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Difference between revisions of "Windscreen"

m (Updated BibTeX entry.)
 
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{{preliminary}} <!-- Do not remove -->
 
 
 
 
[[Category:benchmark]]
 
[[Category:benchmark]]
 
[[Category:Oberwolfach]]
 
[[Category:Oberwolfach]]
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[[Category:Affine parameter representation]]
 
[[Category:Affine parameter representation]]
 
[[Category:Parametric]]
 
[[Category:Parametric]]
[[Category:Parametric 1 parameter]]
 
 
[[Category:SISO]]
 
[[Category:SISO]]
 
[[Category:Sparse]]
 
[[Category:Sparse]]
  +
  +
{{Infobox
  +
|Title = Windscreen
  +
|Benchmark ID = windscreen_n22692m1q1
  +
|Category = oberwolfach
  +
|System-Class = LTI-SOS
  +
|nstates = 22692
  +
|ninputs = 1
  +
|noutputs = 1
  +
|nparameters = 0
  +
|components = B, C, K, M
  +
|License = NA
  +
|Creator = [[User:Himpe]]
  +
|Editor =
  +
* [[User:Himpe]]
  +
* [[User:Mlinaric]]
  +
* [[User:Yue]]
  +
|Zenodo-link = NA
  +
}}
   
 
==Description==
 
==Description==
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:<math>
 
:<math>
 
\begin{align}
 
\begin{align}
K_d x - \omega^2 M x & = f \\
+
K x + \omega^2 M x & = B \\
y & = f^* x
+
y & = C x
 
\end{align}
 
\end{align}
 
</math>
 
</math>
   
where <math>f</math> represents a unit point load in one unknown of the state vector.
+
where <math>B</math> represents a unit point load in one unknown of the state vector, <math>C = B^T </math>,
<math>M</math> is a symmetric positive-definite matrix and <math>K_d = (1+i\gamma) K</math> where <math>K</math> is symmetric positive semi-definite.
+
<math>M</math> is a symmetric positive-definite matrix, and <math>K = (1+i\gamma) \widetilde{K}</math> with <math>\widetilde{K}</math> symmetric positive semidefinite.
   
 
The test problem is a structural model of a car windscreen. <ref name="meerbergen2007"/>
 
The test problem is a structural model of a car windscreen. <ref name="meerbergen2007"/>
 
This is a 3D problem discretized with <math>7564</math> nodes and <math>5400</math> linear hexahedral elements (3 layers of <math>60 \times 30</math> elements).
 
This is a 3D problem discretized with <math>7564</math> nodes and <math>5400</math> linear hexahedral elements (3 layers of <math>60 \times 30</math> elements).
The mesh is shown in <xr id="fig1"/>.
+
The mesh is shown in Fig.&nbsp;1.
 
The material is glass with the following properties:
 
The material is glass with the following properties:
The Young modulus is <math>7\times10^{10}\mathrm{N}/\mathrm{m}^2</math>, the density is <math>2490 \mathrm{kg}/\mathrm{m}^3</math>, and the Poisson ratio is <math>0.23</math>. The natural damping is <math>10\%</math>, i.e. <math>\gamma=0.1</math>.
+
The [[wikipedia:Young's_modulus|Young modulus]] is <math>7\times10^{10}\mathrm{N}/\mathrm{m}^2</math>, the density is <math>2490 \mathrm{kg}/\mathrm{m}^3</math>, and the [[wikipedia:Poisson's_ratio|Poisson ratio]] is <math>0.23</math>. The natural damping is <math>10\%</math>, i.e. <math>\gamma=0.1</math>.
 
The structural boundaries are free (free-free boundary conditions).
 
The structural boundaries are free (free-free boundary conditions).
 
The windscreen is subjected to a point force applied on a corner.
 
The windscreen is subjected to a point force applied on a corner.
Line 39: Line 54:
 
The discretized problem has dimension <math>n=22692</math>.
 
The discretized problem has dimension <math>n=22692</math>.
 
The goal is to estimate <math>x(\omega)</math> for <math>\omega\in[0.5,200]</math>.
 
The goal is to estimate <math>x(\omega)</math> for <math>\omega\in[0.5,200]</math>.
In order to generate the plots the frequency range was discretized as <math>\{\omega_1,\ldots,\omega_m\} =
+
In order to generate the plots, the frequency range was discretized as <math>\{\omega_1,\ldots,\omega_m\} =
 
\{0.5j,j=1,\ldots,m\}</math> with <math>m=400</math>.
 
\{0.5j,j=1,\ldots,m\}</math> with <math>m=400</math>.
   
