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…
akes the linear regression of the Schroeder integral over 30 dB worth of decay. Whether it is T-15 or T-30, they all seek to estimate the RT, which is always always the time it takes for sound to decay 60 decibels.
The website has benchmarks, for your reference. You can find them under the 'Pachyderm' drop down menu, under 'Benchmarks'.
Your model may well require millions of rays to be accurate. It sounds like a very large space. I'm sorry if that is an unpleasant answer. Sometimes it does help to have a computer with more cores to help with this. I have gotten up to 90% processor usage on a 12 core machine before.
Arthur…
. From the Thermal Comfort Indices component, Comfort Index 11 (TCI-11):MRT = f(Ta, Tground, Rprim, e)
with:- Ta = DryBulbTemperature coming from ImportEPW component- Tground = f(Ta, N) where N comes from totalSkyCover input. Tground influences the long-wave radiation emitted by the ground in the MRT calculation.- Rprim defined as solar radiation absorbed by nude man = f(Kglob, hS1, ac)- ac is the clothingAlbedo in % (bodyCharacteristics input)- I can't find any definition in the code of Kglob and hS1. Could you tell me please what are those values referencered to? --> probably the globalHorizontalRadiation but how?- e = vapour pressure calculated from Ta and Relative Humidity input
Do you agree that in this case the MRT does not depend on these inputs: location, meanRadiantTemperature, dewPointTemperature and wind speed?It does not depend neither on the other bodyCharacteristics like bodyPosture, age, sex, met, activityDuration...?
MRT calculated by the TCI-11 method is the mean radiant temperature of a vector pointing vertically with a sky view factor of 100%?For ParisOrly epw,
2. From the SolarAdjustedTemperature component (that seems to be more used for the UTCI calculation examples on Hydra compared to TCI-11).
In contrast to the TCI-11, this component distinguishes diffuse and direct radiation and contextualizes the calculation thanks to _ContextShading input, right? It can also be applied to a mannequin thanks to the CumSkyMatrix and thus evaluate the dishomogeneity of radiation exposure.This component seems not to consider the influence of vapour pressure on the result --> is it then more precise to put the MRT output (from the TCI) as an input of meanRadTemperature for SolarAdjustedTemperature?The default groundReflectivity is set to 0.25 --> is GroundReflectivity taken into account in the Tground or MRT calculation in the TCI component? If yes, what is the hypothesised groundReflectivity?The default clothing albedo of 37% (TCI-11 bodyCharacteristics) corresponds to Clothing Absorptivity of 63%?
If the CumSkyMatrix input is not supplied, I get 9 results for the mannequin --> where are those points/results coming from?
If the CumSkyMatrix input is supplied,I suppose the calculation of the 482 results correspond to a calculation method similar to the radiation analysis component that is averaged over the analysis period. Right?But I don't understand why the mannequin is composed of 481 faces and meshFaceResult gives 482 results.
Finally, what is the link between the MESH results, the solarAdjustedMRT and the Effective Radiant field ? Is there a paper to have a detailed explanation of the method?
3. Here are some results for the ParisOrly energyplus weather data. You can find here attached the grasshopper definition.There is no shading in this simulation and the result coming from the ThermalComfort indices for MRT is very different compared to the solar adjusted MRT.Why such a big difference and which of the result should be plugged into the UTCI calculation component?
Results for ParisOrly.epwM,D,H:1,1,12
Ta : 6.5°Crh: 100%globalHorizontalRadiation: 54 Wh/m2totalSkyCover: 10MRT (TCI-11): 1.2°C
_CumSkyMtxOrDirNormRad = directNormalRadiation : 0 Wh/m2diffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.64°CMRTDelta: 4.14°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.47°CMRTDelta: 3.97°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = MRT (TCI-11)solarAdjustedMRT: 5.17°CMRTDelta: 3.97°C
Thanks a lot for your helpRegards,
Aymeric
…
edit 29/04/14 - Here is a new collection of more than 80 example files, organized by category:
KangarooExamples.zip
This zip is the most up to date collection of examples at the moment, and collects t
he "return" is comment out as shown below?
