Crystallon is an open source project for creating lattice structures using Rhino and Grasshopper3D. The goal is to generate lattice structures within Rhino’s design environment without exporting t
sinergetici associati alla compresenza simultanea di differenti strumenti di analisi e digital design all'interno di un processo di progettazione in svolgimento. I partecipanti utilizzeranno Grasshopper (modellatore parametrico per Rhino): l'uso di questo editor grafico di algoritmi si integra alla perfezione con gli strumenti di modellazione di Rhinoceros 3D espandendo le possibilità di corstruire modelli parametrici altamente complessi. Per generare una complessità simile saranno utilizzati collegamenti live ai diversi programmi elencati di seguito: . Autodesk Ecotect Analysis via GECO . FEA software GSA via SSI Durante questi intensi 3 giorni, i partecipanti impareranno il workflow dei plug-ins con l'aiuto di esempi esplorando una panoramica dei differenti software, le possibilità di testare le performances di un progetto o l'uso di strumenti addizionali non legati ad un singolo sistema (es. accentuazione, formazione, reazione parametrica) [english text] The focus of the workshop is to integrate and correlate the synergistic effect associated with simultaneous presence of different digital design- and analysis tools in an ongoing design process. The main attention is set on easy to handle interface , which should be used at a early stage of conceptual design to respond to external and internal influences in a intelligent and sustainable way. Participants will use the software Grasshopper as a parametric modeling plug-in for Rhino. The usage of this graphical algorithm editor tightly integrated with Rhino's 3-D modeling tools open up the possibility to construct highly parametrical complex models. To generate this complexity we will use live linkages to several programs listed below: . Autodesk Ecotect Analysis via GECO . FEA software GSA via SSI In this 3 intense days, the participants should learn the workflow of the plug-ins with the help of examples and get an overview of the different software's, there possibilities for evaluating the performance of a design or the usage of additional tools to be not chained to a single system . (e.g. parametrical accentuation, parametrical formation, parametrical reaction) [.] Dettagli : Istruttori: Thomas Grabner & Ursula Frick from [uto]. lingua del corso: inglese (saranno disponibili tutor di supporto ma è richiesta una conoscenza di base della lingua unglese).
Quote d'iscrizione (min 12 max 20 posti): educational* : € 280.00 + iva professional: € 450.00 + iva * studenti, docenti, ricercatori, dottorandi e laureati fino a un anno dalla data di laurea OFFERTA EARLY BIRD SPECIAL: le prime 5 domande di iscrizione pervenute entro il 31 Dicembre 2011 avranno diritto ad una quota di iscrizione scontata del 20% Quote d'iscrizione E.B. SPECIAL: E.B. SPECIAL educational* : € 224.00+ iva E.B. SPECIAL professional: € 360.00+ iva. ulteriori info, dettagli e iscrizioni: http://www.co-de-it.com/wordpress/nexus-advanced-grasshopper-workshop-with-uto.html…
ocessed once Grasshopper is done with whatever it's doing now.
3) Grasshopper tells the Slider object that the mouse moved and the slider works out the new value as implied by the new cursor position.
4) The slider then expires itself and its dependencies ([VB Step 1] in this case, but there can be any number of dependent objects).
5) When [VB Step 1] is expired by the slider, it will in turn expire its dependencies (VB Step 2), and so on, recursively until all indirect dependencies of the slider have been expired.
6) When the expiration shockwave has subsided, runtime control is returned to the slider object, which tells the parent document that stuff has changed and that a new solution is much sought after.
7) The Document class then iterates over all its objects (they are stored in View order, not from left to right), solving each one in turn. (Assuming the object needs solving, but since in your example ALL objects will be expired by a slider change, I shall assume that here).
8) It's hard to tell which object will get triggered first. You'd have to superimpose them in order to see which one is visually the bottom-most object, but let's assume for purposes of completeness that it's the [VB Step 1] object which is solved first.
9) [VB Step 1] is triggered by the document, which causes it to collect all the input data.
