diff --git a/README.md b/README.md
index 605a921d..abaef9ba 100644
--- a/README.md
+++ b/README.md
@@ -42,6 +42,7 @@ Advanced notebooks use JPype directly or through the Python distribution. They c
 * [Mechanical design to interactive 3D equipment](notebooks/process/mechanical_design_to_3d_models.ipynb) – Generate separator and compressor models from calculated NeqSim dimensions, inspect cutaways, compare flow cases, and exchange qualified STL/GLB/JSON artifacts.
 
 * [Hot-oil commissioning and ML risk screening](notebooks/flowassurance/hot_oil_commissioning_neqsim_ml.ipynb) – Combine NeqSim properties, wax, thermal resistance and a native heater/pipeline process with a conservative transient displacement model, numerical checks, RF/MLP surrogates and explicit gel-restart assumptions.
+* [Multi-burner hot-oil heater and CO-emissions diagnostics](notebooks/process/multi_burner_hot_oil_heater_co_emissions.ipynb) – Run source-pinned finite-rate burner and post-flame zones for seven/five burners, fixed-air load and 10–40 MW sweeps; retain actual CO mass, dry and reference-O₂ bases, thermal duty, fuel-slip diagnostics, projection omissions, provenance and conservation gates. GRI-Mech 3.0 remains a software demonstration rather than C3/C4 qualification.
 * [open-DARTS waterflood simulation and a NeqSim process handoff](notebooks/reservoir/open_darts_waterflood_to_neqsim.ipynb) – Build and validate an open-DARTS reservoir model, exercise well controls, check analytical and numerical sensitivity, and transfer component rates into NeqSim; connect the tutorial to the existing OPM Flow, RMS, and ERT examples.
 * [Elemental sulfur in oil stabilization and gas recompression](notebooks/process/elemental_sulfur_stabilization_recompression.ipynb) – Calculate H2S/O2 equilibrium and kinetics, sulfur deposition, rust/FeS effects, separator oil/condensate carryover, compressor fouling, and potential mitigation and cleaning measures.
 * [LNG process simulation and benchmark comparison](notebooks/process/LNG_Process_Benchmark_Comparison.ipynb) – Run closed-loop SMR, C3MR, DMR, and nitrogen-expander models with common KPIs, literature checks, and an exchanger grid-convergence study.
diff --git a/notebooks/examples_of_NeqSim_in_Colab.ipynb b/notebooks/examples_of_NeqSim_in_Colab.ipynb
index 4b761f08..4d3de666 100644
--- a/notebooks/examples_of_NeqSim_in_Colab.ipynb
+++ b/notebooks/examples_of_NeqSim_in_Colab.ipynb
@@ -366,6 +366,7 @@
     "* [NCS wind, battery, and gas-turbine electrification with NeqSim](power/ncs_wind_battery_gas_electrification.ipynb): build NeqSim from a pinned repository commit, derive an offshore process load, dispatch Hywind-scale synthetic wind and balancing gas, evaluate native battery storage, and screen direct CO₂, curtailment, ramps, reserve, and field-maturity sensitivities.\n",
     "* [Process-coupled offshore electrification with NeqSim](power/process_coupled_offshore_electrification_study.ipynb): extend a real separation and recompression process with 70-to-160 bara export compression, derive flow-dependent electrical demand from solved equipment duties, and compare gas turbines, shore power, wind, battery storage, and hybrid operation.\n",
     "* [Natural-gas combustion, burner devices, and NeqSim integration with Cantera](reactions/natural_gas_combustion_with_cantera.ipynb): compare fuel and oxidizer blends; boiler, furnace, low-NOx, gas-turbine, duct-burner, and flare cases; validate composition and mass closure; model staged combustion; and run a Cantera custom unit inside a NeqSim process.\n",
+    "* **Advanced** - [Multi-burner hot-oil heater and CO-emissions diagnostics](process/multi_burner_hot_oil_heater_co_emissions.ipynb): run source-pinned finite-rate burner and post-flame zones for seven/five burners, fixed-air load and 10–40 MW sweeps; retain CO mass and dry/reference-O2 bases, thermal duty, fuel-slip diagnostics, projection omissions, provenance, and conservation gates.\n",
     "* [Gas-fired power plants with NeqSim](power/Gas_fired_power_plants.ipynb): fuel quality, stoichiometric combustion, Brayton-cycle states, heat recovery, balances, direct CO2 intensity, and operating sensitivities.\n",
     "* [Natural-gas combined-cycle power plant with NeqSim](power/combined_cycle_power_plant.ipynb): Brayton gas turbine, single-pressure HRSG, CPA water/steam Rankine cycle, balances, quality checks, and operating sensitivities.\n",
     "\n",
diff --git a/notebooks/maintenance_ledger/multi_burner_heater_20261004.json b/notebooks/maintenance_ledger/multi_burner_heater_20261004.json
new file mode 100644
index 00000000..fb106268
--- /dev/null
+++ b/notebooks/maintenance_ledger/multi_burner_heater_20261004.json
@@ -0,0 +1,45 @@
+{
+  "schema_version": 1,
+  "updated_at": "2026-10-04T06:34:00Z",
+  "notebooks": [
+    {
+      "path": "notebooks/process/multi_burner_hot_oil_heater_co_emissions.ipynb",
+      "verified_date": "2026-10-04",
+      "verified_at_utc": "2026-10-04T06:34:00Z",
+      "neqsim_version": "3.23.0 dependencies with source overlay at 64e0a0a5997c0d130b9326a78d46269063f5bc94",
+      "python_version": "3.12.14",
+      "java_version": "openjdk 17.0.20",
+      "execution_status": "passed",
+      "execution_method": "All 11 code cells executed sequentially in a fresh Python process and shared namespace. The managed validator blocks Jupyter ZeroMQ sockets, so execution used ordinary Python while retaining stdout, rich HTML tables, PNG figures and execution counts. Java loaded connector-reconstructed source classes compiled at the pinned NeqSim master commit over public NeqSim 3.23.0 dependencies; Cantera 3.2.0 supplied GRI-Mech 3.0 finite-rate chemistry.",
+      "code_cells": 11,
+      "markdown_cells": 8,
+      "publication": {
+        "branch": "feat/multi-burner-heater-colab",
+        "mode": "draft pull request",
+        "commit": "this atomic commit"
+      },
+      "retained_figures": {
+        "count": 4,
+        "purposes": [
+          "seven/five burner comparison at equal total fuel and air",
+          "fixed-common-air CO mass, concentration, oxygen and temperature sweep",
+          "useful heat, residual chemical power, methane, organic carbon and assumed local-air capture",
+          "10–40 MW useful-heat and CO scaling"
+        ],
+        "visual_inspection": "Passed at original resolution: titles, units, legends, scales and rise/fall CO behavior are readable with no clipping or overlap."