<xr id="fig1"/> shows the mesh of the car windscreen and <xr id="fig2"/> the frequency response <math>\vert \Re(y(\omega)) \vert</math>.
+
Fig.&nbsp;1 shows the mesh of the car windscreen and Fig.&nbsp;2 the frequency response <math>\vert \Re(y(\omega)) \vert</math>.
   
 
==Origin==
 
==Origin==
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Download matrices in the [http://math.nist.gov/MatrixMarket/ Matrix Market] format:
 
Download matrices in the [http://math.nist.gov/MatrixMarket/ Matrix Market] format:
   
* [https://portal.uni-freiburg.de/imteksimulation/downloads/benchmark/Windscreen%20%2838886%29/files/fileinnercontentproxy.2010-02-26.3407583176 windscreen.tar.gz] (21.5 MB)
+
* [https://csc.mpi-magdeburg.mpg.de/mpcsc/MORWIKI/Oberwolfach/Windscreen-dim1e4-windscreen.tar.gz Windscreen-dim1e4-windscreen.tar.gz] (21.5 MB)
   
The archive contains files <tt>windscreen.K</tt>, <tt>windscreen.M</tt> and <tt>windscreen.B</tt> representing <math>K_d</math>, <math>-M</math> and <math>f</math> accordingly.
+
The archive contains files <tt>windscreen.K</tt>, <tt>windscreen.M</tt> and <tt>windscreen.B</tt> representing <math>K</math>, <math>M</math> and <math>B</math> accordingly.
   
 
==Dimensions==
 
==Dimensions==
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\begin{align}
 
\begin{align}
 
(K + \omega^2 M) x & = B \\
 
(K + \omega^2 M) x & = B \\
y & = B^{\mathrm{T}} x
+
y & = C x
 
\end{align}
 
\end{align}
 
</math>
 
</math>
Line 71: Line 86:
 
<math>K \in \mathbb{C}^{22692 \times 22692}</math>,
 
<math>K \in \mathbb{C}^{22692 \times 22692}</math>,
 
<math>M \in \mathbb{R}^{22692 \times 22692}</math>,
 
<math>M \in \mathbb{R}^{22692 \times 22692}</math>,
<math>B \in \mathbb{R}^{22692 \times 1}</math>.
+
<math>B \in \mathbb{R}^{22692 \times 1}</math>,
  +
<math>C \in \mathbb{R}^{1 \times 22692}</math>,
   
 
==Citation==
 
==Citation==
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* For the benchmark itself and its data:
 
* For the benchmark itself and its data:
:: Oberwolfach Benchmark Collection, '''Windscreen'''. hosted at MORwiki - Model Order Reduction Wiki, 2004. http://modelreduction.org/index.php/Windscreen
+
:: Oberwolfach Benchmark Collection, '''Windscreen'''. hosted at MORwiki - Model Order Reduction Wiki, 2018. https://modelreduction.org/morwiki/Windscreen
 
 
 
@MISC{morwiki_windscreen,
 
@MISC{morwiki_windscreen,
Line 83: Line 99:
 
title = {Windscreen},
 
title = {Windscreen},
 
howpublished = {hosted at {MORwiki} -- Model Order Reduction Wiki},
 
howpublished = {hosted at {MORwiki} -- Model Order Reduction Wiki},
url = <nowiki>{http://modelreduction.org/index.php/Windscreen}</nowiki>,
+
url = <nowiki>{https://modelreduction.org/morwiki/Windscreen}</nowiki>,
year = 2004
+
year = 20XX
 
}
 
}
   
 
* For the background on the benchmark:
 
* For the background on the benchmark:
   
@article{Mee,
+
@article{Mee07,
 
author = {K. Meerbergen},
 
author = {K. Meerbergen},
title = {Fast frequency response computation for Rayleigh damping},
+
title = {Fast frequency response computation for {R}ayleigh damping},
 
journal = {International Journal for Numerical Methods in Engineering},
 
journal = {International Journal for Numerical Methods in Engineering},
volume = 73,
+
volume = {73},
number = 1,
+
number = {1},
 
pages = {96--106},
 
pages = {96--106},
year = 2007,
+
year = {2007},
 
doi = {10.1002/nme.2058},
 
doi = {10.1002/nme.2058},
 
}
 
}
Line 106: Line 122:
 
<ref name="korvink2005"> J.G. Korvink, E.B. Rudnyi, <span class="plainlinks">[https://doi.org/10.1007/3-540-27909-1_11 Oberwolfach Benchmark Collection]</span>, In: Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 311--315, 2005.</ref>
 
