Classification, Types of Equations, Boundary and Initial Conditions

One of the main goals of the theory of partial differential equations is to express the unknown

function of several independent variables from an identity where this function appears together

with its partial derivatives. In the sequel, we keep the following notation: denotes the time

variable, x, y, z, stand for the spatial variables. The general partial differential equation in 3D

can be written as

, (1)

where , is a given domain in and is a time interval. If

is a vector-valued function, , and we look for several unknown functions

, then

(2)

is a system of partial differential equations. It is clear that these relations can be, in general, very

complicated, and only some of their particular cases can be successfully studied by a

mathematical theory. That is why it is important to know how to recognize these types and to

distinguish them.

1. Basic Types of Equations, Boundary and Initial Conditions

Partial differential equations can be classified from various points of view. If time is one of the

independent variables of the searched-for function, we speak about evolution equations. If it is

not the case (the equation contains only spatial independent variables), we speak about

stationary equations. The highest order of the derivative of the unknown function in the

equation determines the order of the equation. If the equation consists only of a linear

combination of and its derivatives (for example, it does not contain products as ,

etc.), we speak about a linear equation. Otherwise, it is a nonlinear equation. A linear equation

can be written symbolically by means of a linear differential operator , i.e., the operator with

the property

, (3)

where are real constants and are real functions. The equation

(4)

is called homogeneous,the equation

, (5)

where is a given function, is called nonhomogeneous.The function represents the “right-

hand side” of the equation. According to the above-mentioned aspects, we can classify the

following equations:

1. The transport equation in one spatial variable:

(6)

is evolution, of the first order, linear with , homogeneous.

2. The Laplace equation in three spatial variables:

(7)

is stationary, of the second order, linear with , homogeneous.

3. The Poisson equation in two spatial variables:

, (8)

where is a given function, is stationary, of the second order, linear with

, nonhomogeneous.

4. The wave equation with interaction in one spatial variable:

. (9)

is evolution, of the second order, nonlinear. The interaction is represented by the term .

5. The diffusion equation in one spatial variable:

(10)

is evolution, of the second order, linear with , nonhomogeneous.

6. The equation of the vibrating beam:

(11)

is evolution, of the fourth order, linear with , homogeneous.

7. The Schrodinger equation (a special case):

(12)

is evolution, of the second order, linear with , homogeneous (here is the

imaginary unit: ).

8. The equation of a disperse wave:

(13)

is evolution, of the third order, nonlinear.

A function u is called a solution of a partial differential equation if, when substituted

(together with its partial derivatives) into the equation, the latter becomes an identity. As in the

case of ordinary differential equations, a solution of the partial differential equation is not

determined uniquely. Thus we come to the notion of the general solution.

Let us notice the difference between the general solution of an ordinary differential

equation (ODE) and the general solution of a partial differential equation (PDE): the general

solution of an ODE includes arbitrary constants (their number is given by the order of the

equation); the general solution of PDE includes arbitrary functions. This fact is illustrated by the

examples below.

Example 1. Let us search for a function of two variables satisfying the equation

. (14)

This problem can be solved by direct integration of equation (2.1).Since we integrate with

respect to x, the integration “constant” can depend, in general, on y . From (14) it follows that

and, by further integration,

. (15)

We thus obtain a general solution of equation (14), and and are arbitrary functions of the

variable .

Example 2. Let us search for a function satisfying the equation

. (16)

Similarly to the case of the ODE for the unknown function ,

,

when the general solution is a function with arbitrary constants

, the general solution of equation (16) has the form

, (17)

where and are arbitrary functions of the variable .

Example 3. Let us search for a function satisfying the equation

. (18)

Integrating (18) with respect to y, we obtain

( is an arbitrary “constant” depending on ). Further integration with respect to then leads

to

, (19)

where . Functions and are again arbitrary. If we look for twice continuously

differentiable function , then its second partial derivatives are exchangeable. Hence we can

integrate (18) first with respect to and then with respect to . Thus both and must be

differentiable.

