Tools · Fluids & Thermodynamics

Mechanism Reduction

Shrink a detailed kinetic mechanism to a skeletal one that still matches ignition delay and flame speed within your error limit.

Updated October 1, 2026

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Detailed kinetic mechanisms (for example from RMG Mechanism Generator) can have hundreds of species and thousands of reactions, too many to simulate quickly. Mechanism Reduction removes species and reactions that don't matter for the conditions you care about, keeping ignition delay and laminar flame speed within the error you allow. It uses pyMARS and Cantera, on CPU.

How it works

You give the parent mechanism, the conditions to preserve, and an error limit.
pyMARS runs a graph-based reduction: DRGEP (the default), DRG, or PFA. Each ranks species by how much they affect the target species, and removes the least important while the error stays under error_limit_pct.
Optionally, sensitivity_analysis (greedy or initial) then tries removing more species one at a time, checking the error after each.

Targets: autoignition delay at up to 20 conditions (ignition_conditions) and laminar flame speed at up to 5 (flame_conditions); at least one condition is required. Each condition gives temperature (K), pressure (Pa), and either an equivalence ratio with fuel and oxidizer or an explicit reactant mixture.

Inputs

The parent mechanism: built-in gri30 or h2o2 (mechanism_id), or your own as Cantera YAML or a single CHEMKIN file with thermodynamic data, uploaded or from an artifact. Up to 1,000 species.
target_species (up to 10) that drive the reduction, typically fuel and oxidizer, and retained_species (up to 100) to always keep, such as diluents.

Outputs

File	Contents
`mechanism/primary.yaml`	The reduced mechanism, ready for Cantera
`errors.csv`	Ignition delay (s) and flame speed (m/s) for the parent and reduced mechanisms at every condition, and the error
`removed.csv`	Every species and reaction removed
`pymars_input.yaml`	The exact pyMARS input, to reproduce the run yourself
`summary.json`	Method, limits, species and reaction counts, and the worst condition

Generate mechanisms with RMG Mechanism Generator, and simulate the reduced one in Cantera.

Run it from the API

Submit with Submit a job and the job_type below. Price it first with Estimate job reservation cost: submitting reserves that amount from your wallet, and the charge settles at the actual runtime.

Mechanism Reduction `mechanism-reduce`

Job type: mechanism-reduce
Hardware: cpu (default)
Typical runtime: 30 min on CPU

Payload

Provide exactly one of: mechanism, mechanism_id.

Payload fields
Field	Type	Description
`mechanism`	`file_object`
mechanism.`name`	`string`	Limits: `min length 1`
mechanism.`filename`	`string`	Limits: `min length 1`
mechanism.`content_b64`	`string`	Limits: `min length 1`
mechanism.`content`	`any`
mechanism.`bytes`	`any`
`mechanism_id`	`string`	One of: `"gri30", "h2o2"`
`phase_name`	`string`	Limits: `min length 1`
`method`	`string`	Default: `"DRGEP"`One of: `"DRG", "DRGEP", "PFA"`
`error_limit_pct`	`number`	Default: `10`Limits: `> 0, ≤ 50`
`target_species[]`required	`string[]`	Limits: `min items 1, max items 10`
`retained_species[]`	`string[]`	Limits: `max items 100`
`sensitivity_analysis`	`boolean`	Default: `false`
`sensitivity_type`	`string`	One of: `"initial", "greedy"`
`upper_threshold`	`number`	Limits: `> 0, < 1`
`ignition_conditions[]`	`ignition_condition[]`	Limits: `max items 20`
ignition_conditions.`kind`required	`string`	One of: `"constant_volume", "constant_pressure"`
ignition_conditions.`temperature_k`required	`number`	Limits: `> 0, ≤ 5000`
ignition_conditions.`pressure_pa`required	`number`	Limits: `> 0`
ignition_conditions.`equivalence_ratio`	`number`	Limits: `> 0`
ignition_conditions.`fuel`	`composition`
ignition_conditions.`oxidizer`	`composition`
ignition_conditions.`reactants`	`composition`
ignition_conditions.`end_time_s`	`number`	Limits: `> 0, ≤ 10`
ignition_conditions.`max_steps`	`integer`	Limits: `≥ 1, ≤ 1000000`
`flame_conditions[]`	`flame_condition[]`	Limits: `max items 5`
flame_conditions.`temperature_k`required	`number`	Limits: `> 0, ≤ 5000`
flame_conditions.`pressure_pa`required	`number`	Limits: `> 0`
flame_conditions.`equivalence_ratio`	`number`	Limits: `> 0`
flame_conditions.`fuel`	`composition`
flame_conditions.`oxidizer`	`composition`
flame_conditions.`reactants`	`composition`
flame_conditions.`width_m`	`number`	Limits: `> 0, ≤ 1`

File fields take {"name": "x.pdb", "content_b64": "…"} or a stored artifact, {"$artifact": {"id": "art-…", "port": "…"}}. Files are up to 25 MiB each.

