ow the steps of the successful run when step 1.2 is bypassed (note that the and OpenFOAM session is open in the background while running the Butterfly demo file):
1. create wind tunnel, and use different parameters of (4,4) for _globalRefLevel_ as suggested by Theodoro in this post
2. run blockMesh:
3. run snappyHexMesh:
4. run checkMesh:
5. connect the case from checkMesh to simpleFOAM and run the simulation:
6. the simulation converged at 1865 iteration, but the results visualization part has some problem:
7. so I revised this part according to suggestions from Hagit:
8. and the results can be visualized for P and U values:
The GH file used for the successful run shown above is attached here.
Now, the following is the error I got when the case from the update fvScheme component is used for simpleFOAM simulation:
the warning message on the simpleFOAM component is:
1. Solution exception: --> OpenFOAM command Failed!#0 Foam::error::printStack(Foam::Ostream&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #1 Foam::sigFpe::sigHandler(int) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #2 ? in "/lib64/libc.so.6" #3 double Foam::sumProd<double>(Foam::UList<double> const&, Foam::UList<double> const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #4 Foam::PCG::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #5 Foam::GAMGSolver::solveCoarsestLevel(Foam::Field<double>&, Foam::Field<double> const&) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #6 Foam::GAMGSolver::Vcycle(Foam::PtrList<Foam::lduMatrix::smoother> const&, Foam::Field<double>&, Foam::Field<double> const&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::PtrList<Foam::Field<double> >&, Foam::PtrList<Foam::Field<double> >&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #7 Foam::GAMGSolver::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #8 Foam::fvMatrix<double>::solveSegregated(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libfiniteVolume.so" #9 Foam::fvMatrix<double>::solve(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #10 Foam::fvMatrix<double>::solve() in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #11 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #12 __libc_start_main in "/lib64/libc.so.6" #13 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam"
The error message from the readMe! output node is attached below as a text file.
Hope you can kindly advise what the important steps or parameters I might have missed here. I assume it might be related to OpenFOAM rather than with the Butterfly workflow...
Thank you very much!
- Ji
…
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
…
he "return" is comment out as shown below?
After restarting Rhino and Grasshopper, I opened the outdoors_airflow demo file, and the first step of creating the case file is ok:
Then the blockMesh component gives the following error: seems I have to manually start OF first..
so, as the error message suggested, I open OF by Start_OF.bat:
Then come back to the blockMesh component, now it can be executed while the OF command line window is also openning:
... and the blockMesh finished successfully:
... so I proceeded to run snappyHexMesh, checkMesh and update fvScheme:
... up to the simpleFoam component, I got the error again:
The warning message is:
1. Solution exception: --> OpenFOAM command Failed!#0 Foam::error::printStack(Foam::Ostream&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #1 Foam::sigFpe::sigHandler(int) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #2 ? in "/lib64/libc.so.6" #3 double Foam::sumProd<double>(Foam::UList<double> const&, Foam::UList<double> const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #4 Foam::PCG::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #5 Foam::GAMGSolver::solveCoarsestLevel(Foam::Field<double>&, Foam::Field<double> const&) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #6 Foam::GAMGSolver::Vcycle(Foam::PtrList<Foam::lduMatrix::smoother> const&, Foam::Field<double>&, Foam::Field<double> const&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::PtrList<Foam::Field<double> >&, Foam::PtrList<Foam::Field<double> >&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #7 Foam::GAMGSolver::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #8 Foam::fvMatrix<double>::solveSegregated(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libfiniteVolume.so" #9 Foam::fvMatrix<double>::solve(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #10 Foam::fvMatrix<double>::solve() in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #11 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #12 __libc_start_main in "/lib64/libc.so.6" #13 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam"
... and the command lines in the readMe! output are pretty long and it is saved in the text file attached here.
So, my questions are:
1. why I have to manually start OF first before I can use the blockMesh component? Should butterfly automatically start OF?
2. what might be the cause of the unsuccessful run of simpleFoam in the end?
Hope you can kindly advise! Thank you!
- Ji
…
ooking for an efficient way to perform glazing of complex shapes.
I've only followed the Energy modelling workshops so far so i may have missed some essential components or workflows to achieve my needs. But i've made an attached definition with all my current attempts to get a proper HBzone with the numerous windows faces i will always have to deal with in this project.
