I am reading through a paper that derives the thin-film equation from the Navier Stokes equation; however, am having some trouble understanding the vector calculus notation used. For example, the material derivative is defined as: $$ \frac{D\mathbf{v}}{dt} = \frac{\partial\mathbf{v}}{\partial t}+\mathbf{v}\cdot\nabla\mathbf{v}$$ where in $2D$ we have $\mathbf{v}=(u,w)$ and $\nabla=(\partial_x,\partial_z)$. Hence, the gradient of $\mathbf{v}$ is the transpose of the Jacobian given by: $$ \nabla\mathbf{v} = \begin{bmatrix} u_x & w_x \\ u_z & w_z \end{bmatrix} $$ Now my question is what to make of: $$ \mathbf{v}\cdot\nabla\mathbf{v}=\begin{bmatrix} u \\ w \end{bmatrix} \cdot \begin{bmatrix} u_x & w_x \\ u_z & w_z \end{bmatrix} $$ As far as I am aware the dot product can be defined for two vectors and can be extended to two square matrices but I don't quite know what to make of this when you have a vector and a square matrix.
Specifically, for this case I already know from past experience that: $$ \frac{D\mathbf{v}}{dt} = \frac{\partial \mathbf{v}}{\partial t}+\mathbf{v}\cdot\nabla\mathbf{v} = (u_t+uu_x+wu_z,w_t+uw_x+ww_z) $$ but upon coming back to this I am a little confused as to how to show this given the notation above.
It's better to write $(\mathbf{v}\cdot\nabla)\mathbf{v}.$ That makes it clearer: $$ (\mathbf{v}\cdot\nabla)\mathbf{v} = (u \partial_x + w \partial_y) \begin{bmatrix}u\\w\end{bmatrix} = \begin{bmatrix}(u \partial_x + w \partial_y)u\\(u \partial_x + w \partial_y)w\end{bmatrix}. $$