ake a network of lines (i.e. a graph) and make a Plankton Mesh, from which you can use Cytoskeleton to make a solid mesh (and then smooth it with Weaverbird).
Works with ngons (polygons with 3 or more sides). Other examples I found only worked with tris and quads.
Works on open or closed surfaces
While these examples start with a surface, you could start with a network of lines and make a patch surface
This is meant for 2D networks/surfaces. I haven't attempted filling a 3D volume. My guess is this wouldn't work as it would require a non-manifold mesh that Plankton wouldn't handle.
Note similar results could be achieved with the following:
TSplines
MeshDual (dual of a tri mesh, not as much freedom/control)
Working backwards, here is the GhPython script from Will Pearson that builds a Plankton Mesh from vertices and faces. The vertices are a list of 3D coordinates, the faces are a tree a lists, with each list containing the indices of vertices that form a closed loop. From Will, "Plankton only handles manifold meshes, i.e. meshes which have a front and a back. This orientation is determined by the "right-hand rule" i.e. if the vertices of a face are ordered counter-clockwise then the face normal will be out of the page/screen."
# V: list of Point3d # F: tree of int
import Grasshopper appdata = Grasshopper.Folders.DefaultAssemblyFolder
import clr clr.AddReferenceToFileAndPath(appdata + "Plankton.dll")
import Plankton
pmesh = Plankton.PlanktonMesh()
for pt in V: pmesh.Vertices.Add(pt.X, pt.Y, pt.Z)
for face in F.Branches: face = list(face)[:-1] pmesh.Faces.AddFace(face)
These vertices and faces are precisely the output from Starling. Starling takes in a list of Polylines which form the (properly oriented) face loops.
The polyline face loops can be generated...
Directly from Panels on a surface using LunchBox
Using any network of lines/curves on a surface (curves will need to be converted to polylines before Starling)
The latter was achieved using the Surface Split command, then converting the face edges (converted to curves) into polyline loops to represent faces.
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requires four weather data inputs: air temperature (_dryBulbTemperature), relative humidity (relativeHumidity_), wind speed at 1.1 meters from the ground (windSpeed_) and mean radiant temperature (meanRadiantTemperature_).You can add values to the first three inputs from the Ladybug "Import Epw" component. For the last (meanRadiantTemperature_), you can add it from Ladybug's "Outdoor Solar Adjusted Temperature Calculator" component, or let "Thermal Comfort Index" component to calculate it. Both use different methods to calculate the final values.
I attached an example file below with second option.For more precise calculations you can use Honeybee and Chris' microclimate maps.An icing on the cake for the end: one of Ladybug developers yesterday released a set of Ladybug components for modelling in ENVI-met application. ENVI-met is cutting-edge microclimate software, which can be downloaded for free. It opens a number of advanced new analysis in outdoor domain, which couldn't have been done with the current Ladybug+Honeybee tools. So you can perform the simulation in ENVI-met 4 free software, and then add mean radiant temperature values from ENVI-met simulation to "Thermal Comfort Indices" component. Here is an example file.If you would like to go with the last approach, then the best would be to post a question about it in this topic.
1) You can make a polygonized tree.I haven't subtracted the trunk from the crown, but I guess it makes sense that it can be done.2) In most solar related simulations, a default albedo value of 0.2 is used. This corresponds to average albedo value taken from materials surrounding the urban or countryside location (concrete, grass, gravel, sand, asphalt...). However the presence of snow can significantly magnify the average albedo value several times. "Sunpath shading" components albedo_ input has an ability to calculate albedo due to presence of snow, if nothing is added to it (to albedo_ input). As you are performing the analysis of PET in a horizontal plane, it will not affect your calculations.3) Most thermal comfort indices will require performing analysis at 1.1 meters above the ground. This is considered to be height of standing person's gravity center.The same goes for PET index. So you are correct: you should place the analysis grid at 1.1 meters above the ground before adding it to the "Sunpath Shading" component.It is worth mentioning that "Thermal Comfort Indices" component used in this topic's PET_on_Grid2.gh and PET_on_Grid3.gh files is from last year, and much slower than the newest one (VER 0.0.64 MAR 18 2017) used in the example attached below. Just a remainder if you have been using older version of this component.Let me know if I misunderstood some of your questions, or if I missed to answer some of them.
