requires four weather data inputs: air temperature (_dryBulbTemperature), relative humidity (relativeHumidity_), wind speed at 1.1 meters from the ground (windSpeed_) and mean radiant temperature (meanRadiantTemperature_).You can add values to the first three inputs from the Ladybug "Import Epw" component. For the last (meanRadiantTemperature_), you can add it from Ladybug's "Outdoor Solar Adjusted Temperature Calculator" component, or let "Thermal Comfort Index" component to calculate it. Both use different methods to calculate the final values.
I attached an example file below with second option.For more precise calculations you can use Honeybee and Chris' microclimate maps.An icing on the cake for the end: one of Ladybug developers yesterday released a set of Ladybug components for modelling in ENVI-met application. ENVI-met is cutting-edge microclimate software, which can be downloaded for free. It opens a number of advanced new analysis in outdoor domain, which couldn't have been done with the current Ladybug+Honeybee tools. So you can perform the simulation in ENVI-met 4 free software, and then add mean radiant temperature values from ENVI-met simulation to "Thermal Comfort Indices" component. Here is an example file.If you would like to go with the last approach, then the best would be to post a question about it in this topic.
1) You can make a polygonized tree.I haven't subtracted the trunk from the crown, but I guess it makes sense that it can be done.2) In most solar related simulations, a default albedo value of 0.2 is used. This corresponds to average albedo value taken from materials surrounding the urban or countryside location (concrete, grass, gravel, sand, asphalt...). However the presence of snow can significantly magnify the average albedo value several times. "Sunpath shading" components albedo_ input has an ability to calculate albedo due to presence of snow, if nothing is added to it (to albedo_ input). As you are performing the analysis of PET in a horizontal plane, it will not affect your calculations.3) Most thermal comfort indices will require performing analysis at 1.1 meters above the ground. This is considered to be height of standing person's gravity center.The same goes for PET index. So you are correct: you should place the analysis grid at 1.1 meters above the ground before adding it to the "Sunpath Shading" component.It is worth mentioning that "Thermal Comfort Indices" component used in this topic's PET_on_Grid2.gh and PET_on_Grid3.gh files is from last year, and much slower than the newest one (VER 0.0.64 MAR 18 2017) used in the example attached below. Just a remainder if you have been using older version of this component.Let me know if I misunderstood some of your questions, or if I missed to answer some of them.
EDIT: sorry for posting a double reply. When I posted it the first time, I only got links visible, with no text. Something has been wrong with grasshopper ning forum for the last couple of months.…
nted" in space (at instance definition creation phase): indicates the obvious fact that if garbage in > garbage out (try it).
2. Load the GH thing. Task for you: Using Named Views locate the points of interest as described further and make a suitable view. That way you can navigate rather easily around (hope dies last).
3. Your attractors are controlled from here:
The slider in blue picks some attractor to play with. You can use this while the K2 is running.
4. Don't change anything here (think of it as a black box: who cares how it works? nobody actually):
5. Enable the other "black box": job done your real-life stuff is placed:
6. Enable the solver: your "real-life" things start to bounce around:
7. Go there are play with the slider. A different attractor yields an other solution:
8. With real-life things in place if you disable the C# ... they are instantly deleted and you are back in lines/points and the likes:
9. Either with instance definitions or Lines/points change ... er ... hmm ... these "simple" parameters and discover the truth out there:
10. Since these are a "few" and they affect the simulation with a variety of ways ... we need a "self calibrating" system: some mini big Brother that does the job for us. Kinda like applying safely the brakes when it rains (I hate ABS mind).
NOTE: the rod with springs requires some additional code ,more (that deals with NESTED instance definitions) in order to (b) bounce as a whole and at the same time (b) elongates or shrinks a bit.
More soon.
…
). It deals with the potential possibility to port GH into AEC fields (real-life AEC fields, nothing to do with academic thinking). The bad news are that the smart AEC sector is occupied solely by Bentley/GenComp – expect soon Revit/Dynamo as well (not to mention CATIA). The good news are that there’s millions of designers/engineers/industrial designers out there who could be interested for a 3rd alternative.
