HB.
The paper depicts a framework for optimizing passive performance by exploring elements such as geometry, building orientation, fenestration configurations, and shading devices in response to particular program requirements, site-specific constraints, and climate conditions.
ASHRAE 90.1 was used as compliant reference model for four different climate zones, incorporating real sites and urban overshadowing conditions. The results showed improvements within a range of 4% to 17% in Energy Use Intensity reduction, while improving daylighting within a range of 27% to 65%, depending on the location and climate.
Overall, the framework provide guidance to make more informed decisions in early-stages of design, where as many know, the impacts can be the greatest.
If interested, please visit one of the following links:
Elsevier Publication. Free download option until February 24
Pre-print
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t file** - ply file with just x,y,z locations. I got it from a 3d scanner. Here is how first few lines of file looks like - ply format ascii 1.0 comment VCGLIB generated element vertex 6183 property float x property float y property float z end_header -32.3271 -43.9859 11.5124 -32.0631 -43.983 11.4945 12.9266 -44.4913 28.2031 13.1701 -44.4918 28.2568 13.4138 -44.4892 28.2531 13.6581 -44.4834 28.1941 13.9012 -44.4851 28.2684 ... ... ... In case you need the data - please email me on **nisha.m234@gmail.com**. **Algorithm:** I am trying to find principal curvatures for extracting the ridges and valleys. The steps I am following is: 1. Take a point x 2. Find its k nearest neighbors. I used k from 3 to 20. 3. average the k nearest neighbors => gives (_x, _y, _z) 4. compute covariance matrix 5. Now I take eigen values and eigen vectors of this covariance matrix 6. I get u, v and n here from eigen vectors. u is a vector corresponding to largest eigen value v corresponding to 2nd largest n is 3rd smallest vector corresponding to smallest eigen value 7. Then for transforming the point(x,y,z) I compute matrix T T = [ui ] [u ] [x - _x] [vi ] = [v ] x [y - _y] [ni ] [n ] [z - _z] 8. for each i of the k nearest neighbors:<br> [ n1 ] [u1*u1 u1*v1 v1*v1] [ a ]<br> [ n2 ] = [u2*u2 u2*v2 v2*v2] [ b ] <br> [... ] [ ... ... ... ] [ c ] <br> [ nk ] [uk*uk uk*vk vk*vk]<br> Solve this for a, b and c with least squares 9. this equations will give me a,b,c 10. now I compute eigen values of matrix [a b b a ] 11. This will give me 2 eigen values. one is Kmin and another Kmax. **My Problem:** The output is no where close to finding the correct Ridges and Valleys. I am totally Stuck and frustrated. I am not sure where exactly I am getting it wrong. I think the normal's are not computed correctly. But I am not sure. I am very new to graphics programming and so this maths, normals, shaders go way above my head. Any help will be appreciated. **PLEASE PLEASE HELP!!** **Resources:** I am using Visual Studio 2010 + Eigen Library + ANN Library. **Other Options used** I tried using MeshLab. I used ball pivoting triangles remeshing in MeshLab and then applied the polkadot3d shader. If correctly identifies the ridges and valleys. But I am not able to code it. **My Function:** //the function outputs to ply file void getEigen() { int nPts; // actual number of data points ANNpointArray dataPts; // data points ANNpoint queryPt; // query point ANNidxArray nnIdx;// near neighbor indices ANNdistArray dists; // near neighbor distances ANNkd_tree* kdTree; // search structure //for k = 25 and esp = 2, seems to got few ridges queryPt = annAllocPt(dim); // allocate query point dataPts = annAllocPts(maxPts, dim); // allocate data points nnIdx = new ANNidx[k]; // allocate near neigh indices dists = new ANNdist[k]; // allocate near neighbor dists nPts = 0; // read data points ifstream dataStream; dataStream.open(inputFile, ios::in);// open data file dataIn = &dataStream; ifstream queryStream; queryStream.open("input/query.
