Quang Vinh Vu

Vinh Vu

Engineer turned mathematician with a passion for fluid dynamics and machine learning

Hi, I'm Vinh. I blend engineering and mathematics, delving into the world of fluid dynamics with a focus on machine learning. This is an exciting time with rapid advances in machine learning methods, and I aim to use those advances to help solve significant problems in fluid dynamics. The aim of this website is to showcase my expertise as an applied mathematician in fluid dynamics and machine learning, featuring my resume, academic and personal projects. I will upload these on their own webpage soon.

I hold a PhD in Mathematics, specialising in creating convolutional neural networks to predict turbulent fluid flows. You can read my thesis below. I am currently employed as a Mathematical Modeler at an engineering consultancy, where my responsibilities include utilizing hydraulic models for flood prediction and employing Computational Fluid Dynamics (CFD) models to simulate fluid flow within complex real-world systems.

Additionally, I also provide tuition services. I started tutoring when I was 18 and I have years of experience in doing so. During my PhD, I also taught many tutorials for undergraduate maths and engineering students at the University of Sheffield. I can tutor GCSE, A-Level and Unviersity level Mathematics, and I can tutor civil, mechanical and aerospace engineering at a university level. Please feel free to contact me if you wish to inquire about my tutoring services. test

Thesis
Finally, check out my online CV. Note that I go under Vinh Vu although my formal name is Quang Vinh Vu.

View Resume

Introduction

Turbulent fluid flow through a Sierpinski carpet
3D simulation of the fluid flow through a Sierpinski carpet at a Reynolds number of 11,000. Here, the fluid is flowing from left to right and the colourscale represents the x direction velocity. This simulation was simulated using OpenLB.

I am a joint student between the School of Mathematics and Statistics (SoMaS) and the Department of Mechanical engineering and I am researching into Turbulence. Previously, I did my undergraduate degree in Aerospace Engineering also at the University of Sheffield, obtaining a 2:1.

At the moment, I have two projects ongoing. My first project is using deep learning to predict the turbulent fluid flow through an array of obstacles. I am using Python to create a convolutional encoder-decoder model using Tensorflow to analyse the geometry and predict the turbulent fluid flow.

My second project is focused on simulating and analysing the fluid flow through fractal obstacles such as the Sierpinski carpet as shown above. I am interested in this because the Sierpinski carpet exhibits the property of self-similarity. This property can be explained visually, so if we examine the object we can see that small details emerge from geometry, and the further in we examine, the more detail emerges. In real life, if we look at a city from space we can see a cluster of buildings arranged in a fractal-like manner, and the closer we go in, the more detail that emerges such as individual buildings or trees. I am interested in analysing the fluid flow through arrays of obstacles because it has many real-life applications, such as understanding how pollution propagates through cities or designing how we can best protect our coastlines from erosion.