am to find the coverage for various public-transport stations and is interested under what conditions that coverage will poorly represent reality, then that would fit perfectly within your proposed forum, but the SO people will close it as off-topic before you can say directed-infrastructure-networks.
Or discussing which properties of a transport network would be sufficient to encode into a graph in order to give a model accurate enough for early design iterations.
Or discussing the fabrication costs under various manufacturing methods of elements (a, b, c, ...) with amounts (K, L, M, ...). ie. is it cheaper to manufacture façade panels using manual welding if I have 50*a + 50*b + 25*c or would it be cheaper to have 120*a + 3*b + 2*c?
Or discussing the visual aspects of various types of geometry. Do Bezier or Akima splines look more natural? What about them makes them look natural/unnatural? Can people tell the difference between a perfect circle and a circularish Nurbs curve with 12 points? Does it matter whether the Nurbs curve is small or big? Next to a perfect circle or not? Horizontal or vertical?
What equation would better describe experienced time by humans travelling from A to B rather than measured time?
How can I find out under what wind conditions this sharp edge on my building will start whistling?
How much might the potentially bad smell of this cheaper material lower the value of my building?…
entations (0, 30, 60, ..).
I use a simple definition with native components to extract this information from the epw file. However, I run into some 'trouble'.
There seem to be a lot of 0 values in the wind velocities. Most of these 0 values seem to be associated with the 0 direction (north direction is common in this weather file, i.e. Singapore, but I doubt it is so many 0s).
I then proceeded to cull all the hours with 0 wind velocity and did the averaging over all the remaining hours (around 7100 for this weather file). However, I still get a bit of odd results that don't coincide with other data I have for the area. For example, average wind velocity in the north seems to be 1.12m/s while officially Singapore reports 2.1m/s. More discrepancies arise in the frequencies of the wind directions (the hours of each direction per year divided by total hours) from publically available data.
Anyways, I don't want to tire you with so many specifics. The question to the forum is if anyone has used .epw files to collect wind data before and if we believe they are dependable for such calculations? If not, do you have any idea on where I could find open wind data of good quality?
Thank you very much in advance.
Kind regards,
Theodore.
P.S.: Will be adding the definition once I'm in the office, even though it is quite straightforward.…
Loop'. The fun part of the slower version is that you can see what it's doing while it's running. 'Fast Loop' gives no indication that it's working, so you want to test it with small numbers and be sure it's coded properly before bumping the iteration count up.
The GH profiler running the slow version showed between 1 and 1.5 seconds per loop, but the reality was more like ~10 seconds per loop toward the end of an 11 X 11 grid, or ~20 minutes total. It's easier to be patient because you know it's working.
The 'Fast Loop' finished the same grid in 1.6 minutes! An impressive improvement. I've been running it on a 30 X 30 grid (900 points) for ~23 minutes so far and see nothing yet. Not the ~12 minutes I had hoped for... Now 36 minutes on this loop for 900 points... hope it's not stuck. Not fast! Later - DONE!! Profiler says 59 minutes for 900 points but it was more like an hour and twenty minutes total. It succeeded, I have a single 'Closed Brep' from 900 extruded rings, baked to Rhino.
Another strategy to explore would be doing 'SUnion' on a smaller grid using the Anemone loop, then replicate it by moving it as needed to form a larger grid; then run the copies through another 'SUnion' loop. I went ahead and implemented that while waiting. It works and is fast! Started with 3 X 3 and ran the result again as 5 X 5 (9 X 25 = 225 total) in barely ~70 seconds!? Trying 36 X 36 now... 1,296 points appears to have succeeded in less than ten minutes! Though it seems to take quite awhile after the loop ends before control is restored to GH/Rhino. I'll let you do your own experiments and benchmarks.
I encapsulated the loop in a cluster called 'suLoop' (blue groups).
Internal of 'suLoop' cluster:
…
Added by Joseph Oster at 11:14pm on March 22, 2017
know how to solve.
It appears in
11 - Honeybee Energy Modeling - The Laws of Geometry in E+ Part 3: Curved Geometry
where I need to retrieve .idf file,
and shows this message:
1. Solution exception:'hb_EPZoneSurface' object has no attribute 'punchedGeometry'
I've added .gh file at a state where I meet the problem.
Also, I've looked around the forum and found some mention OpeanStudio related problems, mainly one's lack of it. Could it be the source of the problem, because I only followed Installation Instructions and haven't installed OpenStudio.
…
, low/high bounds etc):
Then I usually go to monthly analysis where I simply animate a slider from 1 to 12 and export hi-res png images. Problem here is that radiation rose scales up and down for each month differently and I can't find a way to control it, in the end I get a consistent background with inconsistent rad rose.