pts", ios::in);// open data file queryIn = &queryStream; while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) nPts++; kdTree = new ANNkd_tree( // build search structure dataPts, // the data points nPts, // number of points dim); // dimension of space while (readPt(*queryIn, queryPt)) // read query points { kdTree->annkSearch( // search queryPt, // query point k, // number of near neighbors nnIdx, // nearest neighbors (returned) dists, // distance (returned) eps); // error bound double x = queryPt[0]; double y = queryPt[1]; double z = queryPt[2]; double _x = 0.0; double _y = 0.0; double _z = 0.0; #pragma region Compute covariance matrix for (int i = 0; i < k; i++) { _x += dataPts[nnIdx[i]][0]; _y += dataPts[nnIdx[i]][1]; _z += dataPts[nnIdx[i]][2]; } _x = _x/k; _y = _y/k; _z = _z/k; double A[3][3] = {0,0,0,0,0,0,0,0,0}; for (int i = 0; i < k; i++) { double X = dataPts[nnIdx[i]][0]; double Y = dataPts[nnIdx[i]][1]; double Z = dataPts[nnIdx[i]][2]; A[0][0] += (X-_x) * (X-_x); A[0][1] += (X-_x) * (Y-_y); A[0][2] += (X-_x) * (Z-_z); A[1][0] += (Y-_y) * (X-_x); A[1][1] += (Y-_y) * (Y-_y); A[1][2] += (Y-_y) * (Z-_z); A[2][0] += (Z-_z) * (X-_x); A[2][1] += (Z-_z) * (Y-_y); A[2][2] += (Z-_z) * (Z-_z); } MatrixXd C(3,3); C <<A[0][0]/k, A[0][1]/k, A[0][2]/k, A[1][0]/k, A[1][1]/k, A[1][2]/k, A[2][0]/k, A[2][1]/k, A[2][2]/k; #pragma endregion EigenSolver<MatrixXd> es(C); MatrixXd Eval = es.eigenvalues().real().asDiagonal(); MatrixXd Evec = es.eigenvectors().real(); MatrixXd u,v,n; double a = Eval.row(0).col(0).value(); double b = Eval.row(1).col(1).value(); double c = Eval.row(2).col(2).value(); #pragma region SET U V N if(a>b && a>c) { u = Evec.row(0); if(b>c) { v = Eval.row(1); n = Eval.row(2);} else { v = Eval.row(2); n = Eval.row(1);} } else if(b>a && b>c) { u = Evec.row(1); if(a>c) { v = Eval.row(0); n = Eval.row(2);} else { v = Eval.row(2); n = Eval.row(0);} } else { u = Eval.row(2); if(a>b) { v = Eval.row(0); n = Eval.row(1);} else { v = Eval.row(1); n = Eval.row(0);} } #pragma endregion MatrixXd O(3,3); O <<u, v, n; MatrixXd UV(k,3); VectorXd N(k,1); for( int i=0; i<k; i++) { double x = dataPts[nnIdx[i]][0];; double y = dataPts[nnIdx[i]][1];; double z = dataPts[nnIdx[i]][2];; MatrixXd X(3,1); X << x-_x, y-_y, z-_z; MatrixXd T = O * X; double ui = T.row(0).col(0).value(); double vi = T.row(1).col(0).value(); double ni = T.row(2).col(0).value(); UV.row(i) << ui * ui, ui * vi, vi * vi; N.row(i) << ni; } Vector3d S = UV.colPivHouseholderQr().solve(N); MatrixXd II(2,2); II << S.row(0).value(), S.row(1).value(), S.row(1).value(), S.row(2).value(); EigenSolver<MatrixXd> es2(II); MatrixXd Eval2 = es2.eigenvalues().real().asDiagonal(); MatrixXd Evec2 = es2.eigenvectors().real(); double kmin, kmax; if(Eval2.row(0).col(0).value() < Eval2.row(1).col(1).value()) { kmin = Eval2.row(0).col(0).value(); kmax = Eval2.row(1).col(1).value(); } else { kmax = Eval2.row(0).col(0).value(); kmin = Eval2.row(1).col(1).value(); } double thresh = 0.0020078; if (kmin < thresh && kmax > thresh ) cout << x << " " << y << " " << z << " " << 255 << " " << 0 << " " << 0 << endl; else cout << x << " " << y << " " << z << " " << 255 << " " << 255 << " " << 255 << endl; } delete [] nnIdx; delete [] dists; delete kdTree; annClose(); } Thanks, NISHA…
nd improvements. Many of the new features and components announced in the last release have become stable and have emerged from their WIP section. Additionally, after two years of work, we are happy to announce that we finally have full support of an OpenStudio connection within Honeybee, which has ushered in a whole host of new features, notably the modelling of detailed HVAC systems. As always you can download the new release from Food4Rhino. Make sure to remove the older version of Ladybug and Honeybee and update your scripts.