10) The input parameter [x] is asked to collect all its data, which in turn will trigger the Slider to solve itself (it got expired in step 4 remember?). This is not a tricky operation, it merely copies the slider value into the slider data structure and shouts "DONE!".
11) [x] then collects the number, stores it into its own data structure and returns priority to the [VB Step 1] object.
12) [VB Step 1] now has sufficient data to get started, so it will trigger the script inside of it. When the script completes, the component is all ready and it will tell the parent document it can move on to the next object (the iteration loop from step 7).
13) Let us assume that the slider object is next on the list, but since it has already been solved (it was solved because [VB Step 1] needed the value) it can be skipped right away, which leaves us with the last object in the document which is still unsolved.
14) [VB Step 2] will be triggered by the document in very much the same way as [VB Step 1] was triggered in step 9. It will also start by collecting all input data.
15) Since all the input data for [VB Step 2] is either defined locally or provided by an object which has already been solved, this process is now swift and simple.
16) Upon collecting all data and running the user script, the component will surrender priority and the document becomes active again.
17) The document triggers a redraw of the Grasshopper Canvas and the Rhino viewports and then surrenders priority again and so on and so forth all the way up the hierarchy until Grasshopper becomes idle again.
[end boring]
Pretty involved for a small 3-component setup, but there you have it.
To answer somewhat more directly your questions:
- The order in which objects are solved is the same as the order in which they are drawn. This is only the case at present, this behaviour may change in the future.
- Adding a delay will not solve anything, since the execution of all components is serial, not parallel. Adding a delay simply means putting everything on hold for N milliseconds.
- [VB Step 1] MUST be solved prior to [VB Step 2] because otherwise there'd be no data to travel from [GO] to [Activate]. The only tricky part here is that sometimes [VB Step 1] will be solved as part of the process of [VB Step 2], while at other times it may be solved purely on its own merits. This should not make a difference to you as it does not affect the order in which your scripts are called.
--
The Man from Scene 24…
Added by David Rutten at 4:43pm on December 10, 2009
number of divisions on that curve as in the defintion (i.e. by 4). The offset in the def is slightly different and should cull two or three more curves as in the lists that show my aim below.
Basically I want to look into each branch of the groups of points from each closed curve . Marking in a list whether it contains a one or a zero (0= outside 1 = coincidents).
{0;0}0. 21. 22. 23. 2 {0;1} 0. 01. 22. 03. 2 {0;2}0. 01. 02. 03. 0 {0;3}0. 21. 22. 23. 2 {0;4}0. 21. 22. 23. 2 {0;5}0. 21. 22. 23. 2 {0;6}0. 01. 22. 23. 1 {0;7}0. 21. 22. 03. 0 {0;8}0. 21. 22. 23. 2 {0;9}0. 21. 22. 23. 2 {0;10}0. 21. 22. 23. 2 {0;11}0. 21. 22. 23. 2 {0;12}0. 21. 22. 23. 2 {0;13}0. 01. 22. 23. 0 {0;14}0. 21. 22. 23. 2
I want to create a list from these points. That marks each curve that pokes out, in a cull pattern as such:
20022210222202
Using a 1 where there are co-incidents in the curve points and the boundary. A 2 for true (outside points) and a 0 for containment. So I might be able to use the 1 in future developments - however if a true false list is easiest I can live with that.
So could I use F(x) function? - to look for 0 or 1's in each bunch of points and thus list as such for a cull pattern? or will Path mapper help me here? Or can I rely on simply grafting and splitting??
