Ladybug + Honeybee:
(Follow steps 0-4 for basic functionality and 0-9 for full functionality)
0. If you have an old version of LB+HB, download the file here (https://app.box.com/s/ds96em9l6stxpcw8kgtf)
and open it in Grasshopper to remove your old Ladybug and Honeybee version.
1. Make sure that you have a working copy of both Rhino and Grasshopper installed.
2. Open Rhino and type "Grasshopper" into the command line (without quotations). Wait for grasshopper to load.
3. Install GHPython 0.6.0.3 by downloading the file at this link (http://www.food4rhino.com/project/ghpython?ufh) and
drag the .gha file onto the Grasshopper canvas.
4. Select and drag all of the userObject files (downloaded with this instructions file) onto your Grasshopper canvas.
You should see Ladybug and Honeybee appear as tabs on the grasshopper tool bar.
(If you are reading this instruction on github you can download them from http://www.food4rhino.com/project/ladybug-honeybee)
5. Restart Rhino and Grasshopper. You now have a fully-functioning Ladybug. For Honeybee, continue to the following:
6. Install Radiance to C:\Radiance by downloading it from this link (https://github.com/NREL/Radiance/releases/download/4.2.2/radiance-4.2.2-win32.exe) and running the exe.
7. Install Daysim 4.0 for Windows to C:\DAYSIM by downloading it at this link (http://daysim.ning.com/page/download) and running the exe.
8. Install EnergyPlus 8.1 to C:\EnergyPlusV8-1-0 by going to the DOE website (http://apps1.eere.energy.gov/buildings/energyplus/energyplus_download.cfm), making an account, going to "download older
versions of EnergyPlus, selecting 8.1 and running the exe.
9. Copy falsecolor2.exe (http://pyrat.googlecode.com/files/falsecolor2.exe) and evalglare.exe (http://www.ise.fraunhofer.de/en/downloads-englisch/software/evalglare_windows.zip/at_download/file) to C:\Radiance\bin
10. You now have a fully-working version of Ladybug + Honeybee. Get started visualizing weather data with these video tutorials (https://www.youtube.com/playlist?list=PLruLh1AdY-Sj_XGz3kzHUoWmpWDXNep1O).
After I've done all the above I followed this video
https://vimeo.com/96155674
And everything works well.
…
nted" in space (at instance definition creation phase): indicates the obvious fact that if garbage in > garbage out (try it).
2. Load the GH thing. Task for you: Using Named Views locate the points of interest as described further and make a suitable view. That way you can navigate rather easily around (hope dies last).
3. Your attractors are controlled from here:
The slider in blue picks some attractor to play with. You can use this while the K2 is running.
4. Don't change anything here (think of it as a black box: who cares how it works? nobody actually):
5. Enable the other "black box": job done your real-life stuff is placed:
6. Enable the solver: your "real-life" things start to bounce around:
7. Go there are play with the slider. A different attractor yields an other solution:
8. With real-life things in place if you disable the C# ... they are instantly deleted and you are back in lines/points and the likes:
9. Either with instance definitions or Lines/points change ... er ... hmm ... these "simple" parameters and discover the truth out there:
10. Since these are a "few" and they affect the simulation with a variety of ways ... we need a "self calibrating" system: some mini big Brother that does the job for us. Kinda like applying safely the brakes when it rains (I hate ABS mind).
NOTE: the rod with springs requires some additional code ,more (that deals with NESTED instance definitions) in order to (b) bounce as a whole and at the same time (b) elongates or shrinks a bit.
More soon.
…
ng/702/30
EDIT: DK2 works, not with positional tracking yet (14/09/15)
Source is here:
https://github.com/provolot/RhinoRift
Steps:
1) Download these files (also attached below):
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper_v0.4.ghx
https://github.com/provolot/oculus-grasshopper/raw/master/OpenTrackRiftGrasshopperUDP.ini
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper-test_v0.1.3dm
2) Download OpenTrack - http://ananke.laggy.pk/opentrack/, and setup/install. Once installed, double-click to open.
3) In OpenTrack, load the 'OpenTrackRiftGrasshopperUDP.ini' profile. Click the 'Start' button and move your Rift around - make sure that it looks like the Yaw/Pitch/Roll data is being sent. TX/TY/TZ will all be 0, as Oculus doesn't have absolute positioning data.