+      },
+      "key_checks": [
+        "11 of 11 code cells executed in order with zero stored errors",
+        "seven/five cases passed independent zone mass and every-element residuals below 1e-7, full energy residual below 1e-6 and omitted-element fractions below the native 1e-6 projection limit",
+        "fixed-air sweep maximum omitted-element fraction was 3.247241e-4 against its declared 1e-3 limit; maximum full-energy residual was 1.788856e-7",
+        "CO mass rose to 18.0719 kg/h at 30% load and fell to 9.4747 kg/h at 20% load while useful hot-oil heat stayed positive, so complete extinction was not used as the explanation",
+        "10, 20, 30 and 40 MW scale points produced 8.7454, 17.5066, 26.2714 and 35.0381 MW useful hot-oil heat",
+        "actual CO kg/h, raw dry ppmv and mg/Nm3, 3 vol% O2-corrected mg/Nm3, O2, burner/stack temperatures, residual chemical power, CH4 and organic-carbon diagnostics are retained separately",
+        "loaded MultiBurnerFiredHeater class origin, exact NeqSim source ref, Cantera version, GRI-Mech mechanism fingerprint, species/reaction counts and top omitted hydrogen species are displayed",
+        "four retained figures were extracted and visually inspected after the final execution"
+      ],
+      "limitations": "GRI-Mech 3.0 is only a software demonstration. Local-air capture, effective tube sink, chamber geometry and steady refractory are declared assumptions. The notebook does not claim C3/C4 benchmark qualification, spatial CFD, dynamic refractory storage, plant calibration, VOC-instrument equivalence, emissions compliance, burner safety or heater-design certification.",
+      "summary": "Adds an executed, source-pinned demonstration of the native NeqSim multi-burner fired-heater API with finite-rate Cantera chemistry, explicit hot-oil heat transfer and fail-closed projection/conservation evidence."
+    }
+  ]
+}
diff --git a/notebooks/notebook_maintenance_ledger.json b/notebooks/notebook_maintenance_ledger.json
index f2f6ba06..8268375d 100644
--- a/notebooks/notebook_maintenance_ledger.json
+++ b/notebooks/notebook_maintenance_ledger.json
@@ -1,5 +1,5 @@
 {
-  "active_notebook_count": 321,
+  "active_notebook_count": 322,
   "retired_notebooks": [
     {
       "follow_up": "Replace with the planned NeqSim-master data-reconciliation and Bayesian digital-twin notebook.",
diff --git a/notebooks/process/multi_burner_hot_oil_heater_co_emissions.ipynb b/notebooks/process/multi_burner_hot_oil_heater_co_emissions.ipynb
new file mode 100644
index 00000000..b0cd7c65
--- /dev/null
+++ b/notebooks/process/multi_burner_hot_oil_heater_co_emissions.ipynb
@@ -0,0 +1,707 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Multi-burner hot-oil heater and CO-emissions diagnostics\n",
+    "\n",
+    "This notebook demonstrates the native NeqSim `MultiBurnerFiredHeater` with an optional Cantera 3.2.0 finite-rate backend. It keeps two experiments separate:\n",
+    "\n",
+    "1. seven versus five active burners at equal total fuel and common-air supply; and\n",
+    "2. a fuel-load sweep at fixed common-air flow with an explicitly assumed local-air capture curve.\n",
+    "\n",
+    "The example reports actual CO mass rate, dry concentration, 3 vol% O2-corrected concentration, oxygen, burner and stack temperatures, useful hot-oil heat, residual chemical power, methane, organic-carbon diagnostics, projection omissions, and energy/conservation checks.\n",
+    "\n",
+    "> **Scope:** GRI-Mech 3.0 is used only as a software and physics demonstration. The model is not calibrated to plant measurements and does not qualify C3/C4 chemistry, spatial geometry, emissions compliance, burner safety, or heater design.\n"
+   ],
+   "id": "1eb47919cb07"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reproducible setup\n",
+    "\n",
+    "The clean-runtime path pins NeqSim commit `64e0a0a5997c0d130b9326a78d46269063f5bc94`, builds its Java classes, and verifies that `MultiBurnerFiredHeater` is loaded from that build. Local validation may supply an audited source directory and classpath through `NEQSIM_SOURCE_ROOT` and `NEQSIM_LOCAL_CLASSPATH`; the saved numerical outputs below were produced from connector-reconstructed source at the same commit plus NeqSim 3.23.0 dependencies.\n"
+   ],
+   "id": "fa310969295a"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "Setup mode: audited connector source with compiled master overlay\nPinned NeqSim commit: 64e0a0a5997c0d130b9326a78d46269063f5bc94\nNeqSim dependency baseline: 3.23.0\nCantera: 3.2.0\nLoaded Java class: neqsim.process.equipment.reactor.MultiBurnerFiredHeater\nLoaded class origin: file:/workspace/scratch/ce81b797f3da/overlay-classes/\n"
+    }
+   ],
+   "source": [
+    "import hashlib\n",
+    "import json\n",
+    "import os\n",
+    "from pathlib import Path\n",
+    "import subprocess\n",
+    "import sys\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "\n",
+    "NEQSIM_SOURCE_REF = \"64e0a0a5997c0d130b9326a78d46269063f5bc94\"\n",
+    "PINNED_NEQSIM_SHA = NEQSIM_SOURCE_REF\n",
+    "os.environ.setdefault(\"NEQSIM_JVM_AUTOSTART\", \"false\")\n",
+    "PINNED_NEQSIM_VERSION = \"3.23.0\"\n",
+    "PINNED_CANTERA_VERSION = \"3.2.0\"\n",
+    "\n",
+    "local_source = os.environ.get(\"NEQSIM_SOURCE_ROOT\")\n",
+    "local_classpath = os.environ.get(\"NEQSIM_LOCAL_CLASSPATH\")\n",
+    "\n",
+    "if local_source and local_classpath:\n",
+    "    source_root = Path(local_source).resolve()\n",
+    "    classpath = local_classpath.split(os.pathsep)\n",
+    "    resolved_source_ref = NEQSIM_SOURCE_REF\n",