LADYBUG
1 - Solar Hot Water Components Out of WIP
After much beta-testing, bug-fixing, and general development, all of the Photovoltaic and Solar Hot Water components are now fully out of WIP! The main component is based on a Chengchu Yan's publication. Components have been added to Ladybug thanks to the efforts of Chengchu Yan and Djordje Spasic.. See Djorje’s original release post of the solar hot water components for more information on the components that just made it out of WIP.
2 - New Terrain Shading Mask Released in WIP
In addition to Djordje’s prolific addition of renewable energy components, he has also contributed a widely-useful component to generate terrain shading masks, which account for the shading of surrounding mountains/terrain in simulations. While initially added to assist the solar radiation radiation and renewable energy components, the component will undergo development to optimize it for energy and daylight simulations over the next few months. Another new component called Horizon Angles can be used to visualize and export horizon angles. You can test them out now by accessing them in the WIP section. For more information, see Djordje’s release post on the GH forum here.
3 - New Mesh Selector Component
After realizing that the Optimal Shade Creator component has applications to a whole range of analyses, it has now been re-branded as the Mesh Selector and has been optimized to work easily with these many analyses. Specifically, the component selects out the portion of a mesh that meets a given threshold. This can be the portion of a shade benefit analysis meeting a certain level of shade desirability, the portion of a radiation study meeting a certain level of fulx, the portion of a daylight analysis meeting a certain lux threshold, and much more!
4 - Solar Adjusted Temperature Now Includes Long Wave Radiation
Thanks to a question asked by Aymeric and a number of clarifications made by Djordje Spasic, the Solar Adjusted Temperature component now includes the ability to account for long-wave radiative loss to the sky in addition to it original capability to account for short wave radiation from the sun. As such, the component now includes all capabilities of similar outdoor comfort tools such as RayMan. The addition of this capability is also paralleled by the addition of a new horizontalInfraredRadiation output on the ImportEPW component. See the updated solar adjusted example file hereto see how to use the component properly.
5 - Support for both Log and Power Law Wind Profiles
In preparation for the future release of the Butterfly CFD-modelling insect, the Ladybug Wind Profile component now includes the option of either power law or log law wind profiles, which are both used extensively in CFD studies. Thanks goes to Theodoros Galanos for providing the formulas!
6 - New Radiant Asymmetry Comfort Components
Prompted by a suggestion from Christian Kongsgaard, Ladybug now includes components to calculate radiant asymmetry discomfort! For examples of how to use the components see this example file for spatial analysis of radiant asymmetry discomfort and this example for temporal analysis.
7 - Pedestrian Wind Comfort Component Released in WIP
In preparation for the impending release of the butterfly CFD-modelling insect, Djordje Spasic with assistance from Liam Harrington has contributed a component to evaluate outdoor discomfort and pedestrian safety. The component identifies if certain areas around the building are suitable for sitting, building entrances-exits, window shopping... based on its wind microclimate. Dangerous areas due to high wind speeds are also identified.You can check it out now in the WIP section.
