CURVILINEAR COORDINATES

(Redirected from Curvilinear)
'Curvilinear coordinates' are a coordinate system for the Euclidean space based on some transformation that converts the standard Cartesian coordinate system to a coordinate system with the same number of coordinates in which the coordinate lines are curved. In the two-dimensional case, instead of Cartesian coordinates ''x'' and ''y'', e.g., ''p'' and ''q'' are used: the level curves of ''p'' and ''q'' in the ''xy''-plane. Required is that the transformation is locally invertible (a one-to-one map) at each point. This means that one can convert a point given in one coordinate system to its curvilinear coordinates and back.
Depending on the application, a curvilinear coordinate system may be simpler to use than the Cartesian coordinate system.
For instance, a physical problem with spherical symmetry defined in 'R'³ (e.g., motion in the field of a point mass/charge),
is usually easier to solve in spherical polar coordinates than in Cartesian coordinates. Also boundary conditions may enforce symmetry. One would describe the motion of a particle in a rectangular box in Cartesian coordinates, whereas one would prefer spherical coordinates for a particle in a sphere.
Many of the concepts in vector calculus, which are given in Cartesian or spherical polar coordinates, can be formulated in arbitrary curvilinear coordinates.
This gives a certain economy of thought, as it is possible to derive general expressions—valid for any curvilinear coordinate system—for concepts as gradient, divergence, curl, and the Laplacian.
Well-known examples of curvilinear systems are polar coordinates for 'R'²,
and cylinder and spherical polar coordinates for 'R'³.
The name ''curvilinear coordinates'', coined by the French mathematician Lamé, derives from the fact that the coordinate surfaces of the curvilinear systems are curved . While a Cartesian coordinate surface is a plane, e.g., ''z'' = 0 defines the ''x''-''y'' plane, the coordinate surface ''r'' = 1 in spherical polar coordinates is the surface of a unit sphere in 'R'³—which obviously is curved.

Contents

General curvilinear coordinates

Example: Spherical coordinates

Local basis

Covariant basis

Contravariant basis

Example

Line and surface integrals

Line integrals

Surface integrals

Grad, curl, div, Laplacian

References

See also

External links

General curvilinear coordinates

In Cartesian coordinates, the position of a point ''P(x,y,z)'' is determined by the intersection of three mutually perpendicular planes, ''x'' = const, ''y'' = const, ''z'' = const. The coordinates ''x, y'' and ''z'' are related to three new quantities ''q₁,q₂'', and ''q₃'' by the equations:
:''x = x(q₁,q₂,q₃)''     'direct transformation'
:''y = y(q₁,q₂,q₃)''     (curvilinear to Cartesian coordinates)
:''z = z(q₁,q₂,q₃)''
The above equation system can be solved for the arguments ''q₁, q₂'', and ''q₃'' with solutions in the form:
:''q₁ = q₁(x, y, z)''     'inverse transformation'
:''q₂ = q₂(x, y, z)''     (Cartesian to curvilinear coordinates)
:''q₃ = q₃(x, y, z)''
The transformation functions are such that there is one-to-one relationship between points in the "old" and "new" coordinates, that is, those functions are bijections, and fulfil the following requirements within their domains:
:1) They are smooth functions
:2) The Jacobian determinant
:$\{partial(q\_1,\; q\_2,\; q\_3)\; over\; partial(x,\; y,\; z)\}$
=egin{vmatrix}
rac{partial q_1}{partial x} & rac{partial q_2}{partial x} & rac{partial q_3}{partial x}
\ rac{partial q_1}{partial y} & rac{partial q_2}{partial y} & rac{partial q_3}{partial y}
\ rac{partial q_1}{partial z} & rac{partial q_2}{partial z} & rac{partial q_3}{partial z} end{vmatrix}
eq 0
is not zero; that is, the transformation is invertible according to the inverse function theorem.
A given point may be described by specifying either ''x, y, z'' or ''q₁, q₂, q₃'' while each of the inverse equations describes a surface in the new coordinates and the intersection of three such surfaces locates the point in the three-dimensional space (Fig. 1). The surfaces ''q₁'' = const, ''q₂'' = const, ''q₃'' = const are called the ''coordinate surfaces''; the space curves formed by their intersection in pairs are called the ''coordinate lines''. The ''coordinate axes'' are determined by the tangents to the coordinate lines at the intersection of three surfaces. They are not in general fixed directions in space, as is true for simple Cartesian coordinates. The quantities ''(q₁, q₂, q₃ )'' are the ''curvilinear coordinates'' of a point ''P(q₁, q₂, q₃ )''.
In general, ''(q₁, q₂ ... q_n )'' are curvilinear coordinates in n-dimensional space.