I am usure of the neatest solution and would love to learn. Hope you can direct me.rgrds
J.…
. 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
…
rtical Sky Component (VSC), and now Sky Exposure Factor (SEF). For everyone else following this post, this discussion has been ongoing in these other threads:
http://www.grasshopper3d.com/forum/topics/sky-view-factor-vs-vertical-sky-component?groupUrl=ladybug&xg_source=msg_com_gr_forum&groupId=2985220%3AGroup%3A658987&id=2985220%3ATopic%3A1377260&page=1#comments
https://github.com/mostaphaRoudsari/ladybug/issues/230
Grasshope, you have gone right to Oke, the grandfather of urban climatology, whose papers I have several times and yet I somehow I always missed the finer details of the sky view calculation. From his definition, I had always thought of Sky View Factor as a purely solid angle or "view factor" calculation in the sense of Mean Radiant Temperature. However, the numbers and formulas that you give here clearly show that Oke meant that this metric for quantifying and understanding urban heat island must refer back to the urban surfaces and their orientation in relation to the sky. It cannot simply be the view from points in space.
To clarify the distinction in simple geometric terms: The key difference is that Sky Exposure refers to the sky seen by a point in space while Sky View refers to that seen by a surface. Both of them involve the calculation of either projected rays or solid angle calculations to the sky (since they both are “view” calculations). However, while Sky Exposure treats each patch of the sky with relatively equal weight, Sky View weights these patches by their area after being projected into the plane of the surface being evaluated. In other words, the sky view calculation for a horizontal surface would give more importance to the sky patches that are directly overhead than those near the horizon because these overhead patch are “in front” of the surface (as opposed to on the side).
To express this difference in the trigonometric terms you cite here:
Wall View = 0.5(sin2 θ + cos θ – 1) / (cos θ)
Wall Exposure = θ/π
I both cases:
θ = tan-1(H / 0.5W) - ** This is the solid angle or ray-tracing calculation
SkyViewOrExposure = (1 - 2 (WallViewOrExposure))
To put this in more simpler terms for the View Analysis component, all that I actually have to do to convert sky exposure to sky view is multiply each of the traced view rays by 2cos(ϕ), where ϕ is the angle between the surface normal and the given view ray being traced.
I have done this by adding this line of code () and I have verified that I get the values from Oke’s paper that you cite above, Grasshope. Accordingly, the View Analysis component now has the option to compute either Sky Exposure or Sky View. You can see this happening in this new example file:
http://hydrashare.github.io/hydra/viewer?owner=chriswmackey&fork=hydra_2&id=Sky_Exposure,_Sky_View,_and_Sky_Component&slide=0&scale=1&offset=0,0
To (once and for all!) clearly define the difference between the three metrics at the top of my reply and to explain how to calculate each with Ladybug Honeybee:
Sky Exposure Factor - The percentage of the overlying hemispherical sky that is directly visible from a given POINT or set of POINTS. This is equivalent to a geometric solid angle calculation or ray-tracing calculation from points. It is useful for evaluating one's general visual connection to the sky at a given point and should be applied to cases where direct views to the sky are the parameter in question.
Sky exposure is calculated with the Ladybug_View Analysis component like so:
Sky View Factor – The percentage of the overlying hemispherical sky that is directly visible from a given SURFACE or set of SURFACES. While Sky Exposure treats each patch of the sky with relatively equal weight, Sky View weights these patches by their area projected into the plane of the surface being evaluated. In other words, Sky View for a horizontal surface would give more importance to the sky patches that are overhead and less to those near the horizon. Sky View is an important factor in for modelling urban heat island since the inability of warm urban surfaces to radiate heat to a cool night sky is one of the largest contributors of the heat island effect.
Sky View is calculates with either the Ladybug_View Analysis component like so:
Or with the Honeybee_Vertical Sky Component Recipe like so:
Sky Component - The portion of the daylight factor (at a surface indoors) contributed by luminance from the sky, excluding direct sunlight. This is essentially the same as Sky View Factor but it often incorporates a sky condition that is not uniform, such as a cloudy sky or sky that is more indicative of diffuse sky light. Another way of conceiving of this metric is a Daylight Factor calculation without any light bounces. It is useful for understanding the direct daylight contribution of diffuse skylight and, although many consider it an older (and perhaps outdated) daylight metric, it is still required by some codes and standards.