<ref name="korvink2005"> J.G. Korvink, E.B. Rudnyi, <span class="plainlinks">[https://doi.org/10.1007/3-540-27909-1_11 Oberwolfach Benchmark Collection]</span>, In: Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 311--315, 2005.</ref>
   
<ref name="meerbergen2007"> K. Meerbergen, <span class="plainlinks">[https://doi.org/10.1002/nme.2058 Fast frequency response computation for Rayleigh damping]</span>, International Journal for Numerical Methods in Engineering, '''73'''(1): 96--106, 2007.</ref>
+
<ref name="meerbergen2007"> K. Meerbergen, <span class="plainlinks">[https://doi.org/10.1002/nme.2058 Fast frequency response computation for Rayleigh damping]</span>, International Journal for Numerical Methods in Engineering, 73(1): 96--106, 2007.</ref>
   
 
</references>
 
</references>

Latest revision as of 07:42, 17 June 2025


Windscreen
Background
Benchmark ID

windscreen_n22692m1q1

Category

oberwolfach

System-Class

LTI-SOS

Parameters
nstates
22692
ninputs

1

noutputs

1

nparameters

0

components

B, C, K, M

Copyright
License

NA

Creator

Christian Himpe

Editor
Location

NA


Description

Figure 1
Figure 2

This is an example for a model in the frequency domain of the form


\begin{align}
  K x + \omega^2 M x & = B \\
  y & = C x
\end{align}

where B represents a unit point load in one unknown of the state vector, C = B^T , M is a symmetric positive-definite matrix, and K = (1+i\gamma) \widetilde{K} with \widetilde{K} symmetric positive semidefinite.

The test problem is a structural model of a car windscreen. [1] This is a 3D problem discretized with 7564 nodes and 5400 linear hexahedral elements (3 layers of 60 \times 30 elements). The mesh is shown in Fig. 1. The material is glass with the following properties: The Young modulus is 7\times10^{10}\mathrm{N}/\mathrm{m}^2, the density is 2490 \mathrm{kg}/\mathrm{m}^3, and the Poisson ratio is 0.23. The natural damping is 10\%, i.e. \gamma=0.1. The structural boundaries are free (free-free boundary conditions). The windscreen is subjected to a point force applied on a corner. The goal of the model reduction is the fast evaluation of y. Model reduction is used as a fast linear solver for a sequence of parametrized linear systems.

The discretized problem has dimension n=22692. The goal is to estimate x(\omega) for \omega\in[0.5,200]. In order to generate the plots, the frequency range was discretized as \{\omega_1,\ldots,\omega_m\} =
\{0.5j,j=1,\ldots,m\} with m=400.

Fig. 1 shows the mesh of the car windscreen and Fig. 2 the frequency response \vert \Re(y(\omega)) \vert.

Origin

This benchmark is part of the Oberwolfach Benchmark Collection[2]; No. 38886.

Data

Download matrices in the Matrix Market format:

The archive contains files windscreen.K, windscreen.M and windscreen.B representing K, M and B accordingly.

Dimensions

System structure:


\begin{align}
  (K + \omega^2 M) x & = B \\
  y & = C x
\end{align}

with \omega \in [0.5, 200].

System dimensions:

K \in \mathbb{C}^{22692 \times 22692}, M \in \mathbb{R}^{22692 \times 22692}, B \in \mathbb{R}^{22692 \times 1}, C \in \mathbb{R}^{1 \times 22692},

Citation

To cite this benchmark, use the following references:

  • For the benchmark itself and its data:
Oberwolfach Benchmark Collection, Windscreen. hosted at MORwiki - Model Order Reduction Wiki, 2018. https://modelreduction.org/morwiki/Windscreen
@MISC{morwiki_windscreen,
  author =       {{Oberwolfach Benchmark Collection}},
  title =        {Windscreen},
  howpublished = {hosted at {MORwiki} -- Model Order Reduction Wiki},
  url =          {https://modelreduction.org/morwiki/Windscreen},
  year =         20XX
}
  • For the background on the benchmark:
@article{Mee07,
  author =       {K. Meerbergen},
  title =        {Fast frequency response computation for {R}ayleigh damping},
  journal =      {International Journal for Numerical Methods in Engineering},
  volume =       {73},
  number =       {1},
  pages =        {96--106},
  year =         {2007},
  doi =          {10.1002/nme.2058},
}

References

  1. K. Meerbergen, Fast frequency response computation for Rayleigh damping, International Journal for Numerical Methods in Engineering, 73(1): 96--106, 2007.
  2. J.G. Korvink, E.B. Rudnyi, Oberwolfach Benchmark Collection, In: Dimension Reduction of Large-Scale Systems, Lecture Notes in Computational Science and Engineering, vol 45: 311--315, 2005.