a problem with SSL. Any Ideas? I am using the following code:
import json,httplib connection = httplib.HTTPSConnection('api.parse.com', 443) connection.connect() connection.request('GET', '/1/classes/MY-CLASS', '', { "X-Parse-Application-Id": "MY-APP-ID", "X-Parse-REST-API-Key": "MY-REST-API-KEY" }) result = json.loads(connection.getresponse().read()) print result
I Get the Following Messages:
Runtime error (IOException): Authentication failed because the remote party has closed the transport stream. Traceback: line 280, in do_handshake, "C:\Program Files\Rhinoceros 5.0 (64-bit)\Plug-ins\IronPython\Lib\ssl.py" line 120, in __init__, "C:\Program Files\Rhinoceros 5.0 (64-bit)\Plug-ins\IronPython\Lib\ssl.py" line 336, in wrap_socket, "C:\Program Files\Rhinoceros 5.0 (64-bit)\Plug-ins\IronPython\Lib\ssl.py" line 1156, in connect, "C:\Program Files\Rhinoceros 5.0 (64-bit)\Plug-ins\IronPython\Lib\httplib.py" line 3, in script Any help would be greatly appreciated! Thanks in advance! -Zach…
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
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ion of both Ladybug and Honeybee. Notable among the new components are 51 new Honeybee components for setting up and running energy simulations and 15 new Ladybug components for running detailed comfort analyses. We are also happy to announce the start of comprehensive tutorial series on how to use the components and the first one on getting started with Ladybug can be found here:
https://www.youtube.com/playlist?list=PLruLh1AdY-Sj_XGz3kzHUoWmpWDXNep1O
A second one on how to use the new Ladybug comfort components can be found here:
https://www.youtube.com/playlist?list=PLruLh1AdY-Sho45_D4BV1HKcIz7oVmZ8v
Here is a short list highlighting some of the capabilities of this current Honeybee release:
1) Run EnergyPlus and OpenStudio Simulations - A couple of components to export your HBZones into IDF or OSM files and run energy simulations right from the grasshopper window! Also included are several components for adjusting the parameters of the simulations and requesting a wide range of possible outputs.
2) Assign EnergyPlus Constructions - A set of components that allow you to assign constructions from the OpenStudio library to your Honeybee objects. This also includes components for searching through the OpenStudio construction/material library and components to create your own constructions and materials.
3) Assign EnergyPlus Schedules and Loads - A set of components for assigning schedules and Loads from the Openstudio library to your Honeybee zones. This includes the ability to auto-assign these based on your program or to tweak individual values. You can even create your own schedules from a stream of 8760 values with the new “Create CSV Schedule” component. Lastly, there is a component for converting any E+ schedule to 8760 values, which you can then visualize with the standard Ladybug components
4) Assign HVAC Systems - A set of components for assigning some basic ASHRAE HVAC systems that can be run with the Export to OpenStudio component. You can even adjust the parameters of these systems right in Grasshopper.
Note: The ASHRAE systems are only available for OpenStudio and can’t be used with Honeybee’s EnergyPlus component. Also, only ideal air, VAV and PTHP systems are currently available but more will be on their way soon!
5) Import And Visualize EnergyPlus Results - A set of components to import numerical EnergyPlus simulation results back into grasshopper such that they can be visualized with any of the standard Ladybug components (ie. the 3D chart or Psychrometric chart). Importers are made for zone-level results as well as surface results and surfaces results can be easily separated based on surface type. This also means that E+ results can be analyzed with the new Ladybug comfort calculator components and used in shade or natural ventilation studies. Lastly, there are a set of components for coloring zone/surface geometry with EnergyPlus results and for coloring the shades around zones with shade desirability.
6) Increased Radiance and Daysim Capabilities - Several updates have also been made to the existing Radiance and Daysim components including parallel Radiance Image-based analysis.
7) Visualize HBObject Attributes - A few components have been added to assist with setting up honeybee objects and ensuing the the correct properties have been assigned. These include components to separate surfaces based on boundary condition and components to label surfaces and zones with virtually any of their EnergyPlus or Radiance attributes.
8) WIP Grizzly Bear gbxml Exporter - Lastly, the release includes an WIP version of the Grizzly Bear gbXML exporter, which will continue to be developed over the next few months.
And here’s a list of the new Ladybug capabilities:
1) Comfort Models - Three comfort models that have been translated to python for your use in GH: PMV, Adaptive, and Outdoor (UTCI). Each of these models has a “Comfort Calculator” component for which you can input parameters like temperature and wind speed to get out comfort metrics. These can be used in conjunction with EPW data or EnergyPlus results to calculate comfort for every hour of the year.
