Orthogonal coordinate systems

Orthogonal transfonnation of a Cartesian vector A with components Ai, T2 and. 43 in the system of ol23, under rotation of the coordinate system to nl 2 3 is expressed by the following equation... 

Now we intend to derive nonpenetration conditions for plates and shells with cracks. Let a domain Q, d B with the smooth boundary T coincide with a mid-surface of a shallow shell. Let L, be an unclosed curve in fl perhaps intersecting L (see Fig.1.2). We assume that F, is described by a smooth function X2 = i ixi). Denoting = fl T we obtain the description of the shell (or the plate) with the crack. This means that the crack surface is a cylindrical surface in R, i.e. it can be described as X2 = i ixi), —h < z < h, where xi,X2,z) is the orthogonal coordinate system, and 2h is the thickness of the shell. Let us choose the unit normal vector V = 1, 2) at F,, ... 

Let the mid-surface of the Kirchhoff-Love plate occupy a domain flc = fl Tc, where C is a bounded domain with the smooth boundary T, and Tc is the smooth curve without self-intersections recumbent in fl (see Fig.3.4). The mid-surface of the plate is in the plane z = 0. Coordinate system (xi,X2,z) is assumed to be Descartes and orthogonal, x = xi,X2)-... 

Coordinate Systems The commonly used coordinate systems are three in number. Others may be used in specific problems (see Ref. 212). The rectangular (cartesian) system (Fig. 3-25) consists of mutually orthogonal axes x, y, z. A triple of numbers x, y, z) is used to represent each point. The cylindricm coordinate system (/ 0, z Fig. 3-26) is frequently used to locate a point in space. These are essentially the polar coordinates (/ 0) coupled with the z coordinate. As... 

A linear coordinate transformation may be illustrated by a simple two-dimensional example. The new coordinate system is defined in term of the old by means of a rotation matrix, U. In the general case the U matrix is unitary (complex elements), although for most applications it may be chosen to be orthogonal (real elements). This means that the matrix inverse is given by transposing the complex conjugate, or in the... 

In this case the basis functions (coordinate system) are non-orthogonal, the overlaps are contained in the S matrix. By multiplying from the left by S and inserting a unit matrix written in the form (13.19) may be reformulated as... 

Equation (13.20) corresponds to a symmetrical orthogonalization of the basis. The initial coordinate system, (the basis functions %) is non-orthogonal, but by multiplying with a matrix such as S the new coordinate system has orthogonal axes. 

While the foregoing discussion of stress and strain is based on a Cartesian coordinate system, any orthogonal coordinate system may be used. 

Figure 6-3. Top Structure of the T6 single crystal unit cell. The a, b, and c crystallographic axes are indicated. Molecule 1 is arbitrarily chosen, whilst the numbering of the other molecules follows the application of the factor group symmetry operations as discussed in the text. Bottom direction cosines between the molecular axes L, M, N and the orthogonal crystal coordinate system a, b, c. The a axis is orthogonal to the b monoclinic axis.

Very often, the axes of the new coordinate system, or factor space are chosen to be mutually orthogonal, but this is not an absolute requirement. Of the above examples, the axes chosen for 3 and S are generally not mutually orthogonal. 

A simple Michelson interferometer. If we place two mirrors at the end of two orthogonal arms of length L oriented along the x and y directions, a beamsplitter plate at the origin of our coordinate system and send photons in both arms trough the beamsplitter. Photons that were sent simultaneously will return on the beamsplitter with a time delay which will depend on which arm they propagated in. The round trip time difference, measured at the beamsplitter location, between photons that went in the a -arm (a -beam) and photons that went in the y arm (y-beam) is... 

We have referred to the various interactions which can cause line broadening in the solid state. One of these, which is normally not a problem in liquid state NMR, is due to the fact that the chemical shift itself is a tensor, i.e. in a coordinate system with orthogonal axes x, y and z its values along these axes can be very different. This anisotropy of the chemical shift is proportional to the magnetic field of the spectrometer (one reason why ultra-high field spectrometers are not so useful), and can lead in solid state spectra to the presence of a series of spinning sidebands, as shown in the spectra of solid polycrystalline powdered triphenylphosphine which follows (Fig. 49). In the absence of spinning, the linewidth of this sample would be around 75 ppm ... 

The PCA can be interpreted geometrically by rotation of the m-dimensional coordinate system of the original variables into a new coordinate system of principal components. The new axes are stretched in such a way that the first principal component pi is extended in direction of the maximum variance of the data, p2 orthogonal to pi in direction of the remaining maximum variance etc. In Fig. 8.15 a schematic example is presented that shows the reduction of the three dimensions of the original data into two principal components. 