Intro: Well, in the old days (when men had mustache and muttonchops) AEC design performed in a nice top-to-bottom sequence (kinda like a vector) : the Big Man (aka The Brain) did some sketches (with crayons) and the rest (known as the “others”) struggled to make The Idea a reality. Today things are different, mind. Or they should be different. Or may be different. Or whatever. The big easy:For a zillion o reasons (AEC matures, PLM, cost, outsourcing, sustainable engineering…add several more) this vector like process of the past is like a Brown motion these days: Right down the moment that you (or your team) “sketch” The Big Idea … another team design simultaneously (i.e. in parallel) the components (parts) that compose the whole. This is the so called bottom-to-top design mentality. So the whole and the parts meet in some "middle point" instead the later being dictated by the former. In quite a few occasions parts dictate the whole (cost, cost and cost being the main reasons). The more a design is contemporary the more this bottom-to-top thing plays a critical role. Ignore it and have a very big time (sooner or later).The bad news:If you accept the above…well GH – at present phase - is not ready for contemporary AEC work. At.All.3 Main reasons for that:1.You can’t use parametric parts (i.e. nested blocks to speak Rhino language) into a given definition (in this case attached : truss nodes, connection flanges, mount plates, cable tensioners, planar glazing components, roof skin components…etc etc). This is obviously a Rhino domain.2.You can’t bake a given solution in such a way that the Rhino file is structured (i.e. assemblies of nested blocks). Or you can do it theoretically writing some VB/C code – but the core of the matter is that corresponding components are MIA. That means that you can’t export anything useful actually into established AEC oriented apps and/or established MCAD apps (for doing/calculating the parts for real-life production).3.The GH process can’t being interrupted. Imagine defining, say, a building “envelope” in GH and then …er…use Evolute tools in order to optimize things (say quad planarization and the likes). Then …continue in GH for more detailed work. Then design the parts as in 1 above. Then back to Evolute. Then back to GH.So…if anyone is interested I would be glad to start the mother of all debates and/or some kind of crusade (GH for President, that is).PS: This definition is a WIP thing – more refined stuff to follow (in particular a complex canopy tubes pre-stress system).
PS: Tree8 components are used sporadically.
PS: Use Saved Views
May the Dark Force be with us.Best, Peter …
ng/702/30
EDIT: DK2 works, not with positional tracking yet (14/09/15)
Source is here:
https://github.com/provolot/RhinoRift
Steps:
1) Download these files (also attached below):
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper_v0.4.ghx
https://github.com/provolot/oculus-grasshopper/raw/master/OpenTrackRiftGrasshopperUDP.ini
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper-test_v0.1.3dm
2) Download OpenTrack - http://ananke.laggy.pk/opentrack/, and setup/install. Once installed, double-click to open.
3) In OpenTrack, load the 'OpenTrackRiftGrasshopperUDP.ini' profile. Click the 'Start' button and move your Rift around - make sure that it looks like the Yaw/Pitch/Roll data is being sent. TX/TY/TZ will all be 0, as Oculus doesn't have absolute positioning data.
4) In Rhino, open the test 3dm. You'll notice that there are two viewports - called 'LeftEye' and 'RightEye'. These have been placed to mimic where the screens should be for the Oculus Rift --- but only when Rhino is in fullscreen mode, with the command 'Fullscreen'. The placement needs to be tweaked, but should work.
If you want to use your own model, you can load your own .3dm file in Rhino, then you can right-click on the viewport name, and go to Viewport Layout > Read from File. If you then load my test file, Rhino should open my two viewports, sized correctly, onto your model.
The placement of these viewports need to be tweaked; if you find a better viewport layout, upload an empty Rhino file with your viewports, and we can share eye-layout 'templates'!
5) In Grasshopper, open the .ghx definition. Everything that is multiple-grouped is a value that can be changed. Two things here:
- IPD: Set this and convert it to the proper units for your model.
- Left/right viewport names. In this case, leave this as-is, since you're using my example file.
6) Turn on the Grasshopper Timer, if it isn't on already.
7) In the GH definition, toggle 'SyncEyes' to be True. Then, in the left viewport, try orbiting around with the mouse. The 'RightEye' viewport should move around as well, pretty much simultaneously.