HONEYBEE
1 - New HVAC Systems and Full OpenStudio Support
After a significant amount of development on the part of the OpenStudio team and two years of effort on the part of LB+HB developers, we (finally!) have full support for an OpenStudio connection within Honeybee. By this, we mean that any energy simulation property that can be assigned to a HBZone will be taken into account in the simulation run by the OpenStudio component. The connection to OpenStudio has brought with it several new capabilities. Most notably, you can now assign full HVAC systems and receive energy results in units of electricity and fuel instead of simple heating and cooling loads. This Honeybee release includes 14 built-in HVAC template systems that can be assigned to the zones, each of which can be customized:
0. Ideal Air Loads 1. PTAC | Residential 2. PTHP | Residential 3. Packaged Single Zone - AC 4. Packaged Single Zone - HP 5. Packaged VAV w/ Reheat 6. Packaged VAV w/ PFP Boxes 7. VAV w/ Reheat 8. VAV w/ PFP Boxes 9. Warm Air Furnace - Gas Fired 10.Warm Air Furnace - Electric 11.Fan Coil Units + DOAS 12.Active Chilled Beams + DOAS 13.Radiant Floors + DOAS 14.VRF + DOAS
Systems 1-10 are ASHRAE Baseline systems that represent much of what has been added to building stock over the last few decades while systems 11-14 are systems that are commonly being installed today to reduce energy use. Here is an example file showing how to assign these systems in Honeybee and interpret the results and here is an example showing how to customize the HVAC system specifications to a wide variety of cases. To run the file, you will need to have OpenStudio installed and you can download and install OpenStudio from here.
In addition to these template systems within Honeybee, the OpenStudio interface includes hundreds of HVAC components to build your own custom HVAC systems. OpenStudio also has a growing number of user-contributed HVAC system templates that have been integrated into a set of scripts called "Measures" that you can apply to your OpenStudio model within the OpenStudio interface. You can find these system templates by searching for them in the building components library. Here is a good tutorial video on how to apply measures to your model within the OpenStudio interface. Honeybee includes a component that runs these measures from Grasshopper (without having to use the OpenStudio interface), which you can see a demo video of here. However, this component is currently in WIP as OpenStudio team is still tweaking the file structure of measures and it is fairly safe to estimate that, by the next stable release of Honeybee, we will have full support of OpenStudio measures within GH.
2 - Phasing Out IDF Exporter
With the connection to OpenStudio now fully established, this release marks the start of a transition away from exporting directly to EnergyPlus and the beginning of Honeybee development that capitalizes on OpenStudio’s development. As such THIS WILL BE THE LAST STABLE RELEASE THAT INCLUDES THE HONEYBEE_RUN ENERGY SIMULATION COMPONENT.
The Export to OpenStudio component currently does everything that the Run Energy Simulation component does and, as such, it is intended that all GH definitions using the Run Energy Simulation component should replace it with the OpenStudio component. You can use the same Read EP Result components to import the results from the OpenStudio component and you can also use the same Energy Sim Par/Generate EP Output components to customize the parameters of the simulation. The only effective difference between the two components is that the OpenStudio component enables the modeling of HVAC and exports the HBZones to an .osm file before converting it to an EnergyPlus .idf.
For the sake of complete clarity, we should state that OpenStudio is simply an interface for EnergyPlus and, as such, the same calculation engine is under the hood of both the Export to OpenStudio component and the Run Energy Simulation component. At present, you should get matching energy simulation results between the Run Energy Simulation component and a run of the same zones with the OpenStudio component (using an ideal air system HVAC).
All of this is to say that you should convert your GH definitions that use the Run Energy Simulation component to have the OpenStudio component and this release is the best time to do it (while the two components are supported equally). Additionally, with this version of Honeybee you will no longer need to install EnergyPlus before using Honeybee and you will only need to install OpenStudio (which includes EnergyPlus in the install).