As in ODEs, a single PDE does not provide sufficient information to enable us to determine its

solution uniquely. For the unique determination of a solution, we need further information. In

the case of stationary equations, it is usually boundary conditions which, together with the

equation, form a boundary value problem. For example,

(20)

forms a homogeneous Dirichlet boundary value problem for the Laplace equation. If, in general,

is a bounded domain in , we distinguish the following basic types of (linear) boundary

conditions.

The Dirichlet boundary condition:

, (21)

the Neumann boundary condition:

, (22)

the Robin (sometimes called also Newton) boundary condition:

, (23)

where

denotes the derivative with respect to the outer normal to the boundary (surface)

of the domain , are given constants. If on various parts of the boundary

different types of boundary conditions are given, we speak about a problem with mixed

boundary conditions. In the case , the boundary conditions are called homogeneous,

otherwise they are nonhomogeneous. In one dimension, that is in the case of problems on the

interval , the boundary consists of two points . Then, for example,

the nonhomogeneous Neumann boundary conditions reduce to

. (24)

On an unbounded domain, for example, on the interval , where it is not possible to

speak about a value of the given function at the point “infinity”, the homogeneous Dirichlet

boundary condition has the form

. (25)

In the case of evolution equations, we usually deal, besides boundary conditions, also with

initial conditions which, together with the equation and the boundary conditions, form an initial

boundary value problem. For example,

(26)

forms an initial boundary value problem for the one-dimensional wave equation. Here the

boundary conditions are the homogeneous Dirichlet ones. The function denotes the initial

displacement and stands for the initial velocity at a given point . The derivative at time

is understood as the derivative from the right. If we look for the so-called classical

solution, the functions and are supposed to be continuous and also the function is

continuous (in fact, even the partial derivatives of the second order are continuous). That is

why the boundary and initial conditions must satisfy the compatibility conditions

. (27)

By a solution (classical solution) of the initial boundary (or boundary) value problem, we

understand a function which satisfies the equation as well as the boundary and initial

conditions pointwise. In particular, the solution must be differentiable up to the order of the

equation. These requirements can be too strong and thus the notion of a solution of a PDE (or

of a system of PDEs) is often understood in another (generalized) sense.

Another notion is that of a well-posed boundary (or initial boundary) value problem. The

problem is called well-posed if the following three conditions are satisfied:

(i) a solution of the problem exists;

(ii) the solution of the problem is determined uniquely ;

(iii) the solution of the problem is stable with respect to the given data , which

means that a “small change” of initial or boundary conditions, right-hand side,

etc., causes only a “small change” of the solution.

The last condition concerns especially models of physical problems, since the given data

can never be measured with absolute accuracy. However, the question left in the

definition of stability is what does “very small” or “small” change mean. The answer

depends on the particular problem and, at this moment, we put up with only an

intuitive understanding of this notion.

The contrary of a well-posed problem is the ill-posed problem, i.e., a problem

which does not satisfy at least one of the three previous requirements. If the solution

exists but the uniqueness is not ensured, the problem can be underdetermined.

Conversely, if the solution does not exist, it can be an overdetermined problem. An

underdetermined problem, overdetermined problem, as well as unstable problem can,

however, make real sense. Further, it is worth mentioning that the notion of a well-

posed problem is closely connected to the definition of a solution. For example, the

wave equation with non-smooth initial conditions is, in the sense of the classical

solution defined above, an ill-posed problem, since its classical solution does not exist.

However, if we consider the solution in a more general sense, the problem becomes

well-posed, the generalized solution exists, it is unique and stable with respect to

“small” changes of given data.

2. Classification of Linear Equations of the Second Order

In this section we state the classification of the basic types of PDEs of the second order that can

be found most often in practical models.

