C omputation is defined as ‘ the processing of information and interactions between elements which constitute
a specific environment; it provides a framework for negotiating and influencing the interrelation of datasets with the capacity to generate complex order, form and structure.  From this definition, it refers to the use of computer to process information through algorithm. This later allows exploration of new ideas with the control over parameters and changes made throughout the process. The flexibility of algorithm allows the design to accommodate any changes in parameters effectively. Computational designers tend to generate and explore architectural concepts through modification in algorithms that relate to the respective element. In generative design, it does not simply transform what we can design but having a huge impact on how we build. From a simple cube, it can turn into a variety of different creative geometrical outcomes after went through different explorations. Today, the parametric families of components and the control of data are playing important roles in computational approach to convert the compositional geometry to a generative product. A generative approach designs the process, but not the form. Designer decides where to make the change, how it being made with the ratio set. Hence, the end product contains the ‘story’ of its origin through the algorithm.
Design can be said as an innate ability, which makes human unique. In this matter, design democracy as in Hester’s proposal is definitely a good move to engage with multiple views in reaching a best trade-off solution for sustainment.
Nevertheless, algorithm, which is a front-end analysis needs a clear set of rules in order to run the process in computer. This can be a challenging part for setting a correct input. Sometimes we not sure whether or not the information provided is enough to guess the algorithms. If the points were drawn on a blackboard, we must probably have no problem in sketching their convex hull. However, if it needs us to locate the points in order to form a certain shape, it would require an understanding on how to make it and have a great imagination to figure out the point locations before draw them on the blackboard. This is why most people found algorithm is hard to practice. We need to have a clear image of what we want and how we could make it in order to carry out this task. By imagine what the outcome might be at the end, we can decide the input of the algorithm and most of the time, the outcome is not exactly what we aim for, which there are always unexpected possibilities gained at the end of the stage. What does it mean to be a good algorithm? It’s hard to know when the algorithm is complete and it is good enough that we should stop exploring. Similar to designing, it is crucial for the designers to know when to stop design. Algorithmic practice allows us to keep evaluating the output of each step and if the next stage is giving negative impact on design, we could always back to the previous step.
Parametric modelling would be the main tool for us to run the project of Copenhagen site. Varies from the ordinary design pathway, learning the algorithmic process allows us to practice the digital design thinking as well as the ‘bottom-up’ approach as another alternative for design futuring.
Architecture is currently experiencing a shift from the drawing to the algorithm as the method of capturing and communicating designs. Algorithmic concept allows architects to capture the complexity of how to build a project as well as providing clear information about the parameters that lead to the form formation. This is important since a good design always gone through repetitive experiments and evaluation stages. Algorithm allows architects to easily retrieve back the procedure. Hence, the responsiveness of computational simulation tool allows architects to explore and analyse new decisions during the design process.
Published on Jun 11, 2014