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{{Other uses|Rotation operator (disambiguation){{!}}Rotation operator}}
 
This article derives the main properties of rotations in 3-dimensional space.
 
The three [[Euler angles|Euler rotations]] are one way to bring a [[rigid body]] to any desired orientation by sequentially making [[rotations]] about axis' fixed relative to the object.  However, this can also be achieved with one single rotation ([[Euler's rotation theorem]]). Using the concepts of [[linear algebra]] it is shown how this single
rotation can be performed.
 
==Mathematical formulation==
Let
:<math>\hat e_1\ ,\ \hat e_2\ ,\ \hat e_3</math>
 
be a [[coordinate system]] fixed in the body that through a change in orientation is brought to the new directions
:<math>\mathbf{A}\hat e_1\ ,\ \mathbf{A}\hat e_2\ ,\ \mathbf{A}\hat e_3.</math>
 
Any [[euclidean vector|vector]]
:<math>\bar x\ =x_1\hat e_1+x_2\hat e_2+x_3\hat e_3</math>
 
rotating with the body is then brought to the new direction
:<math>\mathbf{A}\bar x\ =x_1\mathbf{A}\hat e_1+x_2\mathbf{A}\hat e_2+x_3\mathbf{A}\hat e_3</math>
 
i.e. this is a [[linear operator]]
 
The [[Matrix (mathematics)|matrix]] of this [[Operator (mathematics)|operator]] relative to the coordinate system
:<math>\hat e_1\ ,\ \hat e_2\ ,\ \hat e_3</math>
 
is
:<math>
\begin{bmatrix}
  A_{11} & A_{12} & A_{13} \\
  A_{21} & A_{22} & A_{23} \\
  A_{31} & A_{32} & A_{33}
\end{bmatrix} =
\begin{bmatrix}
  \langle\hat e_1 | \mathbf{A}\hat e_1 \rangle & \langle\hat e_1 | \mathbf{A}\hat e_2 \rangle & \langle\hat e_1 | \mathbf{A}\hat e_3 \rangle \\
  \langle\hat e_2 | \mathbf{A}\hat e_1 \rangle & \langle\hat e_2 | \mathbf{A}\hat e_2 \rangle & \langle\hat e_2 | \mathbf{A}\hat e_3 \rangle \\
  \langle\hat e_3 | \mathbf{A}\hat e_1 \rangle & \langle\hat e_3 | \mathbf{A}\hat e_2 \rangle & \langle\hat e_3 | \mathbf{A}\hat e_3 \rangle
\end{bmatrix}
</math>
 
As
:<math> \sum_{k=1}^3 A_{ki}A_{kj}= \langle \mathbf{A}\hat e_i | \mathbf{A}\hat e_j \rangle
= \begin{cases}
0 & i\neq j, \\                                                                                1 & i = j,
\end{cases}
</math>
 
or equivalently in matrix notation
 
:<math>
\begin{bmatrix}
  A_{11} & A_{12} & A_{13} \\
  A_{21} & A_{22} & A_{23} \\
  A_{31} & A_{32} & A_{33}
\end{bmatrix}^T
\begin{bmatrix}
  A_{11} & A_{12} & A_{13} \\
  A_{21} & A_{22} & A_{23} \\
  A_{31} & A_{32} & A_{33}
\end{bmatrix} =
\begin{bmatrix}
  1 & 0 & 0 \\
  0 & 1 & 0 \\
  0 & 0 & 1
\end{bmatrix}
</math>
the matrix is [[Orthogonal matrix|orthogonal]] and as a "right hand" base vector system is re-orientated into another "right hand" system the [[determinant]] of this matrix has the value 1.
 
===Rotation around an axis===
Let
 
:<math>\hat e_1\ ,\ \hat e_2\ ,\ \hat e_3</math>
 
be an orthogonal positively oriented base vector system in <math>R^3</math>.
 
The linear operator
 
"Rotation with the angle <math>\theta</math> around the axis defined by <math>\hat e_3</math>"
 
has the matrix representation
 
:<math>
\begin{bmatrix}
  Y_1  \\
  Y_2  \\
  Y_3
\end{bmatrix}
=
\begin{bmatrix}
  \cos\theta & -\sin\theta & 0 \\
  \sin\theta &  \cos\theta & 0 \\
          0 &          0 & 1
\end{bmatrix}
\begin{bmatrix}
  X_1  \\
  X_2  \\
  X_3
\end{bmatrix}
</math>
 
relative to this basevector system.
 
