We are interested in detailed understanding of the late-time consequences of mixing driven by hydro-dynamical instabilities promoted by initial conditions at accelerated material interfaces, as in ICF capsule implosions. Dominating effects of the flow instabilities can be captured with coarse graining (CG) modeling based on the primary conservation equations and effectively codesigned physics and algorithms. Modeling and predictability issues for underresolved flow and mixing driven by underresolved velocity fields and underresolved initial and boundary conditions are revisited in the context of CG (scale-resolving) simulations modeling prototypical (CEA and GATECH) shock-tube experiments are used to exemplify relevant issues, challenges, and strategies [1]. Next, we build on previous coarse graining (CG) simulations [2] of the indirect-drive NIF cryogenic capsule N170601 experiment – a precursor of N221205 which resulted in net energy gain, requiring Multi-Group Radiation-Diffusion to transport x-ray energy from the cylindrical Hohlraum to the target capsule (Fig.1). We apply effectively combined initialization aspects and multiphysics coupling in conjunction with newly available xRAGE hydrodynamics methods [3] -- including directional unsplit HLLC algorithms and low Mach-number correction (LMC), key advances enabling high fidelity CG simulations of radiation-hydrodynamics driven transition. The simulation model involves miscible (gas / plasma Schmidt number ~1) material interfaces and 3T plasma physics treatments, using relatively coarse 2D runs followed by mapping to highly resolved 3D mesh through onset of turbulence. Figure 2 exemplifies simulation results for the N170601 LMC-xRAGE simulations -- showing material interface boundaries of the DT and HDC shell regions, as well as velocity-gradient tensor visualization analysis (based on 2 isosurfaces), to characterize the unstable 3D vortex structure dynamics. Material mixing is driven by transitional vortex rings and outgoing jetting at one of the poles –with larger initial surface roughness (emulating fill-tube effects). CG simulation strategies and uncertainty quantification challenges are discussed in this context (and separately [4]).