After restarting Rhino and Grasshopper, I opened the outdoors_airflow demo file, and the first step of creating the case file is ok:
Then the blockMesh component gives the following error: seems I have to manually start OF first..
so, as the error message suggested, I open OF by Start_OF.bat:
Then come back to the blockMesh component, now it can be executed while the OF command line window is also openning:
... and the blockMesh finished successfully:
... so I proceeded to run snappyHexMesh, checkMesh and update fvScheme:
... up to the simpleFoam component, I got the error again:
The warning message is:
1. Solution exception: --> OpenFOAM command Failed!#0 Foam::error::printStack(Foam::Ostream&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #1 Foam::sigFpe::sigHandler(int) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #2 ? in "/lib64/libc.so.6" #3 double Foam::sumProd<double>(Foam::UList<double> const&, Foam::UList<double> const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #4 Foam::PCG::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #5 Foam::GAMGSolver::solveCoarsestLevel(Foam::Field<double>&, Foam::Field<double> const&) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #6 Foam::GAMGSolver::Vcycle(Foam::PtrList<Foam::lduMatrix::smoother> const&, Foam::Field<double>&, Foam::Field<double> const&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::PtrList<Foam::Field<double> >&, Foam::PtrList<Foam::Field<double> >&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #7 Foam::GAMGSolver::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #8 Foam::fvMatrix<double>::solveSegregated(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libfiniteVolume.so" #9 Foam::fvMatrix<double>::solve(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #10 Foam::fvMatrix<double>::solve() in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #11 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #12 __libc_start_main in "/lib64/libc.so.6" #13 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam"
... and the command lines in the readMe! output are pretty long and it is saved in the text file attached here.
So, my questions are:
1. why I have to manually start OF first before I can use the blockMesh component? Should butterfly automatically start OF?
2. what might be the cause of the unsuccessful run of simpleFoam in the end?
Hope you can kindly advise! Thank you!
- Ji
…
I tell you what I had to do and how I did it.
I have the following situation. A urban context with a square plot 40m x 40m surrounded by buildings.
If I extrude the plot I get 4 surfaces and I need to calculate the minimum daily quantity of direct sunlight hours each test point receives in the period from 22nd of April to 22nd of August. For example for the test point at index 21 of surface with index 1 (I am just creating these numbers in my mind) the minimum is on 27th of April and the test point receive 8 hours (this is also invented for the sake of the example) of direct sunlight. All the other days it receives more. So the values I have to found are these minimums for all the test points. Now how to calculate these minimum quantities is a different issue of the topic of this post and actually I manage it.
Continuing with the explanation of what I had to... so I have only the initial plot that generate 4 surfaces, then I want to test smaller plots generated by an offset of 4 m of the original one, and the relative 4 surfaces for each smaller plot.
So in this case I think I cannot use your suggestion because the object don't exist yet.
I managed creating a loop with Anemone, the loop generate an offset starting from the original at 0 until 4 (then I multiply it by 4 to obtain the offset at 0, 4, 8, 12 and 16. Then I did like you also suggest I record every time the result with the DataRecorder and I create for each result a different branch with the index coming from the loop (0, 1, 2, 3 and 4) with the Flatten component.
In this image you can see all the surfaces saved in the same way as described above and in white the test points that receive minmum or equal than 2.5 hours per day of direct sunlight in the period from from 22nd of April to 22nd of August and in dark gray the test points that receive less.
The main point of this discussion is just the fact that instead use this tricky way I used, or the one you suggest, to analyze separately (because they shade each other) 20 geometries (in this case 20 they could be many more) it would be good if it would be possible just to input all the geometries at the same time and they would not shade each other so to get directly all the results with one run and in a more simple way.
Francesco
…
y part of existing files, you typically mark the old component as [Obsolete]* and write an entirely new component which has the changes. This allows you to open old files and have them work in the same way as before, by loading the obsolete component instead of the current one. You can then choose to add an automatic upgrader which is a class which knows how to replace an obsolete component with an updated version in situ. You can load all upgraders via the Solution->Upgrade Components... menu.
