nowledge, tools, materials and machines. The Clusters provide a focus for workshop participants working together within a common framework.
Clusters provide a forum for the exchange of ideas, processes and techniques and act as a catalyst for design resolution. The Workshop is made up of ten Clusters that respond in diverse ways to the sg2012 Challenge Material Intensities. The Call for Clusters is now open to proposals which respond in innovative ways to this year's challenge.
Deadline: September 19 2011
More information can be found here:
http://smartgeometry.org/index.php?option=com_content&view=article&id=129&Itemid=146
sg2012 takes place from 19-24 March 2012 at EMPAC (http://empac.rpi.edu/) and is hosted by Rensselaer Polytechnic Institute in Troy, upstate New York USA. The Workshop and Conference will be a gathering of the global community of innovators and pioneers in the fields of architecture, design and engineering.
The event will be in two parts: a four day Workshop 19-22 March, and a public conference beginning with Talkshop 23 March, followed by a Symposium 24 March. The event follows the format of the highly successful preceding events sg2010 Barcelona and sg2011 Copenhagen.
sg2012 Challenge Material Intensities
Simulation, Energy, Environment
Imagine the design space of architecture was no longer at the scale of rooms, walls and atria, but that of cells, grains and vapour droplets. Rather than the flow of people, services, or construction schedules, the focus becomes the flow of light, vapour, molecular vibrations and growth schedules: design from the inside out.
The sg2012 challenge, Material Intensities, is intended to dissolve our notion of the built environment as inert constructions enclosing physically sealed spaces. Spaces and boundaries are abundant with vibration, fluctuating intensities, shifting gradients and flows. The materials that define them are in a continual state of becoming: a dance of energy and information.Material potential is defined by multiple properties: acoustical, chemical, electrical, environmental, magnetic, manufacturing, mechanical, optical, radiological, sensorial, and thermal. The challenge for sg2012 Material Intensities is to consider material economy when creating environments, micro-climates and contexts congenial for social interaction, activities and organisation. This challenge calls for design innovation and dialogue between disciplines and responsibilities.sg2010 Working Prototypes strove to emancipate digital design from the hard drive by moving from the virtual to the actual in wrestling with the tangible world of physical fabrication. sg2011 Building the Invisible focused on informing digital design with real world data. sg2012 Material Intensities strives to energise our digital prototypes and infuse them with material behaviour. They have the potential to become rich simulations informed by the material dynamics, chemical composition, energy flows, force fields and environmental conditions that feed back into the design process.
More information can be found at http://www.smartgeometry.org…
radiance parameters to get rid of blotching. To add another level of complexity to my problem, I am running simulations with a translucent material with the following properties: void trans testTrans
0
0
7 0.478 0.478 0.478 0.000 0.010 0.178 0.635
I have had no issues with the renderings when I use clear glazing, as seen on this image:
However the blotching-issue becomes very noticeable when I introduce translucent glazing into the scene:
For the two above cases I used the following parameters:
_av_ is set to 0
xScale is set to 2
_ab_ is set to 6
_dc_ is set to 0.5
_aa_ is set to 0.2
_ad_ is set to 2048
_st_ is set to 0.5
yScale is set to 2
_ps_ is set to 4
_ar_ is set to 64
_as_ is set to 2048
_ds_ is set to 0.25
_pt_ is set to 0.1
_dr_ is set to 1
_pj_ is set to 0.9
_dp_ is set to 256
_dt_ is set to 0.25
_lr_ is set to 6
_dj_ is set to 0.5
_lw_ is set to 0.01
I ran another test with increased Radiance parameters and got the following output:
with the following parameters:
_av_ is set to 0
xScale is set to 6
_ab_ is set to 6
_dc_ is set to 0.75
_aa_ is set to 0.1
_ad_ is set to 4096
_st_ is set to 0.15
yScale is set to 6
_ps_ is set to 2
_ar_ is set to 128
_as_ is set to 4096
_ds_ is set to 0.05
_pt_ is set to 0.05
_dr_ is set to 3
_pj_ is set to 0.9
_dp_ is set to 512
_dt_ is set to 0.15
_lr_ is set to 8
_dj_ is set to 0.7
_lw_ is set to 0.005
Although the second blotching case is much better than the first, it is still very bad for hours when the sun is lower in the sky. The above images are rendered for a clear sky at 18:00 in Germany in a West-facing room.
Sorry for the long post! Can someone help? Kind regards, Örn
…
the space that you are designing and your design intent. Just think about an atrium vs a museum. And now think of the atrium in two different climate zones. As a [lighting] designer you make the decision on how do you want the space to be, how the climate is and then try to take advantage of skylight and/or direct sunlight to achieve your design goals.
2. Yes. There is a watchTheSky component next to sky types which let you visualize the sky. There is also an example file that you can check.
3. This one again depends on your model. For your model I would suggest a minimum number of 4 for your final analysis. -ab is only one of the parameters. Check this slides by John Mardaljevic if you want to have a better understanding of radiance parameters and their effect on the results.
