Hi,

I work in the area of multiphase modeling and encountered the following problem.

I want to use weno algorithm on the projected characteristic variables of the problem, as follows

W(i)=inverse(P(i+1/2)) V(i)

The estimation of P is done via arithmetic average or roe's averaging of V(i) and V(i+1) where V is the primitive vector, W is the characteristic vector and P is the diagonalization matrix of the corresponding jacobian matrix of the system.

However, the cell value of the characteristic have the following structure: the same value for all the cells except on cell which has a different value. This structure of the data is obtained for the shock tube problem (and some other problems as well). If I try to implement weno on this kind of data pattern, eventually spurious oscillation would be emerged.

Summarizing s the problem: W(i)=1 for all “i” except for one cell which has value other than one.

For the one-phase problem, the data pattern of the characteristic values is different and therefore this problem does not exist. Trying implementing weno on conservative or primitive variables, results in oscillations as well

Is it possible to circumvent this problem somehow? should I think of other ways to obtain high order spacial accuracy without weno knowing this data structure of characteristic variavles?

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