Curvilinear coordinates

Coordinates, basis, and vectors For now, consider 3-D space. A point P in 3-D space (or its position vector r) can be defined using Cartesian coordinates (x, y, z) [equivalently written (x1, x2, x3)], by \mathbf{r} = x \mathbf{e}_x + y\mathbf{e}_y + z\mathbf{e}_z, where ex, ey, ez are the standard basis vectors. It can also be defined by its curvilinear coordinates (q1, q2, q3) if this triplet of numbers defines a single point in an unambiguous way. The relation between the coordinates is then given by the invertible transformation functions: : x = f^1(q^1, q^2, q^3),\, y = f^2(q^1, q^2, q^3),\, z = f^3(q^1, q^2, q^3) : q^1 = g^1(x,y,z),\, q^2 = g^2(x,y,z),\, q^3 = g^3(x,y,z) The surfaces q1 = constant, q2 = constant, q3 = constant are called the coordinate surfaces; and the space curves formed by their intersection in pairs are called the coordinate curves. The coordinate axes are determined by the tangents to the coordinate curves at the intersection of three surfaces. They are not in general fixed directions in space, which happens to be the case for simple Cartesian coordinates, and thus there is generally no natural global basis for curvilinear coordinates. In the Cartesian system, the standard basis vectors can be derived from the derivative of the location of point P with respect to the local coordinate :\mathbf{e}_x = \dfrac{\partial\mathbf{r}}{\partial x}; \; \mathbf{e}_y = \dfrac{\partial\mathbf{r}}{\partial y}; \; \mathbf{e}_z = \dfrac{\partial\mathbf{r}}{\partial z}. Applying the same derivatives to the curvilinear system locally at point P defines the natural basis vectors: :\mathbf{h}_1 = \dfrac{\partial\mathbf{r}}{\partial q^1}; \; \mathbf{h}_2 = \dfrac{\partial\mathbf{r}}{\partial q^2}; \; \mathbf{h}_3 = \dfrac{\partial\mathbf{r}}{\partial q^3}. Such a basis, whose vectors change their direction and/or magnitude from point to point is called a local basis. All bases associated with curvilinear coordinates are necessarily local. Basis vectors that are the same at all points are global bases, and can be associated only with linear or affine coordinate systems. For this article e is reserved for the standard basis (Cartesian) and h or b is for the curvilinear basis. These may not have unit length, and may also not be orthogonal. In the case that they are orthogonal at all points where the derivatives are well-defined, we define the Lamé coefficients (after Gabriel Lamé) by :h_1 = |\mathbf{h}_1|; \; h_2 = |\mathbf{h}_2|; \; h_3 = |\mathbf{h}_3| and the curvilinear orthonormal basis vectors by :\mathbf{b}_1 = \dfrac{\mathbf{h}_1}{h_1}; \; \mathbf{b}_2 = \dfrac{\mathbf{h}_2}{h_2}; \; \mathbf{b}_3 = \dfrac{\mathbf{h}_3}{h_3}. These basis vectors may well depend upon the position of P; it is therefore necessary that they are not assumed to be constant over a region. (They technically form a basis for the tangent space of \mathbb{R}^3 at P, and so are local to P.) In general, curvilinear coordinates allow the natural basis vectors hi not all mutually perpendicular to each other, and not required to be of unit length: they can be of arbitrary magnitude and direction. The use of an orthogonal basis makes vector manipulations simpler than for non-orthogonal. However, some areas of physics and engineering, particularly fluid mechanics and continuum mechanics, require non-orthogonal bases to describe deformations and fluid transport to account for complicated directional dependences of physical quantities. A discussion of the general case appears later on this page. ==Vector calculus==