Consider a coordinate system in which the orientation of the paramagnetic species is defined by the orthogonal axes and H is a vector as described in Fig. 11. The sphere has unit area and every orientation or point on the sphere is equally probable. Now the number of radicals with a magnetic field orientation between 0 and 0 + A0 and between and + A is given by the solid angle Afi where... 

The special class of transformation, known as symmetry (or unitary) transformation, preserves the shape of geometrical objects, and in particular the norm (length) of individual vectors. For this class of transformation the symmetry operation becomes equivalent to a transformation of the coordinate system. Rotation, translation, reflection and inversion are obvious examples of such transformations. If the discussion is restricted to real vector space the transformations are called orthogonal. 

Any three-dimensional orthogonal coordinate system may be specified in terms of the three coordinates q, q2 and q3. Because of the orthogonality of the coordinate surfaces, it is possible to set up, at any point, an orthogonal set of three unit vectors ex, e2, e3, in the directions of increasing qx, q2, q3, respectively. It is important to select the qt such that the unit vectors define a right-handed system of axes. The set of three unit vectors defines a Cartesian coordinate system that coincides with the curvilinear system in... 

The group of all real orthogonal matrices of order 3 and determinant +1 will be denoted by 0(3). Such matrices correspond to pure rotation or proper rotation of the coordinate system. An orthogonal matrix with determinant —1 corresponds to the product of pure rotation and inversion. Such transformations are called improper rotations. The matrix corresponding to inversion is the negative of the unit matrix... 

In PCA, for instance, each pair j, k of loading vectors is orthogonal (all scalar products bj h/, are zero) in this case, matrix B is called to be orthonormal and the projection corresponds to a rotation of the original coordinate system. 

Principal component analysis (PCA) can be considered as the mother of all methods in multivariate data analysis. The aim of PCA is dimension reduction and PCA is the most frequently applied method for computing linear latent variables (components). PCA can be seen as a method to compute a new coordinate system formed by the latent variables, which is orthogonal, and where only the most informative dimensions are used. Latent variables from PCA optimally represent the distances between the objects in the high-dimensional variable space—remember, the distance of objects is considered as an inverse similarity of the objects. PCA considers all variables and accommodates the total data structure it is a method for exploratory data analysis (unsupervised learning) and can be applied to practical any A-matrix no y-data (properties) are considered and therefore not necessary. 

The PCA scores have a very powerful mathematical property. They are orthogonal to each other, and since the scores are usually centered, any two score vectors are uncorrelated, resulting in a zero correlation coefficient. No other rotation of the coordinate system except PCA has this property. 

All PCA loading vectors are orthogonal to each other PCA is a rotation of the original orthogonal coordinate system resulting in a smaller number of axes. 

Figure 7. A "snapshot" of a typical cellulosic chain trajectory taken from a Monte Carlo sample of cellulosic chains, all based on die conformational energy map of Fig. 6. Filled circles representing glycosidic oxygens, linked by virtud bonds spanning the sugar residues (not shown), allow one to trace the instantaneous chain trajectory in a coordinate system that is rigidly fixed to the residue at one end of the chain. Projections of the chain into three mutually orthogonal planes assist in visualization of the trajectory in three dimensions.

An often-overlooked issue is the inherent non-orthogonality of coordinate systems used to portray data points. Almost universally a Euclidean coordinate system is used. This assumes that the original variables are orthogonal, that is, are uncorrelated, when it is well known that this is generally not the case. Typically, principal component analysis (PCA) is performed to generate a putative orthogonal coordinate system each of whose axes correspond to directions of maximum variance in the transformed space. This, however, is not quite cor-... 

Ligand positions about the iron are designated X, Y, Z, —X, -Y, and -Z, where X, Y, and Z, define the directions of an idealized right-handed orthogonal coordinate system centered about the iron site. 

We are now ready for the main conclusion of this chapter If all elements of a symmetry group are represented by orthogonal matrices in a consistent coordinate system, the matrices will form a group under the operation of matrix multiplication that is isomorphic to the symmetry group. The set of matrices is said to be a representation of the group. 

To tabulate the properties of symmetry species, it would be useful to work with quantities that are independent of the coordinate system, such as the traces or determinants of the matrices of a representation. But because all symmetry operations are orthogonal transformations, the determinants are all 1. The determinants of the matrices of the representations, although independent of the coordinate system, do not contain enough information. 

The mutual orthogonality of the character vectors is reminiscent of the axes of a Cartesian coordinate system, and suggests the valuable idea that the character vectors of a group form a basis for the symmetry. Any vector can be resolved into components of different symmetry types. The projection of any vector onto any symmetry species is calculable. So we have returned to the geometrical point of view ... 

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