tors: R.G.D.E tutors Mostafa R. A. Khalifa, Architect (PhD - UNICAM - Italy)
Assistants: Nagham Baitawy - Architect - Jordan
Ahmed Hassan - Architect & TA - Egypt
deadline registration August, 25th , 2013
http://grasshopperworkshopamman.blogspot.com/ introduction: This workshop will introduce basic and advanced notions of Grasshopper and the methodology of parametric design and algorithmic modeling and its usage in Architecture, design, landscape, and urban scale. It is intended for professionals and students with a minimum experience in 3D Modeling.
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with various protocols and applications.
One module, led by Luis E. Fraguada will focus on the communication between Processing and Grasshopper utilizing the various protocols available through the gHowl add on for Grasshopper.
The four modules include:
Processing+Grasshopper: Luis E. Fraguada (Barcelona) - http://tinyurl.com/6m49x5e
Processing+OSC: Alba Corral (Barcelona) -
Processing+Shypon: Miguel Espada (Madrid) - http://tinyurl.com/7no8egx
OpenFrameworks+Kinect: Carles Gutierrez (Barcelona) - http://tinyurl.com/79mmsnd
For registration, please email: hola@welovecode.net.
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Added by Luis Fraguada at 4:11am on February 29, 2012
arget group The workshop is addressed to students of architecture and civil engineering faculties at master level from Estonia (11 seats), Latvia (3 seats), Lithuania (3 seats) and Sweden (3 seats). The selected students will have full scholarship that will include travel, board and lodging in Tallinn for 10 days (arrival on Sunday 03.07.2016 departure on Wednesday 13.07.2016). The workshop is funded by the NORDPLUS programme of the Nordic Council of Ministers (NCM) - Higher Education objective.
Description The use of digital and computational design tools is increasingly important for the activity of design and research for architects and engineers. It permits to integrate environmental and energy aspects from the very early stages of the design and planning process to achieve more performative, efficient and integrated buildings and urban environments. The workshop attendants will broaden their design and technical knowledge with solar design, daylighting and energy efficiency topics and will learn how to integrate environmental analysis and building performance analysis tools with parametric and generative methodologies in architecture and planning.
Location
Tallinn University of Technology – Departments of Structural Design and Environmental Engineering
Dates
From 04 to 12 July 2016
Workshop blog
For detailed program, info and registration visit the blog at ceedtut.blogspot.com
In the weeks just before the workshop the blog will present also materials and tutorials to get a basic knowledge of the topics prior to the beginning of the workshop.
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ells new products like the Firefly Interactive Prototyping Shield which mounts on top of your Arduino Uno and provides access to a number of useful input (ie. sensors) and output (ie. motors) devices. It includes features like:
Three linear slide potentiometers connected to analog pins 0, 1, and 2
Two-axis joystick connected to analog pins 3 and 4
Light sensor (photocell) connected to analog pin 5
Three push buttons connected to digital pins 2, 4, and 7
Red LED connected to digital pin 13
RGB LED connected to digital pins 3, 5, and 6
Two servo connections on digital pins 8 and 9
A connection to the Easy Stepper Driver (co-designed by Sparkfun Electronics and Brian Schmalz) to control stepper motors. The direction of the motor is controlled through digital pin 10 and the number of steps through digital pin 12
High-voltage MOSFET circuit capable of driving lights, valves, DC motors, solenoids, or anything else requiring higher voltage or current. The gate of the MOSFET is connected to digital pin 11 (PWM).
Some come take a look and let us know what you think!
