Mathematics Webinar | Computational Methods for Fluid Flow
the chair
13th Mathematics Webinar
Computational Methods for Fluid Flow
Mesh generation and its adaptivity are recognised as one of the major challenges in Computational Fluid Dynamics (CFD) workflow in the NASA report: CFD Vision 2030 study. The quality of a mesh is extremely important to obtain reliable solutions and guarantee numerical stability. Adaptive mesh refinement strategies offer the potential for superior accuracy at reduced cost, but the issues include robustness, error estimation, and software complexity. This webinar introduces adaptive mesh-free methods in CFD modelling and adaptive mesh refinement methods proposed based on the qualitative theory of differential equations and their performance.
Date: 15 October 2024
Time: 9:00 a.m. CEST | 3:00 a.m. EDT | 3:00 p.m. CST Asia
Webinar ID: 846 1040 4481
Webinar Secretariat: journal.webinar@mdpi.com
Meet the Event Chair
Meet Our Speakers
Dr. Tao Zhang
School of Engineering, University of Leicester, UK;
Dr Tao Zhang is currently a Lecturer in Engineering at the University of Leicester, UK. He obtained his PhD degree in Aerospace Engineering from the University of Glasgow in 2022. He joined the University of Leicester and became a Lecturer/Assistant Professor in the same year. His research covers high-fidelity aerodynamic and acoustic modelling and optimisation methods for rotary-wing aircrafts, helicopters, and novel advanced air mobility vehicles. His recent research focuses on high-fidelity meshless CFD methods for aerodynamic modelling.
Dr. Zhenquan Li
School of Computing and Mathematics, Charles Sturt University, Australia;
Dr Li is currently a Senior Lecturer at Charles Sturt University. He has been teaching Mathematics at the tertiary level for over 20 years and worked at universities in China, Japan, New Zealand, Fiji, and Australia. He has held positions from Assistant Professor to Professor (as per the US standard professional titles). His research interests include mathematical modelling, neural networks, and computational methods for fluid flow.
Dr. Rajnesh Lal
School of Mathematical and Computing Science,
Fiji National University, Fiji;
Dr. Rajnesh Lal is an Assistant Professor of Mathematics at Fiji National University, a position he has held since 2018. He earned his Ph.D. in Mathematics and Modelling in 2017 from the University of Montpellier, France. His research interests are diverse, encompassing computational methods for fluid flow, inverse problems, data assimilation, mathematical modelling, and machine learning.
Sponsors and Partners
Organizer
The webinar was hosted via Zoom and required registration to attend. The full recording can be found below. In order to learn about future webinars, you can sign up to our newsletter by clicking “Subscribe” at the top of the page.
|
Speaker/Presentation |
Time in CEST/CET |
Time in CST Asia |
|
Dr. Zhenquan Li Chair Introduction |
9:00 – 9:05 am |
3:00 – 3:05 pm |
|
Dr. Tao Zhang Collocation-Based Mesh-Free CFD Methods for Aerodynamics Modelling |
9:05 – 9:30 am |
3:05 – 3:30 pm |
|
Q&A |
9:30 – 9:35 am |
3:30 – 3:35 pm |
|
Dr. Zhenquan Li Adaptive Mesh Refinement Methods Based on the Qualitative Theory of Differential Equation |
9:35 – 10:00 am |
3:35 – 4:00 pm |
|
Q&A |
10:00 – 10:05 am |
4:00 – 4:05 pm |
|
Dr. Rajnesh Lal The Process of Velocity Driven Adaptive Mesh Refinement Method |
10:05 – 10:30 am |
4:05 – 4:30 pm |
|
Q&A |
10:30 – 10:35 am |
4:30 – 4:35 pm |
|
Closing of Webinar Dr. Zhenquan Li |
10:35 - 11:00 am |
4:35 – 5:00 pm |
Advanced Computational Methods for Fluid Dynamics and Applications
Guest Editor: Dr. Zhenquan Li
Deadline for manuscript submissions: 30 November 2024