In fact, annual study produce such a huge rose that I had to scale it down with factor of 0.3, after which monthly roses were tiny:
So in order for them to look somewhat close to the intended size I had to rescale them up 400%, here it is easier to notice size inconsistency (look at the text's position):
I understand that the size somehow correlates to radiation amount, I would like to ask our kind and awesome developers to add consistency not only to rad rose but anywhere where it is absent. Something like wind rose's maxFrequency, super awesome feature, just look at these sexy graphs, they are all the same size, beautiful, mmmmm XD:
…
d of interpenetrating surfaces somewhere:
Now all links (except a possible single ball on the very end of odd numbered ball series) are four balls long, including the jostled ones. Without that step, those items simply don't appear in the output, leaving way too big of gaps to ignore, eventually leaving huge gaps at later stages of segment doubling:
So if I turn the jostling multiplication factor way down it should work imperceptibly:
Ta-dah! The jostling strategy WORKS! Granted, only in this special case where I know I'm dealing with adjacent pairs of worms along a curve, not generic objects arranged in space by some artist.
Now I just need to wrap the multiple Python script components I'm stringing together into one script.
How long does the full 2400 balls take, finally? It took 12 Python scripts that merge pairs, to achieve this breakdown: 2400 -> 1200 -> 600 -> 300 -> 150 -> 75 -> 38 -> 19 -> 9 -> 5 -> 3 -> 2 -> 1. Time was 2 minutes 50 seconds, so there is some extra struggle for 2X as many balls as 1200 that took 1 minute 20 seconds, but only ten more seconds.
…
Added by Nik Willmore at 9:06pm on February 17, 2016
, presso la sede Manens-Tifs, nei giorni 26,27 e 28 maggio 2016.
Il comfort visivo e la gestione dell’illuminazione naturale in relazione al risparmio energetico diventano sempre più rilevanti per una progettazione innovativa degli edifici. Ad esempio, il nuovo protocollo LEED 4 riconosce crediti per le simulazioni di daylighting e conferma l’importanza degli aspetti progettuali per “collegare gli occupanti con lo spazio esterno, rinforzare i ritmi circadiani, ridurre i consumi di energia elettrica per l’illuminazione artificiale con l’introduzione della luce naturale negli spazi”. Senza strumenti software per la simulazione della luce non è possibile ottenere risultati di qualità. Radiance è un software validato, utilizzato sia a livello di ricerca che dai progettisti ed è tra i più accurati per la simulazione professionale della luce naturale e artificiale. Non ha limiti di complessità geometrica ed è adatto a essere integrato in altri software di calcolo e interfacce grafiche. Queste ultime facilitano le procedure di programmazione. Le principali e più versatili saranno oggetto del corso (DIVA4Rhino e Ladybug+ Honeybee, plug-in per Grasshopper e Rhinoceros 3D).
Il corso è rivolto a progettisti e ricercatori che vogliano acquisire strumenti pratici per la simulazione con Radiance al fine di mettere a punto e verificare le soluzioni più adatte alle proprie esigenze. Sono previste lezioni di teoria e pratica con esempi ed esercitazioni volte a coprire in modo dimostrativo ed interattivo i concetti trattati.
Le domande di iscrizione devono essere presentate entro il 12 maggio 2016.
La brochure con i contenuti del corso e tutte le informazioni sono disponibili su questo link
Il corso è sponsorizzato da Pellinindustrie.…
Introduzione a Grasshopper", il primo manuale su Grasshopper.
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I corsi PLUG IT nascono dalla volontà di promuovere le nuove tecnologie digitali di supporto alla progettazione e condividere il know-how maturato attraverso ricerca, collaborazione con i più importanti studi di architettura e pubblicazioni internazionali.
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Verranno introdotte le nozioni base di Grasshopper approfondendo le metodologie della progettazione parametrica e le tecniche di modellazione algoritmica per la generazione di forme complesse. Il corso è rivolto a studenti e professionisti con esperienza minima nella modellazione 3D e si articolerà in lezioni teoriche ed esercitazioni.
. Argomenti trattati:
- Introduzione alla progettazione parametrica: teoria, esempi, casi studio - Grasshopper: concetti base, logica algoritmica, interfaccia grafica - Nozioni fondamentali: componenti, connessioni, data flow
- Funzioni matematiche e logiche, serie, gestione dei dati - Analisi e definizione di curve e superfici
- Definizione di griglie e pattern complessi - Trasformazioni geometriche, paneling - Attrattori, image sampler
- Data tree: gestione di dati complessi - Digital fabrication: teoria ed esempi - Nesting: scomposizione di oggetti tridimensionali in sezioni piane per macchine CNC
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Verrà rilasciato un attestato finale.
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Ulteriori info e programma completo su: www.arturotedeschi.com e su www.edizionilepenseur.it…
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…