I first thought that i was not using the HBObjWGZ correctly, then after some readings it was maybe an upgrading issue, then effectively i had my Therm 7.5 that needed to be reinstaled, but then ... I must be missing an essential HB tricks or workflow i guess ...
So I divided my attempt in two series :
- The Serie 1 : is a simplier version of the project step i'm working on but i'd be glad to achieve it first !
- The Serie 2 : is the real final direction of the project, which consist in sorting/dispatch faces to windowon one side and to an other material on the other, according to the winter sun and a pourcentage param.
Despite it is more complicated than the Serie one, it seems seems to create the same diversity of issues.
Until now, with the 5 different combinations of Serie 1, and the 3 of Serie 2, with and without using the different Glazing/window components, here are the logs i got from both HBZone component or OpenStudio component:
From OpenStudio - "1. The simulation has not run correctly because of this severe error: ** Severe ** BuildingSurface:Detailed="00073E23257843B6A948", invalid Construction Name="ETFE" - has Window materials.">> Has to deal with the way i'm trying to assign too early a customized EPConstruction material ? Done it wrong ? I tried to reload it in the library but doesn't change anything...
From OpenStudio - "1. The simulation has not run correctly because of this severe error: ** Severe ** BuildingSurface:Detailed="000579CD749E46DFA5EA", invalid Construction Name="EXTERIOR WINDOW" - has Window materials.">> Is it an issue in the way i define my surfs both as "WINDOW" (5) for srfType and Outdoors on the same component ?
From Create HBZone -"1. Solution exception:'EPZone' object has no attribute 'shdCntrlZoneInstructs'"
>> Happens when i try to introduce my ETFE EpMaterial after creating my first HBZone, with a Set EP Zone Construction, so this material seems to be not working either before and after trying to create an HB Zone
From Create HBZone- "1. Solution exception: 73df51a3b2144b1e858b has been moved, scaled or rotated."If you need to move or rotate a Honeybee object you should use Honeybee move, rotate or mirror components. You can find them under 12|WIP tab.
>> >> wich seems to exist in some on other thread Here and was a coding bug supposed to be fixed.
And last but not least ...
From OpenStudio - "1. The simulation has not run correctly because of this severe error: ** Severe ** checkSubSurfAzTiltNorm: Outward facing angle of subsurface differs more than 90.0 degrees from base surface.2. The simulation has failed because of this fatal error: ** Fatal ** GetSurfaceData: Errors discovered, program terminates" .
I'm attaching the file with each attempt in this post. The definitions are disabled and the log already copied separatly so there is no need to compute each of them to see what's wrong.
If someone from the beginner to one of the Kings of HoneyBee has any relevant answer/solution to this attempt with complex geometry Issue it will be really nice for me so i could to move forward !!
Thanks in advance guys and have a great day !
…
rring to the above image)
Area
effective
effective
Second
Elastic
Elastic
Plastic
Radius
Second
Elastic
Plastic
Radius
of
Vy shear
Vz shear
Moment
Modulus
Modulus
Modulus
of
Moment
Modulus
Modulus
of
Section
Area
Area
of Area
upper
lower
Gyration
of Area
Gyration
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(weak axis)
(weak axis)
(weak axis)
(weak axis)
A
Ay
Az
Iy
Wy
Wy
Wply
i_y
Iz
Wz
Wplz
i_z
cm2
cm2
cm2
cm4
cm3
cm3
cm3
cm
cm4
cm3
cm3
cm
I have a very similar table which I could import to the Karamba table. But I have i_v or i_u values as well as radius of inertia for instance.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
dimensjon
Masse
Areal
akse
Ix
Wpx
ix
akse
Iy
Wpy
iy
akse
Iv
Wpv
iv
Width
Thickness
Radius R
[kg/m]
[mm2]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm]
[mm]
[mm]
L 20x3
0.89
113
x-x
4,000
290
5.9
y-y
4,000
290
5.9
v-v
1,700
200
3.9
20
3
4
L 20x4
1.15
146
x-x
5,000
360
5.8
y-y
5,000
360
5.8
v-v
2,200
240
3.8
20
4
4
L 25x3
1.12
143
x-x
8,200
460
7.6
y-y
8,200
460
7.6
v-v
3,400
330
4.9
25
3
4
L 25x4
1.46
186
x-x
10,300
590
7.4
y-y
10,300
590
7.4
v-v
4,300
400
4.8
25
4
4
L 30x3
1.37
175
x-x
14,600
680
9.1
y-y
14,600
680
9.1
v-v
6,100
510
5.9
30
3
5
L 30x4
1.79
228
x-x
18,400
870
9.0
y-y
18,400
870
9.0
v-v
7,700
620
5.8
30
4
5
L 36x3
1.66
211
x-x
25,800
990
11.1
y-y
25,800
990
11.1
v-v
10,700
760
7.1
36
3
5
L 36x4
2.16
276
x-x
32,900
1,280
10.9
y-y
32,900
1,280
10.9
v-v
13,700
930
7.0
36
4
5
L 36x5
2.65
338
x-x
39,500
1,560
10.8
y-y
39,500
1,560
10.8
v-v
16,500
1,090
7.0
36
5
5
I have diagonals (bracings) which can buckle in these "non-regular" directions too, and they do. If I could add those values then in the Karamba model I could assign specific buckling scenarios..... I can see another challenge which will be at the ModifyElement component, I will not be able to choose these buckling lengths, in these directions.