4) In Rhino, open the test 3dm. You'll notice that there are two viewports - called 'LeftEye' and 'RightEye'. These have been placed to mimic where the screens should be for the Oculus Rift --- but only when Rhino is in fullscreen mode, with the command 'Fullscreen'. The placement needs to be tweaked, but should work.
If you want to use your own model, you can load your own .3dm file in Rhino, then you can right-click on the viewport name, and go to Viewport Layout > Read from File. If you then load my test file, Rhino should open my two viewports, sized correctly, onto your model.
The placement of these viewports need to be tweaked; if you find a better viewport layout, upload an empty Rhino file with your viewports, and we can share eye-layout 'templates'!
5) In Grasshopper, open the .ghx definition. Everything that is multiple-grouped is a value that can be changed. Two things here:
- IPD: Set this and convert it to the proper units for your model.
- Left/right viewport names. In this case, leave this as-is, since you're using my example file.
6) Turn on the Grasshopper Timer, if it isn't on already.
7) In the GH definition, toggle 'SyncEyes' to be True. Then, in the left viewport, try orbiting around with the mouse. The 'RightEye' viewport should move around as well, pretty much simultaneously.
8) In OpenTrack, click 'Start', then toggle 'ReadUDP' to be True. You should see the 'OpenTrackInfo' panel fill with data that's constantly changing.
9) Move around the landscape with your camera, and when you set on a starting view that's ideal, click the triangle of the Data Dam component to 'store' the data.
10) Finally, toggle 'OculusMove' to be true. If all works correctly, both viewports should move based on the Rift's movement.
Let me know if you have any problems!
Cheers,
Dan…
Added by Dan Taeyoung at 11:47pm on December 10, 2013
xes as well.
If you want to jump straight in, you can download the latest build from the Firefly website or from Food4Rhino project page. Or, if you'd rather learn more about all the new features, keep reading!
Improved Arduino Support The Firefly Firmata (Arduino Sketch) has gone through a massive overhaul - making it much more compact, efficient, and extensible. The sketch is now just over 230 lines of code (compared to more than 500 in the previous version). But more importantly, the firmata is now more extensible; making it easier to add support for new Arduino boards... Like what you ask? Well, support for the new Arduino Due platform for example. The Arduino Due is an advanced board and while it may look similar to the Arduino Mega... it's actually quite different under the hood. It features an ARM Cortex-M3 CPU which means its really fast. It also features 12-bit analog resolution for reading and writing (which is pretty awesome). As I said, the Due is a more advanced board and it does require some caution when getting started. You can find out more about the Due platform at the Arduino Due Getting Started page.
One of the biggest changes with the revision of the Firmata was that it required some structural changes with how the data is sent/received from Grasshopper. So, if you are planning on using the latest version of the Firmata, you'll need to also have the latest Firefly components installed as well. This shouldn't be an issue because the installer will place the new Firefly Firmata in your sketchbook folder and install the new components as well... but it's worth noting so you don't try to mix and match the versions.
Kinect Version 2 Support Earlier this summer, Microsoft released a new and improved version of its popular Kinect motion tracking sensor. The sensor includes better body, hand, and joint orientation, 1080p color video (1920x1080), depth video (512x424), and a new active infrared video (512x424). The sensor now has the capability to track up to 6 people at once (compared to only two people with the previous version).
This build of Firefly now comes with three new components to work with this new sensor. The Video Stream can access the color, depth, and infrared video streams at different resolutions. Simply right-click on the video component to choose the video feed and resolution. Note: You may need to update your graphics card in order to get the infrared video stream to work properly (at least I did before it began working properly). The Skeleton Tracker is similar to the previous version, but can now track up to 6 people. And the Mesh Reconstruction component will build a fully colored 3D mesh using the color and depth data from the sensor. I plan to add more components to this section soon, but I wanted to go ahead and release this so more people could use it! [EDIT: I would like to thank Panagiotis Michalatos for his collaboration in the development of the Kinect V2 tools].
New Computer Vision Tools This release also includes a number of new computer vision tools. One component to note is the Bitmap Tracer, which can be seen in action here. The Bitmap Tracer component spawns a number of randomly generated particles which trace the edges of a bitmap using the nearest contouring vector. Another pair of components is the Bitmap Decompose/Recompose which can either decompose or reconstruct a bitmap using a list of values for its constituent channels. These two can be used together to swap channels in an image (think chroma keying). There's also a Bitmap Threshold component which uses the average dithering algorithm to find the color quantization of an image. Lastly, I've updated the Leap Motion Finger Tracking component to work with the latest release of the Leap v2.2.1 software release. The component now has improved finger tracking including joint and bone position/orientation.
