Optimizing forms as per natural conditions 


Digital technologies are profoundly changing the way that we design and interact with our built environment. Both computerized and computational tools open new opportunities for architects to explore and visit uncharted territories. Computational design thus serves as a design thinking tool that helps collaborate to solve complex and simple problems easily. As designers work to create affordable, high-quality buildings that perform efficiently we face a growing set of competing constraints.

Sustainability criteria like energy performance, embodied carbon and design for deconstruction often compete with quality criteria like daylight, acoustic performance, solar gain and wind conditions.

Than to conventional trends of taking decisions based on simplified/part study or intuition, parametric design offers a solid impact in primary design decisions. By analyzing multiple options and giving quantitative feedback it helps arrive at a solution efficiently.

Using specific tools in parametric architecture, we can explore a complete range of design options thus building a unified solution that reconciles with client demands. The start of this process can simply take place by collectively agreeing on taking the site conditions and key performance indicators of the project. These key parameters can be inputted and changes can happen interactively, with the model updating automatically.

One of the genetic algorithm for rank terraces

For instance, ‌Rank terraces a commercial project is derived from solar analysis and genetic algorithms. The analysis is such that it ensures that the office spaces get the least solar radiation and thus optimizes the performance of the design.  

Final result for the project

Apart from solar analysis, the generated morphology is an output of using various parameters, some of which includes the regional immediate site conditions, user experience amongst others.  This methodology has thus enabled to produce numerous iterations of the same design and to select the final form based on the optimum result generated.

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