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eroberfläche des Grasshopper Programms
Funktionsprinzip eines grafischen Algorithmus-Editors (Datenfluss)
Unterscheidung von Parametern (Datentypen) und Komponenten (Datenverarbeitung)
Erzeugung, Bearbeitung und Analyse von Geometrie-Typen: Punkte, Vektoren, Linien, Kurven, Flächen (surfaces, brep) und Netze (meshes)
Strukturierung der Daten anhand von Listen und Bäumen
unterschiedliche Verknüpfungsmöglichkeiten von Parametern (data matching)
praxisnahe Grundlagen der Geometrie und Vektorrechnung für generatives Design
effizienter Aufbau von parametrischen Modellen anhand Übungsaufgaben
Auszug von Daten aus Modellen für die Fertigung; Daten aus Tabellen (Excel, CSV) importieren, exportieren
Einsatz von benutzerdefinierten Komponenten (custom components)
Vorkenntnisse: Rhinoceros3d Benutzeroberfläche der Software: Englisch Unterrichtssprache: Deutsch
Details und Anmeldung:
www.vhs-sha.de
click: SUCHE
Kurstitel: GRASSHOPPER
oder direkt:
http://www.vhs-sha.de/index.php?id=90&kathaupt=11&knr=3151053&kursname=Grasshopper+I
Trainer: Peter Mehrtens
Kursdauer: 3 Tage / 8 Stunden pro Tag
Freitag, 19.07.2013, 08:00-17:00 Uhr Samstag, 20.07.2013, 08:00-17:00 Uhr Sonntag, 21.07.2013, 08:00-17:00 Uhr Ort: Volkshochschule Schwäbisch Hall, im Haus der Bildung
Teilnahmegebühr: 349,00 € Teilnehmerzahl: 4-10 Personen
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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…
teraction for its Correlations cycle, AA Athens Visiting School scales up its design intentions in order to investigate links among discrete individual architectural systems in its 2013 version, Recharged.
Recharged with interconnectivity on different levels, the theme of investigation will revolve around the design of semi-independent design prototypes acting together to form elaborate unified results. The driving force in Cipher City: Recharged is the synergistic effect behind complex form-making systems where interactive design patterns arise out of a multiplicity of relatively simple rules.
In collaboration with the National Technical University of Athens, Cipher City: Recharged will explore participatory design and active engagement modeling and will continue building novel prototypes upon horizontal planes.
As in 2012, the design agendas of AA Athens and AA Istanbul Visiting Schools will directly create feedback on one another, allowing participation in either one or both Programmes.
Discounts
The AA offers several discount options for participants wishing to apply as a group or participants wishing to apply for both AA Istanbul and AA Athens Visiting Schools:
1. Standard application
The AA Visiting School requires a fee of £695 per participant, which includes a £60 Visiting Membership. If you are already a member, the total fee will be reduced automatically by £60 by the online payment system. Fees are non refundable.
2. Group registration
For group applications, there will be a range of discounts depending on the number of people in the group. The discounted fee will be applied to each individual in the group.
Type A. 3-6 people group: £60 (AA Membership fee) + 635*0.75 = £536.25 (25 %) Type B. 6-15 people group: £60 + 635*0.70 = £504.5 (30%) Type C. more than 15 people group: £60 + 635*0.65 = £472.75 (35%)
3. Participants attending both AA Istanbul and AA Athens | 40% discount
For people wishing to attend both AA Istanbul 2013 and AA Athens 2013, a discount of 40% will be made for each participant. (The participant will pay the £60 membership fee only once.)
£60 (AA Membership fee) + (635*0.60)*2 = £822
For more information in discounts, please visit:
http://ai.aaschool.ac.uk/athens/portfolio/discounts-2013/
Applications
The deadline for applications is 11 March 2013. A portfolio or CV is not required, only the online application form and payment. The online application can be reached from:
http://www.aaschool.ac.uk/STUDY/VISITING/athens…
Added by elif erdine at 12:33pm on December 13, 2012
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…
Target group The workshop is fully funded and is addressed to students of architecture and civil engineering faculties at master level from Estonia (11 seats), Latvia (3 seats), Lithuania (3 seats) and Sweden (3 seats). The selected students will have full scholarship that will include travel, board and lodging in Tallinn for 10 days (arrival on Sunday 03.07.2016 departure on Wednesday 13.07.2016). The workshop is funded by the NORDPLUS programme of the Nordic Council of Ministers (NCM) - Higher Education objective.
Description The use of digital and computational design tools is increasingly important for the activity of design and research for architects and engineers. It permits to integrate environmental and energy aspects from the very early stages of the design and planning process to achieve more performative, efficient and integrated buildings and urban environments. The workshop attendants will broaden their design and technical knowledge with solar design, daylighting and energy efficiency topics and will learn how to integrate environmental analysis and building performance analysis tools with parametric and generative methodologies in architecture and planning.
Location
Tallinn University of Technology – Departments of Structural Design and Environmental Engineering
Dates
From 04 to 12 July 2016
Workshop blog
For detailed program, info and registration visit the blog at ceedtut.blogspot.com
In the weeks just before the workshop the blog will present also materials and tutorials to get a basic knowledge of the topics prior to the beginning of the workshop.
…