set.
The general idea being:
Create a collection of characters that enumerate your source collection. In this case the characters 0, 1 and 2 because you have 3 source words (cat, dog and tree).
Using the CharPool component you generate all possible permutations (39 in this case). These permutations start with {0}, {1}, {2}, {0,0}, {0,1}, {0,2}, {1,0}, ... and end in ..., {2,2,0}, {2,2,1},{2,2,2}
Create valid sets from these permutations, meaning any number which appears more than once will be removed. Ie. {0,1,0} becomes {0,1}, while {2,2,2} becomes {2}, while {2,0,1} remains {2,0,1}.
Sort all permutation groups. This will allow us to detect that {2,0,1}, {0,1,2} and {0,2,1} are all in fact the same thing.
Glue the individual characters in each set back into strings again, so {0;1} becomes "01" and {1,2} becomes "12".
Create a new set from all the glued together permutation groups. This once again removes duplicates.
We now have the answer we were looking for, just not in the form we can use. We need to peel apart the strings again into individual characters and then use those characters are indices into our collection of source words.
…
Added by David Rutten at 10:36am on December 13, 2016
EP output variables are to calculate outdoorAirEnergy?
Thank you very much!
Output variables on the Read EP Results component:[1] totalThermalEnergy=cooling+heating[2] thermalEnergyBalance=cooling (-)andheating (+)[3] cooling= Zone Ideal Loads Supply Air Total Cooling Energy [J](Hourly)=Zone Ideal Loads Supply Air Sensible Cooling Energy [J](Hourly)+ Zone Ideal Loads Supply Air Latent Cooling Energy [J](Hourly)[4] heating= Zone Ideal Loads Supply Air Total Heating Energy [J](Hourly)= Zone Ideal Loads Supply Air Sensible Heating Energy [J](Hourly) + Zone Ideal Loads Supply Air Latent Heating Energy [J](Hourly)[5] electricLight=Zone Lights Electric Energy [J](Hourly)[6] electricEquip=Electric Equipment Electric Energy [J](Hourly)[7] peopleGains=Zone People Total Heating Energy [J](Hourly)[8] totalSolarGain=Zone Windows Total Transmitted Solar Radiation Energy[9] infiltrationEnergy=Zone Infiltration Total Heat Gain Energy (+)andZone Infiltration Total Heat Loss Energy (-)[10] outdoorAirEnergy= ???[11] natVentEnergy=Zone Ventilation Total Heat Gain Energy (+)andZone Ventilation Total Heat Loss Energy (-)[12] operativeTemperature=Zone Operative Temperature[13] airTemperature=Zone Mean Air Temperature[14] meanRadTemperature=Zone Mean Radiant Temperature[15] relativeHumidity=Zone Air Relative Humidity[16] airFlowVolume=[infiltrationFlow] Zone Infiltration Standard Density Volume Flow Rate+[natVentFlow] Zone Ventilation Standard Density Volume Flow Rate+[mechSysAirFlow] Zone Mechanical Ventilation Standard Density Volume Flow Rate+[earthTubeFlow] Earth Tube Air Flow Volume[17] airHeatGainRate=[surfaceAirGain] Zone Air Heat Balance Surface Convection Rate+[systemAirGain] Zone Air Heat Balance System Air Transfer Rate
Output variables on the Read EP Surface Results component:[1] surfaceIndoorTemp= Surface Inside Face Temperature[2] surfaceOutdoorTemp=Surface Outside Face Temperature[3] surfaceEnergyFlow=[opaqueEnergyFlow] Surface Average Face Conduction Heat Transfer Energy+[glazEnergyFlow] Surface Window Heat Gain Energy[4] opaqueEnergyFlow =Surface Average Face Conduction Heat Transfer Energy[5] glazEnergyFlow= Surface Window Heat Gain Energy[6] windowTotalSolarEnergy=Surface Window Transmitted Solar Radiation Energy[7] windowBeamEnergy=Surface Window Transmitted Beam Solar Radiation Energy[8] windowDiffEnergy=Surface Window Transmitted Diffuse Solar Radiation Energy[9] windowTransmissivity=Surface Window System Solar Transmittance…
s para resolver problemas que hoy se presentan en el diseño y fabricación digital de formas complejas, que en conjunto, son las tendencias e instrucciones mas utilizadas por las oficinas de arquitectura del mundo.
Tomando como plataforma Rhinoceros de McNeel Associates, se optimiza el diseño y fabricación usando Grasshopper, RhinoNest y RhinoCAM.
Se realizará en Lima, Perú el 12 y 13 Setiembre, de 8:00 AM a 6:00 PM., con un total de 16 horas.
Cupo máximo: 20 alumnos.
Inversión. (no incluye impuestos)
S/.900.00 Incluye Licencia Rhino
S/.750.00 NO incluye Licencia Rhino
Ambas incluyen certificado de McNeel Miami.
