perienced with grasshopper, but so far I've managed to combine the following:
Giulio Piacentino's "Catenary arch from height" script
Pirouz Nourian's "Mobius" script (Obtained from a friend)
End Result:
Here's where I'm stuck: I want the mobius twist to revolve around the midpoint of the arch, but the script uses the input values to determine the endpoints, resulting in a weird sinuous shape when viewed from above. Also, the secondary end points (generated by the mobius script, determining the width of the surface) are generated by default along the z axis, resulting in an arch that only touches the "ground" at two points. I attempted to work around this issue by trying to force the zHeight parameter to correspond with the y axis (thus rotating the arch 90 degrees so it would lay "flat"), but the script interprets the third point as a value and not as an actual point to bisect. I thought this might be an issue with the C# component that I obtained from Giulio Piacentino's script, so I attempted to tinker around with the source code. Unfortunately, I'm not fluent in C# so I only managed to mess everything up (I've since recovered the code from the cache). Anybody got some ideas? -BC …
onsidered period.
Even if the end of July for the mediterranean climate is not the best period to perform an adaptive comfort analysis (it's just a pretest to define a LB model) I want to refine the Adaptive comfort Chart (AC) by changing the external air temperature data imported from the .epw file with that of monitored data as reported here below:
Where the monitored ext air temperature are in this form (green panel below):
I have used the comfortPar component to set the following parameters:
Adaptive chart as defined by EN 15251
90% of occupants comfortable
the prevailing outdoor temperature from a weighted running mean of the last week
fully conditioned space (even if it is not properly in line with AC as already discussed)
The question is this: the AC component could correctly apply the code below if there is only a list of external temperature data for a restricted period (without indication about the limits of this period) and not for an entire year?
else: #Calculate a running mean temperature. alpha = 0.8 divisor = 1 + alpha + math.pow(alpha,2) + math.pow(alpha,3) + math.pow(alpha,4) + math.pow(alpha,5) dividend = (sum(_prevailingOutdoorTemp[-24:-1] + [_prevailingOutdoorTemp[-1]])/24) + (alpha*(sum(_prevailingOutdoorTemp[-48:-24])/24)) + (math.pow(alpha,2)*(sum(_prevailingOutdoorTemp[-72:-48])/24)) + (math.pow(alpha,3)*(sum(_prevailingOutdoorTemp[-96:-72])/24)) + (math.pow(alpha,4)*(sum(_prevailingOutdoorTemp[-120:-96])/24)) + (math.pow(alpha,5)*(sum(_prevailingOutdoorTemp[-144:-120])/24)) startingTemp = dividend/divisor if startingTemp < 10: coldTimes.append(0) outdoorTemp = _prevailingOutdoorTemp[7:] startingMean = sum(outdoorTemp[:24])/24 dailyRunMeans = [startingTemp] dailyMeans = [startingMean] prevailTemp.extend(duplicateData([startingTemp], 24)) startHour = 24
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p; 3D Urban ModelingOn the topography subject I get the next message: "One or more boundaries may be outside the bounds of the topo dataset" I'm not sure if it's the .IMG file I'm loading since I found so many IMG files nearing my polyline area (Miami Lat:26 Lon:-81 aprox.) or maybe my polygon doesn't match the topo area? I have no idea why it isn't working :(On the Shapefile subject, haven't been able to find a Building Height SHP File, so far have downloaded around 8 SHP files which only contain Polylines, my solution is to meanwhile randomize Z heights, but of course this data is not "technically" correct.P.S.: I've already tried all example links and also the ones posted by you and Benjamin in this video.Been strugling last few days, hope you can help me, thanks in advance!!…
try now to integrate Geco in an interdisciplinary architectural engineering studio: hoping we can show you some nice applications of your tool, I'll keep you update and sending now details by e-mail. Here the file (very welcome to be shared). It most probably contais trivial errors by me, thanks for helping and giving some tip! Gr. Michela
FILE:
Ok, right, I see the outputs update correctly. Origin of problems must be in some different mistake I do:
- Incident radiation: I am not sure I understand what is going on: why I get so many 'not a number' ? (The Galapagos report is full of NaNs).
Bio-Diversity: 0.887 Genome[0], Fitness=NaN, Genes [89% · 44%] { Record: Too many fitness values supplied } ...
