Category: Okategoriserade
Contracting rigid-foldable tubes
After the introduction of converging planes, I extracted one of the resulting curves and reintroduced convergence, but this time the limiting element was a point. A few tests and adjustments resulted in selection of two ‘visually optimal’ shapes. Thinking of small-scale structures I envisioned them as tents for one person. The next step was to explore different approaches for inside-outside movement with a system of foldable elements that allow opening/closing.
The first proposal is based on the idea of curved rigid-foldable tubes. Their structure would allow movement along tracks (rails) as they contract/expand to open/close. At this point, they can be observed as cells that group to form a small organism – camp on the island.
Trying to connect the proposed structures with the context, I reflected on the site-selection task. I concluded that the identified pixels with irradiation above a threshold value are to be used as important factor for arranging the elements. Thinking of the approaches for correlating them, I lost track of the true meaning of these pixels and took a ‘wrong direction’ in the process.
The proposal included two ways of manipulating the pixels into shapes with MATLAB and Rhino. First is the Point Spread Function (PSF), which generates Gaussian distribution of the pixels in a selected region (see graphs that visualize the algorithm). This gives a certain degree of blurring which is determined by the x- and y-axes and an intensity factor. The second proposal uses a Motion Function (MF) that is adjusted for different directions and intensities. The outcomes in both cases are treated as height maps that translate to lines which define their shape. Then, one of the results is chosen to try the principle of curved rigid-foldable tubes.
(MATLAB+ Rhino.Python) (increasing – top to bottom)
At this point the obtained product contradicts with the idea of utilizing irradiated pixels for daily activities. The structures on top of them do not justify their purpose, so I will iterate back to the previous step by further developing the contracting-cells proposal.
Converging-limited foldability
I tried to explore some of the possibilities from folding a piece of paper while constraining with various “levels of freedom”. The following diagrams explain the results from different limiting points and how they can be reproduced with one foldable element. By introducing the limiting plane the original constraining points are removed but the folding results are attained.
Clustered results
Quite often architects are challenged with the need to analyze large sets of data in the design process. However, there is a lack of defined approaches and therefore in most cases detailed analyses are avoided. Through this project I tried to observe a fraction of what could be used as a valuable assessment tool in various projects. Clustering approaches are not uncommon in different fields when in need to observe data, but in architecture these have been poorly investigated. I have used the MATLAB programming language developed by MathWorks to investigate the potential for architectural use.
This is a brief description of the steps in the process:
1. Looking at the height maps as a set of pixels containing height data and clustering with kmeans. (This is an unsupervised learning technique that does the analysis without predefined criteria.) The results give groups of heights that share similar ‘intensity’.
2. A region of interest is selected with clustering division at k=5.
3. Radiation maps of the site are generated using Ladybug. (Different relevant maps or parameters can be used for evaluation depending on the requirements.)
4. k-means clustering is applied on a radiation map. The points that satisfy values above a defined threshold are selected and interpolated to the previously defined region of interest. This gives points that satisfy certain irradiation criteria within the specified height region.
5. New clusters are created in order to define optimal building areas and building shapes are defined at locations where the points satisfy certain density.
The results from the steps are shown in the following isometric drawing.
An experiment with varying k-number values in the kmeans clustering was
Nasi Kuning Tradisional: Resep Warisan Leluhur yang Menggugah Selera Rahasia Kelezatan Nasi Kuning Tradisional di bawah Rahasia Kelezatan Nasi Kuning Tradisional 2024 Resep Nasi Kuning Paling Enak Banget
Wow Master Verry Good Tempat Wisata Bali
Wow Master Verry Good Tempat Wisata Bali
Nasi Kuning Tradisional: Resep Warisan Leluhur yang Menggugah Selera Rahasia Kelezatan Nasi Kuning Tradisional di bawah Rahasia Kelezatan Nasi Kuning Tradisional 2024 Resep Nasi Kuning Paling Enak Banget
https://bidayy.com/serangan-ransomware-lumpuhkan-pusat-data-nasional-data-penting-terancam-hilang/
https://bidayy.com/resep-nasi-kuning-tradisional/
https://bidayy.com/sopir-angkot-lawan-arah-dan-pukul-pemotor-di-bogor-ditangkap-polisi/
https://bidayy.com/ular-sanca-7-meter-berhasil-diamankan-tim-damkar-indramayu/
https://bidayy.com/menkominfo-ungkap-modus-baru-judi-online/
https://bidayy.com/pltu-indramayu-lakukan-inovasi-peningkatan-co-firing-manfaatkan-produksi-biomassa/
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https://bidayy.com/villa-murah-canggu-bali/
https://ejournals.itda.ac.id/index.php/avitec/author/submission/2316performed and the results can be observed in the short animation. For values above 200 it is difficult to read the information from the resulting images, but lower k-numbers can give different levels of detail depending on the requirements of the user.