Instructor:
Andres Gonzalez, CEO McNeel Miami, desarrollador desde 1980. www.rhino3d.com
Organización
McNeel Miami, Pablo C. Herrera,
Pedro Arteaga y MGP Nuevas Artes www.mgp-peru.com
Contacto en Lima, Perú
Claudia Aller / contacto@mgp-peru.com
Contacto en Miami, USA
Jackie Nasser / jackie@mcneel.com…
Ruby, [9] R, [10] PHP ,[11] MATLAB [12]
Maybe it can find it's way into GH somehow..
when using the default GH random number generator i mostly use much higher seed values.…
Added by Robert Vier at 10:08am on December 27, 2012
, 2013)
The most popular year was 2008 (5 responses)
Note: According to Wikipedia: "The first version of Grasshopper, called Explicit History at the time, was originally publicly released in September 2007." Interesting coincidence.
The response to question #2 by those that began before 2007 (How long did it take for you to feel comfortable with designing computationally?):
- Years
- Don't remember, but it felt like a natural way to relate to cad.
- After a few projects
- A month.
Compared to some of the responses of those that began since 2007:
- A month
- A few months
- After 6 weeks
- About 8 weeks
- Within my second design project with GH
- five to six months
- after 1 years of self learning + over 2 years of multiple projects and continuous self learning = Computation skill is comfortable but Computational Design can not be comfortable, Crazy learning curve.
There is much diversity, but some patterns begin to emerge.
Looking forward to more responses!…
NURBS using Rhinoceros. Content includes: Basic terminology, user interface, workflow strategies, using reference material and creating drawings from modeled geometry.
Workshop 2: Introduction to Parametric Design
Instructor: Rajaa Issa
(12:30 PM-3:30 PM)
This workshop will introduce the general framework of parametric thinking with a series of hands-on tutorials using Grasshopper for Rhinoceros. It is meant for beginners who have little to no idea about parametric modeling. The workshop will introduce the general components of an algorithm, design workflow, Grasshopper interface and visualization techniques. The students are expected to have basic knowledge of the Rhino modeling environment. Workshop 1 should fulfill this requirement.
Registration: Computers and software will be provided. Space is limited to 20 seats per workshop. The fee for each workshop is $60 (plus a $4.29 fee). There is a special rate of $30 (plus a $2.64 fee) for students and teachers provided they request a discount here with their school email address before registering. Register now……
e and i get it. If you have time check the attached papers we published a while ago in relation to the contribution of thermal mass in the reduction of temperature in residential buildings. See the nice contribution of the heavy TM or the lower one for light TM.
As for the solarHeatCapacity, your description (of the 50W) is derived on a 1 Facade/Floor ratio and fully glazed. The only way to reduce it is to increase the ratio (bigger facade area). Which is not recommended (energy losses), but this is a different issue. So, roughly, we can say that 50 is the lower value. If i have less glazing area this number will be higher (right?)
I want to define a value list of "architectural situations", so it is easy to explain and understand. One situation can be:
"Ratio facade/floor 1 & Fully glazed" = 50
"Ratio facade/floor 1 & Half glazed" = 75
"Ratio facade/floor 1.5 & Fully glazed" = 30
"Ratio facade/floor 1.5 & Half glazed" = 50
"Ratio facade/floor 0.75 & Fully glazed" = 70
"Ratio facade/floor 0.75 & Half glazed" = 90
Makes sense for you something like this?
I also defined a value list for the timeConstant like this:
Light Building (Mobile home) = 1Medium-light building (Cement tiles on floor) = 4Semi Heavy Building (Concrete floor + Tiles) = 8Heavy Building (Concrete floors/ceilings + Heavy external and internal walls) = 12
As for the first 5-10 cm effective TM in general my assumption is that you take half of the mass to your space and half to the space above/below you. Will be interesting to do a parametric study on just the thermal mass, uninsulated and insulated to see what the depth limits effectivity will be. Interested in doing such a study together? Can be a nice work even for publishing.
Thanks a lot ... again,
-A.…
ld work.
For example there's a grid shell and I've got a number of control points (for example 3) that can move up and down.
Depending on the control points I get forms that are structurally good and some that are bad.
In my office we've got a GH-Component, which leads the geometry in structural members and solves the structural forces and so on through an external Software called Sofistik and afterwards gives back to GH some Values, for example maximum bending moments. (Like Karamba)
Now I want to create this optimization component or something like that to minimize e.g. the bending moments in the given geometry.
Let's start with the work of the component.
So when I've three control points that can only move in z-direction.
P1(0,0,Z1), P2(10,0,Z2), P3(5,5,Z3)
They only depend on Z, so everything depends on Z1 to Z3 which have a range between 0 and 10 f.e.
First I want to get some (between 9 and 15) random Particles, one particle consists of this 3 different Z's.
So for example the first particle Part1 is [Z1=10, Z2=5, Z3=7]
and the second particle Part2 is [Z1=7, Z2=1, Z3=9]
and so on.
I created these Start Particles in a Cluster. See attached file.
I also tried this in C#, but thought it is easier in GH.
After I've got the Start Particles I want to give out the first particle and evaluate with its including Z's the target value in GH. Therefore I had to take the first branch and graft this branch (Discussion before)
Afterwards I want to save this Target Value that depends on the first starting Particle. Then I want to give out the second starting Particle to evaluate its target Value and store it. And so on till the last target Value of the last Starting Particle got assigned.
