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Voigt notation
Mathematical Concept

In mathematics, Voigt notation is a method in multilinear algebra used to represent symmetric tensors by reducing their order, commonly applied in materials science. It simplifies the expression of rank-2 stress and strain tensors, such as the 3×3 stress and strain tensors, by exploiting their symmetry to form 6×1 vectors, preserving scalar invariance. Voigt notation also reduces fourth-order stiffness and compliance tensors (Hooke's law) to 6×6 matrices, facilitating easier computation. This notation, named after physicists Woldemar Voigt and John Nye, has variants like Mandel and Kelvin notations tailored to specific applications.

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Mnemonic rule

A simple mnemonic rule for memorizing Voigt notation is as follows:

  • Write down the second order tensor in matrix form (in the example, the stress tensor)
  • Strike out the diagonal
  • Continue on the third column
  • Go back to the first element along the first row.

Voigt indexes are numbered consecutively from the starting point to the end (in the example, the numbers in blue).

The diagram below also shows the order of the indices: i j = ⇓ α = 11 22 33 23 , 32 13 , 31 12 , 21 ⇓ ⇓ ⇓ ⇓ ⇓ ⇓ 1 2 3 4 5 6 {\displaystyle {\begin{matrix}ij&=\\\Downarrow &\\\alpha &=\end{matrix}}{\begin{matrix}11&22&33&23,32&13,31&12,21\\\Downarrow &\Downarrow &\Downarrow &\Downarrow &\Downarrow &\Downarrow &\\1&2&3&4&5&6\end{matrix}}}

Mandel notation

For a symmetric tensor of second rank σ = [ σ 11 σ 12 σ 13 σ 21 σ 22 σ 23 σ 31 σ 32 σ 33 ] {\displaystyle {\boldsymbol {\sigma }}={\begin{bmatrix}\sigma _{11}&\sigma _{12}&\sigma _{13}\\\sigma _{21}&\sigma _{22}&\sigma _{23}\\\sigma _{31}&\sigma _{32}&\sigma _{33}\end{bmatrix}}} only six components are distinct, the three on the diagonal and the others being off-diagonal. Thus it can be expressed, in Mandel notation,4 as the vector σ ~ M = ⟨ σ 11 , σ 22 , σ 33 , 2 σ 23 , 2 σ 13 , 2 σ 12 ⟩ . {\displaystyle {\tilde {\sigma }}^{M}=\langle \sigma _{11},\sigma _{22},\sigma _{33},{\sqrt {2}}\sigma _{23},{\sqrt {2}}\sigma _{13},{\sqrt {2}}\sigma _{12}\rangle .}

The main advantage of Mandel notation is to allow the use of the same conventional operations used with vectors, for example: σ ~ : σ ~ = σ ~ M ⋅ σ ~ M = σ 11 2 + σ 22 2 + σ 33 2 + 2 σ 23 2 + 2 σ 13 2 + 2 σ 12 2 . {\displaystyle {\tilde {\sigma }}:{\tilde {\sigma }}={\tilde {\sigma }}^{M}\cdot {\tilde {\sigma }}^{M}=\sigma _{11}^{2}+\sigma _{22}^{2}+\sigma _{33}^{2}+2\sigma _{23}^{2}+2\sigma _{13}^{2}+2\sigma _{12}^{2}.}