The basic types of linear evolution equations of the second order are the wave equation

(in one spatial variable):

, (28)

which is of hyperbolic type, and the diffusion equation (in one spatial variable):

, (29)

which is of parabolic type. The basic type of the linear stationary equation of the second order

(in two spatial variables) is the Laplace equation:

, (30)

which is of elliptic type. Formal analogues of these PDEs are equations of conics in the plane:

the equation of a hyperbola, , the equation of a parabola, , and the

equation of an ellipse (here we mention its special case—a circle), . Let us consider

a general linear homogeneous PDE of the second order

(31)

with two independent variables and with six real coefficients that can depend on and .

Let us denote by

(32)

the matrix formed by the coefficients at the partial derivatives of the second order. It is possible

to show that there exists a linear transformation of variables , which reduces equation

(31) to one of the following forms. In this respect, an important role is played by the

determinant of the matrix .

(i) Elliptic form: If , that is , the equation is reducible to the

form

, (33)

where the dots represent terms with derivatives of lower orders.

(ii) Hyperbolic form: If , that is , the equation is reducible to

the form

. (34)

The dots stand for the terms with derivatives of lower orders.

(iii) Parabolic form: If , that is , the equation is reducible to the

form

, (or ) , (35)

unless . Here, again, the dots represent terms with

derivatives of lower orders.

Finding the corresponding transformation relations and reducing the equation is

based on the same idea as the analysis of conics in analytic geometry. For simplicity,

let us consider only the principal terms in the equation, that is, let

, and let us normalize the equation by . If, moreover, we denote

, etc., we can write equation (31) as

and, by formally completing the square, we convert it to

. (36)

Further, let us consider the elliptic case , and denote

which means b R .We introduce new independent variables and by

. (37)

The transformed derivatives assume the form

(38)

(you can prove it using the chain rule), and equation (36) becomes

(39)

or, equivalently,

. (40)

In the remaining two cases, we would proceed analogously (in the parabolic case we have

, and in the hyperbolic case,

).

Example 4. We determine types of the following equations:

(a) , (41)

(b) , (42)

(c) 2 . (43)

In terms of the previous explanation, we decide according to the sign of

. Thus, in case (a), we obtain and the equation is

of hyperbolic type. In case (b), we have , and thus the equation is of parabolic type.

In case (c), we have , and the equation is of elliptic type.

If A is a function of and (i.e., the equation has nonconstant coefficients), then the

type of the equation may be different in different parts of the xy-plane. See the following two

examples.

Example 5. We find regions of the xy-plane where the equation

(44)

is of elliptic, hyperbolic, or parabolic type, respectively.

In this case the coefficients depend on x and y and we obtain

. The equation is thus of parabolic type on the hyperbola

, of elliptic type in

two convex regions , and of hyperbolic type in the connected region . The

reader is invited to sketch a picture of corresponding regions.

Example 6. Again, we find regions of the xy-plane where the equation

(45)

is of elliptic, hyperbolic, or parabolic type, respectively.

This time we have . The equation is thus of

hyperbolic type in the whole plane except the axis y , where it is of parabolic type.

Remark2.7 In a similar way we can classify linear PDEs of the second order with an arbitrary

finite number of variables N .The coefficient matrix A is then of type N × N .The type of the

equation is related to definiteness of the matrix A and can be determined by signs of its

eigenvalues:

(i) the equation is of elliptic type, if the eigenvalues of A are all positive or all negative

(i.e., A is positive or negative definite);

(ii) the equation is of parabolic type, if A has exactly one zero eigenvalue and all the

other eigenvalues have the same sign (i.e., A is a special case of a positive or

negative semidefinite matrix);

(iii) the equation is of hyperbolic type, if A has only one negative eigenvalue and all the

others are positive, or A has only one positive eigenvalue and all the others are

negative (i.e., A is a special case of an indefinite matrix);

(iv) the equation is of ultrahyperbolic type, if A has more than one positive eigenvalue

and more than one negative eigenvalue, and no zero eigenvalues (i.e., A is

indefinite).

Notice that the matrix A is symmetric, since we consider exchangeable second partial

derivatives, and thus all its eigenvalues have to be real.