Our third round of shells fresh out of fabrication is here!
I am excited that we now have shells that are more organic and life-like coming through. To drive this additional complexity I’ve been experimenting with mixing the combinations of data and exploring how these generate more ‘organic’ forms as they are fed into different parameters of the growth grammar.
In my last post I described how I’ve developed a bespoke shell model by programming in JAVA with growth grammars which start out with mathematical principles. These project a spiral onto the surface of a cone in 3D for the primary growth curve. Then I begin to tweak and subvert the surface shape as it grows, adjusting the rhythms and patterning of the data to add a degree of interpretation.
This is very interpretive and not hard science; it is not classic data-visualisation or information graphics. I take sets of health and lifestyle data and make deliberate decisions in how I interpret what kind of ‘expression’ they generate. It is highly designed and crafted process which I am evolving to achieve both an aesthetic outcome, but also one where the data plays a key role that may not be transparent or simply ‘readable’ like a graph, but rather becomes emotive.
This is important and different in that we are trying to produce a sense of meaning that is not read through classic symbols but rather through a tactile and visual experience. The tangible form of the shells embodies rhythm, resonance or dissonance; attraction or repulsion.
What we are attempting is not just a ‘transduction’ of health data into physical form, but a transformation of how we develop relationships with that data and what it means for us. The data is captured and transfigured into the physical form of the shells – producing something which is magical, transformative and which cannot be easily read but is heavy with the potential for meaning. The shells become more like talismans than just static instantiations of data.
This is very different to a technique that just takes data and processes it into a visual or physical form. It is not about numbers but about a model of generating shells that are qualitative, meaning producing and change making. It is about how a person could pick up a shell and begin to read their own meanings into it, knowing that it is generated from their own health data. Knowing that the subtle but strange variations in each shell indicate something to be explored in our lifestyles and behaviours.
This third generation of shells are moving further towards acquiring a ‘life’ of their own, becoming objects of meaning in the world. They are shaped by ‘lived constraints’ in the growth model and are getting expressions that go beyond pure mathematics.
I’m now working on a fourth generation of shells, this time using data posted on the internet using social media.
I have just come back from the Digital Manufacturing Centre 3D printing lab at UCL where we just had our second round of shells made for us.
This time around you can see shells which are beginning to have some life (or data to be exact) put in to them. They are ‘grown’ by using the health data we have previously collected from the body sensors and data logger which we are beginning to use to evolve different types, shapes and sizes of shell.
We captured the initial data over a week back in May which consisted of blood pressure, step counts, length of sleep, body temperature, exposure to air pollution and alcohol intake. These were gathered to provide a range of values we could use to make the shells change the way they are evolved over time.
These different dimensions of data are used in our growth model as parameters that influence where and how much the shell grows and in which particular way. Each set of data values contribute to determining how much it grows, how smooth or jagged the surfaces are and whether or not there are other outgrowths. All together this results in a very personalised and specific shape that is unique to each data set.
We are planning to fabricate two further sets of shells, one with more extensive data sets informing the shell growth pattern, and the second experimenting with different data sources. More posts to come!
Our growth model as mentioned before is using variants of ‘parametric design’ via L-Systems and Growth Grammars. Here is a very quick explanation of what these do in principle:
In a parametric design different numerical values – called parameters – are put into a set of related mathematical formulas or rules. These are able to generate variations of shapes or objects based on different input values. It is for example possible to create a parametric definition of a basic chair that when combining the height and leg length of a person – can generate a chair with proportions that make it comfortable for that person to sit on. So a parametric design in this case captures the idea of a chair that can be made to fit different bodies – i.e. how many legs the chair has, the way the legs are connected to the seat area, the seat sitting area and the height position of the backrest.
These were invented by a man called Aristid Lindenmayer and are type of formal language that uses sequences of letters that define how something grows over several time periods. They can for example express how a tree expands from its trunk into branches and then into leaves or how a flower’s petals are arranged.
These are more complicated variations on L-Systems that have a richer set of features that can be used to describe growth models such as plant models. Growth Grammars are used in not just modelling the structure of plants i.e. how it is put together and its parts but also how it functions and its parts interact with each other.
After what has been a broad exploratory research and foraging phase into shell morphology and modelling systems for our Visualise project, I have just picked up the first round of 3d printed shells which we had done at the Digital Manufacturing Centre @ UCL. Thanks to Martin and Richard for their assistance with the 3d printing process!
What you see here is a twist on classic plain formula driven generative shells that you may have seen before. We are experimenting with ways of adapting shell formation of our 3d shells based on data capture we have started in previous experiments in lifestyle and health data monitoring. I have been looking into a variety of generative modelling systems anywhere from those originating in the CAD world to those for plant modelling in the bio and agricultural sciences.
Now I have settled on using a growth grammar platform called XL (it builds on ideas of l-systems but with much more flexibility and dynamic rewriting of growth rules). The XL grammar is interesting as its been developed for plant morphological and systemic modelling, allowing the generative growth rules to be switched based on time variant environmental factors throughout growth cycles.
This offers some exciting possibilities of mimicking real-world feedback patterns of environmental constraints on living entities such as plants or other living systems giving rise to different possible ‘expressions’ based on the ‘quality of life’ over time they experience in their environment (e.g. through droughts, wet seasons, sparse or rich nutrition, pollution factors, over-shading, etc.).
The shells you see here are a variations of an evolving shell model that can be infused with our previous and ongoing environmental and personal data capture data sets (e.g. with readings such as daily step-count, blood pressure, sleep pattern regularity) to determine the evolving form.
Look out for further variations on these shells shortly!