Differential elements In orthogonal curvilinear coordinates, since the total differential change in r is :d\mathbf{r}=\dfrac{\partial\mathbf{r}}{\partial q^1}dq^1 + \dfrac{\partial\mathbf{r}}{\partial q^2}dq^2 + \dfrac{\partial\mathbf{r}}{\partial q^3}dq^3 = h_1 dq^1 \mathbf{b}_1 + h_2 dq^2 \mathbf{b}_2 + h_3 dq^3 \mathbf{b}_3 so scale factors are h_i = \left|\frac{\partial\mathbf{r}}{\partial q^i}\right| In non-orthogonal coordinates the length of d\mathbf{r}= dq^1 \mathbf{h}_1 + dq^2 \mathbf{h}_2 + dq^3 \mathbf{h}_3 is the positive square root of d\mathbf{r} \cdot d\mathbf{r} = dq^i dq^j \mathbf{h}_i \cdot \mathbf{h}_j (with Einstein summation convention). The six independent scalar products gij=hi.hj of the natural basis vectors generalize the three scale factors defined above for orthogonal coordinates. The nine gij are the components of the metric tensor, which has only three non zero components in orthogonal coordinates: g11=h1h1, g22=h2h2, g33=h3h3. ==Covariant and contravariant bases==

) curvilinear coordinates (q1, q2, q3). The basis and cobasis do not coincide unless the coordinate system is orthogonal. Spatial gradients, distances, time derivatives and scale factors are interrelated within a coordinate system by two groups of basis vectors: • basis vectors that are locally tangent to their associated coordinate pathline: \mathbf{b}_i=\dfrac{\partial\mathbf{r}}{\partial q^i} are contravariant vectors (denoted by lowered indices), and • basis vectors that are locally normal to the isosurface created by the other coordinates: \mathbf{b}^i=\nabla q^i are covariant vectors (denoted by raised indices), ∇ is the del operator. Note that, because of Einstein's summation convention, the position of the indices of the vectors is the opposite of that of the coordinates. Consequently, a general curvilinear coordinate system has two sets of basis vectors for every point: {b1, b2, b3} is the contravariant basis, and {b1, b2, b3} is the covariant (a.k.a. reciprocal) basis. The covariant and contravariant basis vectors types have identical direction for orthogonal curvilinear coordinate systems, but as usual have inverted units with respect to each other. Note the following important equality: \mathbf{b}^i\cdot\mathbf{b}_j = \delta^i_j wherein \delta^i_j denotes the generalized Kronecker delta. {{math proof|proof= In the Cartesian coordinate system ( \mathbf{e}_x , \mathbf{e}_y, \mathbf{e}_z ) , we can write the dot product as: : \mathbf{b}_i\cdot\mathbf{b}^j = \left( \dfrac {\partial x} {\partial q_i} , \dfrac {\partial y} {\partial q_i} , \dfrac {\partial z} {\partial q_i} \right) \cdot \left( \dfrac {\partial q_j} {\partial x} , \dfrac {\partial q_j} {\partial y} , \dfrac {\partial q_j} {\partial z} \right) = \dfrac {\partial x} {\partial q_i} \dfrac {\partial q_j} {\partial x} + \dfrac {\partial y} {\partial q_i} \dfrac {\partial q_j} {\partial y} + \dfrac {\partial z} {\partial q_i} \dfrac {\partial q_j} {\partial z} Consider an infinitesimal displacement d \mathbf{r} = dx \cdot \mathbf{e}_x + dy \cdot \mathbf{e}_y + dz \cdot \mathbf{e}_z . Let dq1, dq2 and dq3 denote the corresponding infinitesimal changes in curvilinear coordinates q1, q2 and q3 respectively. By the chain rule, dq1 can be expressed as: : dq_1 = \dfrac {\partial q_1} {\partial x} dx + \dfrac {\partial q_1} {\partial y} dy + \dfrac {\partial q_1} {\partial z} dz = \dfrac {\partial q_1} {\partial x} dx + \dfrac {\partial q_1} {\partial y} \left(\dfrac {\partial y} {\partial q_1} dq_1 + \dfrac {\partial y} {\partial q_2} dq_2 + \dfrac {\partial y} {\partial q_3} dq_3\right) + \dfrac {\partial q_1} {\partial z} \left(\dfrac {\partial z} {\partial q_1} dq_1 + \dfrac {\partial z} {\partial q_2} dq_2 + \dfrac {\partial z} {\partial q_3} dq_3\right) If the displacement dr is such that dq2 = dq3 = 0, i.e. the position vector r moves by an infinitesimal amount along the coordinate axis q2=const and q3=const, then: : dq_1 = \dfrac {\partial q_1} {\partial x} dx + \dfrac {\partial q_1} {\partial y} \dfrac {\partial y} {\partial q_1} dq_1 + \dfrac {\partial q_1} {\partial z} \dfrac {\partial z} {\partial q_1} dq_1 Dividing by dq1, and taking the limit dq1 → 0: : 1 = \dfrac {\partial q_1} {\partial x} \dfrac {\partial x} {\partial q_1} + \dfrac {\partial q_1} {\partial y} \dfrac {\partial y} {\partial q_1} + \dfrac {\partial q_1} {\partial z} \dfrac {\partial z} {\partial q_1} = \dfrac {\partial