+    "    setup_mode = \"audited connector source with compiled master overlay\"\n",
+    "else:\n",
+    "    source_root = Path(\"/content/neqsim-source\")\n",
+    "    if source_root.exists():\n",
+    "        subprocess.run([\"rm\", \"-rf\", str(source_root)], check=True)\n",
+    "    subprocess.run(\n",
+    "        [\n",
+    "            \"git\",\n",
+    "            \"clone\",\n",
+    "            \"--filter=blob:none\",\n",
+    "            \"https://github.com/equinor/neqsim.git\",\n",
+    "            str(source_root),\n",
+    "        ],\n",
+    "        check=True,\n",
+    "    )\n",
+    "    subprocess.run(\n",
+    "        [\"git\", \"checkout\", \"--detach\", NEQSIM_SOURCE_REF],\n",
+    "        cwd=source_root,\n",
+    "        check=True,\n",
+    "    )\n",
+    "    resolved_source_ref = subprocess.run(\n",
+    "        [\"git\", \"rev-parse\", \"HEAD\"],\n",
+    "        cwd=source_root,\n",
+    "        check=True,\n",
+    "        capture_output=True,\n",
+    "        text=True,\n",
+    "    ).stdout.strip()\n",
+    "    assert resolved_source_ref == NEQSIM_SOURCE_REF\n",
+    "    classpath_file = source_root / \"target\" / \"heater-classpath.txt\"\n",
+    "    subprocess.run(\n",
+    "        [\n",
+    "            \"./mvnw\",\n",
+    "            \"-B\",\n",
+    "            \"-ntp\",\n",
+    "            \"-DskipTests\",\n",
+    "            \"compile\",\n",
+    "            \"dependency:build-classpath\",\n",
+    "            f\"-Dmdep.outputFile={classpath_file}\",\n",
+    "        ],\n",
+    "        cwd=source_root,\n",
+    "        check=True,\n",
+    "    )\n",
+    "    dependencies = classpath_file.read_text(encoding=\"utf-8\").strip().split(os.pathsep)\n",
+    "    classpath = [str(source_root / \"target\" / \"classes\")] + dependencies\n",
+    "    setup_mode = \"clean pinned source build\"\n",
+    "\n",
+    "combustion_examples = source_root / \"examples\" / \"combustion\"\n",
+    "sys.path.insert(0, str(combustion_examples))\n",
+    "\n",
+    "from cantera_backend import CanteraBackend\n",
+    "from multi_burner_fired_heater import (\n",
+    "    build_case,\n",
+    "    initialize_runtime,\n",
+    "    run_demonstration,\n",
+    "    run_with_diagnostics,\n",
+    "    summarize,\n",
+    ")\n",
+    "\n",
+    "import jpype\n",
+    "\n",
+    "for classpath_entry in classpath:\n",
+    "    jpype.addClassPath(classpath_entry)\n",
+    "\n",
+    "JavaType = initialize_runtime(source_root, classpath)\n",
+    "heater_class = JavaType(\"neqsim.process.equipment.reactor.MultiBurnerFiredHeater\")\n",
+    "class_origin = str(\n",
+    "    heater_class.class_.getProtectionDomain().getCodeSource().getLocation()\n",
+    ")\n",
+    "assert \"target/classes\" in class_origin or \"overlay-classes\" in class_origin\n",
+    "backend = CanteraBackend(\"gri30.yaml\")\n",
+    "\n",
+    "print(f\"Setup mode: {setup_mode}\")\n",
+    "print(f\"Pinned NeqSim commit: {resolved_source_ref}\")\n",
+    "print(f\"NeqSim dependency baseline: {PINNED_NEQSIM_VERSION}\")\n",
+    "print(f\"Cantera: {PINNED_CANTERA_VERSION}\")\n",
+    "print(f\"Loaded Java class: {heater_class.class_.getName()}\")\n",
+    "print(f\"Loaded class origin: {class_origin}\")\n"
+   ],
+   "id": "86be2b680edb"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Execute the declared experiments\n",
+    "\n",
+    "The 30 MW reference case uses a 50/50 molar ethane/propane fuel, common air, seven installed burners, a separate n-decane hot-oil stream, grey radiation plus convection to the tubes, and steady refractory loss. The load sweep keeps the common-air stream fixed. Its local-air capture fraction is an illustrative assumption, not a geometry-derived correlation or fitted emissions factor.\n"
+   ],
+   "id": "712b6783c9b1"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "Completed seven/five burners, six load points, and four scale points.\n"
+    }
+   ],
+   "source": [
+    "results = run_demonstration(\n",
+    "    JavaType,\n",
+    "    backend,\n",
+    "    include_sweep=True,\n",
+    "    sweep_projection_tolerance=1.0e-3,\n",
+    ")\n",
+    "\n",
+    "scale_results = []\n",
+    "for firing_mw in (10.0, 20.0, 30.0, 40.0):\n",
+    "    process, heater, fuel, air, oil, fuel_mass = build_case(\n",
+    "        JavaType,\n",
+    "        backend,\n",
+    "        firing_mw,\n",
+    "    )\n",
+    "    run_with_diagnostics(process, heater)\n",
+    "    row = summarize(heater)\n",
+    "    row[\"nominalFiringMW\"] = firing_mw\n",
+    "    scale_results.append(row)\n",
+    "\n",
+    "results[\"explicit_geometry_heat_transfer_scaling\"] = scale_results\n",
+    "print(\"Completed seven/five burners, six load points, and four scale points.\")\n"
+   ],
+   "id": "069b4137e545"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Seven versus five active burners\n",
+    "\n",
+    "Total fuel and total common-air supply are unchanged. Therefore this comparison isolates the reduced network's burner-zone loading effect; it is not a claim about air leakage through closed burner ports.\n"
+   ],
+   "id": "e93832f80d56"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "<pandas.io.formats.style.Styler object at 0x7f3e378c8380>",
