e think. Also, its easier to catch an error because the malicious component simply turns red/orange (in most cases). However, if you are adept at scripting, you are probably very used to recursive looping & conditional evaluation which you miss majorly in GH (it is possible in very limited ways through using series components or comparer components). So an adept scriptor may soon end up switching back to Rhinoscript unless they find the shift from VBscript to VB.net really fast & smooth (which is rare).
GH ofcourse has the advantage of keeping it all 'alive' and changing things with sliders/graphs/image painting, compared to Rhinoscript which is a run-once operation -- so that's where one makes a choice between recursive looping (in RS) & live interactivity (in GH). I'd say RS mostly wins the battle because interactivity is fancy, but recursion can be a necessity.
Now to VB.net. The one barrier I have hit most often with GH is speed. If you were working on a fairly large data set, or doing a number of surface/polysurface/brep operations, you hit the performance ceiling real fast, which is when the interactivity becomes almost useless -- because its nowhere close to real time anymore even if you had 12gb ram. Thus steps in VB.net (A bit of clever scripting can make a really significant difference).
Working a series of geometric operations in a code component is much faster than doing it through native GH components due to the fact that each native component comes with tonnes off error trapping code, preview generation (I think even if you turn it off, its still being computed, only not displayed), etc. while with VB, you can circumvent a lot of that.
If GH were to handle geometry even remotely comparable to what GC/Catia* can do, it would have a long way to go -- I am not sure if that is even the objective. For instance, I am currently working on a tower where all geometry is only meshes and polylines - no degree 3 curves, no surfaces/polysurfaces. This is because if the entire tower is to stay 'alive', Meshes are the lightest option with the amount of geometry being generated. And most of it is through code... there's only the sliders and a couple of other components that are GH native -- and its still in GH due to the interactivity. (I think there's a vast potential with Meshes that GH/Rhino are really not tapping into. There are all the building blocks, but no significant implementation. Giulio's weaverbird plugin is just a small example).
*GC/Catia cost significantly more than Rhino itself, and GH is a free plugin to Rhino. Morever, these softwares were written to be parametric modelling softwares from day1, unlike GH which is an add-on over the RhinoSDK, which was never developed from such a perspective. So a very very unfair comparison there, but GH is becoming so significant that its got a forum of its own -- gaining an almost 'independent software' status. I just hope the McNeel marketing people are not listening :)…
we're actually using PET sheets for our flexures. We try to design so that the flexures don't go through more than +/- 30 degrees of deflection. If the angular deflection is kept small, the lifetime can definitely be on the order of 1000000 cycles.
As for the design process (item 2), ideally the designer would be able to use a simple 3D CAD tool to design a model of a robot, and the geometry would be represented by dimensioning the individual parts in the model. Maybe there should be some parametric primitive kinematic building blocks like four bar linkages, box frames, etc. that a user could build up a robot from. But, the key functionality the tool needs to provide is for the designer to be able to visualize how the robot will move when it's fabricated. This could mean observing (or plotting) the motion of a leg, a wing, or a series of body segments. Ideally, then, the tool would generate an unfolding of the design. How this would work is still very vague - maybe the user would assist in the unfolding, maybe there would be an optimization routine that computes optimal unfoldings based on criteria like minimal waste, or fewest pieces (I would *not* constrain the problem to construction from a single monolithic piece as in origami). The biggest problem we have right now, is that our design process is totally divorced from fabrication. Even if we went through the trouble of extruding individual thin plates in Solidworks and creating an assembly for visualizing the kinematics of a mechanism, that particular representation doesn't transfer easily to the fabrication process because it's essentially monolithic.
Item 3: The 2D drawing is simple a drawing done manually in Solidworks. There are different layers for flexure cuts, outline cuts, and potentially any cuts to be made in the plastic flexure layer. Depending on the robot, there may be many separate pieces for different parts and linkages in a single robot. For example, the drawing for a robot containing a fourbar linkage may have the linkage laid out as a physically separate piece consisting of five rigid links connected by four flexure hinges. During assembly, the designer would then fold up that linkage and insert it into the robot wherever it's supposed to go. If you're curious you can see some sample 2D drawings for older designs here: http://robotics.eecs.berkeley.edu/~ronf/Prototype/ under the "Example Structures" heading.