Example

from cognichem_client import CogniChem

client = CogniChem.from_env()  # reads COGNICHEM_API_KEY
payload = {
    "mechanism_id": "gri30",
    "method": "DRGEP",
    "error_limit_pct": 10,
    "target_species": ["CH4", "O2"],
    "retained_species": ["N2"],
    "sensitivity_analysis": False,
    "ignition_conditions": [
        {
            "kind": "constant_volume",
            "temperature_k": 1000,
            "pressure_pa": 101325,
            "equivalence_ratio": 1,
            "fuel": {"CH4": 1},
            "oxidizer": {"O2": 1, "N2": 3.76},
        },
        {
            "kind": "constant_pressure",
            "temperature_k": 1200,
            "pressure_pa": 2026500,
            "equivalence_ratio": 0.5,
            "fuel": {"CH4": 1},
            "oxidizer": {"O2": 1, "N2": 3.76},
        },
    ],
    "flame_conditions": [
        {
            "temperature_k": 300,
            "pressure_pa": 101325,
            "equivalence_ratio": 1,
            "fuel": {"CH4": 1},
            "oxidizer": {"O2": 1, "N2": 3.76},
        },
    ],
}

estimate = client.jobs.estimate(job_type="mechanism-reduce", payload=payload, resource="cpu")
print(f"Reserves ${estimate.cost:.2f}")

job = client.jobs.submit(
    job_name="my-mechanism-reduce-run",
    job_type="mechanism-reduce",
    payload=payload,
    resource="cpu",
)
status = client.jobs.wait(job.process_id)
if status.status == "completed":
    client.jobs.result(job.process_id, save_path=".")

curl -X POST "https://api.cognichem.com/api/v1/jobs/submit" \
  -H "X-Api-Key: $COGNICHEM_API_KEY" \
  -H "Idempotency-Key: $(uuidgen)" \
  -H "Content-Type: application/json" \
  -d '{
  "job_name": "my-mechanism-reduce-run",
  "job_type": "mechanism-reduce",
  "payload": {
    "mechanism_id": "gri30",
    "method": "DRGEP",
    "error_limit_pct": 10,
    "target_species": [
      "CH4",
      "O2"
    ],
    "retained_species": [
      "N2"
    ],
    "sensitivity_analysis": false,
    "ignition_conditions": [
      {
        "kind": "constant_volume",
        "temperature_k": 1000,
        "pressure_pa": 101325,
        "equivalence_ratio": 1,
        "fuel": {
          "CH4": 1
        },
        "oxidizer": {
          "O2": 1,
          "N2": 3.76
        }
      },
      {
        "kind": "constant_pressure",
        "temperature_k": 1200,
        "pressure_pa": 2026500,
        "equivalence_ratio": 0.5,
        "fuel": {
          "CH4": 1
        },
        "oxidizer": {
          "O2": 1,
          "N2": 3.76
        }
      }
    ],
    "flame_conditions": [
      {
        "temperature_k": 300,
        "pressure_pa": 101325,
        "equivalence_ratio": 1,
        "fuel": {
          "CH4": 1
        },
        "oxidizer": {
          "O2": 1,
          "N2": 3.76
        }
      }
    ]
  },
  "resource": "cpu"
}'

{
  "mechanism_id": "gri30",
  "method": "DRGEP",
  "error_limit_pct": 10,
  "target_species": [
    "CH4",
    "O2"
  ],
  "retained_species": [
    "N2"
  ],
  "sensitivity_analysis": false,
  "ignition_conditions": [
    {
      "kind": "constant_volume",
      "temperature_k": 1000,
      "pressure_pa": 101325,
      "equivalence_ratio": 1,
      "fuel": {
        "CH4": 1
      },
      "oxidizer": {
        "O2": 1,
        "N2": 3.76
      }
    },
    {
      "kind": "constant_pressure",
      "temperature_k": 1200,
      "pressure_pa": 2026500,
      "equivalence_ratio": 0.5,
      "fuel": {
        "CH4": 1
      },
      "oxidizer": {
        "O2": 1,
        "N2": 3.76
      }
    }
  ],
  "flame_conditions": [
    {
      "temperature_k": 300,
      "pressure_pa": 101325,
      "equivalence_ratio": 1,
      "fuel": {
        "CH4": 1
      },
      "oxidizer": {
        "O2": 1,
        "N2": 3.76
      }
    }
  ]
}

Sample data from the job catalog; long values are shortened here. Each job_name must be unique among your jobs.

Workflow inputs

Kinetic mechanism · optionalYAML, CHEMKIN

Workflow outputs

ArchiveZIP
TableCSV
Kinetic mechanismYAML
TableCSV