New code roadmap

[szaghi]

Desiderata features

• Compressible, multi-fluid, multi-phase, Navier-Stokes equations:
  • Preconditioned equations to efficient handling incompressibile, compressible, cavitating and multi-phase stiff problems;
  • Turbulent models:
    • LES:
      • Smagorinsky;
      • Germano;
    • DES-DDES;
    • WM-LES;
    • k-e, k-w;
  • Multi-fluid models:
    • Partial densities species conservation (Standard Thermodynamic Model);
  • Multi-Phase models:
    • Fully-coupled Lagrangian particles transport model;
• Fully-conservative Finite Volume Schemes:
  • Space integration models:
    • Riemann Problem solvers for convective fluxes:
      • Approximate Riemann solver based on (local) Lax-Friedrichs (known also as Rusanov) algorithm;
      • Approximate Riemann solver based on Primitive Variables Linearization algorithm;
      • Approximate Riemann solver based on Two Rarefactions algorithm;
      • Approximate Riemann solver based on Two Shocks algorithm;
      • Approximate Riemann solver based on Adaptive (non iterative) PVL-TR-TS algorithm;
      • Approximate Riemann solver based on Adaptive (non iterative) LF-TR algorithm;
      • Approximate Riemann solver based on HLLC algorithm;
      • Approximate Riemann solver based on Roe linearization.
      • Exact Riemann solver based on iterative solution of u-function;
      • Rotated Riemann solvers;
    • High order finite volume approximations for diffusive (viscous) fluxes;
    • Very High Order WENO reconstructions;
  • Time approximation models:
    • Strong-Stability-Preserving explicit/implicit Runge-Kutta integration;
    • Low Storage explicit/implicit Runge-Kutta integration;
    • Embeded explicit Runge-Kutta integration;
    • Very high-order multi-step Adams-Bashfort-Moulton integration;
    • Backward Differentian Formula integration;
    • Local pseudo-time convergence acceleration for steady simulations;
    • Multi-grid time convergence acceleration:
  • General curvilinear block-structured grids;
    • Adaptive Mesh Refinement (AMR);
    • Dynamic Overlapping Grids;
    • Immersed Boundaries;
  • General curvilinear unstructured grids;
  • Moving grids;
• Programming API:
  • Computational kernels in Fortran (possible Python interface);
  • Computational parallelism (exascale targetting):
    • partitioned global address space (PGAS) model by means of Coarrays Fortran (CAF);
  • Object Oriented Programming (OOP):
    • Abstract Calculus Pattern;
    • Very high-level programming interface;
  • Test Driven Development (TDD);
  • Fully documented;

[zhulianhua]

How about Implicit time stepping feature (LUSGS, or Newton-Krylov method)?