An upgrader is a class which implements the IGH_UpgradeObject interface. There's also a GH_UpgradeUtil class which provides some useful static methods for doing common upgrade stuff. For example, here's the upgrader for the [Polygon Centre] component:
public class Upgrade_PolygonCenterComponent : IGH_UpgradeObject { public Guid UpgradeFrom { get { return new Guid("{7BD7B551-CA79-4f01-B95A-7E9AB876F24D}"); } } public Guid UpgradeTo { get { return new Guid("{87E7F480-14DC-4478-B1E6-2B8B035D9EDC}"); } } public DateTime Version { get { return new DateTime(2011, 12, 7, 16, 30, 00); } } public IGH_DocumentObject Upgrade(IGH_DocumentObject target, GH_Document document) { IGH_Component component = target as IGH_Component; if (component == null) { return null; }
IGH_Component upgradedComponent = GH_UpgradeUtil.SwapComponents(component, UpgradeTo); Grasshopper.Kernel.Parameters.Param_Point extraParameter = new Grasshopper.Kernel.Parameters.Param_Point(); extraParameter.Name = "Center(E)"; extraParameter.NickName = "Ce"; extraParameter.Description = "Average of polyline edges"; upgradedComponent.Params.RegisterOutputParam(extraParameter);
return upgradedComponent; } }
* This can be done either by adding the string "OBSOLETE" to the component class name, or by adding the [Obsolete] attribute to the component. Do note you have to change the exposure to Hidden, otherwise the obsolete component will still show up on the panels.…
Added by David Rutten at 9:36am on October 21, 2017
ahams's question about how shades are accounted for in the simulation/thermal map and Theodore's thought that just accounting for shades in the E+ run was sufficient. I think that it may be clearest to explain what is going on with this infographic:
As the graphic shows, the thermal maps are made from 4 key types of inputs. The radiant temperature map is formed through a consideration of both the temperature of the surfaces surrounding the occupants and the direct solar radiation that might fall onto the occupants through un-shaded windows. The first surface temperature effect is easily computable from your Energy simulation results and the HBZone geometry. However, the second is calculated by seeing how sun vectors pass through the windows of the zones and uses the SolarCal method of the CBE team (http://escholarship.org/uc/item/89m1h2dg) to compute an MRT delta resulting from solar radiation. This delta is then added to the initial values computed through surface temperature view factor. When you do not connect up your shading brep geometry, internal furniture breps, or outdoor context geometry that might block sun to the additionalShading input, the thermal map will assume that sun can pass unobstructed through the window or through indoor furniture to fall onto occupants. It is important to stress that the EnergyPlus simulation does not count for blind geometry or internal furniture as actual geometry. Just as numerical abstractions of surface area and material properties. So we need you to plug in the actual geometry of these things when we compute the MRT delta resulting from sun falling directly onto people.
Next, to clear up the definition of window transmissivity. The important thing to clarify here is that, whether it refers to the tranmittance of glass or to the amount of sun coming through a fine screen of blinds, the value is multiplied by the radiation falling on the occupant and thus has a direct correlation to the MRT Delta from sun falling on occupants. So, if you set transmissivity to zero, the sun falling on the occupants will not be considered in the calculation and, if you set the transmissivity to 1, the assumption is that there is no window (or the window glass is 100% clear). So, Abraham, your definition of it as a coefficient is appropriate.
Normally, I would just recommend that you leave this value at the default 0.7, which corresponds to the transmittance of the default glass material in Honeybee. However, there are 4 cases in which you might consider changing it:
1) You are not using the default Honeybee glazing material, in which case, you should change the transmissivity to be equal to this new value.
2) You have a lot of really small blind/shade geometries and you do not want the view factor component to take several minutes to trace sun vectors through the detailed shade geometry and so you are ok with using just a simple abstraction instead of plugging shade breps into the additionaShading. In this case, you might try to estimate the average percentage of radiation coming through the blind geometry (maybe with some simple Ladybug radiation studies or with your intuition about the amount of sun blocked by the shades). You will then multiply this by the tranmissivity of your glass and this will be the value that you input to the component.
3) Your blinds for your Honeybee simulation are dynamic, in which case, plugging shade breps into additionalShading is not going to work because the component will assume that those shades are always there. In this case, you should be plugging a list of 8760 values into the transmissivity that correspond to when the shades are pulled. When the blinds are completely up, the value should be the tranmittance of your window and, when they are down, the value should be the window tranmittance multiplied by the fraction of light coming through the shades.
4) You have shades/blinds but they are transparent or are not completely opaque. The additionalShading_ input assumes that all shade geometry is opaque and so you cannot use it to account for such shades. Accordingly, you will need to account for it through the tranmissivity.
In the future, I may try to pull more information about blinds and glass properties off of the HBzones inside the view factor component but, for now and for the next few months, the above describes how it works.
Theodore, for curved geometry, I think that your safest bet is going to be planarizing the Rhino geometry before you turn it into a HBZone (so you just divide the curved surface into a few vertical planar panes of glass that approximate the curve well enough). This is essentially what the runSimulation component does for you automatically (it meshes the geometry as you see here: https://www.youtube.com/watch?v=nMQ2Pau4q6c&index=12&list=PLruLh1AdY-SgW4uDtNSMLeiUmA8YXEHT_). If I were to figure out a way to incorporate shades in this automatic meshing workflow, your EnergyPlus simulation would take a very long time to run and I am not even sure if the result will be that accurate with the way E+ abstracts shades. So I don't think that it's really worth it over just planarizing the geometry yourself.