EDIT: sorry for posting a double reply. When I posted it the first time, I only got links visible, with no text. Something has been wrong with grasshopper ning forum for the last couple of months.…
). It deals with the potential possibility to port GH into AEC fields (real-life AEC fields, nothing to do with academic thinking). The bad news are that the smart AEC sector is occupied solely by Bentley/GenComp – expect soon Revit/Dynamo as well (not to mention CATIA). The good news are that there’s millions of designers/engineers/industrial designers out there who could be interested for a 3rd alternative.
Intro: Well, in the old days (when men had mustache and muttonchops) AEC design performed in a nice top-to-bottom sequence (kinda like a vector) : the Big Man (aka The Brain) did some sketches (with crayons) and the rest (known as the “others”) struggled to make The Idea a reality. Today things are different, mind. Or they should be different. Or may be different. Or whatever. The big easy:For a zillion o reasons (AEC matures, PLM, cost, outsourcing, sustainable engineering…add several more) this vector like process of the past is like a Brown motion these days: Right down the moment that you (or your team) “sketch” The Big Idea … another team design simultaneously (i.e. in parallel) the components (parts) that compose the whole. This is the so called bottom-to-top design mentality. So the whole and the parts meet in some "middle point" instead the later being dictated by the former. In quite a few occasions parts dictate the whole (cost, cost and cost being the main reasons). The more a design is contemporary the more this bottom-to-top thing plays a critical role. Ignore it and have a very big time (sooner or later).The bad news:If you accept the above…well GH – at present phase - is not ready for contemporary AEC work. At.All.3 Main reasons for that:1.You can’t use parametric parts (i.e. nested blocks to speak Rhino language) into a given definition (in this case attached : truss nodes, connection flanges, mount plates, cable tensioners, planar glazing components, roof skin components…etc etc). This is obviously a Rhino domain.2.You can’t bake a given solution in such a way that the Rhino file is structured (i.e. assemblies of nested blocks). Or you can do it theoretically writing some VB/C code – but the core of the matter is that corresponding components are MIA. That means that you can’t export anything useful actually into established AEC oriented apps and/or established MCAD apps (for doing/calculating the parts for real-life production).3.The GH process can’t being interrupted. Imagine defining, say, a building “envelope” in GH and then …er…use Evolute tools in order to optimize things (say quad planarization and the likes). Then …continue in GH for more detailed work. Then design the parts as in 1 above. Then back to Evolute. Then back to GH.So…if anyone is interested I would be glad to start the mother of all debates and/or some kind of crusade (GH for President, that is).PS: This definition is a WIP thing – more refined stuff to follow (in particular a complex canopy tubes pre-stress system).
PS: Tree8 components are used sporadically.
PS: Use Saved Views
May the Dark Force be with us.Best, Peter …
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
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. From the Thermal Comfort Indices component, Comfort Index 11 (TCI-11):MRT = f(Ta, Tground, Rprim, e)
with:- Ta = DryBulbTemperature coming from ImportEPW component- Tground = f(Ta, N) where N comes from totalSkyCover input. Tground influences the long-wave radiation emitted by the ground in the MRT calculation.- Rprim defined as solar radiation absorbed by nude man = f(Kglob, hS1, ac)- ac is the clothingAlbedo in % (bodyCharacteristics input)- I can't find any definition in the code of Kglob and hS1. Could you tell me please what are those values referencered to? --> probably the globalHorizontalRadiation but how?- e = vapour pressure calculated from Ta and Relative Humidity input
Do you agree that in this case the MRT does not depend on these inputs: location, meanRadiantTemperature, dewPointTemperature and wind speed?It does not depend neither on the other bodyCharacteristics like bodyPosture, age, sex, met, activityDuration...?