Do you think this functionality can be added within short, or should I try to find another way to model these members?
Br, Balazs
…
doing this with the current tools or a bit of scripting since the Flickr API allows you to make requests in a REST format, but utilizing the Flickr.net API library makes it much simpler.
First and foremost, you need a Flickr API key...do you have one of those?
A great way to get to know the Flickr API is with the API Explorer. Here is a link to the page for the flickr.photos.search method explorer: http://www.flickr.com/services/api/explore/flickr.photos.search
The cool thing about this page is that it generates the REST Http call towards the bottom. So, here is what I did:
1. Grab the coordinates of the bounding box per Flickr API request:
bbox (Optional)
A comma-delimited list of 4 values defining the Bounding Box of the area that will be searched. The 4 values represent the bottom-left corner of the box and the top-right corner, minimum_longitude, minimum_latitude, maximum_longitude, maximum_latitude. Longitude has a range of -180 to 180 , latitude of -90 to 90. Defaults to -180, -90, 180, 90 if not specified. Unlike standard photo queries, geo (or bounding box) queries will only return 250 results per page. Geo queries require some sort of limiting agent in order to prevent the database from crying. This is basically like the check against "parameterless searches" for queries without a geo component. A tag, for instance, is considered a limiting agent as are user defined min_date_taken and min_date_upload parameters — If no limiting factor is passed we return only photos added in the last 12 hours (though we may extend the limit in the future).
So, I went to Google Earth, picked a city (London, UK) and dropped two pins:
This gave me two locations, which I can put into the Explorer Page next to the bbox option. Here is what I put for these two points: -0.155941,51.496768,-0.116783,51.511431
2. Check has_geo
3. In extras, type in geo
4. Make the call!
You will see a list of responses in an XML format, these responses will be from the first page. Geolocated photos are limited to 250 / page, so you will have to grab them page by page.
If you want to add more options (minimum upload date, maximum upload date, etc) you can do this as well)
The best is at the bottom, you get the full http call for this: http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=ffd44f601393a46e86aa3a5f8a013360&bbox=-0.155941%2C51.496768%2C-0.116783%2C51.511431&has_geo=&extras=geo&format=rest&api_sig=b42330e5d1523bd5fe60c2ad43acde99
Notice this call has some other api key, you should eventually replace this with your own.
You could copy and paste this into a browser and you will get the results with the latitude and longitude:
So this is really what you need to know to do this through GH. Since gHowl has an XML parser component that can access files on the web, you should be able to use the same http call into this component.
Eventually, we get a response, and we need to grab the lat and lon data. With gHowl we can map these to xyz coordinates, and generate the heatmap...this is just a linear mapping:
Attached are both the Rhino file and the Grasshopper file, as well as the image underlay.
I am working on a series of components that makes this more straightforward, but for now, this should get you started.
…
mers considering extreme sports reject mainstream retailers and like to check out small stores rather of at chains plus malls. Several smaller retailers discuss trends in sports shoe sales. http://skateszone.com/
Though athletic shoes and sports stores and from doorways retailers have reported somewhat uptick in footwear sales due to the increase in extreme sports, the particular beneficiaries inside the trend are independent surf and skate niche stores.