Example: Spherical coordinates

Spherical coordinates are one of the most used curvilinear coordinate system in such fields as Earth sciences, cartography, and physics (quantum physics, relativity, etc.). The curvilinear coordinates ''(q₁, q₂, q₃)'' in this system are, respectively, ''r'' (''radial distance'' or ''polar radius'', ''r'' ≥ 0), ''θ'' (''azimuth'' or ''latitude'', 0 ≤ ''θ'' ≤ 180°), and ''φ'' (''zenith'' or ''longitude'', 0 ≤ ''φ'' ≤ 360°).
The relationship between Cartesian and spherical coordinates is given by:
:''x = r'' sin ''θ'' cos ''φ''
:''y = r'' sin ''θ'' sin ''φ''
:''z = r'' cos ''θ''       'direct transformation'  (Cartesian to spherical coordinates)
Solving the above equation system for ''r'', ''θ'', and ''φ'' gives the relations between spherical and Cartesian coordinates:
:$r=sqrt\{x^2\; +\; y^2\; +\; z^2\}$
:
ight)  or  
:
ight)  or       'inverse transformation' (spherical to Cartesian coordinates)
The respective spherical coordinate surfaces are derived in terms of Cartesian coordinates by fixing the spherical coordinates in the above inverse transformations to a constant value. Thus (Fig.2), ''r'' = const are concentric spherical surfaces centered at the origin, ''O'', of the Cartesian coordinates, ''θ'' = const are circular conical surfaces with apex in ''O'' and axis the ''Oz'' axis, ''φ'' = const are half-planes bounded by the ''Oz'' axis and perpendicular to the ''xOy'' Cartesian coordinate plane. Each spherical coordinate line is formed at the pairwise intersection of the surfaces, corresponding to the other two coordinates: ''r'' lines (''radial distance'') are beams ''Or'' at the intersection of the cones ''θ'' = const and the half-planes ''φ'' = const; ''θ'' lines (''meridians'') are semi-circles formed by the intersection of the spheres ''r'' = const and the half-planes ''φ'' = const ; and ''φ'' lines (''parallels'') are circles in planes parallel to ''xOy'' at the intersection of the spheres ''r'' = const and the cones ''θ'' = const. The location of a point ''P(r,θ,φ)'' is determined by the point of intersection of the three coordinate surfaces, or, alternatively, by the point of intersection of the three coordinate lines. The ''θ'' and ''φ'' axes in ''P(r,θ,φ)'' are the mutually perpendicular (orthogonal) tangents to the meridian and parallel of this point, while the ''r'' axis is directed along the radial distance and is orthogonal to both ''θ'' and ''φ'' axes.
The surfaces described by the inverse transformations are smooth functions within their defined domains. The Jacobian (functional determinant) of the inverse transformations is:
:
=egin{vmatrix}
sin hetacosarphi & sin hetasinarphi & cos heta\
rac{1}{r}cos hetacosarphi & rac{1}{r}cos hetasinarphi & -rac{1}{r}sin heta \
-rac{1}{r}rac{sinarphi}{sin heta} & rac{1}{r}rac{cosarphi}{sin heta} & 0
end{vmatrix} = rac{1}{r^2 sin{ heta}}
eq 0