Sky Component can be calculated with the Honeybee_Vertical Sky Component Recipe like so:
In addition to the added capability in the view analysis component, I have revised the component description to include the definitions above. I have also corrected the Hydra example file in which I cite sky view as an urban heat island metric to use the new formula:
http://hydrashare.github.io/hydra/viewer?owner=chriswmackey&fork=hydra_2&id=Sky_View_in_an_Urban_Canyon&slide=1&scale=1&offset=0,0
Finally, all of this discussion has made me realize that the Vertical Sky Component recipe for Honeybee might not always be evaluating VERTICAL sky. The sky component might be vertical, horizontal, or in any direction that the input test surface is placed and pts vectors are oriented. Accordingly, Mostapha, I think that we should change the name of the component to simply be “Sky Component” instead of “Vertical Sky Component”. Please let me know if you agree.
Thanks again, Grasshope, for all of the great work! All of this never would have made sense without your research.
-Chris…
A repository of generic or complex examples.
Example 01: Attractor Values
ND_001_AttractorValues.gh
Example 02: Curve Values
ND_002_CurveValues.gh
Example 03: Point Attractor
ND_003_PointAttract
stributes structural supports for a uniformly loaded domain using e.g. the internal energy of the loaded domain as fitness. Here the uniformly loaded domain is represented by the trimmed surface. My genomes are the support positions (green crosses), which are restricted to a set of predefined grid points. I’m currently using an (i,j)-coordinate indexing for these grid points (illustrated in the viewport just below) as opposed to a sequential , “one-dimensional” numbering (illustrated in the viewport further down).
(i,j)-indexing systemAltenative, sequential indexing system
The support positions are computed by two gene pools; one governing the i-index, Gene List {i}, and one governing the j-index, Gene List {j}, of each support. The value of slider 0 in Gene List {i} is paired with the value of slider 0 in Gene List {j} etc. and the amount of sliders corresponds to the amount of supports. The screen shot below depicts the slider constellation corresponding to the support distribution depicted above. Unfortunately the j-index represented in the sliders needs remapping as the number of j-indices vary for each i-index (horizontal row of grid points). With the current setup I have 12^6 x 9^6 = 1,6 x 10^12 different genomes. If I were to use the sequential, “one-dimensional” numbering, I would only use one gene pool with sliders ranging from 0 to 76 meaning that remapping could be avoided and thereby having only 76^6 = 1,9 x 10^11 different genomes.
So, my current genome setup causes a bunch of issues related to the Evolutionary Solver: Remapping Changing one of the j-index sliders, will not necessarily change the related support position but it will still facilitate another genome to be calculated by the solver. (This problem could be eliminated by using the sequential, “one-dimensional” numbering)
Switching slider values around If the values of e.g. slider 0 were to be switched around with the values of slider 5, this again would yield a new genome but an identical solution. (This problem cannot be eliminated by using the sequential, “one-dimensional” numbering)
Coincident support positions Two or more supports may be located in the same position. (This problem cannot be eliminated by using the sequential, “one-dimensional” numbering)
I find it impossible to imagine the fictive “fitness landscape” of this problem and not only because of the multidimensional genome characteristic but just as much because of these listed, intertwined peculiarities. I’ve tried running the Simulated Annealing Solver as well, but my experience is that the Evolutionary Solver yields better results. To my awareness, the solver uses some kind of topographical proximity searcher. This is why, I think that the solving process itself benefits more from analysing the (i,j)-index system, in which neighbouring grid points hold more uniform topographical information than the sequential, “one-dimensional” numbering, which might have big ID-numbering gaps between neighbours. Have I understood this correctly?
Cheers…
onents (radiation, sunlight-hours and view analysis) which let you study the effect of the orientation of your building and the analysis result. When you come to a question similar to "what is the orientation that the building receives the most/least amount of radiation?" is probably the right time to use this component.
HOW?