Lastly, I won't be able to figure out the problem with your current run Theodore, unless I get the GH file from you. Make sure that you are using all up-to-date components.
-Chris…
ted (in the old scheme, all inputs were always taken into account) and it's more obvious what happens to the data just by looking at an image. Also, it clears out the component menu and it's easier to add more functionality later on without creating too much confusion.
Interpolate will 'sample' the data at equally spaced intervals. Let's say you have a list of 8 fruits, as I used in my example. What happens if you interpolate this list using 4 samples? Well, the first and last sample are always centered on the first and last items in the original list. The in between samples are distributed at equidistant intervals:
So you'd end up with a list containing {Lemon, Bergamot, Mandarin, Tangerine}. If you interpolate this list using 12 equally spaced samples, it will look like this:
and it results in a list containing {Lemon, Lime, Lime, Bergamot, Grapefruit, Grapefruit, Orange, Orange, Mandarin, Rangpur, Rangpur, Tangerine}. Of course interpolating a list may result in weird sampled intervals because of the rounding of sample parameter to list indices.
Interpolation does not sample in between values. It will not return a value that is 30% Grapefruit and 70% Orange. This kind of interpolation is only possible on a subset of data types (numbers, vectors, points, colours etc.) but these components must operate on all data types. I added a specific interpolation component as well, that performs numeric sampling using 4 possible interpolation functions, but this is a wholly different kind of interpolation.
--
David Rutten
david@mcneel.com
Poprad, Slovakia…
rring to the above image)
Area
effective
effective
Second
Elastic
Elastic
Plastic
Radius
Second
Elastic
Plastic
Radius
of
Vy shear
Vz shear
Moment
Modulus
Modulus
Modulus
of
Moment
Modulus
Modulus
of
Section
Area
Area
of Area
upper
lower
Gyration
of Area
Gyration
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(weak axis)
(weak axis)
(weak axis)
(weak axis)
A
Ay
Az
Iy
Wy
Wy
Wply
i_y
Iz
Wz
Wplz
i_z
cm2
cm2
cm2
cm4
cm3
cm3
cm3
cm
cm4
cm3
cm3
cm
I have a very similar table which I could import to the Karamba table. But I have i_v or i_u values as well as radius of inertia for instance.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
dimensjon
Masse
Areal
akse
Ix
Wpx
ix
akse
Iy
Wpy
iy
akse
Iv
Wpv
iv
Width
Thickness
Radius R
[kg/m]
[mm2]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm]
[mm]
[mm]
L 20x3
0.89
113
x-x
4,000
290
5.9
y-y
4,000
290
5.9
v-v
1,700
200
3.9
20
3
4
L 20x4
1.15
146
x-x
5,000
360
5.8
y-y
5,000
360
5.8
v-v
2,200
240
3.8
20
4
4
L 25x3
1.12
143
x-x
8,200
460
7.6
y-y
8,200
460
7.6
v-v
3,400
330
4.9
25
3
4
L 25x4
1.46
186
x-x
10,300
590
7.4
y-y
10,300
590
7.4
v-v
4,300
400
4.8
25
4
4
L 30x3
1.37
175
x-x
14,600
680
9.1
y-y
14,600
680
9.1
v-v
6,100
510
5.9
30
3
5
L 30x4
1.79
228
x-x
18,400
870
9.0
y-y
18,400
870
9.0
v-v
7,700
620
5.8
30
4
5
L 36x3
1.66
211
x-x
25,800
990
11.1
y-y
25,800
990
11.1
v-v
10,700
760
7.1
36
3
5
L 36x4
2.16
276
x-x
32,900
1,280
10.9
y-y
32,900
1,280
10.9
v-v
13,700
930
7.0
36
4
5
L 36x5
2.65
338
x-x
39,500
1,560
10.8
y-y
39,500
1,560
10.8
v-v
16,500
1,090
7.0
36
5
5
I have diagonals (bracings) which can buckle in these "non-regular" directions too, and they do. If I could add those values then in the Karamba model I could assign specific buckling scenarios..... I can see another challenge which will be at the ModifyElement component, I will not be able to choose these buckling lengths, in these directions.
Do you think this functionality can be added within short, or should I try to find another way to model these members?
Br, Balazs
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