3 - New Schedule Generation Components
Thanks to the efforts of Antonello Di Nunzio, we now have 2 new components that ease the creation of schedule-generation in Honeybee. The new components make use of the native Grasshopper “Gener Pool” component to give a set of sliders for each hour of the day. Additionally, Antonello has included an annual schedule component that contains a dictionary of all holidays of every nearly every nation (phew!). Finally, this annual schedule component can output schedules in the text format recognized by EnergyPlus, which allows them to be written directly into the IDF instead of a separate CSV file. This will significantly reduce the size of files needed to run simulations and can even reduce the number of components on your canvas that are needed to add custom schedules. For more information, see Antonello’s explanatory images here and Antonello's example file here. You can also see a full example file of how to apply the schedules to energy simulations here.
4 - EnergyPlus Lookup Folder, Re-run OSM/IDF, and Read Result Dictionary
With the new capabilities of OpenStudio, we have also added a number of components to assist with managing all of the files that you get from the simulation. In particular, Abraham Yezioro has added a Lookup EnergyPlus Folder component that functions very similarly to the Lookup Daylight Folder component. This way, you can run an Energy simulation once and explore the results separately. Furthermore, we have added components to Re-Run OpenStudio .osm files or EnergyPlus .idf files within Grasshopper. These components are particularly useful if you edit these .osm or .idf files outside of Honeybee and want to re-run them to analyze their results in Grasshopper. Lastly, a component has been added to parse the .rdd (or Result Data Dictionary) file that EnergyPlus produces, enabling you to see all of the possible outputs that you can request from a given simulation.
5 - Electric Lighting Components Out of WIP
After Sarith Subramaniam’s initial components to model electric lights with Radiance in the last release, we are happy to report that they have been fully tested and are out of WIP. Improvements include support for all types of light fixture geometries and the ability to use the components in a more “Grasshoppery” list-like fashion. See Sarith’s original release post for more information and several example files showing how to use the components can be found here. 1 , 2 , 3 .
6 - Improvements to THERM Components
A number of bug fixes and improvements have been made to the THERM components in order to make their application more flexible and smooth. Special thanks is due to Derin Yilmaz , Mel King , Farnaz , Ben (@benmo1) , and Abraham Yezioro for all of the great feedback in the process of improving these components.
7 - HBObject Transform Components
After some demand for components that can ease the generation of buildings with modular zone types, two components to transform HBObjects with all of their properties have been added to the 00 | Honeybee section. The components allow you to produce copies of zones that are translated or rotated from the original position.
8 - Comfort Maps Supports PET and Integration of CFD Results
Thanks to the addition of the ‘Physiological Equivalent Temperature’ (PET) component by Djordje Spasic in the last stable release, it is now possible to make comfort maps of PET with Honeybee. PET is particularly helpful for evaluating OUTDOOR comfort with detailed wind fields at a high spatial resolution. As such, the new PET recipe has also been optimized for integration with CFD results. The windSpeed_ input can now accept the file path to a .csv file that is organized with 8760 values in each column and a number of columns that correspond to the number of test points. Components to generate this csv from Butterfly CFD results will be coming in later releases. Stay tuned!
As always let us know your comments and suggestions.
Enjoy!Ladybug Analysis Tools Development Team
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utput. A typical parametric analysis involves either toggling input parameters while observing an output response in a cyclic trial and error feedback loop, or by adopting an optimisation approach to search for the 'best' output value based on some target of interest (e.g. in parametric simulation analysis studies).
Either-way, it remains cognitively difficult to keep track of input-output relationships, especially in multi-input parameter scenarios. Furthermore, optimisation outcomes are one-off outcomes that do not provide insight into the underlying input-output causality that is responsible for generating the output in the first place. As a result, it becomes challenging to control the computational workflow intuitively.
