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channel-flow

I coded to study fluid flow. It’s faster in the middle, slower at edges due to interaction with surroundings. I included turbulence, adding complexity, to understand how it impacts transport within the flow.

chaos-and-predictability-matlab-

In My lecture I learnt about the Lorenz curve and chaos equations and we were sent to preform them ourselves to see what type of curve we get using the forward Euler technique and the 2nd and 4th Order Runge Kutta Technique.

freecodecamp-pandas-real-life-example

heat-equation-1d-2d

The Heat equation is a nice introductory project into the world of numerical analysis and CFD. It's pretty simple on the surface whilst having a nice range of uses into a lot of fields In Science.

heathrow-weather-prediction

I did this before with Oxford Weather Data, however there was such a lack of information and data I was NOT satisfied with the prediction. So i chose Heathrow Airport knowing that there wouldn't not be a shortage of data to choose from

lattice-boltzmann-fluid-sim

I’ve developed a fluid simulation code using the Lattice Boltzmann Method (LBM), an alternative to the traditional Navier-Stokes methods. This approach models the fluid as a collection of fictive particles that move and interact on a lattice, providing a unique way to simulate fluid behaviour

navier-stokes---cavity-flow

As a passionate explorer of fluid dynamics, I’ve always been fascinated by the way fluids move and interact with their surroundings. This led me to the Navier-Stokes equations, which are the heart of this field. These equations, born from Newton’s second law of motion, elegantly encapsulate the forces of viscosity and pressure that govern fluid mot

navier-stokes-cavity-flow

The Navier-Stokes equations are fundamental in fluid dynamics, derived from Newton’s second law of motion and accounting for viscous diffusion and pressure forces. They govern the motion of fluids, providing a mathematical framework for understanding fluid flow phenomena.

unconditionally-stable-fluid-diffusion

In numerical analysis, an algorithm is said to be unconditionally stable if it remains stable regardless of the choice of time step. This is crucial in fluid dynamics simulations because it allows us to ensure that our solutions remain accurate and stable, even as we advance in time. And I decided to put that concept to the test

weather-prediction-using-machine-learning-techniques

Using Linear Regression to predict the rainfall and Temperature in Oxford from 1950 to 2023