8) In OpenTrack, click 'Start', then toggle 'ReadUDP' to be True. You should see the 'OpenTrackInfo' panel fill with data that's constantly changing.
9) Move around the landscape with your camera, and when you set on a starting view that's ideal, click the triangle of the Data Dam component to 'store' the data.
10) Finally, toggle 'OculusMove' to be true. If all works correctly, both viewports should move based on the Rift's movement.
Let me know if you have any problems!
Cheers,
Dan…
Added by Dan Taeyoung at 11:47pm on December 10, 2013
radiance parameters to get rid of blotching. To add another level of complexity to my problem, I am running simulations with a translucent material with the following properties: void trans testTrans
0
0
7 0.478 0.478 0.478 0.000 0.010 0.178 0.635
I have had no issues with the renderings when I use clear glazing, as seen on this image:
However the blotching-issue becomes very noticeable when I introduce translucent glazing into the scene:
For the two above cases I used the following parameters:
_av_ is set to 0
xScale is set to 2
_ab_ is set to 6
_dc_ is set to 0.5
_aa_ is set to 0.2
_ad_ is set to 2048
_st_ is set to 0.5
yScale is set to 2
_ps_ is set to 4
_ar_ is set to 64
_as_ is set to 2048
_ds_ is set to 0.25
_pt_ is set to 0.1
_dr_ is set to 1
_pj_ is set to 0.9
_dp_ is set to 256
_dt_ is set to 0.25
_lr_ is set to 6
_dj_ is set to 0.5
_lw_ is set to 0.01
I ran another test with increased Radiance parameters and got the following output:
with the following parameters:
_av_ is set to 0
xScale is set to 6
_ab_ is set to 6
_dc_ is set to 0.75
_aa_ is set to 0.1
_ad_ is set to 4096
_st_ is set to 0.15
yScale is set to 6
_ps_ is set to 2
_ar_ is set to 128
_as_ is set to 4096
_ds_ is set to 0.05
_pt_ is set to 0.05
_dr_ is set to 3
_pj_ is set to 0.9
_dp_ is set to 512
_dt_ is set to 0.15
_lr_ is set to 8
_dj_ is set to 0.7
_lw_ is set to 0.005
Although the second blotching case is much better than the first, it is still very bad for hours when the sun is lower in the sky. The above images are rendered for a clear sky at 18:00 in Germany in a West-facing room.
Sorry for the long post! Can someone help? Kind regards, Örn
…
. 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
…
Karamba.
I am using your plug-in for normal forces evaluation in the transvere wires and spreaders of a sailboat. Mast is solved in another way, so I am not taking forces from Karamba in that case.
Basing on the forces value an adequate wire size (diameter) is choosen. Then masses of wires are being calculated. Loads (forces) on longitudinal wires are calculated without Karamba. The problem is when choosing transverse wires’ mass minimization as a criteria, the Octopus doesn’t get any results - is changing the sliders (genes) too fast for Karamba to calculate the forces (so Octopus gets only nulls):
When minimization of a e.g. longitudinal wires’ mass (calculated without Karamba) is taken as a criteria Octopus works fine.
Which suggests that the problem is in interaction of two plug-ins.
Any ideas how to avoid that problem?
Thanks,
M.
