  The construction of high-order structure-preserving numerical schemes to
solve hyperbolic conservation laws has attracted a lot of attention in the last
decades and various different ansatzes exist. In this paper, we compare three
completely different approaches, i.e. physical constraint limiting, deep neural
networks and the application of polynomial annihilation to construct high-order
oscillation free Finite Volume (FV) blending schemes. We further analyze their
analytical and numerical properties. We demonstrate that all techniques can be
used and yield highly efficient FV methods but also come with some additional
drawbacks which we point out. Our investigation of the different blending
strategies should lead to a better understanding of those techniques and can be
transferred to other numerical methods as well which use similar ideas.
