by CPM
Published:
Our paper entitled ‘A conservative and consistent Lagrangian gradient smoothing method for simulating free surface flows in hydrodynamics’ was accepted by Computationa Particle Mechanics.
Start postdoc works
Published:
Zirui Mao joined Demkowicz’s group as a postdoc researcher at Texas A&M University.
PhD graduation
Published:
Zirui Mao achieved PhD degree in Aerospace Engineering from University of Cincinnati under supervision of Professor G.R. Liu.
Win R.T. Davis Award
Published:
Zirui Mao won R.T Davis Award from University of Cincinnati.
PhD defense
Published:
Zirui Mao successfully passed his PhD defense. Committee Members: Prof. G.R. Liu, Prof. Shaaban A Abdallah, Prof. Mark G. Turner.
portfolio
Meshfree methods for large-deformation problems
2014.08-2019.05 / PhD main project @ UC: A stable and efficient meshfree method for simulating large-deformation fluids and flowing solids
Lid-driven cavity flow
2015.09-2016.06 / PhD side project @ UC: FDM simulation of cavity flow driven by moving lid
Processing of polymeric materials
2015.09-2019.06 / PhD Research @ UC-P&G Simulation Center: High strain-rate mechanical bonding of multi-layer polymeric materials
Optimal Control of Microstructure Evolution
2019.06-present / Postdoc main project @ TAMU: Control of microstructure evolution by coupling phase-field models with reinforcement learning algorithms
Phase Field Modeling of microstructure evolution
2019.06-2021.09 / Postdoc side project @ TAMU: Retraction of layer, finite plate, and cylinder, NMC
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
A comprehensive study on the parameters setting in smoothed particle hydrodynamics (SPH) method applied to hydrodynamics problems
Published in Computers & Geotechnics, 2017
How to cite
Mao Z, Liu GR, Dong X. A comprehensive study on the parameters setting in smoothed particle hydrodynamics (SPH) method applied to hydrodynamics problems. Comput Geotech. 2017;92:77‐95. https://doi.org/10.1016/j.compgeo.2017.07.024. [manuscript]
Abstract
Smoothed particle hydrodynamics (SPH) is a meshfree, Lagrangian particle method which has advantages in handling solids with extremely large deformation. Like any other numerical methods, cares must be taken to ensure its desirable accuracy and stability through considering several correction techniques in calculation. The selection of values for parameters in those correction approaches is a key step in SPH simulation, which is always difficult for new beginners to deal well with effectively. This paper examines the common inconsistency and instability problems in SPH method and studies its computational efficiency when applied to hydrodynamics problems with material strength like soil column collapse. We analyzed in detail how the correction techniques mitigate these inconsistency and instability problems. Also, the numerical testing results associate with different values for the parameters used in the correction techniques are provided for better understanding the influence of these parameters and for finding out the desirable values. It is found that (1) the SPH method is easily subjected to an inconsistency problem in the boundary area due to the boundary deficiency, and it can be treated well by adopting “virtual particles” contributing to the particle summations. (2) The numerical oscillation in SPH simulation can be mitigated effectively by artificial viscosity with the suggested parameter values. (3) The tension cracking treatment, artificial viscosity and artificial stress work well in removing the tensile instability problem in SPH method. In addition, the nearest neighboring particle searching (NNPS) algorithm, spacing ratio, smoothing length and time step influence the efficiency and accuracy of SPH method significantly. It is shown that SPH method with suggested parameters values can produce a very good result compared with the experimental result.
Keyword
Smoothed Particle Hydrodynamics, hydrodynamics with material strength, soil column collapse, tensile instability and artificial stress, artificial viscosity
A Lagrangian gradient smoothing method for solid‐flow problems using simplicial mesh
Published in International Journal for Numerical Methods in Engineering, 2018
How to cite
Mao, Z, Liu, GR. A Lagrangian gradient smoothing method for solid‐flow problems using simplicial mesh. Int J Numer Methods Eng. 2018; 113: 858– 890. https://doi.org/10.1002/nme.5639. [manuscript]
A smoothed particle hydrodynamics model for electrostatic transport of charged lunar dust on the moon surface
Published in Computational Particle Mechanics, 2018
How to cite
Mao, Z., Liu, G.R. A smoothed particle hydrodynamics model for electrostatic transport of charged lunar dust on the moon surface. Comp. Part. Mech. 5, 539–551 (2018). https://doi.org/10.1007/s40571-018-0189-4. [manuscript]
A conservative and consistent Lagrangian gradient smoothing method for simulating free surface flows in hydrodynamics
Published in Computational Particle Mechanics, 2019
How to cite
Mao, Z., Liu, G.R., Dong, X., Lin, T. A conservative and consistent Lagrangian gradient smoothing method for simulating free surface flows in hydrodynamics. Comp. Part. Mech. 6, 781–801 (2019). https://doi.org/10.1007/s40571-019-00262-z. [manuscript]
A local Lagrangian gradient smoothing method for fluids and fluid-like solids: A novel particle-like method
Published in Engineering Analysis with Boundary Elements, 2019
How to cite
Zirui Mao, G.R. Liu, Yu Huang, A local Lagrangian gradient smoothing method for fluids and fluid-like solids: A novel particle-like method, Engineering Analysis with Boundary Elements, Volume 107, 2019, Pages 96-114. https://doi.org/10.1016/j.enganabound.2019.07.003. [manuscript]
A conservative and consistent Lagrangian gradient smoothing method for earthquake-induced landslide simulation
Published in Engineering Geology, 2019
How to cite
Zirui Mao, Guirong Liu, Yu Huang, Yangjuan Bao, A conservative and consistent Lagrangian gradient smoothing method for earthquake-induced landslide simulation, Engineering Geology, Volume 260, 2019, 105226. https://doi.org/10.1016/j.enggeo.2019.105226. [manuscript]
A development of a SPH model for simulating surface Erosion by impact (s) of irregularly shaped particles
Published in International Journal of Computational Methods, 2020
How to cite
Dong, X., Li, Z., Mao, Z., Lin, T. A Development of a SPH Model for Simulating SurfaceErosion by Impacts of Irregularly Shaped Particles. Int J Computational Methods, 15(8), 1850072. (2020). https://doi.org/10.1142/S0219876218500743.