In addition to these new features, there's also a number of bug fixes too (check out the readme if your interested). As always, I welcome any and all feedback on this build. Your support really helps, so please let me know what you think!…
xes as well.
If you want to jump straight in, you can download the latest build from the Firefly website or from Food4Rhino project page. Or, if you'd rather learn more about all the new features, keep reading!
Improved Arduino Support The Firefly Firmata (Arduino Sketch) has gone through a massive overhaul - making it much more compact, efficient, and extensible. The sketch is now just over 230 lines of code (compared to more than 500 in the previous version). But more importantly, the firmata is now more extensible; making it easier to add support for new Arduino boards... Like what you ask? Well, support for the new Arduino Due platform for example. The Arduino Due is an advanced board and while it may look similar to the Arduino Mega... it's actually quite different under the hood. It features an ARM Cortex-M3 CPU which means its really fast. It also features 12-bit analog resolution for reading and writing (which is pretty awesome). As I said, the Due is a more advanced board and it does require some caution when getting started. You can find out more about the Due platform at the Arduino Due Getting Started page.
One of the biggest changes with the revision of the Firmata was that it required some structural changes with how the data is sent/received from Grasshopper. So, if you are planning on using the latest version of the Firmata, you'll need to also have the latest Firefly components installed as well. This shouldn't be an issue because the installer will place the new Firefly Firmata in your sketchbook folder and install the new components as well... but it's worth noting so you don't try to mix and match the versions.
Kinect Version 2 Support Earlier this summer, Microsoft released a new and improved version of its popular Kinect motion tracking sensor. The sensor includes better body, hand, and joint orientation, 1080p color video (1920x1080), depth video (512x424), and a new active infrared video (512x424). The sensor now has the capability to track up to 6 people at once (compared to only two people with the previous version).
This build of Firefly now comes with three new components to work with this new sensor. The Video Stream can access the color, depth, and infrared video streams at different resolutions. Simply right-click on the video component to choose the video feed and resolution. Note: You may need to update your graphics card in order to get the infrared video stream to work properly (at least I did before it began working properly). The Skeleton Tracker is similar to the previous version, but can now track up to 6 people. And the Mesh Reconstruction component will build a fully colored 3D mesh using the color and depth data from the sensor. I plan to add more components to this section soon, but I wanted to go ahead and release this so more people could use it! [EDIT: I would like to thank Panagiotis Michalatos for his collaboration in the development of the Kinect V2 tools].
New Computer Vision Tools This release also includes a number of new computer vision tools. One component to note is the Bitmap Tracer, which can be seen in action here. The Bitmap Tracer component spawns a number of randomly generated particles which trace the edges of a bitmap using the nearest contouring vector. Another pair of components is the Bitmap Decompose/Recompose which can either decompose or reconstruct a bitmap using a list of values for its constituent channels. These two can be used together to swap channels in an image (think chroma keying). There's also a Bitmap Threshold component which uses the average dithering algorithm to find the color quantization of an image. Lastly, I've updated the Leap Motion Finger Tracking component to work with the latest release of the Leap v2.2.1 software release. The component now has improved finger tracking including joint and bone position/orientation.
In addition to these new features, there's also a number of bug fixes too (check out the readme if your interested). As always, I welcome any and all feedback on this build. Your support really helps, so please let me know what you think!
…
nts for Ladybug too. They are based on PVWatts v1 online calculator, supporting crystalline silicon fixed tilt photovoltaics.
You can download them from here, or use the Update Ladbybug component instead. If you take the first option, after downloading check if .ghuser files are blocked (right click -> "Properties" and select "Unblock").
You can download the example files from here.
Video tutorials will follow in the coming period.
In the very essence these components help you answer the question: "How much energy can my roof, building facade, solar parking... generate if I would populate them with PV panels"?
They allow definition of different types of losses (snow, age, shading...) which may affect your PV system:
And can find its optimal tilt and orientation:
Or analyse its performance, energy value, consumption, emissions...
By Djordje Spasic and Jason Sensibaugh, with invaluable support of Dr. Frank Vignola, Dr. Jason M. Keith, Paul Gilman, Chris Mackey, Mostapha Sadeghipour Roudsari, Niraj Palsule, Joseph Cunningham and Christopher Weiss.