I noticed Kangaroo seems to be a popular choice for physical simulations. I don't really even need to include forces like bending resistance - I'm happy to allow the design tool to approximate flexures as pin joint-type hinges. Once the design is unfolded, the details of how to cut the flexures could be worked out in a post-processing step. I wouldn't expect the tool to be able to realistically simulate the bending of the hinges.
I'm going to have to dig a lot deeper into understanding Grasshopper and Kangaroo. I only just got started with Grasshopper today by following the folding plate tutorial on wa11ace.com.au today. …
round each gap is called a compact circle packing, and this isn't always possible to achieve exactly on every surface, but luckily for a sphere it is.
You can break the problem into 2 parts:
-The combinatorics, or connectivity, ie how many circles there are, and which is tangent to which. This is often represented as a mesh, where each vertex is the centre of a circle, and the edges link the centres of the circles which are tangent to each other.
-The sizes and centre positions. If you treat the combinatorics as fixed, you can then concentrate on optimizing the radii and locations of the circles to get them as close to tangent as possible.
I have done some work on solving these 2 parts simultaneously (see video here), and shared some scripts for this here.
Alternatively we can deal with them separately. For the combinatorics you could use something regular, based on subdivision (for a sphere you might want to start with an icosahedron). Alternatively you could use the remeshing tool I recently shared here. This can cover any surface with a mesh of almost equal edge lengths.
For the second part there is a force in Kangaroo which can optimize any triangulated mesh so that there is a packing of spheres centred on its vertices (and if the mesh is smooth, this sphere packing also leads to a circle packing). The file cp_mesh1 in the circle packing directory of the new collection of Kangaroo example files I recently posted shows this.
As for limiting to a small number of specified radii, this is still tricky, and impossible without compromising some of the other conditions. If you allow some variable gaps between the circles, you can replace each one with the closest from your set of radii. If you do not choose your radii in advance, but generate a packing with continuously varying radii then cluster them, it can give a better fit.
Alternatively you can give up the requirement that the packing to be compact and have good tangency, but some gaps with more than 3 sides.
Circle packing is a beautiful and surprisingly deep topic. I'd also recommend taking a look at the work of Ken Stephenson, Bobenko Hoffmann and Springborn, and Mathias Höbinger's thesis, which goes into more detail about triangular meshes with tangent incircles.
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l, you can find examples of parametric design using LB/HB, specifically the HB component pollinator workflows.
In these examples, a GH component (data recorder) is used to locally store either input parameters or output values of different model configurations and transmit them to pollinator. I can imagine, depending on how your facade is made parametric in GH, that you could save those input parameters (e.g. angle of surfaces or height of extrusion) and output variables for each iteration (e.g. annual shading).
This a search process through the design space. I do think that if you would set up the model as such, then it would be ok that the components in the PV workflow resetted after each iteration as the results would be saved. There is even a really good visualization platform Mostapha has shared to go along pollinator.
You can find examples of these workflows in the forum, simply search pollinator. I have one that I shared somewhere as well, although it was doing rudimentary things it would help.
This design space approach is a bit different than the optimization approach utilizing components like galapagos. It gives you an idea of the space of possible different desings and allows you to compare alternatives. Plus, it usually allows me to avoid all these issues of losing results between components in the workflo.
I also find it very handy and much more efficient than simply allowing a component optimize everything for me. However, it can ncrease almost exponantially (or is it geometrically, I am always bad at this) to the range and number of your input parameters. So, if each square on the wall has more than a couple of input values for a a few input parameters, I would expect this to take a long time. Thankfully, the components in the workflow will let you know exactly how many iterations.
If this method is interesting to you and you follow it I would suggest a few things to hasten the process like utilizing only the squared above and on the sides of the PV panel, since the others won't really affect shading, selecting just 2 or 3 characteristic angles for extrusions, and perhaps approximating energy production through annual shading numbers (since I imagine they have an almost linear relationship).