MRT calculated by the TCI-11 method is the mean radiant temperature of a vector pointing vertically with a sky view factor of 100%?For ParisOrly epw,
2. From the SolarAdjustedTemperature component (that seems to be more used for the UTCI calculation examples on Hydra compared to TCI-11).
In contrast to the TCI-11, this component distinguishes diffuse and direct radiation and contextualizes the calculation thanks to _ContextShading input, right? It can also be applied to a mannequin thanks to the CumSkyMatrix and thus evaluate the dishomogeneity of radiation exposure.This component seems not to consider the influence of vapour pressure on the result --> is it then more precise to put the MRT output (from the TCI) as an input of meanRadTemperature for SolarAdjustedTemperature?The default groundReflectivity is set to 0.25 --> is GroundReflectivity taken into account in the Tground or MRT calculation in the TCI component? If yes, what is the hypothesised groundReflectivity?The default clothing albedo of 37% (TCI-11 bodyCharacteristics) corresponds to Clothing Absorptivity of 63%?
If the CumSkyMatrix input is not supplied, I get 9 results for the mannequin --> where are those points/results coming from?
If the CumSkyMatrix input is supplied,I suppose the calculation of the 482 results correspond to a calculation method similar to the radiation analysis component that is averaged over the analysis period. Right?But I don't understand why the mannequin is composed of 481 faces and meshFaceResult gives 482 results.
Finally, what is the link between the MESH results, the solarAdjustedMRT and the Effective Radiant field ? Is there a paper to have a detailed explanation of the method?
3. Here are some results for the ParisOrly energyplus weather data. You can find here attached the grasshopper definition.There is no shading in this simulation and the result coming from the ThermalComfort indices for MRT is very different compared to the solar adjusted MRT.Why such a big difference and which of the result should be plugged into the UTCI calculation component?
Results for ParisOrly.epwM,D,H:1,1,12
Ta : 6.5°Crh: 100%globalHorizontalRadiation: 54 Wh/m2totalSkyCover: 10MRT (TCI-11): 1.2°C
_CumSkyMtxOrDirNormRad = directNormalRadiation : 0 Wh/m2diffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.64°CMRTDelta: 4.14°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.47°CMRTDelta: 3.97°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = MRT (TCI-11)solarAdjustedMRT: 5.17°CMRTDelta: 3.97°C
Thanks a lot for your helpRegards,
Aymeric
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hope this number will grow in future. Currently available features are:
1) Creation of 2d or 3d context for any kind of building related analysis: automatically generate the 2d/3d surrounding buildings for the location where you would like to perform visibility, solar radiation, cfd or any other type of analysis. You need some other plugin for the last three, like Ladybug. It only creates the context=surroundings! The "automatic generation" process also includes creation of the local topography (terrain) along with buildings.
2) Identification of certain 2d or 3d elements in the created context. For example: selection of all hotels, parks, hospitals, restaurants, residential buildings etc.
3) Performing direct terrain analysis (hillshading, slope, ruggedness, roughness, water flow...)
4) Creation of terrain shading masks and horizon files for further solar and photovoltaics analysis.
Gismo will be very grateful if he could get any suggestions, improvements, bug reports and testing in the following period. In case you are willing to provide any of these, the requirements, installation steps and .gh example files can be found here, here and here.
Thank you in advance !!…
Added by djordje to Gismo at 9:10am on January 29, 2017
Karamba.
I am using your plug-in for normal forces evaluation in the transvere wires and spreaders of a sailboat. Mast is solved in another way, so I am not taking forces from Karamba in that case.
Basing on the forces value an adequate wire size (diameter) is choosen. Then masses of wires are being calculated. Loads (forces) on longitudinal wires are calculated without Karamba. The problem is when choosing transverse wires’ mass minimization as a criteria, the Octopus doesn’t get any results - is changing the sliders (genes) too fast for Karamba to calculate the forces (so Octopus gets only nulls):
When minimization of a e.g. longitudinal wires’ mass (calculated without Karamba) is taken as a criteria Octopus works fine.
