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  • Lee Pei Shang

Daylight and Shadow Disposition Optimization with Prasarana HQ Office Block

An Introduction:

Nowadays, designing a passive architecture is widely discussed about in the AEC industry. However, most architects and designers often follows code of practice in buildings and dismiss the importance bespoke analysis on their building design. This traditional practice would lead to more energy consuming building being designed and constructed and mechanical solution is needed to counter the incompetence one a design. As building and information technology today is getting more advanced, environmental simulation analysis software and program is recommended as better long term investment plan to ensure the building design is indeed energy efficient.

The Research Model:

On this research project we want to test out if we could help architects and designers in form and placement finding in relationship with daylight and shadow analysis with the use of computational design. For this research we are using an in-progress construction building of Prasarana HQ and using direct sun hours from Ladybug tools, a plugin for grasshopper for this analysis.

First we start to create a simple massing model of the site and the building blocks, the site consists of three main building blocks;

After that we import a weather file in order for the simulation to work. Since this site is based on Selangor, Malaysia, we used this file from energyplus for the experiment. The direct sun hours component indicates the direct sun hours per day in the given amount of time. Here we set the range of analysis period from 8 am to 7 pm as a constant. The diagram below show an example of how it looks like on top view with a legend indicating the colour in relationship with the total hours of direct sunlight in given amount of time.

After that we split the model into four evenly chosen dates which is all 21st of March, June, September and December from left to right, then ran analysis on them all at once.

Direct sun hours on default position as per architect's design:

From the analysis, we learn that the direct sun hours spread out unevenly on the office block from its colour indication. For an office building, having constant daylight but not too much is important for productivity, therefore we tried to rotate all variations and find the best model using generative evolution the office building to see if there is a better result.

Here's the video of how it looks like in action:

Optimized placement after running analysis:

It only took us about half an hour until we found out that this particular rotation is most suitable in spreading direct daylight evenly throughout the year compared to the current design by the architect. In conclusion, computational design and the use of environmental analysis tools would be a much better choice of designing a building to maximize its efficiency in power consumption.

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