I do hope that I have understood what you want to do and the above information helps. I'm sure Djordje will give much better feedback on the specifics of the PV workflow. I will try and keep this page saved so that I can send over the example once I'm back at work mid of next week.
Good luck!
Kind regards,
Theodore.
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to run at full screen. I've gone as far as using an iPad to use as the second monitor via AirDisplay (which actually works really well) but have never been satisfied with any setup that required you to look back and forth as if at a tennis match all day long.
Not long after first using Grasshopper 3+ years ago I've had the desire for a "Live Viewport" component that would allow a live image of the 3d geometry being generated directly in the canvas. Every once in a while I search the forums with the hope of finding a solution, but always come up empty handed. Someday this might exist although for now I have found what might be the next best thing to a native "Live Viewport" component and its enabled with a small app named Sticky Previews. This app uses the task bar preview feature within Windows 7's aero interface to create custom, floating preview windows from any open window currently running. I've only just discovered the app, but it seems to do the trick and has been stable and problem free so far. -- I will post an update if I find out that I might have spoken too soon. The install allows for a 30 day trial and is $15 bucks to purchase. I just found the app and don't know anything about this group that created the app. If you happen to know of them, Id be curious to find out more.
divided windows, cramped and slow;
unified window with floating rhino model preview;
link to the apps webpage;
http://www.ntwind.com/software/sticky-previews.html
Also works with other apps;
and the about me page screen shot;
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Added by Tyler Selby at 11:25pm on November 26, 2012
rch, september, june.
I did two kind of simulation. The first one - just one hour 10h and then 15:30. The second, 10:00 to 15:30h. I think that's something wrong with the results kWh/m² because the biggest values for radiation, are for winter. And the results simulation 10:00 to 15:30h the result are different too, the biggest values for winter (june), then september, march, and them december (summer)
The results are (kWh/m²)
10:00h 15:30h 10 to15:30h
21/03 0,69 1,15 2,61
21/06 1,14 1,13 3,71
23/09 0,96 0,90 2,79
21/12 1,31 1,22 2,45
I will be very gratiful with your answer I'm using this software to a important academic work, and in my Country Its not commom use this software, I don't know anyone that could help me with this. I'd like to encourage university start to use this kind of software.
Thank you
Camila
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rent actors to work together in real time on an architectural project.
DixieVR was born from the idea that virtual reality could become a fantastic tool for architecture and architects, not only for virtual tours but for the conception at its very core. Inspired by the efficiency of sandbox games, DixieVR will allow you to build a fully parametric 3D model from scratch in a very intuitive way and to simulate various factors like natural and artificial light, gravity, and more. DixieVR is also multi-user oriented : several people, architects or not, are able to work together in real time on the same 3D model and in the same shared immersive environment !
The project started in the Digital Knowledge department of Paris-Malaquais Architecture School.
The DixieVR Softwares can be found here : dixievr.github.io
// Interoperability
DixieVR deals with .dix files. For more information about this file format, please refer to the Interoperability documentation of DixieVR.
You can use this DixieIO plugin for Grasshopper/Rhinoceros for exchanging data between DixieVR (PC) & DixieViewer (Android).
You can import or export objects at any time inside a DixieVR scene. The Software also come with a library of premade objects that you might find useful. Adding your own premade objects to this library might be a good habit.
If you are hosting a scene, you also have the choice to open a .dix file directly from the main menu, this will load the last scene in which the geometry has been saved.
// Plugin
The DixieVR Plugin can be found in the Extra tab, come with 3 components and a example definition:
Dixie2Gh : Import DixieVR geometry to Grasshopper/Rhinoceros reading a .dix file (up to 1000 beams and/or 750 faces).
G2D_Polylines : Export Grasshopper/Rhinoceros Polylines to DixieVR writing a .dix file (up to 1000 line segments).
G2D_Mesh : Export Grasshopper/Rhinoceros Mesh to DixieVR writing a .dix file (up to 750 triangulated faces).
To install:
In Grasshopper, choose File > Special Folders > Components folder. Place the DixieIO_01.gha file there.