Local basis

Coordinates are used to define location or distribution of physical quantities which are scalars, vectors, or tensors. Scalars are expressed as points and their location is defined by specifying their coordinates with the use of coordinate lines or coordinate surfaces. Vectors are objects that possess two characteristics: maginitude and direction. To define a vector in terms of coordinates, an additional coordinate-associated structure, called basis, is needed. A ''basis'' in three-dimensional space is a set of three linearly independent vectors {'e'₁, 'e'₂, 'e'₃}, called ''basis vectors''. Each basis vector is associated with a coordinate in the respective dimension. Any vector can be represented as a sum of vectors ''A_n'''e'''_n'' formed by multiplication of a basis vector by a scalar coefficient, called ''component''. Each vector, then, has exactly one component in each dimension and can be represented by the vector sum: 'A' = ''A''₁'e'₁ + ''A''₂'e'₂ + ''A''₃'e'₃, where ''A_n'' and 'e'''_n'' are the respective components and basis vectors. A requirement for the coordinate system and its basis is that ''A''₁'e'₁ + ''A''₂'e'₂ + ''A''₃'e'₃ ≠ 0 when at least one of the ''A_n'' ≠ 0. This condition is called linear independence. Linear independence implies that there cannot exist bases with basis vectors of zero magnitude because the latter will give zero-magnitude vectors when multiplied by any component. Non-coplanar vectors are linearly independent, and any triple of non-coplanar vectors can serve as a basis in three dimensions.
For the general curvilinear coordinates, basis vectors and components vary from point to point. If vector 'A' whose origin is in point ''P (q₁, q₂, q₃ )'' is moved to point ''P' (q'₁, q'₂, q'₃ )'' in such a way that its direction and orientation are preserved, then the moved vector will be expressed by new components ''A'_n'' and basis vectors 'e''_n''. Therefore, the vector sum that describes vector 'A' in the new location is composed of different vectors, although the sum itself remains the same. A coordinate basis whose basis vectors change their direction and/or magnitude from point to point is called ''local basis''. All bases associated with curvilinear coordinates are necessarily local. Global bases, that is, bases composed of basis vectors that are the same in all points can be associated only with linear coordinates. A more exact, though seldom used, expression for such vector sums with local basis vectors is $mathbf\{A\}\; =\; extstyle\; sum\_\{i=1\}^n\; A\_i(q\_1ldots\; q\_n)mathbf\{e\}\_i(q\_1ldots\; q\_n)$, where the dependence of both components and basis vector on location is made explicit (''n'' is the number of dimensions). Local bases are composed of vectors with arbitrary order, magnitude, and direction and magnitude/direction vary in different points in space.
Basis vectors can be associated with a coordinate system by two methods: they can be built along the coordinate axes (colinear with axes) or they can be built to be perpendicular (normal) to the coordinate surfaces. In the first case (axis-colinear), basis vectors transform like covariant vectors while in the second case (normal to coordinate surfaces), basis vectors transform like contravariant vectors. Those two types of basis vectors are distinguished by the position of their indices: covariant vectors are designated with lower indices while contravariant vectors are designated with upper indices. Thus, depending on the method by which they are built, for a general curvilinear coordinate system there are two sets of basis vectors for every point: {'e'₁, 'e'₂, 'e'₃} is the covariant basis, and {'e'¹, 'e'², 'e'³} is the contravariant basis. A key property of the vector and tensor representation in terms of indexed components and basis vectors is ''invariance'' in the sense that vector components which transform in a covariant manner (or contravariant manner) are paired with basis vectors that transform in a contravariant manner (or covariant manner), and these operations are inverse to one another according to the transformation rules. This means that in terms, in which an index occurs two times, one of the indices in the pair must be upper and the other index must be lower. Thus in the above vector sums, basis vectors with lower indices are multiplied by components with upper indices or vice versa, so that a given vector can be represented in two ways: 'A' = ''A''¹'e'₁ + ''A''²'e'₂ + ''A''³'e'₃ = ''A''₁'e'¹ + ''A''₂'e'² + ''A''₃'e'³. Upon coordinate change, a vector transforms in the same way as its components. Therefore, a vector is covariant or contravariant if, respectively, its components are covariant or contravariant. From the above vector sums, it can be seen that contravariant vectors are represented with covariant basis vectors, and covariant vectors are represented with contravariant basis vectors. This is reflected in the Einstein summation convention according to which in the vector sums $extstyle\; sum\_\{i=1\}^n\; A^i\; mathbf\{e\}\_i$ and $extstyle\; sum\_\{k=1\}^n\; A\_i\; mathbf\{e\}^i$ the basis vectors and the summation symbols are omitted, leaving only ''Aⁱ'' and ''A_i'' which represent, respectively, a contravariant and a covariant vector.