Genome[7], Fitness=NaN, Genes [74%] { Record: No fitness value was supplied } ....
Genome[9], Fitness=NaN, Genes [37% · 11%] { Record: Genome was mutated to avoid collision Record: Too many fitness values supplied }
- Daylight calculations: the geometry accumulates withouth deleting the previous models. As a consequance, results almost do not change after few varations (so, outputs get updated but do not vary). In current daylight definition: the first object being imported is the one where the grid has to fit; its setting makes it cancelling all the other objects during import. All the others, do not delete anything when imported. When running loops (manual or GA) that vary parameters, the entire geometry do not get cancelled - so I guess the loop does not pass back by the cancelling step, but imports only the geometry which has been varied by the parameters using the setting of that import component only? I will then try again by changing the order of the operations, but if you have specfic tips, let me know.
THANKS!
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Simpsons episode were Bart goes into a mall and in the time he goes in and out of a shop all others have been turned into Starbucks.
I personally don't like it but you can't say they are crushing all competitors because, as far as i know, all owners of those software packages voluntarily sold their property for a good price. I would actually be more worried that an antitrust lawsuit was filed against Autodesk.
For example, this is what happened with Rockefeller's Standard Oil:
The antitrust case against Standard Oil also seems absurd because its share of the petroleum products market had actually dropped significantly over the years. From a high of 88 percent in 1890, Standard Oil's market share had fallen to 64 percent by 1911, the year in which the US Supreme Court reaffirmed the lower court finding that Standard Oil was guilty of monopolizing the petroleum products industry.[32]
The court argued, in essence, that Standard Oil was a "large" company with many divisions, and if those divisions were in reality separate companies, there would be more competition. The court made no mention at all of the industry's economic performance; of supposed predatory pricing; of whether industry output had been restrained, as monopoly theory holds; or of any other economic factors relevant to determining harm to consumers. The mere fact that Standard Oil had organized some thirty separate divisions under one consolidated management structure (a trust) was sufficient reason to label it a monopoly and force the company to break up into a number of smaller units.
To economists, "predatory pricing" is theoretical nonsense and has no empirical validity, either.
In other words, the organizational structure that was responsible for the company's great efficiencies and decades-long price cutting and product improving was seriously damaged. Standard Oil became much less efficient as a result, to the benefit of its less efficient rivals and to the detriment of consumers.
From: http://mises.org/daily/2317
(Beware, that site is very ideologically charged)…
points within the bounds of the site boundary and use each location as an attractor point controlling a variable at each point in the grid (radius of a circle/height of a cube/colour based on a gradient etc.).This would be based on proximity to the attractor points with the effect of each attractor point essentially scaled by the percentage associated with it. For example a location with 88% visitor rates would have a more dramatic effect than a location with 26% visitor rates.
I've had a bit of a play around but can't seem to get beyond the point of what is shown in basic point attractor tutorials online. I'm definitely a novice.
Here's how I figured it would be done:
1) Create a grid of source points within a boundary curve.
2) Select 18 pre-defined attractor points.
2) Measure the distance between the source points and the attractor points.
3) Invert this data so that variables increase with proximity rather than decrease.
4) Give each of the attractor points a strength value from 1-100% based on the visitor rates.
5) Use the scaled data to control a variable at each of the source points.
6) Create some way to control the drop-off rate of the effect from each point.
It is at step 3 that I get completely lost.
I hope my description is clear. Any help would be greatly appreciated,
Adam
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troducción a su plugin de modelado paramétrico, Grasshopper.
Con este tipo de herramientas podemos pensar formas más allá de las cajas para diseñar, porque seremos capaces controlar con total rigor geometrías muy complejas.
En el siguiente video, podemos ver un ejemplo realizado durante un curso impartido anteriormente en Madrid por el profesor, Francisco Tabanera, en el que se realiza una interpretación del proyecto de BIG para la Biblioteca Nacional de Kazajstán.
<a title="Interpretación de la Biblioteca Naiconal de Kazakstan, de BIG" href="http://www.youtube.com/watch?v=YLldO-SxgPw" target="_blank"></a>
A lo largo del curso se realizarán diferentes ejemplos que podrán ser realizados por todos los asistentes, ya que no es necesario ningún conocimiento previo para su seguimiento.