Right-click the file > Properties > make sure there is no "blocked" text.
Restart Rhinoceros or Unload Grasshopper.
// Contact - DixieVR
vr.dixie@gmail.com dixievr.github.io
- Oswald Pfeiffer oswaldpfeiffer.com
- Mathieu Venot mathieuvenot.com…
curve or locus] of a segment AB, in English. The set of all the points from which a segment, AB, is seen under a fixed given angle.
When you construct l'arc capable —by using compass— you obviously need to find the centre of this arc. This can be easily done in GH in many ways by using some trigonometry (e.g. see previous —great— solutions). Whole circles instead of arcs provide supplementary isoptics —β-isoptic and (180º-β)-isoptic—. Coherent normals let you work in any plane.
Or you could just construct β-isoptics of AB by using tangent at A (or B). I mean [Arc SED] component.
If you want the true β-isoptic —the set of all the points— you should use {+β, -β} degrees (2 sides; 2 solutions; 2 arcs), but slider in [-180, +180] degrees provides full range of signed solutions. Orthoptic is provided by ±90º. Notice that ±180º isoptic is just AB segment itself, and 0º isoptic should be the segment outside AB —(-∞, A] U [B, +∞)—. [Radians] component is avoidable.
More compact versions can be achieved by using [F3] component. You can choose among different expressions the one you like the most as long as performs counter clockwise rotation of vector AB, by 180-β degrees, around A; or equivalent. [Panel] is totally avoidable.
Solutions in XY plane —projection; z = 0—, no matter A or B, are easy too. Just be sure about the curve you want to find the intersection with —Curve; your wall— being contained in XY plane.
A few self-explanatory examples showing features.
1 & 5 1st ver. (Supplementary isoptics) (ArcCapableTrigNormals_def_Bel.png)
2 & 6 2nd ver. (SED) (ArcCapableSED_def_Bel.png)
3 & 7 3rd ver. (SED + F3) (ArcCapableSEDF3_def_Bel.png)
4 & 8 4th ver. (SED + F3, Projection) (ArcCapableSEDProjInt_def_Bel.png)
If you want to be compact, 7 could be your best choice. If you prefer orientation robustness, 5. Etcetera.
I hope these versions will help you to compact/visualize; let me know any feedback.
Calculate where 2 points [A & B] meet at a specific angle is just find the geometrical locus called arco capaz in Spanish, arc capable in French (l'isoptique d'un segment de droite) or isoptic [curve or locus]
of a segment AB, in English. The set of all the points from which a segment,
AB, is seen under a fixed given angle.…
option, after downloading check if .ghuser files are blocked (right click -> "Properties" and select "Unblock"). Then paste them in File->Special Folders->User Object Folder. You can download the example files from here. They act in similar way, Ladybug Photovoltaics components do: we pick a surface, and get an answer to a question: "How much thermal energy, for a certain number of persons can my roof, building facade... generate if I would populate them with Solar Water Heating collectors"? This information can then be used to cover domestic hot water, space heating or space cooling loads:
Components enable setting specific details of the system, or using simplified ones. They cover analysis of domestic hot water load, final performance of the SWH system, its embodied energy, energy value, consumption, emissions... And finding optimal system and storage size. By Dr. Chengchu Yan and Djordje Spasic, with invaluable support of Dr. Willian Beckman, Dr. Jason M. Keith, Jeff Maguire, Nicolas DiOrio, Niraj Palsule, Sargon George Ishaya and Craig Christensen. Hope you will enjoy using the components! References: 1) Calculation of delivered energy: Solar Engineering of Thermal Processes, John Wiley and Sons, J. Duffie, W. Beckman, 4th ed., 2013. Technical Manual for the SAM Solar Water Heating Model, NREL, N. DiOrio, C. Christensen, J. Burch, A. Dobos, 2014. A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015
2) Domestic hot water load: Modeling patterns of hot water use in households, Ernest Orlando Lawrence Berkeley National Laboratory; Lutz, Liu, McMahon, Dunham, Shown, McGrue; Nov 1996. ASHRAE 2003 Applications Handbook (SI), Chapter 49, Service water heating
3) Mains water temperature Residential alternative calculation method reference manual, California energy commission, June 2013. Development of an Energy Savings Benchmark for All Residential End-Uses, NREL, August 2004. Solar water heating project analysis chapter, Minister of Natural Resources Canada, 2004.