A symmetric tensor of rank four satisfying D i j k l = D j i k l {\displaystyle D_{ijkl}=D_{jikl}} and D i j k l = D i j l k {\displaystyle D_{ijkl}=D_{ijlk}} has 81 components in three-dimensional space, but only 36 components are distinct. Thus, in Mandel notation, it can be expressed as D ~ M = ( D 1111 D 1122 D 1133 2 D 1123 2 D 1113 2 D 1112 D 2211 D 2222 D 2233 2 D 2223 2 D 2213 2 D 2212 D 3311 D 3322 D 3333 2 D 3323 2 D 3313 2 D 3312 2 D 2311 2 D 2322 2 D 2333 2 D 2323 2 D 2313 2 D 2312 2 D 1311 2 D 1322 2 D 1333 2 D 1323 2 D 1313 2 D 1312 2 D 1211 2 D 1222 2 D 1233 2 D 1223 2 D 1213 2 D 1212 ) . {\displaystyle {\tilde {D}}^{M}={\begin{pmatrix}D_{1111}&D_{1122}&D_{1133}&{\sqrt {2}}D_{1123}&{\sqrt {2}}D_{1113}&{\sqrt {2}}D_{1112}\\D_{2211}&D_{2222}&D_{2233}&{\sqrt {2}}D_{2223}&{\sqrt {2}}D_{2213}&{\sqrt {2}}D_{2212}\\D_{3311}&D_{3322}&D_{3333}&{\sqrt {2}}D_{3323}&{\sqrt {2}}D_{3313}&{\sqrt {2}}D_{3312}\\{\sqrt {2}}D_{2311}&{\sqrt {2}}D_{2322}&{\sqrt {2}}D_{2333}&2D_{2323}&2D_{2313}&2D_{2312}\\{\sqrt {2}}D_{1311}&{\sqrt {2}}D_{1322}&{\sqrt {2}}D_{1333}&2D_{1323}&2D_{1313}&2D_{1312}\\{\sqrt {2}}D_{1211}&{\sqrt {2}}D_{1222}&{\sqrt {2}}D_{1233}&2D_{1223}&2D_{1213}&2D_{1212}\\\end{pmatrix}}.}

Applications

It is useful, for example, in calculations involving constitutive models to simulate materials, such as the generalized Hooke's law, as well as finite element analysis,5 and Diffusion MRI.6

Hooke's law has a symmetric fourth-order stiffness tensor with 81 components (3×3×3×3), but because the application of such a rank-4 tensor to a symmetric rank-2 tensor must yield another symmetric rank-2 tensor, not all of the 81 elements are independent. Voigt notation enables such a rank-4 tensor to be represented by a 6×6 matrix. However, Voigt's form does not preserve the sum of the squares, which in the case of Hooke's law has geometric significance. This explains why weights are introduced (to make the mapping an isometry).

A discussion of invariance of Voigt's notation and Mandel's notation can be found in Helnwein (2001).7

See also

References

  1. Woldemar Voigt (1910). Lehrbuch der Kristallphysik. Teubner, Leipzig. Retrieved November 29, 2016. https://archive.org/details/bub_gb_SvPPAAAAMAAJ

  2. Klaus Helbig (1994). Foundations of anisotropy for exploration seismics. Pergamon. ISBN 0-08-037224-4. 0-08-037224-4

  3. Woldemar Voigt (1910). Lehrbuch der Kristallphysik. Teubner, Leipzig. Retrieved November 29, 2016. https://archive.org/details/bub_gb_SvPPAAAAMAAJ

  4. Jean Mandel (1965). "Généralisation de la théorie de plasticité de WT Koiter". International Journal of Solids and Structures. 1 (3): 273–295. doi:10.1016/0020-7683(65)90034-x. /wiki/Doi_(identifier)

  5. O.C. Zienkiewicz; R.L. Taylor; J.Z. Zhu (2005). The Finite Element Method: Its Basis and Fundamentals (6 ed.). Elsevier Butterworth—Heinemann. ISBN 978-0-7506-6431-8. 978-0-7506-6431-8

  6. Maher Moakher (2009). "The Algebra of Fourth-Order Tensors with Application to Diffusion MRI". Visualization and Processing of Tensor Fields. Mathematics and Visualization. Springer Berlin Heidelberg. pp. 57–80. doi:10.1007/978-3-540-88378-4_4. ISBN 978-3-540-88377-7. 978-3-540-88377-7

  7. Peter Helnwein (February 16, 2001). "Some Remarks on the Compressed Matrix Representation of Symmetric Second-Order and Fourth-Order Tensors". Computer Methods in Applied Mechanics and Engineering. 190 (22–23): 2753–2770. Bibcode:2001CMAME.190.2753H. doi:10.1016/s0045-7825(00)00263-2. /wiki/Bibcode_(identifier)