Which suggests that the problem is in interaction of two plug-ins.
Any ideas how to avoid that problem?
Thanks,
M.
Below some screenshots of definition part with Karamba:
1675×807 200 K
image.png1680×789 398 KB
Despite the ‘orange warning’ the values are correct (double checked with other software).However I don't know why does it say that there is a part that can move freely without deformation,as the model looks like this:
image.png1239×343 55.5 KB
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h, and using the BScale and BDistance are creating havoc somehow too. I've simplified first, and used the Kangaroo Frames component along with setting internal iterations, to make MeshMachine act like a normal component, along with releasing the FixC and FixV. The FixV didn't make any sense anyway. I've also set Pull to 0 to speed it up during testing, since much less calculation is involved to just let the meshes collapse, prevented from disappearing altogether by using a mere 15 iterations.
Also, your breps are open so that allows much more chaos and then collapse, though they did manage to close themselves too at times. Here is closed breps with a full 45 iterations:
So now that it's working, lets re-Fix the curves, and the problem arises that there is an extra seam line that is getting fixed too, running along the cylinder, stopping the mesh from pulling tight under tension wherever a vertex happens to be near that line:
So lets grab only the naked edge curves instead:
And what happens if we lose the end caps, now that we don't have an extra line skewing the result?:
There is no real curvature differences since it's not a curvy brep so the Adapt at full 1 setting has little to do. Now what does the BScale and BDist do? Nothing! Why? Your scale is out of whack, 99 mm high cylinders but only a falloff maximum of about 5, so let's make the falloff be 25 instead, but I must restore the end caps or the meshes collapse away for some reason and freezes Rhino for a minute or so the first time I try it:
It's a start.
If I intersect the cylinders, nothing changes, since they are being treated as separate runs. MeshMachine outputs a sequence of two outputs though, due to Frames being set to a bare minimum of 2 needed to get it to work, so I filter out the original run, which is just the unmodified initial mesh it creates.
The lesson so far is that closed meshes are much less prone to collapse and glitches leading to screw ups.
A Boolean union of the cylinders is when it gets funner, here show with and without the fixed curves that seem to define boundaries too where really there are just polysurface edges:
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owing a tutorial is easy and adapting the idea of it again - it's not a fuss - i guess my skills are at 1 - since I can not yet stand alone! However I am very determined to nail this program to the ground and be at a 9 by Easter - of course that means a lot of work and hours testing - but I am young and ambitions!
I am a revit user and I just switched over (from the dark rigid side) to rhino because of a simple math problem which has to do with variations and combinations.
I am investigating the form factor for my thesis.
Form factor= building envelope (the area of the facade+the area of the roof+the area of the footprint)/the total area of the floors.
I have started by defining a specific set of parameters such as height, number of floors, maximum total floor area so I can compare the results.
Therefore the floating number will be the facade area - which in the end, considering the height is a constant - ends up being just the length of a certain shape - circle, square, triangle ...
I have done the calculation through excel after extracting from revit but only on simple shapes as follow(the following examples are my own analyzing work):
My problem is: I need a way to get all possible shapes that meet the criteria i put in - which at the moment will be defined by square meters of a floor- that is why galapagos comes in - I need it to make all possible combinations that can be computed that meet the criteria - so then the user(myself or who ever else want to use it) can make an informed choice. I am not looking for a square - circle, sphere or anything I can manually create by just using basic geometry, I am looking for all the possible combination that equal the same area.
(plan view)
After i can solve it for one level - i will constrain that all the levels add up have specific total area - so if a level get's bigger in size another one gets smaller. Again run it through Galapagos and get all possible outcomes (like the sections below)
I am aiming to get an outcome from which you have options to pick out of -> a design process not a specific shape.
You are thinking too complex - not that it's a bad thing - but I am looking for something more simplistic than that. I need a shape - windows and panels are for later use in my process and at this early stage completely irrelevant - and that will be another percentage math problem rather than aesthetics. I just need shapes to morph based on input parameters.
I hope this was an interesting read for you and I really appreciate your patience with me.…
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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