Thank you for reading, and hope you will enjoy using the components!
EDIT: From march 27 2017, Ladybug Photovoltaics components support thin-film modules as well.
References:
1) System losses:
PVWatts v5 Manual, Dobos, NREL, 2014
2) Sun postion equations by Michalsky (1988):
SAM Photovoltaic Model Technical Reference, Gilman, NREL, 2014
edited by Jason Sensibaugh
3) Angle of incidence for fixed arrays:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
4) Plane-of-Array diffuse irradiance by Perez 1990 algorithm:
PVPMC Sandia National Laboratories
SAM Photovoltaic Model Technical Reference, Gilman, NREL, 2014
5) Sandia PV Array Performance Module Cover:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
6) Sandia Thermal Model, Module Temperature and Cell Temperature Models:
Photovoltaic Array Performance Model, King, Boys, Kratochvill, Sandia National Laboratories, 2004
7) CEC Module Model: Maximum power voltage and Maximum power current from:
Exact analytical solutions of the parameters of real solar cells using Lambert W-function, Jain, Kapoor, Solar Energy Materials and Solar Cells, V81 2004, P269–277
8) PVFORM version 3.3 adapted Module and Inverter Models:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
9) Sunpath diagram shading:
Using sun path charts to estimate the effects of shading on PV arrays, Frank Vignola, University of Oregon, 2004
Instruction manual for the Solar Pathfinder, Solar Pathfinder TM, 2008
10) Tilt and orientation factor:
Application for Purchased Systems Oregon Department of Energy
solmetric.com
11) Photovoltaics performance metrics:
Solar PV system performance assessment guideline, Honda, Lechner, Raju, Tolich, Mokri, San Jose state university, 2012
CACHE Modules on Energy in the Curriculum Solar Energy, Keith, Palsule, Mississippi State University
Inventory of Carbon & Energy (ICE) Version 2.0, Hammond, Jones, SERT University of Bath, 2011
The Energy Return on Energy Investment (EROI) of Photovoltaics: Methodology and Comparisons with Fossil Fuel Life Cycles, Raugei, Fullana-i-Palmer, Fthenakis, Elsevier Vol 45, Jun 2012
12) Calculating albedo: Metenorm 6 Handbook part II: Theory, Meteotest 2007
13) Magnetic declination:
Geomag 0.9.2015, Christopher Weiss…
ng is deciding how and where to store your data. If you're writing textual code using any one of a huge number of programming languages there are a lot of different options, each with its own benefits and drawbacks. Sometimes you just need to store a single data point. At other times you may need a list of exactly one hundred data points. At other times still circumstances may demand a list of a variable number of data points.
In programming jargon, lists and arrays are typically used to store an ordered collection of data points, where each item is directly accessible. Bags and hash sets are examples of unordered data storage. These storage mechanisms do not have a concept of which data comes first and which next, but they are much better at searching the data set for specific values. Stacks and queues are ordered data structures where only the youngest or oldest data points are accessible respectively. These are popular structures for code designed to create and execute schedules. Linked lists are chains of consecutive data points, where each point knows only about its direct neighbours. As a result, it's a lot of work to find the one-millionth point in a linked list, but it's incredibly efficient to insert or remove points from the middle of the chain. Dictionaries store data in the form of key-value pairs, allowing one to index complicated data points using simple lookup codes.
The above is a just a small sampling of popular data storage mechanisms, there are many, many others. From multidimensional arrays to SQL databases. From readonly collections to concurrent k-dTrees. It takes a fair amount of knowledge and practice to be able to navigate this bewildering sea of options and pick the best suited storage mechanism for any particular problem. We did not wish to confront our users with this plethora of programmatic principles, and instead decided to offer only a single data storage mechanism.*
Data storage in Grasshopper
In order to see what mechanism would be optimal for Grasshopper, it is necessary to first list the different possible ways in which components may wish to access and store data, and also how families of data points flow through a Grasshopper network, often acquiring more complexity over time.
A lot of components operate on individual values and also output individual values as results. This is the simplest category, let's call it 1:1 (pronounced as "one to one", indicating a mapping from single inputs to single outputs). Two examples of 1:1 components are Subtraction and Construct Point. Subtraction takes two arguments on the left (A and B), and outputs the difference (A-B) to the right. Even when the component is called upon to calculate the difference between two collections of 12 million values each, at any one time it only cares about three values; A, B and the difference between the two. Similarly, Construct Point takes three separate numbers as input arguments and combines them to form a single xyz point.