Some West Coast surf and skate shops stated teenagers and even more youthful Generation Xers are not only rejecting traditional sports, but they're also shunning mainstream retailers and malls meant for smaller niche shops transporting hard-to-come-by brands.
Eddie Miyoshi, district manager at Atomic Garage, a 3-store chain situated in Gardena, Calif., stated the soaring recognition of skateboard footwear has boosted the retailer's total footwear business 20-thirty percent this year, rather of '95.
Skate footwear presently represent 80-90 % of Atomic Garage's shoe sales, while couple of years back, Dr. Martens and Timberland drove the retailer's footwear business.
Like many retailers, Miyoshi pointed to Airwalk since the trend's catalyst.
However, if Airwalk broadened its distribution to larger chains, which are frequently located in malls, only a few skate shoe customers adopted. Rather, many youthful males have switched for your skate shops for additional elusive brands like Etnies, Duffs, and Electricity Footwear by Circus. By refusing to market bigger retailers or sports stores, these brands are increasing their cachet among youthful consumers.
"Kids don't want stuff which have been within the shops,In . Miyoshi added.
Searching ahead, Miyoshi forecasted skate shoe sales will remain strong through spring '97 provided "the [hot] vendors don't auction other [non-particularly shop] retailers."
"Skaters and non-skaters are rebelling against mainstream retailers so on to surf and skate shops for many looks," echoed Mark Richards, co-online sources Val Surf, a 3-store chain situated in North Hollywood, Calif. Soaring sales of skate footwear have driven total footwear receipts up 25 percent this year rather of '95.
"The quantity of that increase might be connected while using exposure of maximum games? I am unsure. [Skate footwear] may also be actually the think about the moment,In . Richards acknowledged. And in relation to getting this right look, youthful customers can be very picky.
"Skateboard footwear is a huge category for people, but we're not able to own the brands, Etnies, Duffs, Electricity and Nice, simply because they won't sell us," stated Mark Anderson, buyer at Chick's Sports, a six-store chain in Covina, Calif. "We have people coming every single day requesting them." Consequently, skate footwear have consistently ongoing to obtain about 5 % of Chick's overall footwear business. http://skateszone.com/the-top-8-best-skateboards-for-beginners-reviews-2017/
Nonetheless, some outdoors, niche sports and sports retailers are noting the growing recognition and coverage of maximum sports will receive a modest impact on footwear sales. Trailrunning footwear and approach/outdoors crosstrainers will be the two groups benefiting the very best inside the recognition. Like the skate shoe business, some retailers realize that styling instead of function frequently drives sales of individuals footwear.
"At this time the merchandise is a lot more visual than function," stated Chet James, gm of Super Jock 'N Jill, Dallas, speaking about trailrunning footwear. Still, James noted the current hype over adventure sports helps draw more customer traffic. "The marketing campaigns and media help bring growing figures of people in, nonetheless they frequently occasions day an issue that increases results on their own account,Inch he conceded.
John Wilkinson, executive vp inside the 85-store chain Track 'N Trail, Eldorado Hillsides, Calif., stated the shop has "seen some activity in approach footwear," but he requested the amount of consumers depend in it commercially sport. And, instead of accelerating total footwear business, Wilkinson speculated elevated sales of approach footwear and trailrunners are gnawing away at traditional hiking shoe and boot volume.
But Dan Bazinet, president of Overland Exchanging, a 34-store chain situated in Westford, Mass., believes the company-new looks have breathed existence for the wilting hiking boot category. "[Approach-type footwear] don't represent the lion's participate the hiking market, nonetheless they have elevated the hiking business and provided us extra sales," Bazinet stated.
He designated Timberland's Treeline Series and Rockport's Leadville line as strong performers. Unsurprisingly, he noted the company-new looks are attractive to youthful consumer base than traditional hikers.
For that month of June, sales of men's hikers were up 49 percent at Overland, rather of June '95, while sales of women's hikers were up 17 % for that month. Bazinet also attributed elevated sales that shops walked inside the hiking business, departing that business for that specialists.
