Appendix

# Appendix - Appendix A VECTORS TENSORS AND MATRIX NOTATION...

This preview shows pages 1–3. Sign up to view the full content.

Appendix A VECTORS, TENSORS AND MATRIX NOTATION The objective of this section is to review some of the vector operations that you have already covered in your MATH and ENGR courses. For more details and examples you should refer to your calculus text under the chapters on vectors and vector calculus. The following notes will be divided into two parts. The ±rst will review the theory, while the second part will review how to perform various vector operations in Scienti±c Workplace. These calculations will be illustrated in Cartesian rectangular and cylindrical coordinates. First you will learn the basic operations, then you will be shown some examples, and ±nally you will work some problems. A.1 Review of Vector and Matrix Operations In Engineering, we represent physical quantities using three di²erent groups of mathematical ob- jects, i.e., scalars, vectors and tensors. A scalar quantity is represented by a real number with some appropriate units (mass, temperature, energy, time, etc.). A vector is an object that has a scalar magnitude and a direction. A vector in three-dimensional space can be described as a linear com- bination of three base vectors that have unit length and point in the positive direction of the three axes; these form the so-called standard orthonormal basis . They are denoted i , j , and k and point parallel to the x -, y -, and z -axes, respectively. Using them, we can write a three-space vector a in the following form a = a 1 i + a 2 j + a 3 k (A.1) where a 1 , a 2 , a 3 are the scalar components of the vector a with respect to the standard orthonormal basis. Note that in printed text, lower-case roman boldface letters are generally used to represent vectors, and subscripted lower-case italic letters represent their components. In handwriting, the vector a is often written as ¯ a , ~a or a . A given vector a can be expressed in matrix form as a 3 × 1 column matrix whose entries are the components of the vector: [ a ]= a 1 a 2 a 3 (A.2) 357

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
358 APPENDIX A. VECTORS, TENSORS AND MATRIX NOTATION We normally think of a vector as a column matrix, but a vector may also be written in matrix notation as a 1 × 3row matrix: [ a ]= £ a 1 a 2 a 3 ¤ (A.3) Addition of vectors is deFned component-wise by ( a + b ) i = a i + b i for all i . (A.4) Multiplication of a vector by a scalar is deFned component-wise by ( c a ) i = c · a i for all i . (A.5) The di±erence a b is simply a +( 1) b . Analogous deFnitions hold for general matrices. The above deFnitions arise from their geometrical usefulness and from obvious analogy to oper- ations on the real numbers. How to deFne a useful form of multiplication of one vector by another is not so obvious. We deFne three products of vectors: the dot product (or scalar product), the cross product (or vector product) and the dyadic product (or tensor product). All are products
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 10/01/2011 for the course ME 509 taught by Professor Wereley during the Spring '11 term at Purdue.

### Page1 / 6

Appendix - Appendix A VECTORS TENSORS AND MATRIX NOTATION...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online