This then means that a vector
 
:<math>
\bar x=\begin{bmatrix}
  \hat e_1 & \hat e_2 & \hat e_3
\end{bmatrix}
\begin{bmatrix}
  X_1  \\
  X_2  \\
  X_3
\end{bmatrix}
</math>
 
is rotated to the vector
 
:<math>
\bar y=\begin{bmatrix}
  \hat e_1 & \hat e_2 & \hat e_3
\end{bmatrix}
\begin{bmatrix}
  Y_1  \\
  Y_2  \\
  Y_3
\end{bmatrix}
</math>
 
by the linear operator.
 
The [[determinant]] of this matrix is
 
:<math>
\det
\begin{bmatrix}
  \cos\theta  & -\sin\theta & 0\\
  \sin\theta  &  \cos\theta & 0\\
          0  &          0 & 1
\end{bmatrix}=1
</math>
 
and the [[characteristic polynomial]] is
 
:<math>
\begin{align}
\det\begin{bmatrix}
  \cos\theta -\lambda  & -\sin\theta          & 0        \\
  \sin\theta          &  \cos\theta -\lambda & 0        \\
                    0 &                    0 & 1-\lambda
\end{bmatrix}
&=\big({(\cos\theta -\lambda)}^2 + {\sin\theta}^2 \big)(1-\lambda) \\
&=-\lambda^3+(2\ \cos\theta\ +\ 1)\ \lambda^2 - (2\ \cos\theta\ +\ 1)\ \lambda +1 \\
\end{align}
</math>
 
The matrix is symmetric if and only if <math>\sin\theta=0</math>, i.e. for <math>\theta=0</math>
and for <math>\theta=\pi</math>.
 
The case <math>\theta=0</math> is the trivial case of an identity operator.
 
For the case <math>\theta=\pi</math> the [[characteristic polynomial]] is
 
:<math>
-(\lambda-1){(\lambda +1)}^2
</math>
 
i.e. the rotation operator has the [[eigenvalue]]s
:<math>
\lambda=1 \quad \lambda=-1
</math>
 
The [[eigenspace]] corresponding to <math>\lambda=1</math> is all vectors on the rotation axis, i.e. all vectors
 
:<math>
\bar x  =\alpha \ \hat e_3 \quad -\infty <\alpha < \infty
</math>
 
The [[eigenspace]] corresponding to <math>\lambda=-1</math> consists of all vectors orthogonal to the rotation axis, i.e. all vectors
 
:<math>
\bar x  =\alpha \ \hat e_1 + \beta \ \hat e_2 \quad -\infty <\alpha < \infty \quad -\infty <\beta < \infty
</math>
 
For all other values of <math>\theta</math> the matrix is un-symmetric and as <math>{\sin\theta}^2 > 0</math> there is
only the eigenvalue <math>\lambda=1</math> with the one-dimensional [[eigenspace]] of the vectors on the rotation axis:
 
:<math>
\bar x  =\alpha \ \hat e_3 \quad -\infty <\alpha < \infty
</math>
 
The rotation matrix by angle <math>\theta</math> around a general axis of rotation
<math>
\mathbf{k} = \left[\begin{array}{ccc}
k_1  \\
k_2 \\
k_3
\end{array}\right]
</math>
is given by [[Rodrigues' rotation formula]].
: <math>
  R = I \cos\theta + [\mathbf{k}]_\times \sin\theta + (1 - \cos\theta) \mathbf{k} \mathbf{k}^\mathsf{T}
</math>,
 
where <math>I</math> is the [[identity matrix]] and <math>[\mathbf{k}]_\times</math> is the [[Hodge_star | dual 2-form]] of <math>\mathbf{k}</math> or
[[Cross_product | cross product matrix]],
 
: <math> [\mathbf{k}]_\times  =
\left[\begin{array}{ccc}
0 & -k_3 & k_2 \\
k_3 & 0 & -k_1 \\
-k_2 & k_1 & 0
\end{array}\right]
</math>.
 
Note that <math>[\mathbf{k}]_\times </math> satisfies <math>[\mathbf{k}]_\times \mathbf{v} = \mathbf{k}\times\mathbf{v} </math> for all  <math>\mathbf{v}</math>.
 