I also added the link to "Tutorial on the Use of Daysim Simulations for Sustainable Design" by Christoph Reinhart to teaching materials. I encourage you to at least read chapters 1 and 2 of the tutorial. Check pages 25 and 27 have two examples about selecting the parameters.
Great questions. Keep them coming.
Mostapha…
the space that you are designing and your design intent. Just think about an atrium vs a museum. And now think of the atrium in two different climate zones. As a [lighting] designer you make the decision on how do you want the space to be, how the climate is and then try to take advantage of skylight and/or direct sunlight to achieve your design goals.
2. Yes. There is a watchTheSky component next to sky types which let you visualize the sky. There is also an example file that you can check.
3. This one again depends on your model. For your model I would suggest a minimum number of 4 for your final analysis. -ab is only one of the parameters. Check this slides by John Mardaljevic if you want to have a better understanding of radiance parameters and their effect on the results.
I also added the link to "Tutorial on the Use of Daysim Simulations for Sustainable Design" by Christoph Reinhart to teaching materials. I encourage you to at least read chapters 1 and 2 of the tutorial. Check pages 25 and 27 have two examples about selecting the parameters.
Great questions. Keep them coming.
Mostapha…
evel in which each final branch contains a list of one number from each list in all its variations with the other two lists.
12
AB
xy
Becomes eight possible combinations:
1Ax
1Ay
1Bx
1By
2Ax
2Ay
2Bx
2By
Either I could immediately break into 8 branches or branch twice from 2 items to 4 items then from those 4 items to 8 final items. I keep trying grafting with all manner of tree components and *never* obtain a simple dual branching fractal tree structure. I barely even need a tree actually, but I'd prefer each final branch to contain a list I can pull each final value individual value out of rather than dealing with string extraction. This is all to eventually plug all these variations into a parametric mesh model that now uses three sliders, and Python script also to bake them all as OBJ files.
Crucially I also need to obtain the numbers to use as part of my multiply exported OBJ files. I can so far only get a single range to export as a series of OBJ files automatically but not the whole three list array of them.
…
ace when I start running Galapagos/Octopus (below is "room orientation optimization" shared at http://hydrashare.github.io/hydra/viewer?owner=mostaphaRoudsari&fork=hydra_1&id=Room_Orientation_Optimization&slide=0&scale=1&offset=0,0) It may take quite some time to see some results. That's fine for the above simulation. But my real challenge is, when I am going to optimize room dimension with respect to ASE and sDA calculations, either Galapagos or Octopus goes wildly and never come up with a solution. I believe the time-consuming calculation, especially sDA with higher -ab numbers, trigger the lag a lot? Any suggestion/trick to improve it?
Most importantly, based on your experience, for example to optimize window/exterior shades sizes and achieve ASE<10% and sDA>55% (LEED v.4 requirements), Octopus (due to its capacity of multiple objectives) is the only choice? Any other approaches within grasshopper?
Many thank!
Cheney
…
rce of power.
A fortified emplacement for heavy guns.
Synonyms
accumulator
And use component:
com·po·nent
/kəmˈpōnənt/
Noun
A part or element of a larger whole, esp. a part of a machine or vehicle.
Adjective
Constituting part of a larger whole; constituent.
Synonyms
noun.
constituent - element - ingredient - part
adjective.
constituent - constitutive
…
n to finding a concave contour polyline (which is in general what you need). In your case each contour section contains a series of points of which you do not know the order and you need to sort them so that by connecting them you find the contour. This is fairly easy to do when the contour is convex (basically you find the average point then calculate the vectors from the average to the points and sort the vectors by angle - sorting the points by the same angle gives you the right order for the contour), but generally impossible to find uniquely when the contour is concave (PS: convex means that, for ANY 2 points inside the figure, a straight line connecting them doesn't intersect with the border curve - i.e. circles, ellipses, rectangles, triangles - concave shapes are a star, a crescent moon, an arrow, a boomerang, etc.).
The problem goes like this: given a generic list of points:
Each of these configurations for a perimeter equally fits the above:
Laurent already went for another possible solution, the stochastic approach (by subdividing the connecting lines), I slightly adjusted a few things over his solution:
namely, I added a rounding option to adjust for some weird tolerance issues (some points that should be at Y=80 were at Y=79.99998 or something) and a more straightforward solution to group them by section plane using sets logic. This, coupled with alpha shape, gives a quite good approach, still very coarse in terms of results but that depends on the sampling resolution of the field (i.e. number of height sections in which you calculate the metaballs) and sampling length of the connecting lines.
Definition attached.…
Diffraction , I left it, how it is.
For the unusual issues that comes in the image source component, so, is it something strange? But, I still have the same issues when I sets any integer component (single or multiple) in the “reflection order” of the image source component, in the “image source order” in the ray tracing component, and again, when I connect the output “Direct sound data” of Direct Sound component in the Energy Time Curve.