x} {\partial q_1} \dfrac {\partial q_1} {\partial x} + \dfrac {\partial y} {\partial q_1} \dfrac {\partial q_1} {\partial y} + \dfrac {\partial z} {\partial q_1} \dfrac {\partial q_1} {\partial z} or equivalently: : \mathbf{b}_1\cdot\mathbf{b}^1 = 1 Now if the displacement dr is such that dq1=dq3=0, i.e. the position vector r moves by an infinitesimal amount along the coordinate axis q1=const and q3=const, then: : 0 = \dfrac {\partial q_1} {\partial x} dx + \dfrac {\partial q_1} {\partial y} \dfrac {\partial y} {\partial q_2} dq_2 + \dfrac {\partial q_1} {\partial z} \dfrac {\partial z} {\partial q_2} dq_2 Dividing by dq2, and taking the limit dq2 → 0: : 0 = \dfrac {\partial q_1} {\partial x} \dfrac {\partial x} {\partial q_2} + \dfrac {\partial q_1} {\partial y} \dfrac {\partial y} {\partial q_2} + \dfrac {\partial q_1} {\partial z} \dfrac {\partial z} {\partial q_2} = \dfrac {\partial x} {\partial q_2} \dfrac {\partial q_1} {\partial x} + \dfrac {\partial y} {\partial q_2} \dfrac {\partial q_1} {\partial y} + \dfrac {\partial z} {\partial q_2} \dfrac {\partial q_1} {\partial z} or equivalently: : \mathbf{b}_2 \cdot \mathbf{b}^1 = 0 And so forth for the other dot products. Alternative Proof: :\delta^i_j dq^j=dq^i=\nabla q^i \cdot d\mathbf{r}=\mathbf{b}^i \cdot \dfrac{\partial\mathbf{r}}{\partial q^j} dq^j = \mathbf{b}^i \cdot \mathbf{b}_j dq^j and the Einstein summation convention is implied. }} A vector v can be specified in terms of either basis, i.e., : \mathbf{v} = v^1\mathbf{b}_1 + v^2\mathbf{b}_2 + v^3\mathbf{b}_3 = v_1\mathbf{b}^1 + v_2\mathbf{b}^2 + v_3\mathbf{b}^3 Using the Einstein summation convention, the basis vectors relate to the components by : \mathbf{v}\cdot\mathbf{b}^i = v^k\mathbf{b}_k\cdot\mathbf{b}^i = v^k\delta^i_k = v^i : \mathbf{v}\cdot\mathbf{b}_i = v_k\mathbf{b}^k\cdot\mathbf{b}_i = v_k\delta_i^k = v_i and : \mathbf{v}\cdot\mathbf{b}_i = v^k\mathbf{b}_k\cdot\mathbf{b}_i = g_{ki}v^k : \mathbf{v}\cdot\mathbf{b}^i = v_k\mathbf{b}^k\cdot\mathbf{b}^i = g^{ki}v_k where g is the metric tensor (see below). A vector can be specified with covariant coordinates (lowered indices, written vk) or contravariant coordinates (raised indices, written vk). From the above vector sums, it can be seen that contravariant coordinates are associated with covariant basis vectors, and covariant coordinates are associated with contravariant basis vectors. A key feature of the representation of vectors and tensors 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). ==Integration==

Constructing a covariant basis in one dimension Consider the one-dimensional curve shown in Fig. 3. At point P, taken as an origin, x is one of the Cartesian coordinates, and q1 is one of the curvilinear coordinates. The local (non-unit) basis vector is b1 (notated h1 above, with b reserved for unit vectors) and it is built on the q1 axis which is a tangent to that coordinate line at the point P. The axis q1 and thus the vector b1 form an angle \alpha with the Cartesian x axis and the Cartesian basis vector e1. It can be seen from triangle PAB that : \cos \alpha = \cfrac \quad \Rightarrow \quad |\mathbf{e}_1| = |\mathbf{b}_1|\cos \alpha where |e1|, |b1| are the magnitudes of the two basis vectors, i.e., the scalar intercepts PB and PA. PA is also the projection of b1 on the x axis. However, this method for basis vector transformations using directional cosines is inapplicable to curvilinear coordinates for the following reasons: • By increasing the distance from P, the angle between the curved line q1 and Cartesian axis x increasingly deviates from \alpha. • 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 \alpha. The angles that the q1 line and that 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 be 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 PD/PE (PD being the projection of PE on the x axis) becomes almost exactly equal to \cos\alpha. Let the infinitesimally small intercepts PD and PE be labelled, respectively, as dx and dq1. Then :\cos \alpha = \cfrac{dx}{dq^1} = \frac. Thus, the directional cosines can be substituted in transformations with the more exact ratios between infinitesimally small coordinate intercepts. It follows that the component (projection) of b1 on the x axis is :p^1 = \mathbf{b}_1\cdot\cfrac{\mathbf{e}_1} = |\mathbf{b}_1|\cfrac\cos\alpha = |\mathbf{b}_1|\cfrac{dx}{dq^1} \quad \Rightarrow \quad \cfrac{p^1} = \cfrac{dx}{dq^1}. If qi = qi(x1, x2, x3) and xi = xi(q1, q2, q3) are smooth (continuously differentiable) functions the transformation ratios can be written as \cfrac{\partial q^i}{\partial x_j} and \cfrac{\partial x_i}{\partial q^j}. That is, those ratios are partial derivatives of coordinates belonging to one system with respect to coordinates belonging to the other system. Constructing a covariant basis in three dimensions Doing the same for the coordinates in the other 2 dimensions, b1 can be expressed as: : \mathbf{b}_1 = p^1\mathbf{e}_1 + p^2\mathbf{e}_2 + p^3\mathbf{e}_3 = \cfrac{\partial x_1}{\partial q^1} \mathbf{e}_1 + \cfrac{\partial x_2}{\partial q^1} \mathbf{e}_2 + \cfrac{\partial x_3}{\partial q^1} \mathbf{e}_3 Similar equations hold for b2 and b3 so that the standard basis {e1, e2, e3} is transformed to a local (ordered and normalised) basis {b1, b2, b3} by the following system of equations: :\begin{align} \mathbf{b}_1 & = \cfrac{\partial x_1}{\partial q^1} \mathbf{e}_1 + \cfrac{\partial x_2}{\partial q^1} \mathbf{e}_2 + \cfrac{\partial x_3}{\partial q^1} \mathbf{e}_3 \\ \mathbf{b}_2 & = \cfrac{\partial x_1}{\partial q^2} \mathbf{e}_1 + \cfrac{\partial x_2}{\partial q^2} \mathbf{e}_2 + \cfrac{\partial x_3}{\partial q^2} \mathbf{e}_3 \\ \mathbf{b}_3 & = \cfrac{\partial x_1}{\partial q^3} \mathbf{e}_1 + \cfrac{\partial x_2}{\partial q^3} \mathbf{e}_2 + \cfrac{\partial x_3}{\partial q^3} \mathbf{e}_3 \end{align} By analogous reasoning, one can obtain the inverse transformation from local basis to standard basis: :\begin{align} \mathbf{e}_1 & = \cfrac{\partial q^1}{\partial x_1} \mathbf{b}_1 + \cfrac{\partial q^2}{\partial x_1} \mathbf{b}_2 + \cfrac{\partial q^3}{\partial x_1} \mathbf{b}_3 \\ \mathbf{e}_2 & = \cfrac{\partial q^1}{\partial x_2} \mathbf{b}_1 + \cfrac{\partial q^2}{\partial x_2} \mathbf{b}_2 + \cfrac{\partial q^3}{\partial x_2} \mathbf{b}_3 \\ \mathbf{e}_3 & = \cfrac{\partial q^1}{\partial x_3} \mathbf{b}_1 + \cfrac{\partial q^2}{\partial x_3} \mathbf{b}_2 + \cfrac{\partial q^3}{\partial x_3} \mathbf{b}_3 \end{align} Jacobian of the transformation The above systems of linear equations can be written in matrix form using the Einstein summation convention as :\cfrac{\partial x_i}{\partial q^k} \mathbf{e}_i = \mathbf{b}_k, \quad \cfrac{\partial q^i}{\partial x_k} \mathbf{b}_i = \mathbf{e}_k. This coefficient matrix of the linear system is the Jacobian matrix (and its inverse) of the transformation. These are the equations that can be used to transform a Cartesian basis into a curvilinear basis, and vice versa. In three dimensions, the expanded forms of these matrices are : \mathbf{J} = \begin{bmatrix} \cfrac{\partial x_1}{\partial q^1} & \cfrac{\partial x_1}{\partial q^2} & \cfrac{\partial x_1}{\partial q^3} \\ \cfrac{\partial x_2}{\partial q^1} & \cfrac{\partial x_2}{\partial q^2} & \cfrac{\partial x_2}{\partial q^3} \\ \cfrac{\partial x_3}{\partial q^1} & \cfrac{\partial x_3}{\partial q^2} & \cfrac{\partial x_3}{\partial q^3} \\ \end{bmatrix},\quad \mathbf{J}^{-1} = \begin{bmatrix} \cfrac{\partial q^1}{\partial x_1} & \cfrac{\partial q^1}{\partial x_2} & \cfrac{\partial q^1}{\partial x_3} \\ \cfrac{\partial q^2}{\partial x_1} & \cfrac{\partial q^2}{\partial x_2} & \cfrac{\partial q^2}{\partial x_3} \\ \cfrac{\partial q^3}{\partial x_1} & \cfrac{\partial q^3}{\partial x_2} & \cfrac{\partial q^3}{\partial x_3} \\ \end{bmatrix} In the inverse transformation (second equation system), the unknowns are the curvilinear basis vectors. For any specific location there can only exist one and only one set of basis vectors (else the basis is not well defined at that point). This condition is satisfied if and only if the equation system has a single solution. In linear algebra, a linear equation system has a single solution (non-trivial) only if the determinant of its system matrix is non-zero: : \det(\mathbf{J}^{-1}) \neq 0 which shows the rationale behind the above requirement concerning the inverse Jacobian determinant. ==Generalization to n dimensions==

