Isee this steps in book PDE :
I'm going to understand it :
Steps :
$$u\in\mathbb{R^{N}}$$
And $\Omega \subset\mathbb{R^{N}}$
$$K=\int_{\Omega}\operatorname{div^{2}\vec{u}}dx=\int_{\Omega }\sum_{i,j=1,n}\frac{\partial u_{i}\partial u_{j}}{\partial x_{i}\partial x_{j}}dx$$
integration by part we get :
$$K=\int_{\Omega }\sum_{i,j=1}^{N}\frac{\partial u_{i}\partial u_{j}}{\partial x_{j}\partial x_{i}}dx=\int_{\Omega }(\nabla u)(\nabla u)^{t}dx$$
$$≤\int_{\Omega }|\nabla u|^{2}dx$$
I don't understand the second line how he use integration by part and what the relation to come those to
$ $\nabla =\operatorname{grad}$$ $.$
Now I know that :
$$\nabla u=(\frac{\partial u}{dx_{1}},\frac{\partial u}{dx_{2}},...,\frac{\partial u}{dx_{N}})^{t}$$
And :
$$\operatorname{div\vec{u}}=\sum_{i=1}^{N}\frac{\partial u_{i}}{\partial x_{i}}$$
I have already to see your explain !
It seems that $u$ is a vector-valued function. If $u$ is regular enough and is supposed that $u$ vanishes on the boundary, the second line is obtained using one of Green's identity (commonly called integral by parts), twice. If it is not known whether the function $u$ is regular enough, the "integral by parts" is taken in the context of distributions (motivated by the regular case).
Acutually $\nabla u$ is a $n\times n$ matrix.
The integrand $(\nabla u)(\nabla u)^t$ is the usual inner produt betwenn matrices given by $A\cdot B=\mathrm{tr}(B^TA)$. The last inequality is obtained by using of Young's inequality.