Smoothed Particle Hydrodynamics Simulation of Liquid Drop Impinging Hypoelastic Surfaces
Published in International Journal of Computational Methods, 2020
How to cite
Dong, X., Li, Z.,Mao, Z., Liu, Y. Smoothed particle hydrodynamics simulation of liquid dropimpinging hypoelastic surfaces. Int J Computational Methods. Volume 17, No. 05, 1940001. (2020). https://doi.org/10.1142/S0219876219400012
Perfectly matched layer absorbing boundary conditions for Euler equations with oblique mean flows modeled with smoothed particle hydrodynamics
Published in The Journal of the Acoustical Society of America, 2020
How to cite
Jie Yang, Xinyu Zhang, G. R. Liu, Zirui Mao, and Wenping Zhang, Perfectly matched layer absorbing boundary conditions for Euler equations with oblique mean flows modeled with smoothed particle hydrodynamics, The Journal of the Acoustical Society of America, Volume 147, Issue 2, 1311 (2020). https://doi.org/10.1121/10.0000648.
A 3D Lagrangian gradient smoothing method framework with an adaptable gradient smoothing domain‐constructing algorithm for simulating large deformation free surface flows
Published in International Journal for Numerical Methods in Engineering, 2020
How to cite
Mao, Z, Liu, GR. A 3D Lagrangian gradient smoothing method framework with an adaptable gradient smoothing domain‐constructing algorithm for simulating large deformation free surface flows. Int J Numer Methods Eng. 2020; 121: 1268– 1296. https://doi.org/10.1002/nme.6265. [manuscript]
Chapter 12 - SPH modeling for soil mechanics with application to landslides
Published in Modeling in Geotechnical Engineering, 2021
How to cite
G.R. Liu, Zirui Mao, Yu Huang, Chapter 12 - SPH modeling for soil mechanics with application to landslides, Modeling in Geotechnical Engineering, Academic Press, 2021, Pages 257-289.
Mobility inference of the Cahn–Hilliard equation from a model experiment
Published in Journal of Material Research, 2021
How to cite
Mao, Z., Demkowicz, M.J. Mobility inference of the Cahn–Hilliard equation from a model experiment. Journal of Materials Research (2021). https://doi.org/10.1557/s43578-021-00266-7
Gradient Smoothing Methods with Programming: Applications to Fluids and Landslides
Published in , 2024
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Physic-based models for material processing
MATLAB, in-house code, 2019
Three highly efficient physics-based models are developed in Matlab for predicting the mechanical behaviors of material during processing: large deformation, bound strength, and failure. The software is archived by P&G and here are some samples.
L-GSM platform
FORTRAN & MATLAB, in-house code, 2021
The L-GSM platform provides a meshfree method for handling large deformation problems with a much better performance in stability and efficiency. Applications can be found here. The in-house code will be released as planned.
Phase-Field platform
FORTRAN & MATLAB, in-house code, 2021
The Phase-Field platform solves the general Allan-Cahn and Cahn-Hilliard equations using Finite Difference Method (with uniform grid) or Gradient Smoothing Method (with adaptive grid). Two numerical solvers are provided: a simple explicit solver and an efficient implicit solver. The in-house code will be released as planned associated with upcoming paper publication.
Optimal Controller of microstructure’s evolution
FORTRAN & MATLAB & Python, in-house code, 2021
This software enables optimal control of microstructure’s evolution through coupling phase-field models with reinforcement learning algorithms. The microstructure can be guided from any initial, unstructured state to any target state with the least cost. Please refer to the examples.
1D diffusion freeware
Matlab GUI, Tutorial freeware, 2021
This tutorial freeware (1D diffusion software) aims at providing students/new beginners a direct computational tool for understanding diffusion type of problems in engineering and material science.
1D Phase Field software
Matlab GUI, Tutorial freeware, 2021
This tutorial freeware (1D Phase Field software) aims at providing students/new beginners a direct computational tool for understanding material microstructure evolution in engineering and material science.
Adaptive remeshing for GSM
MATLAB, in-house code, 2022
This software enables adaptive remeshing based on moving material features for Gradient Smoothing Method.
GPU accelerated mixed-precision SPH framework
CUDA and Fortran, Open source, 2023
Herein, we introduce a GPU-accelerated mixed-precision SPH framework by using low precision FP16 in NNPS while maintaining high-precision FP64 in other components.
Gradient Smoothing Methods
Matlab and Fortran, in-house code, 2024
The GSMs source code is released with the GSMs book.