Some retailers draw a good example concerning the hiking boom of two yrs ago combined with the current extreme sport phenomenon. "Plenty of bigger chains will get a specific percent in the industry while [extreme] sports remain a fad because they are selling cost-point type gear," described Steven Carre, assistant hard goods buyer at Adventure 16, a six-store chain situated in Hillcrest.
"However individuals [true enthusiasts] will say `we need real gear' and may shown up at us. That will help us after a while. What Size Skateboard good for an 3 4 5 6 7 8 9 10 11 12 13 14 year old
…
ng is deciding how and where to store your data. If you're writing textual code using any one of a huge number of programming languages there are a lot of different options, each with its own benefits and drawbacks. Sometimes you just need to store a single data point. At other times you may need a list of exactly one hundred data points. At other times still circumstances may demand a list of a variable number of data points.
In programming jargon, lists and arrays are typically used to store an ordered collection of data points, where each item is directly accessible. Bags and hash sets are examples of unordered data storage. These storage mechanisms do not have a concept of which data comes first and which next, but they are much better at searching the data set for specific values. Stacks and queues are ordered data structures where only the youngest or oldest data points are accessible respectively. These are popular structures for code designed to create and execute schedules. Linked lists are chains of consecutive data points, where each point knows only about its direct neighbours. As a result, it's a lot of work to find the one-millionth point in a linked list, but it's incredibly efficient to insert or remove points from the middle of the chain. Dictionaries store data in the form of key-value pairs, allowing one to index complicated data points using simple lookup codes.
The above is a just a small sampling of popular data storage mechanisms, there are many, many others. From multidimensional arrays to SQL databases. From readonly collections to concurrent k-dTrees. It takes a fair amount of knowledge and practice to be able to navigate this bewildering sea of options and pick the best suited storage mechanism for any particular problem. We did not wish to confront our users with this plethora of programmatic principles, and instead decided to offer only a single data storage mechanism.*
Data storage in Grasshopper
In order to see what mechanism would be optimal for Grasshopper, it is necessary to first list the different possible ways in which components may wish to access and store data, and also how families of data points flow through a Grasshopper network, often acquiring more complexity over time.
A lot of components operate on individual values and also output individual values as results. This is the simplest category, let's call it 1:1 (pronounced as "one to one", indicating a mapping from single inputs to single outputs). Two examples of 1:1 components are Subtraction and Construct Point. Subtraction takes two arguments on the left (A and B), and outputs the difference (A-B) to the right. Even when the component is called upon to calculate the difference between two collections of 12 million values each, at any one time it only cares about three values; A, B and the difference between the two. Similarly, Construct Point takes three separate numbers as input arguments and combines them to form a single xyz point.
Another common category of components create lists of data from single input values. We'll refer to these components as 1:N. Range and Divide Curve are oft used examples in this category. Range takes a single numeric domain and a single integer, but it outputs a list of numbers that divide the domain into the specified number of steps. Similarly, Divide Curve requires a single curve and a division count, but it outputs several lists of data, where the length of each list is a function of the division count.
The opposite behaviour also occurs. Common N:1 components are Polyline and Loft, both of which consume a list of points and curves respectively, yet output only a single curve or surface.
Lastly (in the list category), N:N components are also available. A fair number of components operate on lists of data and also output lists of data. Sort and Reverse List are examples of N:N components you will almost certainly encounter when using Grasshopper. It is true that N:N components mostly fall into the data management category, in the sense that they are mostly employed to change the way data is stored, rather than to create entirely new data, but they are common and important nonetheless.
A rare few components are even more complex than 1:N, N:1, or N:N, in that they are not content to operate on or output single lists of data points. The Divide Surface and Square Grid components want to output not just lists of points, but several lists of points, each of which represents a single row or column in a grid. We can refer to these components as 1:N' or N':1 or N:N' or ... depending on how the inputs and outputs are defined.
The above listing of data mapping categories encapsulate all components that ship with Grasshopper, though they do not necessarily minister to all imaginable mappings. However in the spirit of getting on with the software it was decided that a data structure that could handle individual values, lists of values, and lists of lists of values would solve at least 99% of the then existing problems and was thus considered to be a 'good thing'.
