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glS
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The problem is in the way you wrote your last equation as a matrix multiplication.

You have $$ [ \textbf u ( \nabla \textbf u) ]_i = u_j (\partial_i u_j) = (\partial_i u_j) u_j, $$$$ [ \textbf u \cdot ( \nabla \textbf u) ]_i = u_j (\partial_i u_j) = (\partial_i u_j) u_j, $$ so if you want to write this in matrix form you have to multiply the vector $\textbf u$ at the right, as a column vector, i.e.

$$[\mathbf{u}\cdot(\nabla\mathbf{u})]=\left(\begin{array}{cc} \partial_{x}u_{x} & \partial_{x}u_{y}\\ \partial_{y}u_{x} & \partial_{y}u_{y} \end{array}\right) \left(\begin{array}{c} u_{x}\\ u_{y} \end{array}\right) $$$$[\mathbf{u}\cdot(\nabla\mathbf{u})]=\left(\begin{array}{cc} \partial_{x}u_{x} & \partial_{x}u_{y}\\ \partial_{y}u_{x} & \partial_{y}u_{y} \end{array}\right) \left(\begin{array}{c} u_{x}\\ u_{y} \end{array}\right), $$ where the derivatives are intended to act only on the adjacent $u_i$.

Anyway, I don't see where the covariant derivatives comes in here. The $\nabla$ you are using is simply a gradient, not a covariant derivative.

The problem is in the way you wrote your last equation as a matrix multiplication.

You have $$ [ \textbf u ( \nabla \textbf u) ]_i = u_j (\partial_i u_j) = (\partial_i u_j) u_j, $$ so if you want to write this in matrix form you have to multiply the vector $\textbf u$ at the right, as a column vector, i.e.

$$[\mathbf{u}\cdot(\nabla\mathbf{u})]=\left(\begin{array}{cc} \partial_{x}u_{x} & \partial_{x}u_{y}\\ \partial_{y}u_{x} & \partial_{y}u_{y} \end{array}\right) \left(\begin{array}{c} u_{x}\\ u_{y} \end{array}\right) $$

The problem is in the way you wrote your last equation as a matrix multiplication.

You have $$ [ \textbf u \cdot ( \nabla \textbf u) ]_i = u_j (\partial_i u_j) = (\partial_i u_j) u_j, $$ so if you want to write this in matrix form you have to multiply the vector $\textbf u$ at the right, as a column vector, i.e.

$$[\mathbf{u}\cdot(\nabla\mathbf{u})]=\left(\begin{array}{cc} \partial_{x}u_{x} & \partial_{x}u_{y}\\ \partial_{y}u_{x} & \partial_{y}u_{y} \end{array}\right) \left(\begin{array}{c} u_{x}\\ u_{y} \end{array}\right), $$ where the derivatives are intended to act only on the adjacent $u_i$.

Anyway, I don't see where the covariant derivatives comes in here. The $\nabla$ you are using is simply a gradient, not a covariant derivative.

Source Link
glS
  • 15.2k
  • 5
  • 41
  • 109

The problem is in the way you wrote your last equation as a matrix multiplication.

You have $$ [ \textbf u ( \nabla \textbf u) ]_i = u_j (\partial_i u_j) = (\partial_i u_j) u_j, $$ so if you want to write this in matrix form you have to multiply the vector $\textbf u$ at the right, as a column vector, i.e.

$$[\mathbf{u}\cdot(\nabla\mathbf{u})]=\left(\begin{array}{cc} \partial_{x}u_{x} & \partial_{x}u_{y}\\ \partial_{y}u_{x} & \partial_{y}u_{y} \end{array}\right) \left(\begin{array}{c} u_{x}\\ u_{y} \end{array}\right) $$