jCODE: High-speed multiphase/multi-physics flow solver
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jCODE is a high-performance Fortran-based multiphase/multi-physics flow solver developed and maintained by the Capecelatro Research Group at the University of Michigan. The code is capable of solving the multi-component compressible Navier-Stokes equations on structured curvilinear meshes using a class of high-order energy-stable finite difference operators. It features a range of models and methods including Lagrangian particle tracking, combustion mechanisms, immersed boundaries for complex geometries, shock capturing, and discrete adjoint-based sensitivity.


Capabilities


Specific features:

jCODE consists of a number of modules for simulating high-speed (compressible) two-phase and chemically reacting flows in complex geometries, and corresponding adjoint-based sensitivity. Specific features include:
  • High-order narrow stencil finite difference operators that satisfy summation-by-parts (SBP) property
  • Simultaneous-approximation-term (SAT) boundary treatment to ensure an energy estimate
  • A characteristic-based immersed boundary method for efficienty handling complex geometries on structured grids for inviscid and viscous flows
  • Lagrangian particle tracking capabale of simulating upwards of a billion individual particles undergoing mass/momentum/heat exchange and inter-particle collisions
  • Fully discrete adjoint capabilities to provide machine-precision sensitivity for turbulent reacting flows
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    Parallel performance:



    Scale-up of jCODE on OLCF Titan. The code is fully explicit and massively parallel, enabling large-scale computations with billions of grid points and 100s of millions of particles.

    Requesting access to the code

    jCODE is managed on a web-based git repository at Bitbucket. A golden copy of the source code that contains the most up-to-date working version (absent of any unpublished work) will be publicly available soon.


    Papers using jCODE

  • Shallcross, G. S., Capecelatro, J. (2022) An explicit characteristic-based immersed boundary method for compressible flows. Journal of Computational Physics. 449, 110804.
  • Shallcross, G. S., Fox, R. O., & Capecelatro, J. (2020). A volume-filtered description of compressible particle-laden flows. International Journal of Multiphase Flow, 122, 103138.
  • Yao, Y., Shallcross, G. S., Ni, R., Kim, T., Mehta, M., Rabinovitch, J., & Capecelatro, J. (2020) The dynamics of inertial particles in under-expanded jets: A numerical study. AIAA Scitech 2020 Forum, (p. 1327).
  • Kord, A., & Capecelatro, J. (2019). Optimal perturbations for controlling the growth of a Rayleigh–Taylor instability. Journal of Fluid Mechanics, 876, 150-185.
  • Buchta, D. A., Shallcross, G., Capecelatro, J. (2019) Sound and turbulence modulation by particles in high-speed shear flows. Journal of Fluid Mechanics, 875, 254-285.
  • Capecelatro, J., Bodony, D. J., & Freund, J. B. (2019). Adjoint-based sensitivity and ignition threshold mapping in a turbulent mixing layer. Combustion Theory and Modelling, 23(1), 147-179.
  • Shallcross, G. S., & Capecelatro, J. (2018) A parametric study of particle-laden shock tubes using an Eulerian-Lagrangian framework. 2018 AIAA Aerospace Sciences Meeting, (p. 2080).