The formalism extends to any finite dimension as follows. Consider the real Euclidean n-dimensional space, that is Rn = R × R × ... × R (n times) where R is the set of real numbers and × denotes the Cartesian product, which is a vector space. The coordinates of this space can be denoted by: x = (x1, x2,...,xn). Since this is a vector (an element of the vector space), it can be written as: : \mathbf{x} = \sum_{i=1}^n x_i\mathbf{e}^i where e1 = (1,0,0...,0), e2 = (0,1,0...,0), e3 = (0,0,1...,0),...,en = (0,0,0...,1) is the standard basis set of vectors for the space Rn, and i = 1, 2,...n is an index labelling components. Each vector has exactly one component in each dimension (or "axis") and they are mutually orthogonal (perpendicular) and normalized (has unit magnitude). More generally, we can define basis vectors bi so that they depend on q = (q1, q2,...,qn), i.e. they change from point to point: bi = bi(q). In which case to define the same point x in terms of this alternative basis: the coordinates with respect to this basis vi also necessarily depend on x also, that is vi = vi(x). Then a vector v in this space, with respect to these alternative coordinates and basis vectors, can be expanded as a linear combination in this basis (which simply means to multiply each basis vector ei by a number vi – scalar multiplication): : \mathbf{v} = \sum_{j=1}^n \bar{v}^j\mathbf{b}_j = \sum_{j=1}^n \bar{v}^j(\mathbf{q})\mathbf{b}_j(\mathbf{q}) The vector sum that describes v in the new basis is composed of different vectors, although the sum itself remains the same. ==Transformation of coordinates==

From a more general and abstract perspective, a curvilinear coordinate system is simply a coordinate patch on the differentiable manifold En (n-dimensional Euclidean space) that is diffeomorphic to the Cartesian coordinate patch on the manifold. Two diffeomorphic coordinate patches on a differential manifold need not overlap differentiably. With this simple definition of a curvilinear coordinate system, all the results that follow below are simply applications of standard theorems in differential topology. The transformation functions are such that there's a 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: {{ordered list : J^{-1}=\begin{vmatrix} \dfrac{\partial q^1}{\partial x_1} & \dfrac{\partial q^1}{\partial x_2} & \cdots & \dfrac{\partial q^1}{\partial x_n} \\ \dfrac{\partial q^2}{\partial x_1} & \dfrac{\partial q^2}{\partial x_2} & \cdots & \dfrac{\partial q^2}{\partial x_n} \\ \vdots & \vdots & \ddots & \vdots \\ \dfrac{\partial q^n}{\partial x_1} & \dfrac{\partial q^n}{\partial x_2} & \cdots & \dfrac{\partial q^n}{\partial x_n} \end{vmatrix} \neq 0 is not zero; meaning the transformation is invertible: xi(q) according to the inverse function theorem. The condition that the Jacobian determinant is not zero reflects the fact that three surfaces from different families intersect in one and only one point and thus determine the position of this point in a unique way. }} ==Vector and tensor algebra in three-dimensional curvilinear coordinates==

Elementary vector and tensor algebra in curvilinear coordinates is used in some of the older scientific literature in mechanics and physics and can be indispensable to understanding work from the early and mid-1900s, for example the text by Green and Zerna. Some useful relations in the algebra of vectors and second-order tensors in curvilinear coordinates are given in this section. The notation and contents are primarily from Ogden, Naghdi, Simmonds, Green and Zerna, and Ciarlet. ==Tensors in curvilinear coordinates==