Data storage as the outcome of a process
If the problems of 1:N' mappings only occurred in those few components to do with grids, it would probably not warrant support for lists-of-lists in the core data structure. However, 1:N' or N:N' mappings can be the result of the concatenation of two or more 1:N components. Consider the following case: A collection of three polysurfaces (a box, a capped cylinder, and a triangular prism) is imported from Rhino into Grasshopper. The shapes are all exploded into their separate faces, resulting in 6 faces for the box, 3 for the cylinder, and 5 for the prism. Across each face, a collection of isocurves is drawn, resembling a hatching. Ultimately, each isocurve is divided into equally spaced points.
This is not an unreasonably elaborate case, but it already shows how shockingly quickly layers of complexity are introduced into the data as it flows from the left to the right side of the network.
It's no good ending up with a single huge list containing all the points. The data structure we use must be detailed enough to allow us to select from it any logical subset. This means that the ultimate data structure must contain a record of all the mappings that were applied from start to finish. It must be possible to select all the points that are associated with the second polysurface, but not the first or third. It must also be possible to select all points that are associated with the first face of each polysurface, but not any subsequent faces. Or a selection which includes only the fourth point of each division and no others.
The only way such selection sets can be defined, is if the data structure contains a record of the "history" of each data point. I.e. for every point we must be able to figure out which original shape it came from (the cube, the cylinder or the prism), which of the exploded faces it is associated with, which isocurve on that face was involved and the index of the point within the curve division family.
A flexible mechanism for variable history records.
The storage constraints mentioned so far (to wit, the requirement of storing individual values, lists of values, and lists of lists of values), combined with the relational constraints (to wit, the ability to measure the relatedness of various lists within the entire collection) lead us to Data Trees. The data structure we chose is certainly not the only imaginable solution to this problem, and due to its terse notation can appear fairly obtuse to the untrained eye. However since data trees only employ non-negative integers to identify both lists and items within lists, the structure is very amenable to simple arithmetic operations, which makes the structure very pliable from an algorithmic point of view.
A data tree is an ordered collection of lists. Each list is associated with a path, which serves as the identifier of that list. This means that two lists in the same tree cannot have the same path. A path is a collection of one or more non-negative integers. Path notation employs curly brackets and semi-colons as separators. The simplest path contains only the number zero and is written as: {0}. More complicated paths containing more elements are written as: {2;4;6}. Just as a path identifies a list within the tree, an index identifies a data point within a list. An index is always a single, non-negative integer. Indices are written inside square brackets and appended to path notation, in order to fully identify a single piece of data within an entire data tree: {2,4,6}[10].
Since both path elements and indices are zero-based (we start counting at zero, not one), there is a slight disconnect between the ordinality and the cardinality of numbers within data trees. The first element equals index 0, the second element can be found at index 1, the third element maps to index 2, and so on and so forth. This means that the "Eleventh point of the seventh isocurve of the fifth face of the third polysurface" will be written as {2;4;6}[10]. The first path element corresponds with the oldest mapping that occurred within the file, and each subsequent element represents a more recent operation. In this sense the path elements can be likened to taxonomic identifiers. The species {Animalia;Mammalia;Hominidea;Homo} and {Animalia;Mammalia;Hominidea;Pan} are more closely related to each other than to {Animalia;Mammalia; Cervidea;Rangifer}** because they share more codes at the start of their classification. Similarly, the paths {2;4;4} and {2;4;6} are more closely related to each other than they are to {2;3;5}.
The messy reality of data trees.
Although you may agree with me that in theory the data tree approach is solid, you may still get frustrated at the rate at which data trees grow more complex. Often Grasshopper will choose to add additional elements to the paths in a tree where none in fact is needed, resulting in paths that all share a lot of zeroes in certain places. For example a data tree might contain the paths:
{0;0;0;0;0}
{0;0;0;0;1}
{0;0;0;0;2}
{0;0;0;0;3}
{0;0;1;0;0}
{0;0;1;0;1}
{0;0;1;0;2}
{0;0;1;0;3}
instead of the far more economical:
{0;0}
{0;1}
{0;2}
{0;3}
{1;0}
{1;1}
{1;2}
{1;3}
The reason all these zeroes are added is because we value consistency over economics. It doesn't matter whether a component actually outputs more than one list, if the component belongs to the 1:N, 1:N', or N:N' groups, it will always add an extra integer to all the paths, because some day in the future, when the inputs change, it may need that extra integer to keep its lists untangled. We feel it's bad behaviour for the topology of a data tree to be subject to the topical values in that tree. Any component which relies on a specific topology will no longer work when that topology changes, and that should happen as seldom as possible.
