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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milar thing as Amaraa's (http://www.grasshopper3d.com/group/ladybug/forum/topics/finding-an-...), to explore an optimal pv array with the most AC energy production.
Have in mind, that Amaraa's topic dealt with PV system integrated into a facade. And as far as I understood you would like to put your PV modules on a roof. So it may be that some of my replies from that topic, may not apply to your roof PV system.
Also, Amaraa's topic did not deal with optimal PV system size (DC rating in kW). You would like to calculate that one as well?
I plan to set three parameters (orientation, tilt angle and distance of pv), and use Galapagos to make a best horizontal pv grid of most AC energy. So the most important is to avoid the dark core-shadows from shelf shading. If so, I wonder whether the gh document you uploaded in the discussion named "Finding an optimal size of PV panel in given array" will be helpful to me. And should I use the Sun Path component to calculate the self shading?
Ok, so you decided to go with the upper 2)a) solution?
Did I understand that correctly?Btw. sorry if you receive three emails for this reply. For some reason I had to delete it, and post it again. Grasshopper forum is working strange in the last couple of weeks.…
rs as soon as I introduce the glazing surfaces in the geometry and it is the following:
1. Solution exception:'hb_EPZoneSurface' object has no attribute 'coordinates'
I have been trying to solve it for a while and I have noted the following:
- I am using the approach of building the zones using the create HBSfrs component. However, nothing changes if I use the Honeybee masses2zone component (error remains);
- I am introducing the glass surfaces using geometries built in Rhino. However nothing changes if I use the HB component to automatically build the windows based on glass to wall ratio (error remains);
- This problem in the simulation has been introduced only once I have updated all the components to the latest versions of LB and HB. The geometry was working fine with the versions from Feb 2017. Also, I don't expect that curved geometries should cause problems as they have been used in simulations for quite a while now.
Finally, there is another problem in the simulation which relates to the HB context surfaces. Even if the simulation runs with the curved geometry, as soon as I add the roof as a shading element I am again not able to go further. The roof is composed also of curved surfaces and I could eventually simplify them but I am surprised that they are not 'digested' as they are quite simple and 'light' in the end.
I hope that I am missing something here and that the problem can be solved easily. It would be great to have your input!
Thanks a lot in advance and let me know if you have any questions on this!
Carmelo
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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.…
思った感じになりません。
balls の代わりにplanarカーブを直接入れてみましたがエラーが出ます。
ファンクションにしてみたところ、forループので作った数値が反映されていません。
ファンクションのインスタンス?を出力していないと思い上記のようにしましたがエラーが出てしまいます。
以上の事から自分の認識が正しいのかよくわからなくなりました・・・
python自体の深いところをわかっているわけではないので余計こんがらがりました。
そこで、for b in ballsはどのような条件または使い方であれば使えるのでしょうか?
そして、上記のように別のオブジェクトに対しての使い方はどのようにすればできるのでしょうか?
2:同じファンクション内のdist = rs.Distance(self.pos,b.pos)についてですが
この文章も for b in balls によってbはBallのインスタンスであると定義?されたためb.posがbの位置であると分かるのでしょうか?
pythonは定義しなくても動いてしまうのでどのような時に使えるのか文章見ただけではよくわかりません・・・
大変細かいことかもしれませんが、よりpythonをしっかりと理解するためにも、どなたかわかる方ご教授いただけると幸いです。…
tects to overcome the imposition of prefixed architectural forms in order to enhance performance-driven design and responsive kinetic solutions that interact with humans and environment. Lectures on parametric design simulation, generative and form finding as well as environmental optimization, analyzing and digital fabrication prototyping, are integrated together in 2 main modules. Students from the beginning of the school will be divided into groups to compete on a case project increasing their ability to define project parameters, design factors, solving problems, understanding factors relationships, involving environmental and human sensors, and optimizing their projects solutions in smart and inelegance way. In the beginning of the school, parametric modelling will be introduced (Rhino3d and Grasshopper) to build the necessary skills of parametric generative form methods to students. In this module will be dedicated to digital design methods and physical model making by various fabrication techniques, including laser cutting and 3D printing. Students will focus on the idea of creating algorithmic architectural form inspired by nature and their research will be supported by a series of lectures. Also they will be split into groups in order to develop projects assigned by the professors. This Module also adds Form Finding techniques to the parametric design strategies. Students will learn how material system behaviors, physical forces and responsive structure system can be digitally simulated into parametric models in order to explore complex forms that optimized and adapted to its natural behaviors, initial forces, material, particles, and structure systems. Series of lectures on form finding, natural structural algorithms, material behaviors, and physical forces will lead student to optimize their project forms. It is experimental laboratory in which kinetic interactive Architectural models are tested and designed. Students will develop novel solutions, building upon learning responsive kinetic systems. They will design Architectural responsive robotic systems inspired by nature. Projects will transform by adapting to environmental conditions and human behaviors happening at real and virtual levels.
…
nd linear/planar tectonics. Within this new field of investigation, the Stuttgart VS will be researching into novel techniques of material mixtures and grading, associative design and double curvature surface generation.
For the second cycle of this exploration we will be based at the Institute for Lightweight Structures and Conceptual Design (ILEK) at the University of Stuttgart. Drawing from the Institute’s long history of experimentation and research on tensile structures instigated by Frei Otto in the 1960s and conducted at present by Werner Sobek, this year we will be focusing on the design and fabrication of materially graded membranes, as well as the application of UHPC and FGC on fabric formworks. The workflow followed will be divided into two stages:
1. Computing Membranes: Computational form finding methods will be taught by professional engineers and architects from ILEK and str.ucture GmbH. The aim will be to utilise the latest software technologies to form find membranes for textile structures, or fabric formworks for complex concrete structures. The results will be evaluated against criteria such as internal air pressure, as well as asymmetric and wind loading. The outcome of this research will inform the material grading procedures (i.e. changing the stiffness, thickness or porosity of the membranes themselves, or the consistency of the concrete poured into the formworks) that will follow in stage two.
2. Fabricated Grading: The digitally computed membranes or formworks will eventually be fabricated physically, utilising the workshop and robotic fabrication facilities at ILEK. The objective will be to rethink conventional research on tensile and concrete structures as isotropic constructs, by customising attributes such as materiality, reinforcement, rigidity, translucency, patterning, and porosity among others. The final, graded prototypes will be made up of mixtures of materials, all accurately engineered to respond to variable environmental, structural and aesthetic criteria, in essence forming multi-material structures that have finally caught up with the latest material developments.
Prominent Features of the workshop/ skills developed:
Teaching team consisting of AA diploma tutors and ILEK and str.ucture GmbH engineers.
Access to the Institute of Lightweight Structures and Conceptual Design (ILEK), the Materials Testing Institute and Concrete Spraying Robotic facilities at the University of Stuttgart, as well as to the office of str.ucture GmbH Structural Design Engineering.
Computational skills tuition on Grasshopper, Rhino Membrane, and Karamba.
Lectures series by leading academics and practitioners in architecture and engineering.
Fabrication of functionally graded membrane and/or concrete structures.
Eligibility
The workshop is open to current architecture and design students, PhD candidates and young professionals. Software Requirements: Rhino (SR7 or later) and Grasshopper.
Fees
The AA Visiting School requires a student fee of £595 and a young professional fee of £895 per participant, which includes a £60 Visiting membership fee.
The deadline for applications is 10 July 2017.
For more information, please visit:
http://www.aaschool.ac.uk/STUDY/VISITING/stuttgart?name=stuttgart
For inquiries, please contact:
mixedmatters@aaschool.ac.uk…
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…