Then I want to assign the particles with its target values. E.g. part1: t=0.9, part2: t=1.8...
Then I want to define neighborhoods or the count of the expected local minima.
These neighborhoods can look like: Each neighborhood has to include not less than 3 particles. And the particles have to be next to each other.
E.g. if there are 12 particles and I want to have a look for 3 local minima, I need 3 or 4 neighborhoods. Then I would take 3 neighborhoods, because the more particles in one neighborhood, the better.
So the Count of the neighborhoods would be N=min{(Count of Part/3)& N_min}
How to define these neighborhoods I don't know at the moment. I think it has to be searched for the distance between the particles. E.g. part1 with (9,9,9) and part2 with (9,9,8) are next to each other but part 3 with(1,1,2) is far away.
Then each StartParticle is set to Partx_localbest.
And in each Neighbourhood the best of these localbeststs is Part_NyBest. (The best ist the one with the smallest target Value)
Loop:
Now I want to create new Particles. These Particles don't change their Z-values randomly. They change their Z-Values depending on Part_NxBest and Part_localBest. Therefore it has to be evaluated a new velocityfactor with v_Partx_new=0,792*v_PartxOld+1,5*random(0,1)*(partx_localbest-partx)+1,5*random(0,1)*(part_NyBest-partx)
The new particles will then be partx_new=partx+v_Partx_new.
The new Particle partx_new will be set to partx and then set in the output.
then there has to be caught the targetValue of part1 afterwards part2 can be put out and its target value caught and so on.
Then it has to be looked for the Partx_localbest through comparing the partx_localbest and its target value with the new part_x and its target value. If the target value of the new partx is smaller than partx_localbest,
then partx_localbest is the new partx.
This has to be done for each partx. Afterwards the same for neighborhoods best (best of all partx_localbest in one neighborhood)
Endloop if velocity gets small.
Output all part_NxBest
Output all targetvalues of the part_NxBests.
So in the Input there have to be:
StartParticles if they are given through the cluster attached.
Device on the target Value like in the attached gh.file from David Rutten I found in the discussions
Count of neighborhoods
And in the output
Output particle for evaluation
Output all part_NxBest
Output all targetvalues of the part_NxBests
Hope didn’t forget anything. And hope it isn’t crushed to badly. Sorry for my bad English by the way ;-)
For more explanation, how the PSO works in other programs. There’s attached a workflow script (is it called like that?) I think for GH it should be a little bit changed like I tried in my explanations.
So if you can help me a in some parts or you have any advices would be great, otherwise thank you nevertheless!!!!
Thankfully there’s no limit for the words in the discussions :-D
Best, Heiko
…
isms. Through simple mechanisms embedded within the material logic of natural systems, specific stimuli can activate a particular response. This response occurs in carnivorous plants such as the Venus fly-trap, which uses turgor pressure to trap small insects in order to feed, and worms, which by contracting differently oriented muscles, achieve movement. This ten-day intensive workshop, co-taught by the faculty of the Emergent Technologies and Design Programme at the AA and the faculty of Architecture and MEDIAlab at California College of the Arts, will explore active systems in nature, investigating biomimetic principles in order to analyze, design and fabricate prototypes that respond to electronic and environmental stimuli. Students will work in teams to research specific biological systems, extracting logics of organization, geometry, structure and mathematics. Advanced analysis, simulation, modeling and fabrication tools will be introduced in order to apply this information to the design of both passive and active responsive architectural systems. Investigation and application of robotics, sensors and actuators will be employed for the activation of the material system investigation through the construction of working responsive prototypes.
+ CONTENT TAGS: Biodynamic, Parametric, Scripted, Mimetic, Responsive, Interactive, Digitally Fabricated
+ SOFTWARE: Rhino, Grasshopper, Firefly, RhinoScript, Arduino, Processing
CORE FACULTY
Michael Weinstock (Academic Head, Director of Emergent Technologies Programme, AA London UK)
Christina Doumpioti, Evan Greenberg, Konstantinos Karatzas (Tutors, AA EmTech Programme, London UK)
Jason Kelly Johnson [Future Cities Lab], Andrew Kudless [Matsys] (CCA MediaLab Coordinators, SF CA)
ASSOCIATED FACULTY
George Jeronimidis (Director of Center for Biomimetics, University of Reading UK); Andrew Payne (LIFT Architects, Grasshopper Primer); Daniel Segraves (ASGG Adrian Smith + Gordon Gill Architecture); Ronnie Parsons + Gil Akos (Studio Mode, NY); Daniel Piker (Kangaroo Project Live Physics)
ENROLLMENT INFORMATION
http://sanfrancisco.aaschool.ac.uk; or visit the CCA MEDIAlab website: http://mlab.cca.edu
(Workshops are non-credit. Enrollment is processed by the AA. Workshop will run the full 10 days.)
CONTACT
visitingschool@aaschool.ac.uk or mlab@cca.edu
DOWNLOADS
Application Form…
, 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.…