Covariant basis

As stated above, ''contravariant vectors'' are vectors with contravariant components whose location is determined using 'covariant' basis vectors that are built along the coordinate axes. In analogy to the other coordinate elements, transformation of the covariant basis of general curvilinear coordinates is described starting from the Cartesian coordinate system whose basis is called standard basis. The standard basis is a global basis that is composed of 3 mutually orthogonal vectors {'i', 'j', 'k'} of unit length, that is, the magnitude of each basis vector equals 1. Regardless of the method of building the basis (axis-colinear or normal to coordinate surfaces), in Cartesian system the result is a single set of basis vectors, namely, the standard basis. To avoid misunderstanding, in this section the standard basis will be thought of as built along the coordinate axes.
In point ''P'', taken as an origin, let ''x'' is one of the Cartesian coordinates, and ''q₁'' is one of the curvilinear coordinates (Fig. 3). The local basis vector is 'e'₁ and it is built on the ''q₁'' axis which is a tangent to ''q₁'' curved line at the point ''P''. The axis ''q₁'' and thus the vector 'e'₁ form an angle ''α'' with the Cartesian ''x'' axis. It can be seen from triangle ''PAB'' that where |'e'₁| is the magnitude of the basis vector 'e'₁ (the scalar intercept ''PB'') and ''x'' is the projection of 'e'₁ on the ''x'' axis (the scalar intercept ''PA''). It follows, then, that and . However, this method for basis vector transformations using ''directional cosines'' is inapplicable to curvilinear coordinates for the following reason. With increasing the distance from ''P'', the angle between the curved line ''q₁'' and Cartesian axis ''x'' increasingly deviates from ''α''. At the distance ''PB'' the true angle is that which the tangent 'at point C' forms with the ''x'' axis and the latter angle is clearly different from ''α''. The angles that the ''q₁'' line and ''q₁'' axis form with the ''x'' axis become closer in value the closer one moves towards point ''P'' and become exactly equal at ''P''. Let point ''E'' is located very close to ''P'', so close that the distance ''PE'' is infinitesimally small. Then ''PE'' measured on the ''q₁'' axis almost coincides with ''PE'' measured on the ''q₁'' line. At the same time, the ratio $frac\{PD\}\{PE\}$ (''PD'' being the projection of ''PE'' on the ''x'' axis) becomes almost exactly equal to cos ''α''. Let the infinitesimally small intercepts ''PD'' and ''PE'' be labelled, respectivelly, as ''dx'' and ''dq₁''. Then and . Thus, the directional cosines can be substituted in transformations with the more exact ratios between infinitesimally small coordinate intercepts. As pointed out above, $q\_1\; equiv\; q\_1(x,y,z)$ and $x\; equiv\; x(q\_1,q\_2,q\_3)$ are smooth (continuously differentiable) functions and, therefore, the transformation ratios can be written as $frac\{dq\_1\}\{dx\}\; =\; frac\{dq\_1(x,y,z)\}\{dx\}\; =\; frac\{partial\; q\_1\}\{partial\; x\}$ and $frac\{dx\}\{dq\_1\}\; =\; frac\{dx(q\_1,q\_1,q\_3)\}\{dq\_1\}\; =\; frac\{partial\; x\}\{partial\; q\_1\}$, that is, those ratios are partial derivatives of coordinates belonging to one system with respect to coordinates belonging to the other system.
From the foregoing discussion, it follows that the component (projection) of 'e'₁ on the ''x'' axis is . Let require further that |'e'₁| = 1 (so that the local basis is normalised) and make that projection a vector directed along the ''x'' axis by multiplying it with the basis vector 'i' of the standard basis. Doing the same for the coordinates in the other 2 dimensions, 'e'₁ can be expressed as: $mathbf\{e\}\_1\; =\; frac\{partial\; x\}\{partial\; q\_1\}\; mathbf\{i\}\; +\; frac\{partial\; y\}\{partial\; q\_1\}\; mathbf\{j\}\; +\; frac\{partial\; z\}\{partial\; q\_1\}\; mathbf\{k\}$. Similar equations hold for 'e'₂ and 'e'₂ so that the standard basis {'i', 'j', 'k'} is transformed to local (ordered and normalised) basis {'e'₁, 'e'₂, 'e'₃} by the following system of equations:

frac{partial x}{partial q_1} mathbf{i} + frac{partial y}{partial q_1} mathbf{j} + frac{partial z}{partial q_1} mathbf{k} = mathbf{e}_1 \
frac{partial x}{partial q_2} mathbf{i} + frac{partial y}{partial q_2} mathbf{j} + frac{partial z}{partial q_2} mathbf{k} = mathbf{e}_2 \
frac{partial x}{partial q_3} mathbf{i} + frac{partial y}{partial q_3} mathbf{j} + frac{partial z}{partial q_3} mathbf{k} = mathbf{e}_3
end{cases}
Vectors 'e'₁, 'e'₂, and 'e'₃ at the right hand side of the above equation system are unit vectors (magnitude = 1) directed along the 3 axes of the curvilinear coordinate system. However, basis vectors in general curvilinear system are not required to be of unit length: they can be of arbitrary magnitude and direction. It can easily be shown that the condition |'e'₁| = |'e'₂| = |'e'₃| = 1 is a result of the above transformation, and not an ''a priori'' requirement imposed on the curvilinear coordinate system. Let the local basis {'e'₁, 'e'₂, 'e'₃} is not normalised, in effect, leaving the basis vectors with arbitrary magnitudes. Then, instead of 'e'₁, 'e'₂, and 'e'₃ in the right hand side, there will be $frac\{mathbf\{e\}\_1\}\{|mathbf\{e\}\_1|\}$, $frac\{mathbf\{e\}\_2\}\{|mathbf\{e\}\_2|\}$, and $frac\{mathbf\{e\}\_3\}\{|mathbf\{e\}\_3|\}$ which are again unit vectors directed along the curvilinear coordinate axes.
By analogous reasoning, but this time projecting the standard basis on the curvilinear axes ( |'i'| = |'j'| = |'k'| = 1 according to the definition of standard basis), one can obtain the inverse transformation from local basis to standard basis:

frac{partial q_1}{partial x} mathbf{e}_1 + frac{partial q_2}{partial x} mathbf{e}_2 + frac{partial q_3}{partial x} mathbf{e}_3 = mathbf{i} \
frac{partial q_1}{partial y} mathbf{e}_1 + frac{partial q_2}{partial y} mathbf{e}_2 + frac{partial q_3}{partial y} mathbf{e}_3 = mathbf{j} \
frac{partial q_1}{partial z} mathbf{e}_1 + frac{partial q_2}{partial z} mathbf{e}_2 + frac{partial q_3}{partial z} mathbf{e}_3 = mathbf{k}
end{cases}
The above systems of linear equations can be written in matrix form as $frac\{partial\; x\_i\}\{partial\; q\_k\}\; mathbf\{i\}\_i\; =\; mathbf\{e\}\_k$ and $frac\{partial\; q\_i\}\{partial\; x\_k\}\; mathbf\{e\}\_i\; =\; mathbf\{i\}\_k$ where ''x_i'' (''i'' = 1,2,3) are the Cartesian coordinates ''x, y, z'' and 'i'''_i'' are the standard basis vectors 'i, j, k'. The system matrices (that is, matrices composed of the coefficients in front of the unknowns) are, respectively, $frac\{partial\; x\_i\}\{partial\; q\_k\}$ and $frac\{partial\; q\_i\}\{partial\; x\_k\}$. At the same time, those two matrices are the Jacobian matrices ''J_ik'' and ''J^-1_ik'' of the transformations of basis vectors from curvilinear to Cartesian coordinates and ''vice versa''. In the second equation system (the inverse transformation), the unknowns are the curvilinear basis vectors which are subject to the condition that in each point of the curvilinear coordinate system there must exist one and only one set of basis vectors. This condition is satisfied iff (if and only if) the equation system has a single solution. From linear algebra, it is known that a linear equation system has a single solution only if the determinant of its system matrix is non-zero. For the second equation system, the determinant of the system matrix is $det\{J^\{-1\}\_\{ik\}\}\; =\; J^\{-1\}\; =\; frac\{partial(q\_1,\; q\_2,\; q\_3)\}\{partial(x,\; y,\; z)\}$
eq 0 which shows the rationale behind the above requirement concerning the inverse Jacobian determinant.
Another, very important, feature of the above transformations is the nature of the derivatives: in front of the Cartesian basis vectors stand derivatives of Cartesian coordinates while in front of the curvilinear basis vectors stand derivatives of curvililear coordinates. In general, the following definition holds:

'Covariant vector' is an object that in the system of coordinates ''x'' is defined by ''n'' ordered numbers or functions (components) ''a_i''(''x¹'', ''x²'', ''x³'') and in system ''q'' it is defined by ''n'' ordered components ''ā_i''(''q¹'', ''q²'', ''q²'') which are connected with ''a_i'' (''x¹'', ''x²'', ''x³'') in each point of space by the transformation: . ''Mnemonic'': Coordinates 'co-vary' with the vector.