Growth on terrain
In this project, I was interested in a tree-like distribution and configurations on the terrain as well as in terrain analysis, which was my starting point to the design.
Machine learning, translation and architecture
Exploring cGAN-based image-to-image translation in an architectural context.
2. terrain analysis
As a starting point to the design proposal I used Photoshop, Grasshopper plug-ins and Lidar data to create a terrain analysis, showing greenery, water slope directions, height map etc.
As a starting point to the design proposal I used Photoshop, Grasshopper plug-ins and Lidar data to create a terrain analysis, showing greenery, water slope directions, height map etc.
CNC milled model:
LCLA
ii. big data and nomadic robotics.
Studio 9_Project 3_Task 2: Occupations and Interventions.
To occupy the site I began by collecting and analysing site data for Malmön. The program QGIS for editing and analysing geospatial information was used to extract the vector information; topography, population and marine geology. A colour png map provided the basis for extracting the 3D terrain data using a python script and into Rhino, with initial topography analysis through flow diagrams in grasshopper. A photographic study was also carried out and compiled into a booklet.
The intervention aspect was based heavily on ABM research – agent based models. An agent is aware of its surroundings and its abilities. When acting in a collective manner they exhibit swarm intelligence, the collective behaviour of decentralised self-organised systems. This means each member autonomously offers its abilities in order to study an overall system. The members, or agents, self-coordinates without a leader and cooperate in solidarity resulting in a self-healing system. This allows members to be added or removed dynamically as the agents will recalibrate in a constant feedback loop.
‘Boids’ by Craig Reynolds was the grounds for my research into swarms and flocking behaviours for computer simulations. His theory is a basic flocking model consisting of three steering behaviours; separation, alignment and cohesion. Ant colonies that organise using pheromone and visibility factors were also part of the initial studies.
I would like to base project 3 on the collection of site data using agents and subsequently allowing the agents to alter the collected data in order to intervene and implement the summer camp design on Malmön. To engage with this theory in the material dimension, I decided give form to the agent as a mini Arduino robot name Mö. This allows for real-time feedback with the tests I run for the agent simulation on site. Giving robotics agent behaviours has its own research and theory basis. Although Craig Reynolds theory of Boids is a great foundation, I also studied vehicle behaviour and coding in ‘Vehicles: Experiments in Synthetic Psychology’ by Valentino Braitenberg. Processing and Arduino will be the main programming softwares, with C and Java as scripting languages. The Nature of Code on youtube and Github, as well as Studio 09’s own processing tutorials have been great learning platforms for this.
The Hivemind
My initial interest in participatory design led me to start working with multi agent systems. The idea that consensus emerges without anybody actually taking charge or leading the group felt like it might have an interesting analogous connection to questions of democracy (and I also found Grasshopper plugins that seemed fun to try), so I decided to go in this direction.
The agents are programmed to have several concurrent behaviors, the main ones being attraction and repulsion. After starting to play with the idea that the agents were in fact aliens out to colonize Malmön (and laughing out loud at my own silliness) I got the ideas that the repellants would be the existing housing on the island and the attractor points certain terrain conditions. Obviously, aliens want to keep their colonization efforts secret from the humans on the island, and they are here to gather data on the granite that is so abundant in Malmön…
Moving on, first of all I want to see how I can take the concepts I’ve worked with so far from 2D to 3D. Furthermore, I’m also thinking about experimenting with a hierarchy within the swarm; the brief includes 5 ”camp leaders”, something that both works well with my hypothetical alien colony situation and could potentially generate interesting results depending on how the leaders and the swarm interact with each other.