===The general case===
The operator
 
"Rotation with the angle <math>\theta</math> around a specified axis"
 
discussed above is an orthogonal mapping and its matrix relative to any base vector system is therefore an
[[orthogonal matrix]] . Furthermore its determinant  has the value 1.
A non-trivial fact is the opposite, i.e. that for any orthogonal linear mapping in <math>R^3</math> having
determinant = 1 there exist base vectors
 
:<math>\hat e_1\ ,\ \hat e_2\ ,\ \hat e_3</math>
 
such that the matrix takes the "canonical form"
 
:<math>
\begin{bmatrix}
\cos\theta & -\sin\theta & 0 \\
\sin\theta &  \cos\theta & 0 \\
          0 &          0 & 1\end{bmatrix}
</math>
 
for some value of <math>\theta</math>.
 
In fact, if a linear operator has the [[orthogonal matrix]]
 
:<math>
\begin{bmatrix}
  A_{11} & A_{12} & A_{13} \\
  A_{21} & A_{22} & A_{23} \\
  A_{31} & A_{32} & A_{33}
\end{bmatrix}
</math>
relative some base vector system
:<math>\hat f_1\ ,\ \hat f_2\ ,\ \hat f_3</math>
 
and this matrix is symmetric, the "Symmetric operator theorem" valid in <math>R^n</math> (any dimension) applies saying
 
that it has ''n'' orthogonal eigenvectors.  This means for the 3-dimensional case that there exists a coordinate system
:<math>\hat e_1\ ,\ \hat e_2\ ,\ \hat e_3</math>
 
such that the matrix takes the form
:<math>
\begin{bmatrix}
  B_{11} &    0 &    0 \\
      0  & B_{22} &    0 \\
      0  &    0 & B_{33}
\end{bmatrix}
</math>
As it is an orthogonal matrix these diagonal elements <math>B_{ii}</math> are either 1 or &minus;1. As the determinant is 1 these elements
are either all 1 or one of the elements is 1 and the other two are &minus;1.
 
In the first case it is the trivial identity operator corresponding
to  <math>\theta=0</math>.
 
In the second case it has the form
 
:<math>
\begin{bmatrix}
    -1  &    0 &    0 \\
      0  &    -1 &    0 \\
      0  &    0 &    1
\end{bmatrix}
</math>
 
if the basevectors are numbered such that the one with eigenvalue 1 has index 3. This matrix is then of the desired form for <math>\theta=\pi</math>.
 
If the matrix is un-symmetric, the vector
:<math>
\bar E = \alpha_1\ \hat f_1 + \alpha_2\ \hat f_2 + \alpha_3\ \hat f_3
</math>
 
where
 
:<math>\alpha_1=\frac{A_{32}-A_{23} }{2} </math>
:<math>\alpha_2=\frac{A_{13}-A_{31}}{2}</math>
:<math>\alpha_3=\frac{A_{21}-A_{12}}{2}</math>
 
is non-zero. This vector is an eigenvector with eigenvalue
 
:<math>
\lambda=1
</math>
 
Setting
:<math>
\hat e_3=\frac{\bar E}{|\bar E|}
</math>
 
and selecting any two orthogonal unit vectors in the plane orthogonal to <math>\hat e_3</math>:
 
:<math>\hat e_1\ ,\ \hat e_2</math>
 
such that
 
:<math>\hat e_1\ ,\ \hat e_2,\ \hat e_3</math>
 
form a positively oriented triple, the operator takes the desired form with
:<math>\cos \theta=\frac{A_{11}+A_{22}+A_{33}-1}{2}</math>
:<math>\sin \theta=|\bar{E}|</math>
 
The expressions above are in fact valid also for the case of a symmetric
rotation operator corresponding to a rotation with <math>\theta = 0</math>
or <math>\theta = \pi</math>. But the difference is that for <math>\theta = \pi</math>
the vector
:<math>
\bar E = \alpha_1\ \hat f_1 + \alpha_2\ \hat f_2 + \alpha_3\ \hat f_3
</math>
 
is zero and of no use for finding the eigenspace of eigenvalue 1, i.e. the
rotation axis.
 