A second-order tensor can be expressed as : \boldsymbol{S} = S^{ij}\mathbf{b}_i\otimes\mathbf{b}_j = S^i{}_j\mathbf{b}_i\otimes\mathbf{b}^j = S_i{}^j\mathbf{b}^i\otimes\mathbf{b}_j = S_{ij}\mathbf{b}^i\otimes\mathbf{b}^j where \scriptstyle\otimes denotes the tensor product. The components Sij are called the contravariant components, Si j the mixed right-covariant components, Si j the mixed left-covariant components, and Sij the covariant components of the second-order tensor. The components of the second-order tensor are related by : S^{ij} = g^{ik}S_k{}^j = g^{jk}S^i{}_k = g^{ik}g^{j\ell}S_{k\ell} The metric tensor in orthogonal curvilinear coordinates At each point, one can construct a small line element , so the square of the length of the line element is the scalar product dx • dx and is called the metric of the space, given by: :d\mathbf{x}\cdot d\mathbf{x} = \cfrac{\partial x_i}{\partial q^j}\cfrac{\partial x_i}{\partial q^k}dq^jdq^k . The following portion of the above equation : \cfrac{\partial x_k}{\partial q^i}\cfrac{\partial x_k}{\partial q^j} = g_{ij}(q^i,q^j) = \mathbf{b}_i\cdot\mathbf{b}_j is a symmetric tensor called the fundamental (or metric) tensor of the Euclidean space in curvilinear coordinates. Indices can be raised and lowered by the metric: : v^i = g^{ik}v_k Relation to Lamé coefficients Defining the scale factors hi by : h_ih_j = g_{ij} = \mathbf{b}_i\cdot\mathbf{b}_j \quad \Rightarrow \quad h_i =\sqrt{g_{ii}}= \left|\mathbf{b}_i\right|=\left|\cfrac{\partial\mathbf{x}}{\partial q^i}\right| gives a relation between the metric tensor and the Lamé coefficients, and : g_{ij} = \cfrac{\partial\mathbf{x}}{\partial q^i}\cdot\cfrac{\partial\mathbf{x}}{\partial q^j} = \left( h_{ki}\mathbf{e}_k\right)\cdot\left( h_{mj}\mathbf{e}_m\right) = h_{ki}h_{kj} where hij are the Lamé coefficients. For an orthogonal basis we also have: : g = g_{11}g_{22}g_{33} = h_1^2h_2^2h_3^2 \quad \Rightarrow \quad \sqrt{g} = h_1h_2h_3 = J ====Example: Polar coordinates==== If we consider polar coordinates for R2, : (x, y)=(r \cos \theta, r \sin \theta) (r, θ) are the curvilinear coordinates, and the Jacobian determinant of the transformation (r,θ) → (r cos θ, r sin θ) is r. The orthogonal basis vectors are br = (cos θ, sin θ), bθ = (−r sin θ, r cos θ). The scale factors are hr = 1 and hθ= r. The fundamental tensor is g11 =1, g22 =r2, g12 = g21 =0. The alternating tensor In an orthonormal right-handed basis, the third-order alternating tensor is defined as : \boldsymbol{\mathcal{E}} = \varepsilon_{ijk}\mathbf{e}^i\otimes\mathbf{e}^j\otimes\mathbf{e}^k In a general curvilinear basis the same tensor may be expressed as : \boldsymbol{\mathcal{E}} = \mathcal{E}_{ijk}\mathbf{b}^i\otimes\mathbf{b}^j\otimes\mathbf{b}^k = \mathcal{E}^{ijk}\mathbf{b}_i\otimes\mathbf{b}_j\otimes\mathbf{b}_k It can also be shown that : \mathcal{E}^{ijk} = \cfrac{1}{J}\varepsilon_{ijk} = \cfrac{1}{+\sqrt{g}}\varepsilon_{ijk} Christoffel symbols ;Christoffel symbols of the first kind \Gamma_{kij}: : \mathbf{b}_{i,j} = \frac{\partial \mathbf{b}_i}{\partial q^j} = \mathbf{b}^k \Gamma_{kij} \quad \Rightarrow \quad \mathbf{b}_k \cdot \mathbf{b}_{i,j} = \Gamma_{kij} where the comma denotes a partial derivative (see Ricci calculus). To express Γkij in terms of gij, : \begin{align} g_{ij,k} & = (\mathbf{b}_i\cdot\mathbf{b}_j)_{,k} = \mathbf{b}_{i,k}\cdot\mathbf{b}_j + \mathbf{b}_i\cdot\mathbf{b}_{j,k} = \Gamma_{jik} + \Gamma_{ijk}\\ g_{ik,j} & = (\mathbf{b}_i\cdot\mathbf{b}_k)_{,j} = \mathbf{b}_{i,j}\cdot\mathbf{b}_k + \mathbf{b}_i\cdot\mathbf{b}_{k,j} = \Gamma_{kij} + \Gamma_{ikj}\\ g_{jk,i} & = (\mathbf{b}_j\cdot\mathbf{b}_k)_{,i} = \mathbf{b}_{j,i}\cdot\mathbf{b}_k + \mathbf{b}_j\cdot\mathbf{b}_{k,i} = \Gamma_{kji} + \Gamma_{jki} \end{align} Since :\mathbf{b}_{i,j} = \mathbf{b}_{j,i}\quad\Rightarrow\quad\Gamma_{kij} = \Gamma_{kji} using these to rearrange the above relations gives :\Gamma_{kij} = \frac{1}{2}(g_{ik,j} + g_{jk,i} - g_{ij,k}) = \frac{1}{2}[(\mathbf{b}_i\cdot\mathbf{b}_k)_{,j} + (\mathbf{b}_j\cdot\mathbf{b}_k)_{,i} - (\mathbf{b}_i\cdot\mathbf{b}_j)_{,k}] ;Christoffel symbols of the second kind \Gamma^k{}_{ji}: :\Gamma^k{}_{ij} = g^{kl}\Gamma_{lij} = \Gamma^k{}_{ji},\quad \cfrac{\partial \mathbf{b}_i}{\partial q^j} = \mathbf{b}_k \Gamma^k{}_{ij} This implies that : \Gamma^k{}_{ij} = \cfrac{\partial \mathbf{b}_i}{\partial q^j}\cdot\mathbf{b}^k = -\mathbf{b}_i\cdot\cfrac{\partial \mathbf{b}^k}{\partial q^j}\quad since \quad\cfrac{\partial}{\partial q^j}(\mathbf{b}_i\cdot\mathbf{b}^k)=0. Other relations that follow are : \cfrac{\partial \mathbf{b}^i}{\partial q^j} = -\Gamma^i{}_{jk}\mathbf{b}^k,\quad \boldsymbol{\nabla}\mathbf{b}_i = \Gamma^k{}_{ij}\mathbf{b}_k\otimes\mathbf{b}^j,\quad \boldsymbol{\nabla}\mathbf{b}^i = -\Gamma^i{}_{jk}\mathbf{b}^k\otimes\mathbf{b}^j Vector operations {{ordered list The scalar product of two vectors in curvilinear coordinates is : \mathbf{u}\cdot\mathbf{v} = u^iv_i = u_iv^i = g_{ij}u^iv^j = g^{ij}u_iv_j The cross product of two vectors is given by : \mathbf{u}\times\mathbf{v} = \epsilon_{ijk}{u}_j{v}_k\mathbf{e}_i where \epsilon_{ijk} is the permutation symbol and \mathbf{e}_i is a Cartesian basis vector. In curvilinear coordinates, the equivalent expression is : \mathbf{u}\times\mathbf{v} = [(\mathbf{b}_m\times\mathbf{b}_n)\cdot\mathbf{b}_s]u^mv^n\mathbf{b}^s = \mathcal{E}_{smn}u^mv^n\mathbf{b}^s where \mathcal{E}_{ijk} is the third-order alternating tensor. }} ==Vector and tensor calculus in three-dimensional curvilinear coordinates==

Adjustments need to be made in the calculation of line, surface and volume integrals. For simplicity, the following restricts to three dimensions and orthogonal curvilinear coordinates. However, the same arguments apply for n-dimensional spaces. When the coordinate system is not orthogonal, there are some additional terms in the expressions. Simmonds, The magic of this theory will hardly fail to impose itself on anybody who has truly understood it; it represents a genuine triumph of the method of absolute differential calculus, founded by Gauss, Riemann, Ricci, and Levi-Civita. Vector and tensor calculus in general curvilinear coordinates is used in tensor analysis on four-dimensional curvilinear manifolds in general relativity, in the mechanics of curved shells, and in many other fields. Some useful relations in the calculus of vectors and second-order tensors in curvilinear coordinates are given in this section. The notation and contents are primarily from Ogden, Simmonds, Green and Zerna, Basar and Weichert, and Ciarlet. Let φ = φ(x) be a well defined scalar field and v = v(x) a well-defined vector field, and λ1, λ2... be parameters of the coordinates Geometric elements {{ordered list : {\partial \mathbf{x} \over \partial \lambda} = {\partial \mathbf{x} \over \partial q^i}{\partial q^i \over \partial \lambda} = \left( h_{ki}\cfrac{\partial q^i}{\partial \lambda}\right)\mathbf{b}_k is a tangent vector to C in curvilinear coordinates (using the chain rule). Using the definition of the Lamé coefficients, and that for the metric gij = 0 when i ≠ j, the magnitude is: : \left|{\partial \mathbf{x} \over \partial \lambda} \right| = \sqrt{h_{ki}h_{kj}\cfrac{\partial q^i}{\partial \lambda}\cfrac{\partial q^j}{\partial \lambda}} = \sqrt{ g_{ij}\cfrac{\partial q^i}{\partial \lambda}\cfrac{\partial q^j}{\partial \lambda}} = \sqrt{h_{i}^2\left(\cfrac{\partial q^i}{\partial \lambda}\right)^2} : {\partial \mathbf{x} \over \partial \lambda_1}\times {\partial \mathbf{x} \over \partial \lambda_2} =\left({\partial \mathbf{x} \over \partial q^i}{\partial q^i \over \partial \lambda_1}\right) \times \left({\partial \mathbf{x} \over \partial q^j}{\partial q^j \over \partial \lambda_2}\right) = \mathcal{E}_{kmp}\left( h_{ki}{\partial q^i \over \partial \lambda_1}\right)\left(h_{mj}{\partial q^j \over \partial \lambda_2}\right) \mathbf{b}_p where \mathcal{E} is the permutation symbol. In determinant form: :{\partial \mathbf{x} \over \partial \lambda_1}\times {\partial \mathbf{x} \over \partial \lambda_2} =\begin{vmatrix} \mathbf{e}_1 & \mathbf{e}_2 & \mathbf{e}_3 \\ h_{1i} \dfrac{\partial q^i}{\partial \lambda_1} & h_{2i} \dfrac{\partial q^i}{\partial \lambda_1} & h_{3i} \dfrac{\partial q^i }{\partial \lambda_1} \\ h_{1j} \dfrac{\partial q^j}{\partial \lambda_2} & h_{2j} \dfrac{\partial q^j}{\partial \lambda_2} & h_{3j} \dfrac{\partial q^j }{\partial \lambda_2} \end{vmatrix} }} Integration : Differentiation The expressions for the gradient, divergence, and Laplacian can be directly extended to n-dimensions, however the curl is only defined in 3D. The vector field bi is tangent to the qi coordinate curve and forms a natural basis at each point on the curve. This basis, as discussed at the beginning of this article, is also called the covariant curvilinear basis. We can also define a reciprocal basis, or contravariant curvilinear basis, bi. All the algebraic relations between the basis vectors, as discussed in the section on tensor algebra, apply for the natural basis and its reciprocal at each point x. : ==Fictitious forces in general curvilinear coordinates==

By definition, if a particle with no forces acting on it has its position expressed in an inertial coordinate system, (x1, x2, x3, t), then there it will have no acceleration (d2xj/dt2 = 0). In this context, a coordinate system can fail to be "inertial" either due to non-straight time axis or non-straight space axes (or both). In other words, the basis vectors of the coordinates may vary in time at fixed positions, or they may vary with position at fixed times, or both. When equations of motion are expressed in terms of any non-inertial coordinate system (in this sense), extra terms appear, called Christoffel symbols. Strictly speaking, these terms represent components of the absolute acceleration (in classical mechanics), but we may also choose to continue to regard d2xj/dt2 as the acceleration (as if the coordinates were inertial) and treat the extra terms as if they were forces, in which case they are called fictitious forces. The component of any such fictitious force normal to the path of the particle and in the plane of the path's curvature is then called centrifugal force. This more general context makes clear the correspondence between the concepts of centrifugal force in rotating coordinate systems and in stationary curvilinear coordinate systems. (Both of these concepts appear frequently in the literature.) For a simple example, consider a particle of mass m moving in a circle of radius r with angular speed w relative to a system of polar coordinates rotating with angular speed W. The radial equation of motion is mr” = Fr + mr(w + W)2. Thus the centrifugal force is mr times the square of the absolute rotational speed A = w + W of the particle. If we choose a coordinate system rotating at the speed of the particle, then W = A and w = 0, in which case the centrifugal force is mrA2, whereas if we choose a stationary coordinate system we have W = 0 and w = A, in which case the centrifugal force is again mrA2. The reason for this equality of results is that in both cases the basis vectors at the particle's location are changing in time in exactly the same way. Hence these are really just two different ways of describing exactly the same thing, one description being in terms of rotating coordinates and the other being in terms of stationary curvilinear coordinates, both of which are non-inertial according to the more abstract meaning of that term. When describing general motion, the actual forces acting on a particle are often referred to the instantaneous osculating circle tangent to the path of motion, and this circle in the general case is not centered at a fixed location, and so the decomposition into centrifugal and Coriolis components is constantly changing. This is true regardless of whether the motion is described in terms of stationary or rotating coordinates. ==See also==