University:
Massachusetts Institute of Technology
Course:
18.354J | Nonlinear Dynamics II: Continuum Systems
Academic year:

2019
Views:

322

Pages:

3
Author:

Bailey Hester

18.354J Nonlinear Dynamics II: Continuum Systems 1 1.1 Lecture 1 Math basics Derivatives and differential equations In this course, we will mostly deal with ordinary differential equations (ODEs) and partial differential equations (PDEs) real-valued scalar or vector fields. Usually, non-bold symbols will be reserved for scalar objects f (e.g., mass density) and bold font f = (f1 , f2 , . . .) for vector-valued objects, such as time-dependent position vectors x(t) or velocity fields v(t, x) = (v1 (t, x), v2 (t, x), . . .). ODEs are equations that contain derivatives of scalar or vector-valued or, more generally, tensor-valued functions f (x) of a single variable x. Depending on context, we will denote derivatives of such functions by df = f˙ = f 0 = fx dt (1) PDEs are equations that contain derivatives of scalar or vector-valued functions f (x1 , x2 , . . .) of more than one variable. Depending on context, we will denote partial derivatives by ∂f = ∂xi f = ∂i f = fxi = f,i ∂xi (2) In standard 3D Cartesian coordinates (x1 , x2 , x3 ) defined with respect to some global orthonormal frame Σ, spanned by the basis vectors (e1 , e2 , e3 ), the gradient-operator ∇ is defined by ∇ = ∂x e1 + ∂y e2 + ∂z e3 = 3 X ∂i e i ≡ ∂i e i , (3) i=1 where we have introduced the Einstein summation convention on the rhs. Applying ∇ to a scalar function f gives a vector ∇f = (∂1 f, ∂2 f, . . .) (4) whereas application of ∇ to a tensorial quantity depends on the choice of the product: For instance, in the case of a 3D vector field v(t, x), we can obtain a scalar field called divergence ∇ · v ≡ ∂i vi , (5a) another (pseudo-)vector field called curl ∇ ∧ v ≡ (ijk ∂j vk ) (5b) ∇v ≡ (∂i vj ). (5c) and the gradient matrix The (scalar) Laplacian operator 4 in Cartesian coordinates is defined by X 4 ≡ ∇2 ≡ ∂i ∂i = ∂ii . i Please recall how these operators look in cylindrical and spherical coordinates. (6) 1.2 Linear and nonlinear objects A mathematical operator - or, more generally, some property – P defined on vectors or functions f, g, is said to be linear, if it satisfies P(αf + βg) = αP(f ) + βP(g) (7) Important examples are derivatives, integrals and expectation values. A famous linear ODE, is the simple harmonic oscillator equation ẍ(t) = −ω 2 x(t) (8) which has fundamental sin- and cos-solutions, that can be used to construct more general solutions by superposition. An important (homogeneous) linear PDE, is Laplace’s equation ∇2 f (t, x) = 0. (9) Functions f satisfying this equation are called harmonic. Later on, we will often try to approximate nonlinear PDEs through linear PDEs. 1.3 Complex numbers and functions Although we will mostly deal with real fields in this course, it is sometimes helpful to rewrite equations in terms of complex quantities, especially, when dealing with 2D hydrodynamic problems. Complex numbers are 2D extensions of real numbers, i2 = −1 z = x + iy ∈ C , (10) with real part