Another common category of components create lists of data from single input values. We'll refer to these components as 1:N. Range and Divide Curve are oft used examples in this category. Range takes a single numeric domain and a single integer, but it outputs a list of numbers that divide the domain into the specified number of steps. Similarly, Divide Curve requires a single curve and a division count, but it outputs several lists of data, where the length of each list is a function of the division count.
The opposite behaviour also occurs. Common N:1 components are Polyline and Loft, both of which consume a list of points and curves respectively, yet output only a single curve or surface.
Lastly (in the list category), N:N components are also available. A fair number of components operate on lists of data and also output lists of data. Sort and Reverse List are examples of N:N components you will almost certainly encounter when using Grasshopper. It is true that N:N components mostly fall into the data management category, in the sense that they are mostly employed to change the way data is stored, rather than to create entirely new data, but they are common and important nonetheless.
A rare few components are even more complex than 1:N, N:1, or N:N, in that they are not content to operate on or output single lists of data points. The Divide Surface and Square Grid components want to output not just lists of points, but several lists of points, each of which represents a single row or column in a grid. We can refer to these components as 1:N' or N':1 or N:N' or ... depending on how the inputs and outputs are defined.
The above listing of data mapping categories encapsulate all components that ship with Grasshopper, though they do not necessarily minister to all imaginable mappings. However in the spirit of getting on with the software it was decided that a data structure that could handle individual values, lists of values, and lists of lists of values would solve at least 99% of the then existing problems and was thus considered to be a 'good thing'.
Data storage as the outcome of a process
If the problems of 1:N' mappings only occurred in those few components to do with grids, it would probably not warrant support for lists-of-lists in the core data structure. However, 1:N' or N:N' mappings can be the result of the concatenation of two or more 1:N components. Consider the following case: A collection of three polysurfaces (a box, a capped cylinder, and a triangular prism) is imported from Rhino into Grasshopper. The shapes are all exploded into their separate faces, resulting in 6 faces for the box, 3 for the cylinder, and 5 for the prism. Across each face, a collection of isocurves is drawn, resembling a hatching. Ultimately, each isocurve is divided into equally spaced points.
This is not an unreasonably elaborate case, but it already shows how shockingly quickly layers of complexity are introduced into the data as it flows from the left to the right side of the network.
It's no good ending up with a single huge list containing all the points. The data structure we use must be detailed enough to allow us to select from it any logical subset. This means that the ultimate data structure must contain a record of all the mappings that were applied from start to finish. It must be possible to select all the points that are associated with the second polysurface, but not the first or third. It must also be possible to select all points that are associated with the first face of each polysurface, but not any subsequent faces. Or a selection which includes only the fourth point of each division and no others.
The only way such selection sets can be defined, is if the data structure contains a record of the "history" of each data point. I.e. for every point we must be able to figure out which original shape it came from (the cube, the cylinder or the prism), which of the exploded faces it is associated with, which isocurve on that face was involved and the index of the point within the curve division family.
A flexible mechanism for variable history records.
The storage constraints mentioned so far (to wit, the requirement of storing individual values, lists of values, and lists of lists of values), combined with the relational constraints (to wit, the ability to measure the relatedness of various lists within the entire collection) lead us to Data Trees. The data structure we chose is certainly not the only imaginable solution to this problem, and due to its terse notation can appear fairly obtuse to the untrained eye. However since data trees only employ non-negative integers to identify both lists and items within lists, the structure is very amenable to simple arithmetic operations, which makes the structure very pliable from an algorithmic point of view.
A data tree is an ordered collection of lists. Each list is associated with a path, which serves as the identifier of that list. This means that two lists in the same tree cannot have the same path. A path is a collection of one or more non-negative integers. Path notation employs curly brackets and semi-colons as separators. The simplest path contains only the number zero and is written as: {0}. More complicated paths containing more elements are written as: {2;4;6}. Just as a path identifies a list within the tree, an index identifies a data point within a list. An index is always a single, non-negative integer. Indices are written inside square brackets and appended to path notation, in order to fully identify a single piece of data within an entire data tree: {2,4,6}[10].