This definition is so general that it applies to covariance in the very abstract sense, and includes not only basis vectors, but also all vectors, components, tensors, pseudovectors, and pseudotensors. It also serves to define tensors in one of their most usual treatment.
The partial derivative coefficients through which vector transformation is achieved are called also ''scale factors'' or Lamé coefficients (named after Gabriel Lamé): $h\_\{ik\}\; =\; frac\{partial\; x^i\}\{partial\; q^k\}$. However, the ''h_ik'' designation is very rarely used, being largely replaced with √''g_ik'', the components of the metric tensor.

Contravariant basis

Note that the coordinate system we choose need not be orthogonal, but for the purposes of this article, they are treated as being so. The system is defined to be orthogonal when
: $mathbf\{e\}\_\{x\_i\text{'}\}cdotmathbf\{e\}\_\{x\_j\text{'}\}\; =\; delta\_\{ij\}$
where δ_''ij'' is the Kronecker delta.
Cartesian coordinates $x\_1,x\_2,x\_3$ which have the
scalar product, are called Euclidean coordinates. It is often convenient to associate the points of Euclidean space with vectors, for example, with each point P we associate the vector (or arrow) with its tail at the origin of coordinates and its tip at P. This vector is called the radius vector with components $(x\_1,\; x\_2,\; x\_3)$. At any point P of Euclidean space we can construct the small line element
:
which is vector too.
Two vectors $h\; =\; (x\_1,\; x\_2,\; x\_3)$ and $f=(y\_l,\; y\_2,\; y\_3)$ from the same origin can be added and result is the vector with coordinates $(x\_l+\; y\_l,\; x\_2\; +\; y\_2,\; x\_3\; +\; y\_3)$. A vector can also be multiplied by any real number. The Euclidean scalar product of two (real) vectors is the number
: $lang\; f,h$
ang =sum_{i} x_{i} y_{i} ,!.
The scalar product of the vector with itself give the square of the vector
length.
The square of the length of a line element in space with scalar product is called the metric of the space. The metric of Euclidean space is
: $lang\; dmathbf\{x\},dmathbf\{x\}$
ang = dx_1^2+dx_2^2+dx_3^2 .
The same Euclidean metric in curvilinear coordinates is
: $lang\; dmathbf\{x\},dmathbf\{x\}$
ang = sum_{k=1}^3 rac{partial{x_k}}{partial{x_i'}} rac{partial{x_k}}{partial{x_j'}} dx_i' dx_j' .
The symmetric tensor
:
are called the fundamental (or metric) tensor of the Euclidean space in curvilinear coordinates.
Connection between fundamental tensor and Lamé coefficients is $g\_\{i,i\}(x\_i\text{'},x\_j\text{'})=\; h\_i^2$.

Example

If we consider polar coordinates for 'R'², note that
: $(x,\; y)=(r\; cos\; heta,\; r\; sin\; heta)\; ,!$
(r, θ) are the curvilinear coordinates, and the Jacobian determinant of the transformation (''r'',θ) → (''r'' cos θ, ''r'' sin θ) is ''r''.
The basis vectors are '''b'''_''r'' = (cos θ, sin θ), '''b'''_θ = (−''r'' sin θ, ''r'' cos θ), with unit basis vectors '''e'''_''r'' = (cos θ, sin θ), '''e'''_θ = (−sin θ, cos θ) with scale factors ''h''_''r'' = 1 and ''h''_θ= ''r''. The fundamental tensor is ''g''_1,1 =1, ''g''_2,2 =''r''², ''g''_1,2 = ''g''_2,1 =0.

Line and surface integrals

Since we use curvilinear coordinates to aid in the calculation in vector calculus, there are adjustments we need to make in the calculation of line, surface and volume integrals.