El curso se desarrollará en las oficinas de Arquitecton en Barcelona con el siguiente horario:
HORARIO
Sábado 1 de Marzo
De 9.30 a 13.30h.
Sábado 1 de Marzo
De 15.30 a 19.30h.
El curso está planteado para un máximo de 9 alumnos, para conseguir el máximo aprovechamiento posible por parte de los mismos.
El curso tiene un precio de 90€. Estudiantes y desempleados tienen un descuento del 10%. Es posible asegurarte una plaza con un primer pago de 25€ a modo de reserva.
Apúntate aquí…
next level.
This Parametric Design course will provide the participants with the necessary knowledge and ability to use Grasshopper, a free visual programming plugin in Rhinoceros; you will be guided through a series of hands-on exercises that highlight NURBS modeling and its concepts. We will introduce Grasshopper as a graphical algorithm editor tightly integrated with Rhino’s 3D modeling tools. You will also learn how Rhino is used to render models for visualization, translate 3D models for prototyping, and export 3D models into 2D CAD or graphics programs.
English is the course main language.
Location: Düsseldorf city center
Registration and buying Tickets
www.digitalparametrics.eventbrite.de
Course Calendar:
4 Days 6 hours each
Total duration 24h
2 weekends
Date:
Sat. 17 - Sun. 18 June
Sat. 24 - Sun. 25 June
10:00 - 17:00
Getting Started in Rhino. 2 days (17 - 18 June)
Getting Started in Grasshopper. 2 days (24 - 25 June)
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Participants will be given a certificate of participation at the end of the course.
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Course fees:
Professionals: 600€ (excl. MwSt.) Students: 500€ (excl. MwSt.) Students need to provide: Copy of current student ID or proof of student enrollment at University/School.
Group discounts:
Group of 3 professionals: 3x500 = 1500€ (excl. MwSt.)
Group of 3 Students: 3x400 = 1200€ (excl. MwSt.)
Participants are kindly asked to bring their own laptops and have pre-installed Rhino + Grasshopper.
Useful Resources:
Rhinoceros Installation (90 days full version trial available): http://www.rhino3d.com/download
Rhinoceros for Mac (includes Grasshopper) http://www.rhino3d.com/download/rhino-for-mac/5/wip
Grasshopper Free Installation: http://www.grasshopper3d.com/page/download-1
Grasshopper Free Plugins: http://www.food4rhino.com/app/lunchbox http://www.giuliopiacentino.com/weaverbird
Main Tutor:
Rihan
M.A. Dipl.Ing. Architect
Architect at RKW Architektur + Düsseldorf
For any questions about the course, please email: info@immersive-studio.com…
ll geometry.
The difference with programs like Inventor is that they are made for production, regardless of the fabrication method. I won't go into detail about that, and instead focus on the modeling process.
In this little model, the starting point actually is a bit obvious, the foundation.
The only contents in the 3dm file are 27 lines. These indicate the location of each footing, and the direction of the tilt of each column. Everything else is defined in GH with the use of numbers as input parameters.
Needless to say, instead of those lines you could obviously generate lines and control the number of columns and panels, hence establish their layout, with any algorithmic or non-algorithmic criteria you please. That marks a major difference between GH and Inventor.
You can generate geometry with Inventor via scripting/customization (beyond iLogic), with transient graphics for visual feedback similar to GH's red-default previews. However Inventor's modeling functions are not set to input and output data trees. I won't go into detail on that, but suffice to say that the data tree associativity of GH was for me the first major difference I noticed. I've used other apps with node diagram interfaces like digital fusion for non-linear video editing since the late 90's, so the canvas did not call my attention when I first started using GH.
Anyways, here's a screen capture of the foundational lines:
In the first group of components, the centerlines of the rear columns are modeled:
And the locations in elevation for connection points are set. Those elevations were just numbers I copied from Excel, but you can obviously control that any way you please. I was just trying to model this quickly.
The same was done for the rear columns:
The above, believe it or not, took me the first 5 hours to get.
Here's a screen capture of what the model and definition looked like after 4 hours, not much:
If you're interested, next post I can get into the sketching part you mentioned, which is a bit cumbersome with GH, but not really.