I'll try to explain the steps using a simple example. Here is my design geometries. The building in the center is the building to be designed and the rest of the buildings are context. I want to see the effect of orientation on the amount of the radiation on the test building surfaces from the start of Oct. to the end of Feb. for Chicago.
First I need to set up the normal radiation analysis and run it for the building as it is right now. [I'm not going to explain how you can set up this since you can find it in the sample file (Download the sample file from here)]
Now I need to set up the parameters for orientation study using orientationStudyPar component. You can find it under the Extra tab:
At minimum I need to input the divisionAngle, and the totalAngle and set runTheStudy to True. In this case I put 45 for divisionAngle and 180 for the totalAngle which means I want the study to be run for angles 0, 45, 90, 135 and 180.
[Note1: The divisionAngle should be divisible by totalAngle.]
[Note 2: If you don't provide any point for the basePoint, the component will use the center of the geometry as the center of the rotation.]
[Note 3: You can also rotate the context with the geometry! Normally you don't have the chance to change the context to make your design work but if you got lucky the rotateContext input is for you! Set it to True. The default is set to False.]
You're all set for the orientation study, just connect the orientationStudyPar output to OrientationStudyP input in the component and wait for the result!
The component will run the study for all the orientations and preview the latest geometry. To see the result just grab a quick graph and connect it to totalRadiation. As you can see in the graph 135 is the orientation that I receive the maximum radiation. Dang!
If you want to see all the result geometries set bakeIt to True, and the result will be baked under LadyBug> RadaitionStudy>[projectname]> . The layer name starts with a number which is the totalRadiation.
Mostapha…
her people) a tremendous amount of time creating them by hand. Dog Treat was far from perfect, however it was good enough to use almost daily.
Three years is a long time. Since 2016 my Gh knowledge has expanded and I’ve seen how dodgy some of the scripting is. With this in mind I started work on a new build. Many things have been tweaked and some things have been rebuilt from the ground up.
Everything has been designed to be leaner and be a general solution to the problem of creating dog bone corners on geometry for quick, efficient and safe CNC fabrication.
Some of these things are:
Adding prompts about user geometry to make them aware about open curves, varying curve heights and if their geometry had been altered (mostly removing unnecessary points on curves).
Smooth Transfers. If you’re in a rush and need to speed through cutting, smooth transfers mean that a lead in geometry is now created alongside the actual dog bone arc. This means the router bit doesn’t have to come to a minute stop at every corner. This is turned on by default.
Acute Angle Condition If the angle between the two curves adjacent to a dog bone point is acute, previously the dog bone corner was useless. This was because the distance between the end points of the dog bone arc were less than the diameter of the router bit. There are many ways this condition could be addressed. I chose to circumscribe a larger arc based on the original angle between the adjacent curves. While it removes more material from the corner, it minimises tool wear and any potential for material to burn.
Single Curve A single curve can now be input into Dog Treat. It will be output with both internal and external treatments.
I’ll continue to update Dog Treat as the need arises, it’s become somewhat of a hobby now. Maybe one day it will become part of a Plug-in… once I learn to code it though!
Happy Treating!
Hi Everyone,
Here's a tool I've been working on for the past 4 months or so in my free time. It's a dog bone corner generator, however it's a little different to some of the existing ones. It's designed to be used for large amounts of geometry and as such, it avoids using any curve boolean operations that are computationally taxing. You don't have to split your curves up into internal and external lots either, it works it all out so you can be lazy. I've also incorporated Lunch Box's Object Bake Component for a one click operation that bakes geometry back out to Internal and External profile layers.
Let me know how it goes, will update where necessary.
Best,
Darcy
Change Log
06/11/19 - Version 2.0 SECOND DINNER - Rebuild
29/09/17 - Version 1.3 - Now with smooth corners option, True for smooth default/False for original
18/05/17 - Version 1.2 - Now includes variable angle domain input (defaults at 90°) for angled corners
13/11/16 - slight change to enable acceptance of very large interior curves
…
Added by Darcy Zelenko at 8:44pm on November 9, 2016