Line integrals

Normally in the calculation of line integrals we are interested in calculating
: $int\_C\; f\; ,ds\; =\; int\_a^b\; f(mathbf\{x\}(t))left|\{partial\; mathbf\{x\}\; over\; partial\; t\}$
ight|; dt
where '''x'''(''t'') parametrizes C in Cartesian coordinates.
In curvilinear coordinates, the term
: $left|\{partial\; mathbf\{x\}\; over\; partial\; t\}$
ight| = left| sum {partial mathbf{x} over partial x_i'}{partial x_i' over partial t}
ight|
by the chain rule. But from the definition of the curvilinear coordinates,
: $\{partial\; mathbf\{x\}\; over\; partial\; x\_i\text{'}\}\; =\; h\_i\; mathbf\{e\}\_\{x\_i\text{'}\}$
and thus
: $left|\{partial\; mathbf\{x\}\; over\; partial\; t\}$
ight| = sqrt{sum h_i mathbf{e}_{x_i'} {partial x_i' over partial t}}
and we can proceed normally.

Surface integrals

Likewise, if we are interested in a surface integral, the relevant calculation, with the parameterization of the surface in Cartesian coordinates is:
: $int\_S\; f\; ,ds\; =\; iint\_T\; f(mathbf\{x\}(s,\; t))\; left|\{partial\; mathbf\{x\}\; over\; partial\; s\}\; imes\; \{partial\; mathbf\{x\}\; over\; partial\; t\}$
ight| ds dt
Again, in curvilinear coordinates, the term
: $left|\{partial\; mathbf\{x\}\; over\; partial\; s\}\; imes\; \{partial\; mathbf\{x\}\; over\; partial\; t\}$
ight| = left|{partial mathbf{x} over partial x_i'}{partial x_i' over partial s} imes {partial mathbf{x} over partial x_i'}{partial x_i' over partial t}
ight|
and we make use of the definition of curvilinear coordinates again to yield
: $\{partial\; mathbf\{x\}\; over\; partial\; x\_i\text{'}\}\{partial\; x\_i\text{'}\; over\; partial\; s\}\; =\; sum\; \{partial\; x\_i\text{'}\; over\; partial\; s\}\; h\_\{x\_i\text{'}\}\; mathbf\{e\}\_\{x\_i\text{'}\}$
and
: $\{partial\; mathbf\{x\}\; over\; partial\; x\_i\text{'}\}\{partial\; x\_i\text{'}\; over\; partial\; t\}\; =\; sum\; \{partial\; x\_i\text{'}\; over\; partial\; t\}\; h\_\{x\_i\text{'}\}\; mathbf\{e\}\_\{x\_i\text{'}\}$
where the cross product, in terms of curvilinear coordinates, will be:
:
mathbf{e}_{x_1'} & mathbf{e}_{x_2'} & mathbf{e}_{x_3'} \
&& \
h_1 {partial x_1' over partial s} & h_2 {partial x_2' over partial s} & h_3 {partial x_3' over partial s} \
&& \
h_1 {partial x_1' over partial t} & h_2 {partial x_2' over partial t} & h_3 {partial x_3' over partial t} end{vmatrix}

Grad, curl, div, Laplacian

In orthogonal curvilinear coordinates, one can express the gradient, curl, divergence, and Laplacian of a function or vector field as follows:
: $$
abla f = sum_i {1 over h_i} {partial f over partial {x_i}} hat e_{x_i}
: $$

abla imes {ec v} = rac{1}{Omega} sum_i hat e_{x_i}
sum_{jk} epsilon_{ijk} h_i rac{partial h_k v_k}{partial x_j}
qquad (hbox{only for } n=3)

: $$
ablacdot {ec v} = sum_i {1 over Omega} {partial over {partial {x_i}}} left ({Omega v_i over h_i}
ight )
:$$

abla^2 f = rac{1}{Omega} sum_i rac{partial}{partial x_i} rac{Omega}{h_i^2} rac{partial f}{partial x_i},

where $Omega$ is the product of all $h\_i$
and $epsilon\_\{ijk\}$ is the Levi-Civita symbol.

References

★ M. R. Spiegel, ''Vector Analysis'', Schaum's Outline Series, New York, (1959).

★ Mathematical Methods for Physicists, Arfken, George, , , Academic Press, 1995,

See also

★ Covariance and contravariance

★ Basic introduction to the mathematics of curved spacetime

★ Orthogonal coordinates

External links

★ Derivation of Unit Vectors in Curvilinear Coordinates

★ MathWorld's page on Curvilinear Coordinates