Defining <math>E_4</math> as <math>\cos \theta</math> the matrix for the
rotation operator is
 
:<math>
\frac{1-E_4}{{E_1}^2+{E_2}^2+{E_3}^2}
\begin{bmatrix}
E_1 E_1 & E_1 E_2 & E_1 E_3 \\
E_2 E_1 & E_2 E_2 & E_2 E_3 \\
E_3 E_1 & E_3 E_2 & E_3 E_3
\end{bmatrix}
+
\begin{bmatrix}
E_4 & -E_3 &  E_2 \\
E_3 &  E_4 & -E_1 \\
-E_2 &  E_1 &  E_4
\end{bmatrix}
</math>
 
provided that
 
:<math>
{E_1}^2+{E_2}^2+{E_3}^2 > 0
</math>
 
i.e. except for the cases <math>\theta=0</math> (the identity operator) and <math>\theta=\pi</math>
 
==Quaternions==
{{Main|Quaternions and spatial rotation}}
 
Quaternions are defined similar to <math>E_1\ ,\ E_2\ ,\ E_3\ ,\ E_4</math> with
the difference that the half angle  <math>\frac{\theta}{2}</math> is used
instead of the full angle <math>\theta</math>.
 
This means that the first 3 components <math>q_1\ ,\ q_2\ ,\ q_3\ </math> are components of a vector defined from
 
:<math>
q_1\ \hat{f_1}\ +\ q_2\ \hat{f_2}\ +\ \ q_3\ \hat{f_1}\ =\ \sin \frac{\theta}{2}\quad \hat{e_3}=\frac{\sin \frac{\theta}{2}}{\sin\theta}\quad \bar E
</math>
and that the fourth component is the scalar
:<math>
q_4=\cos \frac{\theta}{2}
</math>
 
As the angle <math>\theta</math> defined from the canonical form is in the interval
:<math>0 \le \theta \le \pi</math>
 
one would normally have that <math>q_4 \ge 0</math>. But a "dual" representation of a rotation with quaternions
is used, i.e.
:<math>q_1\ ,\ q_2\ ,\ q_3\ ,\ q_4\ </math>
 
and
:<math>-q_1\ ,\ -q_2\ ,\ -q_3\ ,\ -q_4\ </math>
 
are two alternative representations of one and the same rotation.
 
The entities <math>E_k</math> are defined from the quaternions by
:<math> E_1=2 q_4 q_1</math>
:<math> E_2=2 q_4 q_2</math>
:<math> E_3=2 q_4 q_3</math>
:<math> E_4={q_4}^2 -({q_1}^2+{q_2}^2+{q_3}^2)</math>
 
Using quaternions the matrix of the rotation operator is
:<math>\begin{bmatrix}
2({q_1}^2+{q_4}^2)-1        &2({q_1}{q_2}-{q_3}{q_4})      &2({q_1}{q_3}+{q_2}{q_4})  \\
2({q_1}{q_2}+{q_3}{q_4})    &2({q_2}^2+{q_4}^2)-1          &2({q_2}{q_3}-{q_1}{q_4})  \\
2({q_1}{q_3}-{q_2}{q_4})    &2({q_2}{q_3}+{q_1}{q_4})      &2({q_3}^2+{q_4}^2)-1    \\
\end{bmatrix}</math>
 
==Numerical example==
 
Consider the reorientation corresponding to the [[Euler angle]]s
<math>
\alpha=10^\circ \quad \beta=20^\circ \quad \gamma=30^\circ \quad
</math>
relative a given base vector system
:<math>\hat f_1\ ,\ \hat f_2,\ \hat f_3</math>
 
Corresponding matrix relative to this base vector system is (see [[Euler angles#Matrix orientation]])
 
:<math>
\begin{bmatrix}
  0.771281 & -0.633718 &  0.059391 \\
  0.613092 &  0.714610 & -0.336824 \\
  0.171010 &  0.296198 &  0.939693
\end{bmatrix}
</math>
 
and the quaternion is
:<math>
(0.171010,\ -0.030154,\ 0.336824,\ 0.925417)
</math>
 
The canonical form of this operator
:<math>
\begin{bmatrix}
  \cos\theta  & -\sin\theta & 0\\
  \sin\theta  &  \cos\theta & 0\\
          0  &          0 & 1
\end{bmatrix}
</math>
with <math>\theta=44.537^\circ </math> is obtained with
:<math>\hat e_3=(0.451272,-0.079571,0.888832)</math>
 
The quaternion relative to this new system is then
:<math>
(0,\ 0,\ 0.378951,\ 0.925417) = (0,\ 0,\ \sin\frac{\theta}{2},\ \cos\frac{\theta}{2})
</math>
 
Instead of making the three Euler rotations
 
:<math>10^\circ,20^\circ,30^\circ</math>
 
the same orientation can be reached with one single rotation of size <math>44.537^\circ</math> around <math>\hat e_3</math>
 
==References==
* {{citation |title=An Introduction to the Theory of Linear Spaces|first=Georgi|last= Shilov|author-link =Georgii Evgen'evich Shilov|publisher= Prentice-Hall|year=1961|id=Library of Congress 61-13845}}.
 