Since both path elements and indices are zero-based (we start counting at zero, not one), there is a slight disconnect between the ordinality and the cardinality of numbers within data trees. The first element equals index 0, the second element can be found at index 1, the third element maps to index 2, and so on and so forth. This means that the "Eleventh point of the seventh isocurve of the fifth face of the third polysurface" will be written as {2;4;6}[10]. The first path element corresponds with the oldest mapping that occurred within the file, and each subsequent element represents a more recent operation. In this sense the path elements can be likened to taxonomic identifiers. The species {Animalia;Mammalia;Hominidea;Homo} and {Animalia;Mammalia;Hominidea;Pan} are more closely related to each other than to {Animalia;Mammalia; Cervidea;Rangifer}** because they share more codes at the start of their classification. Similarly, the paths {2;4;4} and {2;4;6} are more closely related to each other than they are to {2;3;5}.
The messy reality of data trees.
Although you may agree with me that in theory the data tree approach is solid, you may still get frustrated at the rate at which data trees grow more complex. Often Grasshopper will choose to add additional elements to the paths in a tree where none in fact is needed, resulting in paths that all share a lot of zeroes in certain places. For example a data tree might contain the paths:
{0;0;0;0;0}
{0;0;0;0;1}
{0;0;0;0;2}
{0;0;0;0;3}
{0;0;1;0;0}
{0;0;1;0;1}
{0;0;1;0;2}
{0;0;1;0;3}
instead of the far more economical:
{0;0}
{0;1}
{0;2}
{0;3}
{1;0}
{1;1}
{1;2}
{1;3}
The reason all these zeroes are added is because we value consistency over economics. It doesn't matter whether a component actually outputs more than one list, if the component belongs to the 1:N, 1:N', or N:N' groups, it will always add an extra integer to all the paths, because some day in the future, when the inputs change, it may need that extra integer to keep its lists untangled. We feel it's bad behaviour for the topology of a data tree to be subject to the topical values in that tree. Any component which relies on a specific topology will no longer work when that topology changes, and that should happen as seldom as possible.
Conclusion
Although data trees can be difficult to work with and probably cause more confusion than any other part of Grasshopper, they seem to work well in the majority of cases and we haven't been able to come up with a better solution. That's not to say we never will, but data trees are here to stay for the foreseeable future.
* This is not something we hit on immediately. The very first versions of Grasshopper only allowed for the storage of a single data point per parameter, making operations like [Loft] or [Divide Curve] impossible. Later versions allowed for a single list per parameter, which was still insufficient for all but the most simple algorithms.
** I'm skipping a lot of taxonometric classifications here to keep it simple.…
Added by David Rutten at 2:22pm on January 20, 2015
titute of Architecture at the University of Applied Arts.
Integrated Digital Design and Fabrication Architectural Design at the Angewandte is taught as an integrated, multidisciplinary process. Following this tradition, the design process will be enriched with structural testing of parametric models in Karamba, a structural analysis plugin for Grasshopper developed as a research project at the Department of Structural Design at the Angewandte. The research project was awarded the Austrian “Baupreis 2010/11″. Specialists from Bollinger+Grohmann Engineers will co-tutor the workshop. The handling of virtual simulation methods in the fields of parametric and digital production will be a primary focus of the workshop. This week long intense workshop will result not only in full scale built structures, but will also inform and prepare interested students for the MArch entrance exam (22nd-24th Feb. or 26th-28th Sept. 2012) and the architecture study program at the Angewandte.
Format & Output The Spring Challenge Program will be organized as a 6 day event. Participation is expected fulltime starting 9am. Introduction to Rhino/Grasshopper/Karamba will be followed by project design development and daily reviews of group projects which will enter into a competition mode. Selected projects will be fabricated and assembled as a group effort. The workshop will close with a final presentation with guests. The output will be parametrically designed and digitally produced human scale structures. The used material will be corrugated cardboard.
Organization Time & Location: 13th-18th February 2012 in Studio Greg Lynn / Angewandte / Vienna Info: www.springchallenge2012.wordpress.com www.facebook.com/springchallenge2012 Application, Q&A:
springchallenge2012@uni-ak.ac.at
Material Fee: early bird 150 € (until 25th January) 190 € (after 25th January) Instructors IoA Team: Sen.Sc. Mag.arch. MArch (Harvard) Andrei Gheorghe, Univ.Ass. Mag.arch. Bence Pap Bollinger+Grohmann: Clemens Preisinger…