A Maximum Principle Result for a General Fourth Order Semilinear Elliptic Equation ()
Received 2 June 2016; accepted 27 August 2016; published 30 August 2016
1. Introduction
In [1] , Payne obtains maximum principle results for the semilinear fourth order elliptic equation
(1)
Other works deal with the more general fourth order elliptic operator, where and. In [12] , Dunninger mentions that functionals containing the term can be used to obtain maximum principle results for such linear equations as
A similar approach is taken in [13] for a class of nonlinear fourth order equations.
In this paper, we modify the results in [1] and a matrix result from [14] to deduce maximum principles defined on the solutions to semilinear fourth order elliptic equations of the form:
(2)
Then we briefly indicate how these maximum principles can be used to obtain apriori bounds on a certain quantity of interest.
2. Results
Throughout this paper, the summation convention on repeated indices is used; commas denote partial differentiation. Let be a symmetric matrix. Moreover let, be a uniformly elliptic operator, i.e, the symmetric matrix is positive definite and satisfies the uniform ellipticity condition: , where is a bounded domain in and.
Let u be a solution to the equation
(3)
where f is say, a function. Now we define the functional
We show that is subharmonic and note that the constants and and any constraints on f are yet to be determined.
By a straight-forward calculation, we have
Now we write
(4)
By expanding out the derivative terms in parentheses, we see that is
(5)
The terms in lines 2 and 3 above containing two or more derivatives of can be rewritten using (3) in the form, where denotes the matrix which is the inverse of the positive definite matrix. Furthermore, we use the identity to rewrite the last two terms in line 4. Hence,
(6)
Using the identity above for and the additional identity, , which can be obtained by computing, for the terms at the ends of lines 6 and 3 respectively, we obtain
(7)
To show that is nonnegative, we establish a series of inequalities based on the following one from [14] : Let be any matrix. From the inequality
(8)
One can deduce
(9)
Repeated use of (9) on terms in lines 2, 3, 4, 5 in (7) yields the following:
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
Furthermore, by completing the square, we obtain useful inequalities for the last two terms in line 1 and the third term in line 2 of (7):
(19)
(20)
(21)
We add (10)-(21) and label the resulting inequality, for part of, as
Now,
Since is positive definite, for a sufficiently large value of, where depends on the coefficients and their derivatives, and for a sufficiently large value of, say, where depends on the constants, , , and various derivatives of, can be made nonnegative as desired. Thus we have the following result.
Theorem 1. Suppose that is a solution of (2) and. If, where, , is a nonnegative function such that then there exists positive constants and sufficiently large such that P cannot attain its maximum value in unless it is a constant.
We note that the function satisfies the conditions stated in Theorem 1 for a solution that is bounded above.
3. Bounds
Here we give a brief application of Theorem 1.
Suppose that
By Theorem 1,
Using integration by parts on the first two terms of P yields the identity
Upon integrating both sides of the previous inequality we deduce
(22)
(23)