+      "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_60b80\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_60b80_level0_col0\" class=\"col_heading level0 col0\" >CO kg/h</th>\n      <th id=\"T_60b80_level0_col1\" class=\"col_heading level0 col1\" >CO dry ppmv</th>\n      <th id=\"T_60b80_level0_col2\" class=\"col_heading level0 col2\" >CO dry mg/Nm3</th>\n      <th id=\"T_60b80_level0_col3\" class=\"col_heading level0 col3\" >CO at 3% O2 mg/Nm3</th>\n      <th id=\"T_60b80_level0_col4\" class=\"col_heading level0 col4\" >Dry O2 vol%</th>\n      <th id=\"T_60b80_level0_col5\" class=\"col_heading level0 col5\" >Minimum burner K</th>\n      <th id=\"T_60b80_level0_col6\" class=\"col_heading level0 col6\" >Stack K</th>\n      <th id=\"T_60b80_level0_col7\" class=\"col_heading level0 col7\" >Useful oil heat MW</th>\n      <th id=\"T_60b80_level0_col8\" class=\"col_heading level0 col8\" >Residual chemical MW</th>\n      <th id=\"T_60b80_level0_col9\" class=\"col_heading level0 col9\" >CH4 dry mg/Nm3</th>\n      <th id=\"T_60b80_level0_col10\" class=\"col_heading level0 col10\" >Organic C mgC/Nm3</th>\n    </tr>\n    <tr>\n      <th class=\"index_name level0\" >case</th>\n      <th class=\"blank col0\" >&nbsp;</th>\n      <th class=\"blank col1\" >&nbsp;</th>\n      <th class=\"blank col2\" >&nbsp;</th>\n      <th class=\"blank col3\" >&nbsp;</th>\n      <th class=\"blank col4\" >&nbsp;</th>\n      <th class=\"blank col5\" >&nbsp;</th>\n      <th class=\"blank col6\" >&nbsp;</th>\n      <th class=\"blank col7\" >&nbsp;</th>\n      <th class=\"blank col8\" >&nbsp;</th>\n      <th class=\"blank col9\" >&nbsp;</th>\n      <th class=\"blank col10\" >&nbsp;</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_60b80_level0_row0\" class=\"row_heading level0 row0\" >Seven active</th>\n      <td id=\"T_60b80_row0_col0\" class=\"data row0 col0\" >0.110188</td>\n      <td id=\"T_60b80_row0_col1\" class=\"data row0 col1\" >3.05119</td>\n      <td id=\"T_60b80_row0_col2\" class=\"data row0 col2\" >3.81297</td>\n      <td id=\"T_60b80_row0_col3\" class=\"data row0 col3\" >3.66102</td>\n      <td id=\"T_60b80_row0_col4\" class=\"data row0 col4\" >2.25705</td>\n      <td id=\"T_60b80_row0_col5\" class=\"data row0 col5\" >2109.63</td>\n      <td id=\"T_60b80_row0_col6\" class=\"data row0 col6\" >574.289</td>\n      <td id=\"T_60b80_row0_col7\" class=\"data row0 col7\" >26.2714</td>\n      <td id=\"T_60b80_row0_col8\" class=\"data row0 col8\" >0.0138193</td>\n      <td id=\"T_60b80_row0_col9\" class=\"data row0 col9\" >3.07542e-16</td>\n      <td id=\"T_60b80_row0_col10\" class=\"data row0 col10\" >2.40322e-08</td>\n    </tr>\n    <tr>\n      <th id=\"T_60b80_level0_row1\" class=\"row_heading level0 row1\" >Five active</th>\n      <td id=\"T_60b80_row1_col0\" class=\"data row1 col0\" >0.103241</td>\n      <td id=\"T_60b80_row1_col1\" class=\"data row1 col1\" >2.85881</td>\n      <td id=\"T_60b80_row1_col2\" class=\"data row1 col2\" >3.57256</td>\n      <td id=\"T_60b80_row1_col3\" class=\"data row1 col3\" >3.43076</td>\n      <td id=\"T_60b80_row1_col4\" class=\"data row1 col4\" >2.26017</td>\n      <td id=\"T_60b80_row1_col5\" class=\"data row1 col5\" >2094.83</td>\n      <td id=\"T_60b80_row1_col6\" class=\"data row1 col6\" >574.294</td>\n      <td id=\"T_60b80_row1_col7\" class=\"data row1 col7\" >26.2733</td>\n      <td id=\"T_60b80_row1_col8\" class=\"data row1 col8\" >0.0117943</td>\n      <td id=\"T_60b80_row1_col9\" class=\"data row1 col9\" >0</td>\n      <td id=\"T_60b80_row1_col10\" class=\"data row1 col10\" >2.45311e-08</td>\n    </tr>\n  </tbody>\n</table>\n"
+     }
+    }
+   ],
+   "source": [
+    "burner_cases = {\n",
+    "    \"Seven active\": results[\"seven_burners\"],\n",
+    "    \"Five active\": results[\"five_burners_same_total_fuel_air\"],\n",
+    "}\n",
+    "\n",
+    "burner_rows = []\n",
+    "for label, case in burner_cases.items():\n",
+    "    burner_rows.append(\n",
+    "        {\n",
+    "            \"case\": label,\n",
+    "            \"CO kg/h\": case[\"coMassRateKgPerHour\"],\n",
+    "            \"CO dry ppmv\": case[\"coPpmvDry\"],\n",
+    "            \"CO dry mg/Nm3\": case[\"coMgPerNormalM3DryAt273_15K101325Pa\"],\n",
+    "            \"CO at 3% O2 mg/Nm3\": case[\"coMgPerNormalM3DryAtReferenceOxygen\"],\n",
+    "            \"Dry O2 vol%\": case[\"oxygenDryVolPercent\"],\n",
+    "            \"Minimum burner K\": case[\"minimumBurnerTemperatureK\"],\n",
+    "            \"Stack K\": case[\"temperatureK\"],\n",
+    "            \"Useful oil heat MW\": case[\"usefulHeatToOilW\"] / 1.0e6,\n",
+    "            \"Residual chemical MW\": case[\"residualChemicalPowerW\"] / 1.0e6,\n",
+    "            \"CH4 dry mg/Nm3\": case[\"methaneMgPerNormalM3Dry\"],\n",
+    "            \"Organic C mgC/Nm3\": case[\"organicCarbonMgCPerNormalM3Dry\"],\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "burner_table = pd.DataFrame(burner_rows).set_index(\"case\")\n",
+    "display(burner_table.style.format(\"{:.6g}\"))\n"
+   ],
+   "id": "f4de0f77b8dc"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "image/png": 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+      "text/plain": "<Figure size [13.   3.8]>"
+     }
+    }
+   ],
+   "source": [
+    "figure, axes = plt.subplots(1, 3, figsize=(13, 3.8))\n",
+    "burner_table[\"CO kg/h\"].plot.bar(ax=axes[0], color=[\"#1367a8\", \"#e07a1f\"])\n",
+    "axes[0].set_ylabel(\"CO [kg/h]\")\n",
+    "axes[0].set_xlabel(\"\")\n",
+    "axes[0].tick_params(axis=\"x\", rotation=0)\n",
+    "\n",
+    "burner_table[\"Minimum burner K\"].plot.bar(\n",
+    "    ax=axes[1],\n",
+    "    color=[\"#1367a8\", \"#e07a1f\"],\n",
+    ")\n",
+    "axes[1].set_ylabel(\"Minimum burner temperature [K]\")\n",
+    "axes[1].set_xlabel(\"\")\n",
+    "axes[1].tick_params(axis=\"x\", rotation=0)\n",
+    "\n",
