Scientific VisualisationSystems & Tools 19 February 2013 | 4.47am
Becoming fluent in scientific visualisation requires a significant time investment; its something we’d love to be doing more of but have struggled to find the time and money to make it happen. As engineers we have a good understanding of data sources, where it comes from and how it is created, but when it comes to visualising data, we are either stuck in the land of Excel, or required to outsource the generation of more sophisticated visualisations. This is probably fine for most of the work we do. But, when it comes to more sophisticated data sets there may be significant benefit from embedding the visualisation into our design processes; potentially the visualisation can show us something about the data that we could not have seen otherwise; it might reveal something that improves our design process
With this in mind, we’ve recently used some internal funding to build on our visualisation skills, with an emphasis on developing the capability with some of our engineers. There is no doubt that the creative process of designing a visualisation requires a very good understanding of both the data and the visualisation possibilities and that the best outcome can be realised if both of these skills sit with one person.
The scientific visualisation tools are continually improving and becoming more and more accessible. We’ve started with processing, Circos, Unity and ParaView, the latter two are not really scientific visualisation tools, but they offer immersive 3D capability that is different to the other scripted visualisation software. The images on this page show some of what we’ve achieved in areas of building natural ventilation, mechanical loads and climatic data.
We’ve started with some relatively simple systems, but we’re looking for opportunities to expand into areas that require a better comprehension of system dynamics – particularly in the area of design for resilient behaviour. Scientific visualisation offers the ability to help us see how different systems might cope with disruption and change – there are sure to be applications in such areas as food, transport, energy and water.