Inference Lab is a plug-in that overcomes such challenges by introducing bi-directionality between inputs and outputs, within Grasshopper. In other words, Inference Lab facilitates both forward and inverse computations. An inverse computation implies the ability to set a target output value of interest and instantly reveal the input distributions that are likely to cause the set target. This facilitates an instant cross-section of the input-output mapping. Inference Lab enables interaction with the input and output distributions to explore the cause and effect bi-directionally.
The following demo video illustrates the potential of Inference Lab for a structural design scenario. Given a typical parametric FEA simulation set up, Inference Lab was used to identify 1) how the design parameters influence the maximum deflection and the weight of the cantilever truss structure, and 2) identify the parameter ranges that satisfy specified targets on max deflection and weight.
Under the hood, Inference Lab builds a statistical representation of the input-output workflow from data that is generated automatically from the parametric definition within Grasshopper. The statistical representation takes advantage of a marriage between machine learning and Bayesian inference (a classic technique from probability theory).
More literature about the research underlying Inference Lab can be found here.
Inference Lab is presently composed of four main components: 1) PSlider, 2)POutput, 3)DataGenerator, 4)Model Builder.
Notes:
Inference Lab is a by-product of my very recent PhD work so please forgive me for the lack of information. I intend to update this page with structured tutorials explaining the potential of Inference Lab in various scenarios.
The Inference Lab plug-in is not yet available for download as I am in the process of ironing out a few minor issues. I hope to share an alpha version very soon. …
y (movement, protection, temperature regulation) but also the evolution of cultural expression precisely by exceeding the purely indexical performative relations. Designing not only for the needs but for the desires.
Computational couture looks at the creation of exclusive custom-fitted clothing (typical of haute couture) through the lens of a systemic approach, extending the sartorial techniques with 3D modeling and computation-based approaches developed in Rhinoceros and the visual programming environment Grasshopper.
Aim of the workshop is to exert, infuse and expand the sartorial sensibilities to body proportions and dress making into an algorithmic approach that loops through design and fabrication by means of laser cutting and 3d printing for the design and production of a garment. Participants will be divided in teams focusing on specific aspects of the garment related to the production technique (laser cutting or 3D printing).
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WORKSHOP | calendar
Day 1
Introduction to algorithms and computational design for creative disciplines Basics of 3D modeling in Rhinoceros Basics of Grasshopper Introduction to basic sartorial techniques
Day 2 Testing design options for the dress in Grasshopper (tutored work)
Day 3 Fabrication session . file preparation . parts testing and pre-assembly
Day 4 dress fabrication and assembly
Day 05 finalization of dress final presentation
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WORKSHOP | registration
FEE FOR PARTICIPANTS
Early bird (until 4/5): 250 € Full fee (from 5/5 until 15/5): 350 €
The fee includes materials and fabrication. Plane tickets and accommodation are not included in the fee.