+    "burner_table[\"Useful oil heat MW\"].plot.bar(\n",
+    "    ax=axes[2],\n",
+    "    color=[\"#1367a8\", \"#e07a1f\"],\n",
+    ")\n",
+    "axes[2].set_ylabel(\"Useful hot-oil heat [MW]\")\n",
+    "axes[2].set_xlabel(\"\")\n",
+    "axes[2].tick_params(axis=\"x\", rotation=0)\n",
+    "\n",
+    "figure.suptitle(\"Equal total fuel and air: burner-count comparison\")\n",
+    "figure.tight_layout()\n",
+    "plt.show()\n"
+   ],
+   "id": "df32ea35bf92"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fixed-common-air fuel-load sweep\n",
+    "\n",
+    "Raw dry concentration and 3 vol% O2-corrected concentration are shown separately from actual CO mass rate. This prevents dilution or oxygen correction from being mistaken for a reduction in emitted CO mass.\n"
+   ],
+   "id": "9ce823fa8bf2"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "<pandas.io.formats.style.Styler object at 0x7f3e39199a30>",
+      "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_5ce4f\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_5ce4f_level0_col0\" class=\"col_heading level0 col0\" >Fuel load fraction</th>\n      <th id=\"T_5ce4f_level0_col1\" class=\"col_heading level0 col1\" >Captured air fraction</th>\n      <th id=\"T_5ce4f_level0_col2\" class=\"col_heading level0 col2\" >CO kg/h</th>\n      <th id=\"T_5ce4f_level0_col3\" class=\"col_heading level0 col3\" >CO dry ppmv</th>\n      <th id=\"T_5ce4f_level0_col4\" class=\"col_heading level0 col4\" >CO dry mg/Nm3</th>\n      <th id=\"T_5ce4f_level0_col5\" class=\"col_heading level0 col5\" >CO at 3% O2 mg/Nm3</th>\n      <th id=\"T_5ce4f_level0_col6\" class=\"col_heading level0 col6\" >Dry O2 vol%</th>\n      <th id=\"T_5ce4f_level0_col7\" class=\"col_heading level0 col7\" >Minimum burner K</th>\n      <th id=\"T_5ce4f_level0_col8\" class=\"col_heading level0 col8\" >Stack K</th>\n      <th id=\"T_5ce4f_level0_col9\" class=\"col_heading level0 col9\" >Useful oil heat MW</th>\n      <th id=\"T_5ce4f_level0_col10\" class=\"col_heading level0 col10\" >Residual chemical MW</th>\n      <th id=\"T_5ce4f_level0_col11\" class=\"col_heading level0 col11\" >CH4 dry mg/Nm3</th>\n      <th id=\"T_5ce4f_level0_col12\" class=\"col_heading level0 col12\" >Organic C mgC/Nm3</th>\n      <th id=\"T_5ce4f_level0_col13\" class=\"col_heading level0 col13\" >Diagnostic</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_5ce4f_level0_row0\" class=\"row_heading level0 row0\" >5</th>\n      <td id=\"T_5ce4f_row0_col0\" class=\"data row0 col0\" >0.100000</td>\n      <td id=\"T_5ce4f_row0_col1\" class=\"data row0 col1\" >0.180000</td>\n      <td id=\"T_5ce4f_row0_col2\" class=\"data row0 col2\" >2.959195</td>\n      <td id=\"T_5ce4f_row0_col3\" class=\"data row0 col3\" >76.151024</td>\n      <td id=\"T_5ce4f_row0_col4\" class=\"data row0 col4\" >95.163428</td>\n      <td id=\"T_5ce4f_row0_col5\" class=\"data row0 col5\" >1045.900275</td>\n      <td id=\"T_5ce4f_row0_col6\" class=\"data row0 col6\" >19.271331</td>\n      <td id=\"T_5ce4f_row0_col7\" class=\"data row0 col7\" >1502.913696</td>\n      <td id=\"T_5ce4f_row0_col8\" class=\"data row0 col8\" >549.518247</td>\n      <td id=\"T_5ce4f_row0_col9\" class=\"data row0 col9\" >0.045568</td>\n      <td id=\"T_5ce4f_row0_col10\" class=\"data row0 col10\" >0.010689</td>\n      <td id=\"T_5ce4f_row0_col11\" class=\"data row0 col11\" >0.038363</td>\n      <td id=\"T_5ce4f_row0_col12\" class=\"data row0 col12\" >3.203230</td>\n      <td id=\"T_5ce4f_row0_col13\" class=\"data row0 col13\" >BURNING</td>\n    </tr>\n    <tr>\n      <th id=\"T_5ce4f_level0_row1\" class=\"row_heading level0 row1\" >4</th>\n      <td id=\"T_5ce4f_row1_col0\" class=\"data row1 col0\" >0.200000</td>\n      <td id=\"T_5ce4f_row1_col1\" class=\"data row1 col1\" >0.360000</td>\n      <td id=\"T_5ce4f_row1_col2\" class=\"data row1 col2\" >9.474704</td>\n      <td id=\"T_5ce4f_row1_col3\" class=\"data row1 col3\" >245.719360</td>\n      <td id=\"T_5ce4f_row1_col4\" class=\"data row1 col4\" >307.067396</td>\n      <td id=\"T_5ce4f_row1_col5\" class=\"data row1 col5\" >1622.035289</td>\n      <td id=\"T_5ce4f_row1_col6\" class=\"data row1 col6\" >17.511352</td>\n      <td id=\"T_5ce4f_row1_col7\" class=\"data row1 col7\" >1499.636315</td>\n      <td id=\"T_5ce4f_row1_col8\" class=\"data row1 col8\" >551.158370</td>\n      <td id=\"T_5ce4f_row1_col9\" class=\"data row1 col9\" >2.955600</td>\n      <td id=\"T_5ce4f_row1_col10\" class=\"data row1 col10\" >0.032223</td>\n      <td id=\"T_5ce4f_row1_col11\" class=\"data row1 col11\" >0.110977</td>\n      <td id=\"T_5ce4f_row1_col12\" class=\"data row1 col12\" >7.360326</td>\n      <td id=\"T_5ce4f_row1_col13\" class=\"data row1 col13\" >INCOMPLETE_CONVERSION_OR_NO_USEFUL_HEAT</td>\n    </tr>\n    <tr>\n      <th id=\"T_5ce4f_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n      <td id=\"T_5ce4f_row2_col0\" class=\"data row2 col0\" >0.300000</td>\n      <td id=\"T_5ce4f_row2_col1\" class=\"data row2 col1\" >0.540000</td>\n      <td id=\"T_5ce4f_row2_col2\" class=\"data row2 col2\" >18.071874</td>\n      <td id=\"T_5ce4f_row2_col3\" class=\"data row2 col3\" >472.360224</td>\n      <td id=\"T_5ce4f_row2_col4\" class=\"data row2 col4\" >590.293024</td>\n      <td id=\"T_5ce4f_row2_col5\" class=\"data row2 col5\" >2041.606497</td>\n      <td id=\"T_5ce4f_row2_col6\" class=\"data row2 col6\" >15.724544</td>\n      <td id=\"T_5ce4f_row2_col7\" class=\"data row2 col7\" >1496.978584</td>\n      <td id=\"T_5ce4f_row2_col8\" class=\"data row2 col8\" >553.061544</td>\n      <td id=\"T_5ce4f_row2_col9\" class=\"data row2 col9\" >5.859476</td>\n      <td id=\"T_5ce4f_row2_col10\" class=\"data row2 col10\" >0.056032</td>\n      <td id=\"T_5ce4f_row2_col11\" class=\"data row2 col11\" >0.171499</td>\n      <td id=\"T_5ce4f_row2_col12\" class=\"data row2 col12\" >5.599184</td>\n      <td id=\"T_5ce4f_row2_col13\" class=\"data row2 col13\" >INCOMPLETE_CONVERSION_OR_NO_USEFUL_HEAT</td>\n    </tr>\n    <tr>\n      <th id=\"T_5ce4f_level0_row3\" class=\"row_heading level0 row3\" >2</th>\n      <td id=\"T_5ce4f_row3_col0\" class=\"data row3 col0\" >0.400000</td>\n      <td id=\"T_5ce4f_row3_col1\" class=\"data row3 col1\" >0.720000</td>\n      <td id=\"T_5ce4f_row3_col2\" class=\"data row3 col2\" >7.754922</td>\n      <td id=\"T_5ce4f_row3_col3\" class=\"data row3 col3\" >204.364401</td>\n      <td id=\"T_5ce4f_row3_col4\" class=\"data row3 col4\" >255.387466</td>\n      <td id=\"T_5ce4f_row3_col5\" class=\"data row3 col5\" >651.778391</td>\n      <td id=\"T_5ce4f_row3_col6\" class=\"data row3 col6\" >13.886212</td>\n      <td id=\"T_5ce4f_row3_col7\" class=\"data row3 col7\" >1494.651075</td>\n      <td id=\"T_5ce4f_row3_col8\" class=\"data row3 col8\" >555.279995</td>\n      <td id=\"T_5ce4f_row3_col9\" class=\"data row3 col9\" >8.816740</td>\n      <td id=\"T_5ce4f_row3_col10\" class=\"data row3 col10\" >0.021918</td>\n      <td id=\"T_5ce4f_row3_col11\" class=\"data row3 col11\" >0.000004</td>\n      <td id=\"T_5ce4f_row3_col12\" class=\"data row3 col12\" >0.033677</td>\n      <td id=\"T_5ce4f_row3_col13\" class=\"data row3 col13\" >BURNING</td>\n    </tr>\n    <tr>\n      <th id=\"T_5ce4f_level0_row4\" class=\"row_heading level0 row4\" >1</th>\n      <td id=\"T_5ce4f_row4_col0\" class=\"data row4 col0\" >0.600000</td>\n      <td id=\"T_5ce4f_row4_col1\" class=\"data row4 col1\" >1.000000</td>\n      <td id=\"T_5ce4f_row4_col2\" class=\"data row4 col2\" >0.033054</td>\n      <td id=\"T_5ce4f_row4_col3\" class=\"data row4 col3\" >0.885391</td>\n      <td id=\"T_5ce4f_row4_col4\" class=\"data row4 col4\" >1.106444</td>\n      <td id=\"T_5ce4f_row4_col5\" class=\"data row4 col5\" >1.840177</td>\n      <td id=\"T_5ce4f_row4_col6\" class=\"data row4 col6\" >10.137255</td>\n      <td id=\"T_5ce4f_row4_col7\" class=\"data row4 col7\" >1569.409941</td>\n      <td id=\"T_5ce4f_row4_col8\" class=\"data row4 col8\" >560.506104</td>\n      <td id=\"T_5ce4f_row4_col9\" class=\"data row4 col9\" >14.672404</td>\n      <td id=\"T_5ce4f_row4_col10\" class=\"data row4 col10\" >0.000254</td>\n      <td id=\"T_5ce4f_row4_col11\" class=\"data row4 col11\" >0.000000</td>\n      <td id=\"T_5ce4f_row4_col12\" class=\"data row4 col12\" >0.003879</td>\n      <td id=\"T_5ce4f_row4_col13\" class=\"data row4 col13\" >BURNING</td>\n    </tr>\n    <tr>\n      <th id=\"T_5ce4f_level0_row5\" class=\"row_heading level0 row5\" >0</th>\n      <td id=\"T_5ce4f_row5_col0\" class=\"data row5 col0\" >1.000000</td>\n      <td id=\"T_5ce4f_row5_col1\" class=\"data row5 col1\" >1.000000</td>\n      <td id=\"T_5ce4f_row5_col2\" class=\"data row5 col2\" >0.110188</td>\n      <td id=\"T_5ce4f_row5_col3\" class=\"data row5 col3\" >3.051188</td>\n      <td id=\"T_5ce4f_row5_col4\" class=\"data row5 col4\" >3.812970</td>\n      <td id=\"T_5ce4f_row5_col5\" class=\"data row5 col5\" >3.661017</td>\n      <td id=\"T_5ce4f_row5_col6\" class=\"data row5 col6\" >2.257051</td>\n      <td id=\"T_5ce4f_row5_col7\" class=\"data row5 col7\" >2109.632083</td>\n      <td id=\"T_5ce4f_row5_col8\" class=\"data row5 col8\" >574.288547</td>\n      <td id=\"T_5ce4f_row5_col9\" class=\"data row5 col9\" >26.271354</td>\n      <td id=\"T_5ce4f_row5_col10\" class=\"data row5 col10\" >0.013819</td>\n      <td id=\"T_5ce4f_row5_col11\" class=\"data row5 col11\" >0.000000</td>\n      <td id=\"T_5ce4f_row5_col12\" class=\"data row5 col12\" >0.000000</td>\n      <td id=\"T_5ce4f_row5_col13\" class=\"data row5 col13\" >BURNING</td>\n    </tr>\n  </tbody>\n</table>\n"
+     }
+    }
+   ],
+   "source": [
+    "sweep_rows = []\n",
+    "for case in results[\"constant_air_optional_entrainment_hypothesis\"]:\n",
+    "    sweep_rows.append(\n",
+    "        {\n",
+    "            \"Fuel load fraction\": case[\"fuelLoadFraction\"],\n",
+    "            \"Captured air fraction\": case[\"assumedCapturedAirFraction\"],\n",
+    "            \"CO kg/h\": case[\"coMassRateKgPerHour\"],\n",
+    "            \"CO dry ppmv\": case[\"coPpmvDry\"],\n",
+    "            \"CO dry mg/Nm3\": case[\"coMgPerNormalM3DryAt273_15K101325Pa\"],\n",
+    "            \"CO at 3% O2 mg/Nm3\": case[\"coMgPerNormalM3DryAtReferenceOxygen\"],\n",
+    "            \"Dry O2 vol%\": case[\"oxygenDryVolPercent\"],\n",
+    "            \"Minimum burner K\": case[\"minimumBurnerTemperatureK\"],\n",
+    "            \"Stack K\": case[\"temperatureK\"],\n",
+    "            \"Useful oil heat MW\": case[\"usefulHeatToOilW\"] / 1.0e6,\n",
+    "            \"Residual chemical MW\": case[\"residualChemicalPowerW\"] / 1.0e6,\n",
+    "            \"CH4 dry mg/Nm3\": case[\"methaneMgPerNormalM3Dry\"],\n",
+    "            \"Organic C mgC/Nm3\": case[\"organicCarbonMgCPerNormalM3Dry\"],\n",
+    "            \"Diagnostic\": case[\"branchDiagnostic\"],\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "sweep_table = pd.DataFrame(sweep_rows).sort_values(\"Fuel load fraction\")\n",
+    "display(sweep_table.style.format(precision=6))\n"
+   ],
+   "id": "40b271b86190"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "image/png": 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",
+      "text/plain": "<Figure size [12.  8.]>"
+     }
+    }
+   ],
