  Many hydrodynamic processes can be studied in a way that is scalable over a
vastly relevant physical parameter space. We systematically examine this
scalability, which has so far only briefly discussed in astrophysical
literature. We show how the scalability is limited by various constraints
imposed by physical processes and initial conditions. Using supernova remnants
in different environments and evolutionary phases as application examples, we
demonstrate the use of the scaling as a powerful tool to explore the
interdependence among relevant parameters, based on a minimum set of
simulations. In particular, we devise a scaling scheme that can be used to
adaptively generate numerous seed remnants and plant them into 3D hydrodynamic
simulations of the supernova-dominated interstellar medium.