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REGISTRATION (until 15/5/2015)
For registration please write at :
beyond@iaac.net
for more info visit:
http://beyond.iaac.net/?page_id=1620
…
metric/parəˈmɛtrɪk/adjectiverelating to or expressed in terms of a parameter or parameters.art/ɑːt/nounthe expression or application of human creative skill and imagination, typically in a visual form such as painting or sculpture, producing works to be appreciated primarily for their beauty or emotional power.// Summer School 2017 3 day intensive workshop for design students & professionals will delve into computational & parametric methods (using Rhino3D & Grasshopper3D) to create data-driven art installations, physically manifested into a space through hands-on fabrication & assembly.The experimental studio will run across 2 cities in India (New Delhi & Mumbai) and investigate the agenda of ‘filling the void’ at art installation scale, through the use of computation and parametric methods. Studio is designed as a 3-day event in both cities comprising of technical tutorials, teaching sessions, prototyping & presentations culminating in a symposium / round-table conference / open discussion with leading / emerging professionals that demonstrate computation, parametric design or alternative techniques in their work / practice / academia. // Cities & Dates*New Delhi – 30th June to 2nd July 2017 (Friday to Sunday)Mumbai – 7th July to 9th July 2017 (Friday to Sunday)//VENUE: DELHI: Startup Tunnel, Vihara Innovation CampusD-57, 100 Feet Rd, Pocket D, Dr Ambedkar Colony, Chhattarpur, New Delhi - 110074MUMBAI: Raffles Design International, MumbaiHi Life, 2nd Floor, Phirozshah Mehta Road,Santacruz (W). Mumbai – 400054// Registration DatesAll Registrations End 4 days prior to workshop start date (Or till seats last)// About rat[LAB] EDUCATIONrat[LAB] EDUCATION is an initiative by rat[LAB]-Research in Architecture & Technology (www.rat-lab.org) to start a new discourse in architecture & parallel design disciplines with the use of ‘computational design’ & it’s various subsets. Spread across various cities / countries, we are establishing a global dialogue in the domain of computational design by actively organizing and participating in workshops, lectures, presentations & symposia. While rat[LAB] has taken a top-down approach of exploring computational design through industry, a parallel, bottom-up approach is also in-line to involve students of all levels, from design & related backgrounds.…
pproach that will hopefully work. There's still the last part of putting it all together, but I figured I'd post my progress so you could play around with it if you wanted. This is kind of a lucky situation since its only single face breps and simple trims that are being worked with.
I've attached 3 definitions to this post. The first is my reorganization of your original definition, which creates the surfaces from the point grid and culls out any surfaces that are not "on" the surface so that we don't have to deal with them later down the line. This is done through a small VB component which determines whether any of the corner points lie on the surface. If it does it keeps the surface, if not, then it doesn't. The only issue with this is that in your example file, there are some surfaces which the corner points do not lie on the surface, yet the surface that they create spans the underlying surface. At this point I'm not worrying about those. You mentioned that you only want the surfaces that lie at the edge...this can be done by testing whether all 4 corner points lie on the trimmed surface or not.
The second definition is a coded version of the project function. In the example it will project to all the breps supplied, yet in the final version this probably won't be desired. Also, the direction (z axis) is hard code...this could be swapped out if desired.
The third definition is an shot at trimming a surface with an input curve (that curve happens to be projected). I tried this many ways, but found that the function RhinoCutUpSurface seamed to work alright. The other attempts at doing this directly with through functions available for OnBrep were unsuccessful and very complex. Luckily because the underlying brep is an single, untrimmed surface this function works well for us, but in situations where we have a trimmed or multiface brep we'd be up a creek with out a paddle. The function creates an array of breps, but in our case it will create essentially the same surface split by our curve and joined together as a single brep with two (possibly more) faces. All we have to do is find out which face we want to keep and duplicate that into a separate brep and pass it out of the component. In the example file I'm determining which on to keep based off of the distance from a test point to the centroid of each face.
The other option here, which would trump the need for projection or trimming, would be to extrude the edge curves through the surface in question, and use the BrepSplit function which requires two breps. There would still be the need to sort out what to keep, but if this approach were used, all the split pieces would be separate breps.
So, all the pieces are pretty much working separately, all that I have left to do is put them all together in the base definition. The only thing that is really the hump with that is determining exactly which face to keep. My idea at the moment is to find out which corner of the surface does not like on the base surface and use that to determine which face will be thrown out. This might be one of the easier ways, but will not be rock solid. The other option is to pull a test point that's on one of the faces to the base surface and the other face, then use the distance from test point to the point on the base surface and the distance to the pulled point on the other face to the base surface to figure out which one to keep.
As to sectioning off parts of the solution, you could do this in a number of ways, but here's two simple ones. In a scripting component just add a boolean value to the inputs and put the whole script inside of an if statement that looks at that boolean value. With components just add a boolean gate or a null pattern componet anywhere you want in the stream. Again, hook in a boolean toggle value, and that will stop the info from going to components that are downstream.…