Dennis Román | Project Portfolio

Ben T. Zinn Combustion Lab

BTZCL Reacting Counterflow OpenFOAM Pipeline

Rebuild + validation pipeline for boundary-condition generation with OpenFOAM reacting-flow chemistry. Preserves consistent JSON outputs so Cantera and OpenFOAM results can be compared directly.

Concise summary for portfolio; details available on request.

OpenFOAMPythonfoamRunCanteraJSON I/O
OpenFOAM velocity magnitude field for counterflow validation

Plumbing/field-validation view in the counterflow domain before full compare-loop closure.

Project center

  • This project is centered on my current BTZCL reacting-flow development work.
  • Core goal: preserve consistent JSON outputs so Cantera and OpenFOAM results can be compared directly, while using OpenFOAM's built-in reacting chemistry stack.
  • Outcome target: quantify where OpenFOAM reacting CFD aligns/diverges from the Cantera 1D reference under matched boundary-condition intent.

Context anchor

This project is part of a propulsion and energy research ecosystem centered on combustion science and dynamics at Georgia Tech's Ben T. Zinn Combustion Lab.

Workflow map

  • Reference baseline:
    • Cantera 1D counterflow runs tune inlet conditions for target density ratio (S) and momentum flux ratio (J).
    • JSON outputs store boundary conditions and flame-level metrics.
  • OpenFOAM plumbing checks:
    • Diffusion-only check against analytical complementary error function solution.
    • Passive counterflow case generation and mixing-field validation.
  • OpenFOAM reacting stage:
    • 2D reacting counterflow setup with chemistry/thermo/reaction properties configured in OpenFOAM.
  • Reference compare loop:
    • Preset selection and JSON ingestion from the reference when available.
    • OpenFOAM output written in a comparable structure for direct Cantera vs OpenFOAM comparison.
    • Automated side-by-side result reporting.

Why this matters

  • Moves from single-tool dependence to cross-solver comparison without losing data consistency.
  • Preserves consistent JSON outputs so regression and validation remain trackable.
  • Establishes a reusable path for future reacting counterflow studies with the same comparison approach.

Validation Signals

  • Plumbing check against analytical complementary error function diffusion benchmark

    pass

  • Progressive stage-by-stage case validation before full reacting compare loop

    pass

Reproducibility Signals

  • Consistent JSON outputs

    OpenFOAM and Cantera results are written in a comparable structure for direct comparison.

  • Scripted case generation

    Python runners generate and execute passive and reacting counterflow cases programmatically.

  • Comparison utility

    Automated side-by-side result reporting supports rapid regression checks.