Conclusion
Although data trees can be difficult to work with and probably cause more confusion than any other part of Grasshopper, they seem to work well in the majority of cases and we haven't been able to come up with a better solution. That's not to say we never will, but data trees are here to stay for the foreseeable future.
* This is not something we hit on immediately. The very first versions of Grasshopper only allowed for the storage of a single data point per parameter, making operations like [Loft] or [Divide Curve] impossible. Later versions allowed for a single list per parameter, which was still insufficient for all but the most simple algorithms.
** I'm skipping a lot of taxonometric classifications here to keep it simple.…
Added by David Rutten at 2:22pm on January 20, 2015
nts for Ladybug too. They are based on PVWatts v1 online calculator, supporting crystalline silicon fixed tilt photovoltaics.
You can download them from here, or use the Update Ladbybug component instead. If you take the first option, after downloading check if .ghuser files are blocked (right click -> "Properties" and select "Unblock").
You can download the example files from here.
Video tutorials will follow in the coming period.
In the very essence these components help you answer the question: "How much energy can my roof, building facade, solar parking... generate if I would populate them with PV panels"?
They allow definition of different types of losses (snow, age, shading...) which may affect your PV system:
And can find its optimal tilt and orientation:
Or analyse its performance, energy value, consumption, emissions...
By Djordje Spasic and Jason Sensibaugh, with invaluable support of Dr. Frank Vignola, Dr. Jason M. Keith, Paul Gilman, Chris Mackey, Mostapha Sadeghipour Roudsari, Niraj Palsule, Joseph Cunningham and Christopher Weiss.
Thank you for reading, and hope you will enjoy using the components!
EDIT: From march 27 2017, Ladybug Photovoltaics components support thin-film modules as well.
References:
1) System losses:
PVWatts v5 Manual, Dobos, NREL, 2014
2) Sun postion equations by Michalsky (1988):
SAM Photovoltaic Model Technical Reference, Gilman, NREL, 2014
edited by Jason Sensibaugh
3) Angle of incidence for fixed arrays:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
4) Plane-of-Array diffuse irradiance by Perez 1990 algorithm:
PVPMC Sandia National Laboratories
SAM Photovoltaic Model Technical Reference, Gilman, NREL, 2014
5) Sandia PV Array Performance Module Cover:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
6) Sandia Thermal Model, Module Temperature and Cell Temperature Models:
Photovoltaic Array Performance Model, King, Boys, Kratochvill, Sandia National Laboratories, 2004
7) CEC Module Model: Maximum power voltage and Maximum power current from:
Exact analytical solutions of the parameters of real solar cells using Lambert W-function, Jain, Kapoor, Solar Energy Materials and Solar Cells, V81 2004, P269–277
8) PVFORM version 3.3 adapted Module and Inverter Models:
PVWatts Version 1 Technical Reference, Dobos, NREL, 2013
9) Sunpath diagram shading:
Using sun path charts to estimate the effects of shading on PV arrays, Frank Vignola, University of Oregon, 2004
Instruction manual for the Solar Pathfinder, Solar Pathfinder TM, 2008
10) Tilt and orientation factor:
Application for Purchased Systems Oregon Department of Energy
solmetric.com
11) Photovoltaics performance metrics:
Solar PV system performance assessment guideline, Honda, Lechner, Raju, Tolich, Mokri, San Jose state university, 2012
CACHE Modules on Energy in the Curriculum Solar Energy, Keith, Palsule, Mississippi State University
Inventory of Carbon & Energy (ICE) Version 2.0, Hammond, Jones, SERT University of Bath, 2011
The Energy Return on Energy Investment (EROI) of Photovoltaics: Methodology and Comparisons with Fossil Fuel Life Cycles, Raugei, Fullana-i-Palmer, Fthenakis, Elsevier Vol 45, Jun 2012
12) Calculating albedo: Metenorm 6 Handbook part II: Theory, Meteotest 2007
13) Magnetic declination:
Geomag 0.9.2015, Christopher Weiss…