[[Category:Linear algebra]]
[[Category:Kinematics]]

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This article derives the main properties of rotations in 3-dimensional space.

The three Euler rotations are one way to bring a rigid body to any desired orientation by sequentially making rotations about axis' fixed relative to the object. However, this can also be achieved with one single rotation (Euler's rotation theorem). Using the concepts of linear algebra it is shown how this single rotation can be performed.

Mathematical formulation

Let

e^1,e^2,e^3

be a coordinate system fixed in the body that through a change in orientation is brought to the new directions

Ae^1,Ae^2,Ae^3.

Any vector

x¯=x1e^1+x2e^2+x3e^3

rotating with the body is then brought to the new direction

Ax¯=x1Ae^1+x2Ae^2+x3Ae^3

i.e. this is a linear operator

The matrix of this operator relative to the coordinate system

e^1,e^2,e^3

is

[A11A12A13A21A22A23A31A32A33]=[e^1|Ae^1e^1|Ae^2e^1|Ae^3e^2|Ae^1e^2|Ae^2e^2|Ae^3e^3|Ae^1e^3|Ae^2e^3|Ae^3]

As

k=13AkiAkj=Ae^i|Ae^j={0ij,1i=j,

or equivalently in matrix notation

[A11A12A13A21A22A23A31A32A33]T[A11A12A13A21A22A23A31A32A33]=[100010001]

the matrix is orthogonal and as a "right hand" base vector system is re-orientated into another "right hand" system the determinant of this matrix has the value 1.

Rotation around an axis

Let

e^1,e^2,e^3

be an orthogonal positively oriented base vector system in R3.

The linear operator

"Rotation with the angle θ around the axis defined by e^3"

has the matrix representation

[Y1Y2Y3]=[cosθsinθ0sinθcosθ0001][X1X2X3]

relative to this basevector system.

This then means that a vector

x¯=[e^1e^2e^3][X1X2X3]

is rotated to the vector

y¯=[e^1e^2e^3][Y1Y2Y3]

by the linear operator.

The determinant of this matrix is

det[cosθsinθ0sinθcosθ0001]=1

and the characteristic polynomial is

det[cosθλsinθ0sinθcosθλ0001λ]=((cosθλ)2+sinθ2)(1λ)=λ3+(2cosθ+1)λ2(2cosθ+1)λ+1

The matrix is symmetric if and only if sinθ=0, i.e. for θ=0 and for θ=π.

The case θ=0 is the trivial case of an identity operator.

For the case θ=π the characteristic polynomial is

(λ1)(λ+1)2

i.e. the rotation operator has the eigenvalues

λ=1λ=1

The eigenspace corresponding to λ=1 is all vectors on the rotation axis, i.e. all vectors

x¯=αe^3<α<

The eigenspace corresponding to λ=1 consists of all vectors orthogonal to the rotation axis, i.e. all vectors

x¯=αe^1+βe^2<α<<β<

For all other values of θ the matrix is un-symmetric and as sinθ2>0 there is only the eigenvalue λ=1 with the one-dimensional eigenspace of the vectors on the rotation axis:

x¯=αe^3<α<

The rotation matrix by angle θ around a general axis of rotation k=[k1k2k3] is given by Rodrigues' rotation formula.

R=Icosθ+[k]×sinθ+(1cosθ)kkT,

where I is the identity matrix and [k]× is the dual 2-form of k or cross product matrix,

[k]×=[0k3k2k30k1k2k10].

Note that [k]× satisfies [k]×v=k×v for all v.