+   "source": [
+    "figure, axes = plt.subplots(2, 2, figsize=(12, 8))\n",
+    "x = sweep_table[\"Fuel load fraction\"]\n",
+    "\n",
+    "axes[0, 0].plot(x, sweep_table[\"CO kg/h\"], \"o-\", color=\"#b23a48\")\n",
+    "axes[0, 0].set_ylabel(\"Actual CO [kg/h]\")\n",
+    "\n",
+    "axes[0, 1].plot(x, sweep_table[\"CO dry mg/Nm3\"], \"o-\", label=\"Raw dry\")\n",
+    "axes[0, 1].plot(\n",
+    "    x,\n",
+    "    sweep_table[\"CO at 3% O2 mg/Nm3\"],\n",
+    "    \"s--\",\n",
+    "    label=\"Corrected to 3 vol% O2\",\n",
+    ")\n",
+    "axes[0, 1].set_ylabel(\"CO [mg/Nm3 at 273.15 K, 101325 Pa]\")\n",
+    "axes[0, 1].legend()\n",
+    "\n",
+    "axes[1, 0].plot(x, sweep_table[\"Dry O2 vol%\"], \"o-\", color=\"#4c956c\")\n",
+    "axes[1, 0].set_ylabel(\"Dry O2 [vol%]\")\n",
+    "\n",
+    "axes[1, 1].plot(x, sweep_table[\"Minimum burner K\"], \"o-\", label=\"Burner\")\n",
+    "axes[1, 1].plot(x, sweep_table[\"Stack K\"], \"s--\", label=\"Stack\")\n",
+    "axes[1, 1].set_ylabel(\"Temperature [K]\")\n",
+    "axes[1, 1].legend()\n",
+    "\n",
+    "for axis in axes.flat:\n",
+    "    axis.set_xlabel(\"Fuel load fraction [-]\")\n",
+    "    axis.grid(alpha=0.25)\n",
+    "\n",
+    "figure.suptitle(\"Fixed common air with declared local-air capture assumption\")\n",
+    "figure.tight_layout()\n",
+    "plt.show()\n"
+   ],
+   "id": "8e04a3ecd03e"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "image/png": 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",
+      "text/plain": "<Figure size [14.  4.]>"
+     }
+    }
+   ],
+   "source": [
+    "figure, axes = plt.subplots(1, 3, figsize=(14, 4))\n",
+    "\n",
+    "axes[0].plot(x, sweep_table[\"Useful oil heat MW\"], \"o-\", label=\"Useful heat\")\n",
+    "axes[0].plot(x, sweep_table[\"Residual chemical MW\"], \"s--\", label=\"Residual chemical\")\n",
+    "axes[0].set_ylabel(\"Power [MW]\")\n",
+    "axes[0].legend()\n",
+    "\n",
+    "axes[1].semilogy(x, sweep_table[\"CH4 dry mg/Nm3\"], \"o-\", label=\"CH4\")\n",
+    "axes[1].semilogy(x, sweep_table[\"Organic C mgC/Nm3\"], \"s--\", label=\"Organic carbon\")\n",
+    "axes[1].set_ylabel(\"Dry diagnostic concentration\")\n",
+    "axes[1].legend()\n",
+    "\n",
+    "axes[2].plot(x, sweep_table[\"Captured air fraction\"], \"o-\", color=\"#6f2dbd\")\n",
+    "axes[2].set_ylabel(\"Assumed captured-air fraction [-]\")\n",
+    "\n",
+    "for axis in axes:\n",
+    "    axis.set_xlabel(\"Fuel load fraction [-]\")\n",
+    "    axis.grid(alpha=0.25)\n",
+    "\n",
+    "figure.suptitle(\"Heat generation, fuel-slip diagnostics, and declared air capture\")\n",
+    "figure.tight_layout()\n",
+    "plt.show()\n"
+   ],
+   "id": "13d9d56227b8"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Explicit 10–40 MW scaling\n",
+    "\n",
+    "Reactive volumes and heat-transfer area scale explicitly with firing rate. This is a numerical and energy-balance sensitivity, not a scale-up qualification from a laboratory flame.\n"
+   ],
+   "id": "b75d76c1ed2a"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "<pandas.io.formats.style.Styler object at 0x7f3e049cc9e0>",
+      "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_9f2ed\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_9f2ed_level0_col0\" class=\"col_heading level0 col0\" >Firing MW</th>\n      <th id=\"T_9f2ed_level0_col1\" class=\"col_heading level0 col1\" >CO kg/h</th>\n      <th id=\"T_9f2ed_level0_col2\" class=\"col_heading level0 col2\" >Stack K</th>\n      <th id=\"T_9f2ed_level0_col3\" class=\"col_heading level0 col3\" >Useful oil heat MW</th>\n      <th id=\"T_9f2ed_level0_col4\" class=\"col_heading level0 col4\" >Energy residual</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_9f2ed_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_9f2ed_row0_col0\" class=\"data row0 col0\" >10.00000000</td>\n      <td id=\"T_9f2ed_row0_col1\" class=\"data row0 col1\" >0.03682193</td>\n      <td id=\"T_9f2ed_row0_col2\" class=\"data row0 col2\" >573.94804155</td>\n      <td id=\"T_9f2ed_row0_col3\" class=\"data row0 col3\" >8.74543506</td>\n      <td id=\"T_9f2ed_row0_col4\" class=\"data row0 col4\" >-0.00000005</td>\n    </tr>\n    <tr>\n      <th id=\"T_9f2ed_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_9f2ed_row1_col0\" class=\"data row1 col0\" >20.00000000</td>\n      <td id=\"T_9f2ed_row1_col1\" class=\"data row1 col1\" >0.07351927</td>\n      <td id=\"T_9f2ed_row1_col2\" class=\"data row1 col2\" >574.17702183</td>\n      <td id=\"T_9f2ed_row1_col3\" class=\"data row1 col3\" >17.50658618</td>\n      <td id=\"T_9f2ed_row1_col4\" class=\"data row1 col4\" >-0.00000005</td>\n    </tr>\n    <tr>\n      <th id=\"T_9f2ed_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_9f2ed_row2_col0\" class=\"data row2 col0\" >30.00000000</td>\n      <td id=\"T_9f2ed_row2_col1\" class=\"data row2 col1\" >0.11018808</td>\n      <td id=\"T_9f2ed_row2_col2\" class=\"data row2 col2\" >574.28854711</td>\n      <td id=\"T_9f2ed_row2_col3\" class=\"data row2 col3\" >26.27135433</td>\n      <td id=\"T_9f2ed_row2_col4\" class=\"data row2 col4\" >-0.00000005</td>\n    </tr>\n    <tr>\n      <th id=\"T_9f2ed_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_9f2ed_row3_col0\" class=\"data row3 col0\" >40.00000000</td>\n      <td id=\"T_9f2ed_row3_col1\" class=\"data row3 col1\" >0.14684095</td>\n      <td id=\"T_9f2ed_row3_col2\" class=\"data row3 col2\" >574.35906811</td>\n      <td id=\"T_9f2ed_row3_col3\" class=\"data row3 col3\" >35.03814414</td>\n      <td id=\"T_9f2ed_row3_col4\" class=\"data row3 col4\" >-0.00000005</td>\n    </tr>\n  </tbody>\n</table>\n"