4) Pipe diameters and pump power: Planning & Installing Solar Thermal Systems, Earthscan, 2nd edition
5) Sun postion and POA irradiance, the same as for Ladybug Photovoltaics (Michalsky (1988), diffuse irradiance by Perez (1990), ground reflected irradiance by Liu, Jordan (1963))
6) Optimal system and storage tank size: A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015.…
t defined from the discussion of radiation exchange between urban surfaces and the sky in urban heat island research (See Oke's literature list below). It will be affected by the proportion of sky visible from a given calculation point on a surface (vertical or horizontal) as a result of the obstruction of urban geometry, but it is not entirely associated with the solid angle subtended by the visible sky patch/patches.
So, I think using "geometry way" to approximate Sky View Factor is not correct. Sky View Factor calculation shall be based on the first principle defining the concept: radiation exchange between urban surface and sky hemisphere:
(image extracted from Johnson, G. T., & Watson, 1984)
Therefore, I always refer to the following "theoretical" Sky View Factors calculated at the centre of an infinitely long street canyon with different Height-to-width ratios in Oke's original paper (1981) as the ultimate benchmark to validate different methods to calculate SVF:
So, I agree with Compagnon (2004) on the method he used to calculate SVF: a simple radiation (or illuminance) simulation using a uniform sky.
The following images are the results of the workflow I built in the procedural modeling software Houdini (using its python library) according to this principle by calling Radiance to do the simulation and calculation, and the SVF values calculated for different canyon H/W ratios (shown at the bottom of each image) are very close to the values shown in Oke's paper.
H/W=0.25, SVF=0.895
H/W=1, SVF=0.447
H/W=2, SVF=0.246
It seems that the Sky View Factor calculated from the viewAnalysis component in Ladybug is not aligned with Oke's result for a given H/W ration: (GH file attached)
According to the definition shown in this component, I assume the value calculated is the percentage of visible sky which is a geometric calculation (shooting evenly distributed rays from sensor point to the sky and calculate the ratio of rays not blocked by urban geometry?), i.e solid angle subtended by visible sky patches, and it is not aligned with the original radiation exchange definition of Sky View Factor.
I'd suggest to call this geometrically calculated ratio of visible sky "Sky Exposure Factor" which is "true" to its definition and way of calculation (see the paper on Sky Exposure Factor below) so as to avoid confusion with "The Sky View Factor based on radiation exchange" as discussed in urban climate literature.
Appreciate your comments and advice!
References:
SVF: definition based on first principle
Oke, T. R. (1981). Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of Climatology, 1(3), 237-254.
Oke, T. R. (1987). Boundary layer climates (2nd ed.). London ; New York: Methuen.
Johnson, G. T., & Watson, I. D. (1984). The Determination of View-Factors in Urban Canyons. Journal of American Meteorological Society, 23, 329-335.
Watson, I. D., & Johnson, G. T. (1987). Graphical estimation of sky view-factors in urban environments. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 7(2), 193-197. doi: 10.1002/joc.3370070210
Papers on SVF calculation:
Brown, M. J., Grimmond, S., & Ratti, C. (2001). Comparison of Methodologies for Computing Sky View Factor in Urban Environments. Los Alamos, New Mexico, USA: Los Alamos National Laboratory.
SVF calculation based on first principle:
Compagnon, R. (2004). Solar and daylight availability in the urban fabric. Energy and Buildings, 36(4), 321-328.
paper on Sky Exposure Factor:
Zhang, J., Heng, C. K., Malone-Lee, L. C., Hii, D. J. C., Janssen, P., Leung, K. S., & Tan, B. K. (2012). Evaluating environmental implications of density: A comparative case study on the relationship between density, urban block typology and sky exposure. Automation in Construction, 22, 90-101. doi: 10.1016/j.autcon.2011.06.011
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