2) Ladybug Psychrometric Chart - A new interactive psychrometric chart that was made possible thanks to the releasing of the Berkely Center for the Built Environment Comfort Tool Code (https://github.com/CenterForTheBuiltEnvironment/comfort-tool). The new psychrometric chart allows you to move the comfort polygon around based on PMV comfort metrics, plot EPW or EnergyPlus results on the psych chart, and see how many hours are made comfortable in each case. The component also allows you to plot polygons representing passive building strategies (like internal heat gain or evaporative cooling), which will adjust dynamically with the comfort polygon and are based on the strategies included in Climate Consultant.
3) Solar Adjusted MRT and Outdoor Shade Evaluator - A component has been added to allow you to account for shortwave solar radiation in comfort studies by adjusting Mean Radiant Temperature. This adjusted MRT can then be factored into outdoor comfort studies and used with an new Ladybug Comfort Shade Benefit Evaluator to design outdoor shades and awnings.
4) Wind Speed - Two new components for visualizing wind profile curves and calculating wind speed at particular heights. These allow users to translate EPW wind speed from the meteorological station to the terrain type and height above ground for their site. They will also help inform the CFD simulations that will be coming in later releases.
5) Sky Color Visualizer - A component has been added that allows you to visualize a clear sky for any hour of the year in order to get a sense of the sky qualities and understand light conditions in periods before or after sunset.
Ready to Start?
Here is what you will need to do:
Download Honeybee and Ladybug from the same link here. Make sure that you remove any old version of Ladybug and Honeybee if you have one, as mentioned on the Ladybug group page.
You will also need to install RADIANCE, DAYSIM and ENERGYPLUS on your system. We already sent a video about how to get RADIANCE and Daysim installed (link). You can download EnergyPlus 8.1 for Windows from the DOE website (http://apps1.eere.energy.gov/buildings/energyplus/?utm_source=EnergyPlus&utm_medium=redirect&utm_campaign=EnergyPlus%2Bredirect%2B1).
“EnergyPlus is a whole building energy simulation program that engineers, architects, and researchers use to model energy and water use in buildings.”
“OpenStudio is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.”
Make sure that you install ENERGYPLUS in a folder with no spaces in the file path (e.g. “C:\Program Files” has a space between “Program” and “Files”). A good option for each is C:\EnergyPlusV8-1-0, which is usually the default locations when you run the downloaded installer.
New Example Files!
We have put together a large number of new updated example files and you should use these to get yourself started. You can download them from the link on the group page.
New Developers:
Since the last release, we have had several new members join the Ladybug + Honeybee developer team:
Chien Si Harriman - Chien Si has contributed a large amount of code and new components in the OpenStudio workflow including components to add ASHRAE HVAC systems into your energy models and adjust their parameters. He is also the author of the Grizzly Bear gbxml exporter and will be continuing work on this in the following months.
Trygve Wastvedt - Trygve has contributed a core set of functions that were used to make the new Ladybug Colored Sky Visualizer and have also helped sync the Ladybug Sunpath to give sun positions for the current year of 2014
Abraham Yezioro - Abraham has contributed an awesome new bioclimatic chart for comfort analyses, which, despite its presence in the WIP tab, is nearly complete!
Djordje Spasic - Djordje has contributed a number of core functions that were used to make the new Ladybug Wind Speed Calculator and Wind Profile Visualizer components and will be assisting with workflows to process CFD results in the future. He also has some more outdoor comfort metrics in the works.
Andrew Heumann - Andrew contributed an endlessly useful list item selector, which can adjust based on the input list, and has multiple applications throughout Ladybug and Honeybee. One of the best is for selecting zone-level programs after selecting an overall building program.
Alex Jacobson - Alex also assisted with the coding of the wind speed components.
And, as always, a special thanks goes to all of our awesome users who tested the new components through their several iterations. Special thanks goes to Daniel, Michal, Francisco, and Agus for their continuous support. Thanks again for all the support, great suggestions and comments. We really cannot thank you enough.
Enjoy!,
Ladybug + Honeybee Development Team
PS: If you want to be updated about the news about Ladybug and Honeybee like Ladybug’s Facebook page (https://www.facebook.com/LadyBugforGrasshopper) or follow ladybug’s twitter account (@ladybug_tool).
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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.
