‘Gamification’ – Stellar Evolver

An example of gamification in one of my recent projects called Stellar Evolver (with audio voiceover). This is a fully VR ready experience and will enable players to interact with and watch the evolution of star systems using the visceral mechanics and feedback of a 3D based shooter.

Stellar systems can evolve from simple proto-planets up to red dwarfs and larger giant stars, eventually culminating in the formation of neutron stars and black holes.

Clearly the overall dynamics, scale and time is being exaggerated hereĀ for playability. I hope to demonstrate a working multiplayer prototype at the 2021 Hebridean Dark Sky Festival.

Developed by Mackintosh Modelling & Data Simulations

Covid-19 Analytics

coronavirus-4833754_960_720.jpgI’ve been busy developing a Covid-19 predictive model using R Studio’s Shiny development environment. This project started as a way of informing myself of what might be happening locally but subsequently grew wings.

It’s using UK and Scottish gov. data on infection rates to make predictions of likely infection levels within various health service regions. The concept of recovery is built into the model as a way of measuring residual levels of infectivity within a population. A user can supply the geographic region as well as change model parameters and assumptions about how the virus is impacting a health system

It’s still at a fairly basic stage and more is being added weekly. National metrics on testing rates have recently been implemented, for example.

If you’d like to sample the app please get in touch and I’ll send you a link. With the help of colleagues I’m in the process of securing a permanent server to deploy the app onto so I can share the work more widely.

Developed by Mackintosh Modelling & Data Simulations.

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Covid-19 Infection Rates

I wanted to do my bit to highlight the need to socially distance at the moment. In addition to outreach astronomy I’ve worked as a mathematical modeller and simulation programmer for many years. Yesterday I decided to create a very simple demonstration to show how infectious Covid-19 is relative to something like the flu.

The red balls represent new cases of Covid-19 based on one individual passing the virus on and creating a human chain reaction. The blue balls represent the same situation for flu. The simulation shows you how many more people will become infected with Covid-19 relative to flu after the same number of transmission waves (9 in this case).

Typically an individual with flu will pass the virus onto 1.3 other people (called the R0 value). With Covid 19 this spreading rate is much higher – between 2.3 and 3. At its worst therefore an infected person will pass the virus onto 3 other people. That might not sound like much but due to exponential growth this level of transmission is like a bomb going off.

Stay safe everyone and please heed the guidelines. With proper social distancing the cascade on the right can be repressed.

Note: This simulation is not validated in any way by medical experts and is for illustrative purposes only.

Developed by S Mackintosh (Mackintosh Modelling & Data Simulations)


Red Blood Cell Simulations

I’ve recently finished part one of a mini Unity project looking at the stacking behavior of red blood cells in a basic turbulent flow. In this real time simulation you can see how the contact adhesion and stacking rate of red cells increases as plasma Fibrinogen concentrations increase.

Fluid flow was programmed from first principles using some simplified assumptions and custom code generated for red cell attraction and adhesion as a function of plasma content.

This simulation is VR ready so you can don a headset and fly around and study any part of the domain in real time. This simulation can also be ported over to more complex domains.

Stage two of the simulation will include deformation of the red cells during contact with domain walls and other cells.

These stacking effects happen in patients with various blood clotting conditions or super high haematocrits.
Developed By Mackintosh Modelling and Data Simulations