Do I wrong something with the integer component? I used it already in the first parts, for sets “grasshopper layers”, in the “Scene” component, but here it works. Should I start with a new file?
For the multi-object optimization, thank you for all suggestions. Yes, I red PHD thesis work of Tomas Mendez and the article “ EDT, C80 and G Driven Auditorium design” and still others. Thank you to all these articles, I decided where to focus my thesis.
I understand the potential of Multi-object optimization, and problems that I can finding without using it. Actually, in the beginning of my thesis, I tried to jet in contact with the Politecnico di Torino, but was not easy because I’m not a Politecnico student.
Here, in University of Florence (Building engineering), there isn’t a department or someone that is already familiar with these field of study, so, as you can image, for design my thesis, I can confide on online resources. So far, my Professor suggest me to begin with a Nonlinear Global optimization like Galapagos, and only after see the multi-object. In this way, step by step if something doesn’t work is easier to understand way and where something is going wrong: if are problems due to the setting of the programs, because we are not practical about these, or if there is a wrong in the simulations or in the algorithm and ect.
Do you think is a good way for go on?
Thank you very much,
Kind Regards
Giulia
…
it seems that was this. Now all is working fine !
Glad that it worked! But I am still a bit worried. Gismo components only modify the gdal-data/osmconf.ini file and no other MapWinGIS file. So your MapWinGIS installation files should not be compromised. The fact that you did not get the "COM CLSID" error message when running the "Gismo Gismo" component suggests that MapWinGIS has been properly installed. So I wonder if the cause for the permanent "invalid shapes" warning has again something with the fact that your system is again not allowing the MapWinGIS to properly edit the osmconf.ini. Maybe this problem will appear again, and again, and reinstallation of MapWinGIS every time can be somewhat bothersome.
- About the terrain generation, is it possible to have the texture from google or other provider mapped onto the terrain surface from gismo component ? (Same as using the ladybug terrain generator in fact). I try to used the image extracted by ladybug component and then applied it to the gismo terrain but the texture is rotated by 90°.
The issue with the rotation can be solved by swapping/reversing the U,V directions of the terrain surface. A slightly more important issue is that terrain surface generated with Gismo "Terrain Generator" component might have a bit smaller radius than what the radius_ input required. This stems from the fact that the terrain data first needs to be downloaded in geographic coordinate system, and then projected. Some projecting issues may occur at the very edges of the projected terrain, so I had to slightly cut out the very edges of the terrain which results in the actual terrain diameters being slightly shorted in both directions. This means that if you apply the same satellite image from Ladybug "Terrain Generator" component to Gismo "Terrain Generator" component the results may not be the same.I attached below a python component which tries to solve this issue by extending the edges of Gismo "Terrain Generator" terrain, and then cutting them with the cuboid of the exact dimensions as the radius_ input. Have in mind that this extension of the original terrain at its edges is not a correct representation of the actual terrain in that location. But rather just an extension of the isoparameteric curve of the terrain surface. So basically: some 0 to 10% (0 to 10 percent of the width and length) of the terrain around all four edges is not the actual terrain for that location, but rather just its extension.The python component is located at the very right of the definition attached below.
Also, if you would like to use the satellite images from Ladybug "Terrain Generator" component along with "OSM shapes", sometimes you may find slight differences in position of the shapes. This is due to openstreetmap data not being based on Google Maps (that's what Ladybug "Terrain Generator" component is using), but rather on Bing, MapQuest and a few others.
- About the requiredKeys_ input of OSM shapes, I understand what you mean and your advice, but in most cases I use it, the component was working fine even without input. I think it's better to extract all tags, values and keys of the selected area, instead of searching for specific ones as I try to find all data related to what I want after, isn't it ? To check what keys are present on the area also.
Ineed, you are correct.I though you were trying to only create a terrain, 3d buildings and maybe find some school or similar 3d building, for these two locations. The recommendation I mentioned previously is due to shapefiles having a limit (2044) to how many keys it can contain. This requires further testing of some big cities locations with maybe larger radii, which I haven't performed due to my poor PC configuration. But in theory, I imagine that it may happen that a downloaded .osm file may have more than 2044 keys. In that case shapefile will only record 2044 of them, and disregard the others. That was my point.But again 2044 is a lot of keys, and I haven't been checking much this in practice. For example, when I set the radius_ to 1000 meters, and use your "3 Rue de Bretonvilliers Paris" location I get around 350 something keys, which is way below the 2044.Another reason why one should use the requiredKeys_ input is to make the Gismo OSM components run quicker: for example, the upper mentioned 350 something keys will result in 350 values for each branch of the "OSM shapes" component's "values" output.Which means if you have 10 000 shapes, the "OSM shapes" component will have 10 000 branches with 350 items on each branch (values). This can make all Gismo OSM components very heavy, and significantly elongate the calculation process.With requiredKeys_ input you may end up with only a couple of tens of items per each branch.Sorry for the long reply.…
Added by djordje to Gismo at 8:57am on June 11, 2017