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peuvent se diviser une surface avec ne importe quel motif imaginable. 3. Ici, je fournir un moyen de le faire via Lunchbox ... cela fonctionne mais il est fixe et donc nous avons besoin de jouer avec des arbres de données afin de créer le motif approprié par cas. 4. L'autre composante est un joint C # qui fait beaucoup de choses autres que de diviser ne importe quelle collection de points avec de nombreux modèles (voir le modèle ANDRE que je ai fait pour vous). 5. Vous devez décomposer une polysurface en morceaux afin de travailler sur les subdivisions. 6. Je donne une autre définition ainsi que pourrait agir comme un tutoriel sur la façon de traiter des ensembles de points via des composants de GH standards et des méthodes classiques.
Avertissez si tous ceux-ci apparaissent floue pour vous: Si oui, je pourrais écrire une définition utilisant des composants de GH classiques - mais vous perdrez les variations de motifs de division.
mieux, Peter
…
ers can be applied from the right click Context Menu of either a component's input or output parameters. With the exception of <Principal> and <Degrees> they work exactly like their corresponding Grasshopper Component. When a I/O Modifier is applied to a parameter a visual Tag (icon) is displayed. If you hover over a Tag a tool tip will be displayed showing what it is and what it does.
The full list of these Tags:
1) Principal
An input with the Principal Icon is designated the principal input of a component for the purposes of path assignment.
For example:
2) Reverse
The Reverse I/O Modifier will reverse the order of a list (or lists in a multiple path structure)
3) Flatten
The Flatten I/O Modifier will reduce a multi-path tree down to a single list on the {0} path
4) Graft
The Graft I/O Modifier will create a new branch for each individual item in a list (or lists)
5) Simplify
The Simplify I/O Modifier will remove the overlap shared amongst all branches. [Note that a single branch does not share any overlap with anything else.]
6) Degrees
The Degrees Input Modifier indicates that the numbers received are actually measured in Degrees rather than Radians. Think of it more like a preference setting for each angle input on a Grasshopper Component that state you prefer to work in Degrees. There is no Output option as this is only available on Angle Inputs.
7) Expression
The Expression I/O Modifier allows you change the input value by evaluating an expression such as -x/2 which will have the input and make it negative. If you hover over the Tag a tool tip will be displayed with the expression. Since the release of GH version 0.9.0068 all I/O Expression Modifiers use "x" instead of the nickname of the parameter.
8) Reparameterize
The Reparameterize I/O Modifier will only work on lines, curves and surfaces forcing the domains of all geometry to the [0.0 to 1.0] range.
9) Invert
The Invert Input Modifier works in a similar way to a Not Gate in Boolean Logic negating the input. A good example of when to use this is on [Cull Pattern] where you wish to invert the logic to get the opposite results. There is no Output option as this is only available on Boolean Inputs.
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n be obtained for curved NURBS surfaces as well as unconventional window configurations".
And I also noticed the following information form the optional input in the runEnergySimulation component.
"meshSettings_: Optional mesh settings for your geometry from any one of the native Grasshopper mesh setting components. These will be used to change the meshing of curved surfaces before they are run through EnergyPlus (note that meshing of curved surfaces is done since Energyplus is not able to calculate heat flow through non-planar surfaces). Default Grasshopper meshing is used if nothing is input here but you may want to decrease your calculation time by changing it to Coarse or increase your curvature definition (and calculation time) by making it finer".
1) My case is an one-story, rectangular-plan large hall (40m*70m*25m) with a curved roof. The roof surface is a part of a standard sphere and the walls and floor are all planar (the each wall has one curved edge as showed in the image).
For testing, I threw the original curved roof surface into daylight and energy simulations without making customized meshings, because I assumed that it might be automatically converted to meshs by Honeybee - Am I right? As showed in the image, how can I reduce the number of meshs in a proper way? Must two connected surfaces (i.e. wall and roof) be STRICTLY/SEAMLESSLY connected or not (considering different divisions of meshs in the respective surface)? - Is a connection tolerance allowed?
2) But, when I run the annual daylight simulation for this case, it gave me a lot of warnings "oconv: warning - zero area for polygon".- is that normal? and how to avoid this? Does the daylight simulation allow "curved NURBS surfaces"?
3) Moreover, when I run an energy simulation for this case, it costed extremely long time. It was just so long that I did not even have results out of one simulation. - I guessed it might be the problem caused by the curved roof surface (or automatic meshing?), but I don't have experience of converting a curved NURBS/spheral surface into correct meshs that can be recognized by Honeybee simulations (Daylight and Energy) in a proper way.