Below some screenshots of definition part with Karamba:
1675×807 200 K
image.png1680×789 398 KB
Despite the ‘orange warning’ the values are correct (double checked with other software).However I don't know why does it say that there is a part that can move freely without deformation,as the model looks like this:
image.png1239×343 55.5 KB
…
option, after downloading check if .ghuser files are blocked (right click -> "Properties" and select "Unblock"). Then paste them in File->Special Folders->User Object Folder. You can download the example files from here. They act in similar way, Ladybug Photovoltaics components do: we pick a surface, and get an answer to a question: "How much thermal energy, for a certain number of persons can my roof, building facade... generate if I would populate them with Solar Water Heating collectors"? This information can then be used to cover domestic hot water, space heating or space cooling loads:
Components enable setting specific details of the system, or using simplified ones. They cover analysis of domestic hot water load, final performance of the SWH system, its embodied energy, energy value, consumption, emissions... And finding optimal system and storage size. By Dr. Chengchu Yan and Djordje Spasic, with invaluable support of Dr. Willian Beckman, Dr. Jason M. Keith, Jeff Maguire, Nicolas DiOrio, Niraj Palsule, Sargon George Ishaya and Craig Christensen. Hope you will enjoy using the components! References: 1) Calculation of delivered energy: Solar Engineering of Thermal Processes, John Wiley and Sons, J. Duffie, W. Beckman, 4th ed., 2013. Technical Manual for the SAM Solar Water Heating Model, NREL, N. DiOrio, C. Christensen, J. Burch, A. Dobos, 2014. A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015
2) Domestic hot water load: Modeling patterns of hot water use in households, Ernest Orlando Lawrence Berkeley National Laboratory; Lutz, Liu, McMahon, Dunham, Shown, McGrue; Nov 1996. ASHRAE 2003 Applications Handbook (SI), Chapter 49, Service water heating
3) Mains water temperature Residential alternative calculation method reference manual, California energy commission, June 2013. Development of an Energy Savings Benchmark for All Residential End-Uses, NREL, August 2004. Solar water heating project analysis chapter, Minister of Natural Resources Canada, 2004.
4) Pipe diameters and pump power: Planning & Installing Solar Thermal Systems, Earthscan, 2nd edition
5) Sun postion and POA irradiance, the same as for Ladybug Photovoltaics (Michalsky (1988), diffuse irradiance by Perez (1990), ground reflected irradiance by Liu, Jordan (1963))
6) Optimal system and storage tank size: A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015.…
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
…
ne – power of the many è un corso advanced level che studia la produzione di effetti complessi a partire dalla modellazione di comportamenti semplici su un insieme strutturato con un numero alto di elementi. Attraverso un approccio generico e scaleless sarà possibile affrontare la tematica generale su più fronti e in una molteplicità di declinazioni possibili. Il corso è rivolto a chi,indipendentemente dal proprio background (urbanistica, architettura, ingegneria, design, arte o altro) già possiede una esperienza di base con Rhinoceros e Grasshopper, e desidera sviluppare aspetti di gestione avanzata del flusso di articolato di informazioni attraverso una strategia guidata basata su esempi pratici e sull’implementazione di un progetto personale sul tema generale del “field behaviour”. Sarà trattato anche l’utilizzo di alcuni plug-ins quali gHowl e WeaverBird. Il numero dei partecipanti è fissato a un massimo di 20 per offrire un tutoraggio proficuo ed una effettiva esperienza di learning ad ogni iscritto.
[.] Temi:
teoria
. complessità, emergence, effetti di campo (field behaviour), sensibilità, efficienza multiperformance
tecnica
. dati:gestione e manipolazione avanzata del data tree, streaming e visualizzazione; transizione, blending e modulazione delle geometrie; generazione e controllo multiperformance di popolazioni di componenti; attrattori, drivers e tecniche di modulazione avanzate; uso delle mesh con WeaverBird; ottimizzazione con Galapagos
[.] Dettagli :
Tutors: Alessio Erioli + Andrea Graziano – Co-de-iT
Si richiede esperienza di base nella modellazione in Rhino (equivalente a Rhino training Level 1, il Level 2 è gradito – la documentazione per il training è disponibile gratuitamente all’indirizzo: http://download.rhino3d.com/download.asp?id=Rhino4Training&language=it) e nell’uso di Grasshopper (la suddivisione di una superficie NURBS in componenti tramite isotrim è data come base assodata)
. luogo:
IreCoop – via Vasco De Gama 27 _ Firenze
. durata:
25-27 febbraio 2010 – 3 giornate consecutive _ orario 9:00 – 18:00
. costo:
professionisti – 450.00 € studenti – 280.00 €
. note:
scadenza iscrizioni: 20 febbraio 2010 il corso sarà attivato con un numero minimo di 15 iscritti al termine sarà rilasciato un attestato di frequenza gli iscritti dovrano venire muniti dei propri laptop con software installato. una versione free per 30 giorni è disponibile sul sito www.rhino3d.com
. contatti:
iscrizioni + info alloggi: www.irecooptoscana.it (Cosa offriamo > formazione > altri corsi)
info sul corso: info@co-de-it.com…