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.
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
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
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
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unpublished work) will be publicly available soon.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,
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,
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,
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).