The general case

The operator

"Rotation with the angle θ around a specified axis"

discussed above is an orthogonal mapping and its matrix relative to any base vector system is therefore an orthogonal matrix . Furthermore its determinant has the value 1. A non-trivial fact is the opposite, i.e. that for any orthogonal linear mapping in R3 having determinant = 1 there exist base vectors

e^1,e^2,e^3

such that the matrix takes the "canonical form"

[cosθsinθ0sinθcosθ0001]

for some value of θ.

In fact, if a linear operator has the orthogonal matrix

[A11A12A13A21A22A23A31A32A33]

relative some base vector system

f^1,f^2,f^3

and this matrix is symmetric, the "Symmetric operator theorem" valid in Rn (any dimension) applies saying

that it has n orthogonal eigenvectors. This means for the 3-dimensional case that there exists a coordinate system

e^1,e^2,e^3

such that the matrix takes the form

[B11000B22000B33]

As it is an orthogonal matrix these diagonal elements Bii are either 1 or −1. As the determinant is 1 these elements are either all 1 or one of the elements is 1 and the other two are −1.

In the first case it is the trivial identity operator corresponding to θ=0.

In the second case it has the form

[100010001]

if the basevectors are numbered such that the one with eigenvalue 1 has index 3. This matrix is then of the desired form for θ=π.

If the matrix is un-symmetric, the vector

E¯=α1f^1+α2f^2+α3f^3

where

α1=A32A232
α2=A13A312
α3=A21A122

is non-zero. This vector is an eigenvector with eigenvalue

λ=1

Setting

e^3=E¯|E¯|

and selecting any two orthogonal unit vectors in the plane orthogonal to e^3:

e^1,e^2

such that

e^1,e^2,e^3

form a positively oriented triple, the operator takes the desired form with

cosθ=A11+A22+A3312
sinθ=|E¯|

The expressions above are in fact valid also for the case of a symmetric rotation operator corresponding to a rotation with θ=0 or θ=π. But the difference is that for θ=π the vector

E¯=α1f^1+α2f^2+α3f^3

is zero and of no use for finding the eigenspace of eigenvalue 1, i.e. the rotation axis.

Defining E4 as cosθ the matrix for the rotation operator is

1E4E12+E22+E32[E1E1E1E2E1E3E2E1E2E2E2E3E3E1E3E2E3E3]+[E4E3E2E3E4E1E2E1E4]

provided that

E12+E22+E32>0

i.e. except for the cases θ=0 (the identity operator) and θ=π

Quaternions

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Quaternions are defined similar to E1,E2,E3,E4 with the difference that the half angle θ2 is used instead of the full angle θ.

This means that the first 3 components q1,q2,q3 are components of a vector defined from

q1f1^+q2f2^+q3f1^=sinθ2e3^=sinθ2sinθE¯

and that the fourth component is the scalar

q4=cosθ2

As the angle θ defined from the canonical form is in the interval

0θπ

one would normally have that q40. But a "dual" representation of a rotation with quaternions is used, i.e.

q1,q2,q3,q4

and

q1,q2,q3,q4

are two alternative representations of one and the same rotation.

The entities Ek are defined from the quaternions by

E1=2q4q1
E2=2q4q2
E3=2q4q3
E4=q42(q12+q22+q32)

Using quaternions the matrix of the rotation operator is

[2(q12+q42)12(q1q2q3q4)2(q1q3+q2q4)2(q1q2+q3q4)2(q22+q42)12(q2q3q1q4)2(q1q3q2q4)2(q2q3+q1q4)2(q32+q42)1]

Numerical example

Consider the reorientation corresponding to the Euler angles α=10β=20γ=30 relative a given base vector system

f^1,f^2,f^3

Corresponding matrix relative to this base vector system is (see Euler angles#Matrix orientation)

[0.7712810.6337180.0593910.6130920.7146100.3368240.1710100.2961980.939693]

and the quaternion is

(0.171010,0.030154,0.336824,0.925417)

The canonical form of this operator

[cosθsinθ0sinθcosθ0001]

with θ=44.537 is obtained with

e^3=(0.451272,0.079571,0.888832)

The quaternion relative to this new system is then

(0,0,0.378951,0.925417)=(0,0,sinθ2,cosθ2)

Instead of making the three Euler rotations

10,20,30

the same orientation can be reached with one single rotation of size 44.537 around e^3

References

  • Many property agents need to declare for the PIC grant in Singapore. However, not all of them know find out how to do the correct process for getting this PIC scheme from the IRAS. There are a number of steps that you need to do before your software can be approved.

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