4) The large window on the wall was generated by the "_glzRatio". But the automatically generated wall meshs around this window are just too "fine", which might largely increase simulation time. Is there a proper way to get rid of it? (Considering that the size, shape and position of the window will have large influence on the daylight distribution in the building, it is worthy to keep the size, shape and position of the window as it should be in reality).
In sum, considering all above, could your please provide me some suggestions/tutorials/links that might be helpful for dealing with "curved NURBS surfaces" in Honeybee simulations.
Thank you all in advance!
Best,
Ding
…
ing the maps to the broader community.
At the moment, there are just a few known issues left that I have to fix for complex geometric cases but they should run smoothly for most energy models that you generate with Honeybee. Within the next month, I will be clearing up these last issues and, by the end of the month, there will be an updated youtube tutorial playlist on the comfort tools and how to use them.
In the meantime, there's an updated example file (http://hydrashare.github.io/hydra/viewer?owner=chriswmackey&fork=hydra_2&id=Indoor_Microclimate_Map) and I wanted to get you all excited with some images and animations coming out of the design part of my thesis. I also wanted to post some documentation of all of the previous research that has made these climate maps possible and give out some much deserved thanks. To begin, this image gives you a sense of how the thermal maps are made by integrating several streams of data for EnergyPlus:
(https://drive.google.com/file/d/0Bz2PwDvkjovJaTMtWDRHMExvLUk/view?usp=sharing)
To get you excited, this youtube playlist has a whole bunch of time-lapse thermal animations that a lot of you should enjoy:
https://www.youtube.com/playlist?list=PLruLh1AdY-Sj3ehUTSfKa1IHPSiuJU52A
To give a brief summary of what you are looking at in the playlist, there are two proposed designs for completely passive co-habitation spaces in New York and Los Angeles.
These diagrams explain the Los Angeles design:
(https://drive.google.com/file/d/0Bz2PwDvkjovJM0JkM0tLZ1kxUmc/view?usp=sharing)
And this video gives you and idea of how it thermally performs:
These diagrams explain the New York design:
(https://drive.google.com/file/d/0Bz2PwDvkjovJS1BZVVZiTWF4MXM/view?usp=sharing)
And this video shows you the thermal performance:
Now to credit all of the awesome people that have made the creation of these thermal maps possible:
1) As any HB user knows, the open source engines and libraries under the hood of HB are EnergyPlus and OpenStudio and the incredible thermal richness of these maps would not have been possible without these DoE teams creating such a robust modeler so a big credit is definitely due to them.
2) Many of the initial ideas for these thermal maps come from an MIT Masters thesis that was completed a few years ago by Amanda Webb called "cMap". Even though these cMaps were only taking into account surface temperature from E+, it was the viewing of her radiant temperature maps that initially touched-off the series of events that led to my thesis so a great credit is due to her. You can find her thesis here (http://dspace.mit.edu/handle/1721.1/72870).
3) Since the thesis of A. Webb, there were two key developments that made the high resolution of the current maps believable as a good approximation of the actual thermal environment of a building. The first is a PhD thesis by Alejandra Menchaca (also conducted here at MIT) that developed a computationally fast way of estimating sub-zone air temperature stratification. The method, which works simply by weighing the heat gain in a room against the incoming airflow was validated by many CFD simulations over the course of Alejandra's thesis. You can find here final thesis document here (http://dspace.mit.edu/handle/1721.1/74907).
4) The other main development since the A. Webb thesis that made the radiant map much more accurate is a fast means of estimating the radiant temperature increase felt by an occupant sitting in the sun. This method was developed by some awesome scientists at the UC Berkeley Center for the Built Environment (CBE) Including Tyler Hoyt, who has been particularly helpful to me by supporting the CBE's Github page. The original paper on this fast means of estimating the solar temperature delta can be found here (http://escholarship.org/uc/item/89m1h2dg) although they should have an official publication in a journal soon.
5) The ASHRAE comfort models under the hood of LB+HB all are derived from the javascript of the CBE comfort tool (http://smap.cbe.berkeley.edu/comforttool). A huge chunk of credit definitely goes to this group and I encourage any other researchers who are getting deep into comfort to check the code resources on their github page (https://github.com/CenterForTheBuiltEnvironment/comfort_tool).
6) And, last but not least, a huge share of credit is due to Mostapha and all members of the LB+HB community. It is because of resources and help that Mostapha initially gave me that I learned how to code in the first place and the knowledge of a community that would use the things that I developed was, by fa,r the biggest motivation throughout this thesis and all of my LB efforts.
Thank you all and stay awesome,
-Chris…