I wouldn't say that using GH to do this little model was cumbersome, it just needed some thinking at the beginning. You do similar initial thinking when working with a feature-based modeler.…
Added by Santiago Diaz at 12:44am on February 24, 2011
umbrella of Urban Heat Island (UHI) and I am going to try to separate them out in order to give you a sense of the current capabilities in LB+HB.
1) UHI as defined as a recorded elevated air temperature in an urban area:
If you have access to epw files for both an urban area and a rural area, you can use Ladybug to visualize and deeply explore the differences between the two weather files. Ladybug is primarily a tool for weather file visualization and analysis and it can be very helpful for understanding the consequences of UHI on strategies for buildings or on comfort. This said, if you do not have both rural and urban recorded weather data or you want to generate your own weather files based on criteria about urban areas (as it sounds like you want to do), this definition might not be so helpful.
2) UHI defined by air elevated air temperature but viewed as a computer model-able phenomenon resulting primarily from urban canyon geometry, building materials, and (to a lesser degree) anthropogenic heat:
This definition seems to fit more with they type of thing that you are looking for but it is unfortunately very difficult and computationally intensive such that we do not currently have anything within Ladybug to do this right now. I can say that the state-of-the art for this type of modeling is an application called Town Energy Budget (TEB) and this is what all of the advanced UHI researches that I know use (http://www.cnrm.meteo.fr/surfex/spip.php?article7). Unfortunately for those trying to use it in professional practice, it can take a while to get comfortable with it and it currently runs exclusively on Linux (this does mean that it is open source, though, and that you can really get deep into the assumptions of the model). A couple years ago, a peer of mine translated almost all of TEB into Matlab language making it possible to run it on Windows if you have Matlab. He wrapped everything together into a tool called the Urban Weather Generator (UWG), which can take an epw file of a rural area and warp it to an urban area based on inputs that you give of building height, materials, vegetation, anthropogenic heat, etc. I would recommend looking into this for your project, although, bear in mind that is it not open source like the original TEB tool and that you may need to get a (very expensive) copy of MATLAB (http://urbanmicroclimate.scripts.mit.edu/uwg.php).
3) UHI as defined by a thermal satellite image of an urban area depicting an elevated average radiant environment that reaches a maximum a the city center and changes by land use:
This is the definition of UHI that I am most familiar with and was the basis of much of my past research. I feel that it is also a definition of UHI that is a bit more in line with where a lot of contemporary UHI research is headed, which is away from the notion of UHI as a macro-scale meteorological phenomena that is averaged as an air temperature over a huge area towards one that accepts that different land uses have different microclimates and (importantly) different radiant environments. While the air temperature difference between urban and rural areas usually does not change more than 1-4 C, the radiant environment can be very different (on the order of 10-15 C differences). The best way to understand UHI in this context is with Thermal satellite images, for which there is ha huge database of publicly available data on NASA's glovis website (http://glovis.usgs.gov/) or their ECHO website (http://reverb.echo.nasa.gov/reverb/#utf8=%E2%9C%93&spatial_map=satellite&spatial_type=rectangle). I tend to use thermal data from LANDSAT 5-8 and ASTER satellites in my research. Unfortunately, there is a lot f bad data with a lot of cloud cover mixed in with the really good stuff and it can take some time to find good images. Also, there aren't too many programs that read the GeoTiff file format that you download the data as. I know that ArcGIS will read it, a program called ENVI will read it (I think that the open source QGIS can also red it). I have plans to write a set of components to bring this type of data into Rhino and GH (I may get to it a few months down the line).
4) UHI as a computer model-able notion of "Urban Microclimate" with consideration of local differences and the local radiant environment:
This is where a lot of my research has lead and, thankfully, is an area that Honeybee can help you out a lot with. EnergyPlus simulations can output information on outside building surface temperatures and these can be very helpful in helping get a sense of the radiant environment around individual buildings. Right now, I am focusing just on using this data to fully model the indoor environments of buildings as you see in this video:
https://www.youtube.com/watch?v=fNylb42FPIc&list=UUc6HWbF4UtdKdjbZ2tvwiCQ
I have plans to move this methodology to the outdoors once I complete this initial application to the indoors. For now, you can use the "Surface result reader" and the "color surfaces based on EP result" components to get a sense of variation in the outside temperature of your buildings.
I hope that this helped,
-Chris
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