+     }
+    },
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "image/png": 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",
+      "text/plain": "<Figure size [10.   3.8]>"
+     }
+    }
+   ],
+   "source": [
+    "scale_rows = []\n",
+    "for case in results[\"explicit_geometry_heat_transfer_scaling\"]:\n",
+    "    scale_rows.append(\n",
+    "        {\n",
+    "            \"Firing MW\": case[\"nominalFiringMW\"],\n",
+    "            \"CO kg/h\": case[\"coMassRateKgPerHour\"],\n",
+    "            \"Stack K\": case[\"temperatureK\"],\n",
+    "            \"Useful oil heat MW\": case[\"usefulHeatToOilW\"] / 1.0e6,\n",
+    "            \"Energy residual\": case[\"fullEnergyBalanceRelativeResidual\"],\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "scale_table = pd.DataFrame(scale_rows)\n",
+    "display(scale_table.style.format(precision=8))\n",
+    "\n",
+    "figure, axes = plt.subplots(1, 2, figsize=(10, 3.8))\n",
+    "axes[0].plot(scale_table[\"Firing MW\"], scale_table[\"Useful oil heat MW\"], \"o-\")\n",
+    "axes[0].set_xlabel(\"Firing [MW LHV]\")\n",
+    "axes[0].set_ylabel(\"Useful hot-oil heat [MW]\")\n",
+    "axes[1].plot(scale_table[\"Firing MW\"], scale_table[\"CO kg/h\"], \"o-\", color=\"#b23a48\")\n",
+    "axes[1].set_xlabel(\"Firing [MW LHV]\")\n",
+    "axes[1].set_ylabel(\"CO [kg/h]\")\n",
+    "for axis in axes:\n",
+    "    axis.grid(alpha=0.25)\n",
+    "figure.tight_layout()\n",
+    "plt.show()\n"
+   ],
+   "id": "7051a0c3004f"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conservation, projection, and provenance evidence\n",
+    "\n",
+    "The native default projection tolerance is $10^{-6}$ for the seven/five cases. The optional load sweep declares $10^{-3}$ because frozen trace intermediates grow at lower load; the exact mechanism state remains available and no missing atoms are renormalized. Every reactor-zone mass and element balance is checked independently.\n"
+   ],
+   "id": "a9f178420064"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "Seven/five conservation, energy, and default projection gates passed.\n"
+    },
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "<pandas.io.formats.style.Styler object at 0x7f3e049f6690>",
+      "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_deb6d\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_deb6d_level0_col0\" class=\"col_heading level0 col0\" >max zone mass residual</th>\n      <th id=\"T_deb6d_level0_col1\" class=\"col_heading level0 col1\" >max zone element residual</th>\n      <th id=\"T_deb6d_level0_col2\" class=\"col_heading level0 col2\" >full energy residual</th>\n      <th id=\"T_deb6d_level0_col3\" class=\"col_heading level0 col3\" >omitted C fraction</th>\n      <th id=\"T_deb6d_level0_col4\" class=\"col_heading level0 col4\" >omitted H fraction</th>\n      <th id=\"T_deb6d_level0_col5\" class=\"col_heading level0 col5\" >omitted O fraction</th>\n      <th id=\"T_deb6d_level0_col6\" class=\"col_heading level0 col6\" >omitted N fraction</th>\n    </tr>\n    <tr>\n      <th class=\"index_name level0\" >case</th>\n      <th class=\"blank col0\" >&nbsp;</th>\n      <th class=\"blank col1\" >&nbsp;</th>\n      <th class=\"blank col2\" >&nbsp;</th>\n      <th class=\"blank col3\" >&nbsp;</th>\n      <th class=\"blank col4\" >&nbsp;</th>\n      <th class=\"blank col5\" >&nbsp;</th>\n      <th class=\"blank col6\" >&nbsp;</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_deb6d_level0_row0\" class=\"row_heading level0 row0\" >Seven active</th>\n      <td id=\"T_deb6d_row0_col0\" class=\"data row0 col0\" >5.228e-10</td>\n      <td id=\"T_deb6d_row0_col1\" class=\"data row0 col1\" >5.228e-10</td>\n      <td id=\"T_deb6d_row0_col2\" class=\"data row0 col2\" >5.451e-08</td>\n      <td id=\"T_deb6d_row0_col3\" class=\"data row0 col3\" >3.719e-13</td>\n      <td id=\"T_deb6d_row0_col4\" class=\"data row0 col4\" >8.722e-07</td>\n      <td id=\"T_deb6d_row0_col5\" class=\"data row0 col5\" >6.466e-07</td>\n      <td id=\"T_deb6d_row0_col6\" class=\"data row0 col6\" >3.769e-11</td>\n    </tr>\n    <tr>\n      <th id=\"T_deb6d_level0_row1\" class=\"row_heading level0 row1\" >Five active</th>\n      <td id=\"T_deb6d_row1_col0\" class=\"data row1 col0\" >3.588e-13</td>\n      <td id=\"T_deb6d_row1_col1\" class=\"data row1 col1\" >3.600e-13</td>\n      <td id=\"T_deb6d_row1_col2\" class=\"data row1 col2\" >5.454e-08</td>\n      <td id=\"T_deb6d_row1_col3\" class=\"data row1 col3\" >3.795e-13</td>\n      <td id=\"T_deb6d_row1_col4\" class=\"data row1 col4\" >8.624e-07</td>\n      <td id=\"T_deb6d_row1_col5\" class=\"data row1 col5\" >6.393e-07</td>\n      <td id=\"T_deb6d_row1_col6\" class=\"data row1 col6\" >2.962e-11</td>\n    </tr>\n  </tbody>\n</table>\n"
+     }
+    }
+   ],
+   "source": [
+    "def maximum_zone_residual(case):\n",
+    "    maximum_mass = 0.0\n",
+    "    maximum_element = 0.0\n",
+    "    for zone in case[\"zoneConservationDiagnostics\"]:\n",
+    "        maximum_mass = max(maximum_mass, abs(zone[\"massBalanceRelativeResidual\"]))\n",
+    "        for element in zone[\"elementBalances\"].values():\n",
+    "            value = element[\"acceptanceScaledResidual\"]\n",
+    "            maximum_element = max(maximum_element, abs(value))\n",
+    "    return maximum_mass, maximum_element\n",
+    "\n",
+    "validation_rows = []\n",
+    "for label, case in burner_cases.items():\n",
+    "    maximum_mass, maximum_element = maximum_zone_residual(case)\n",
+    "    validation_rows.append(\n",
+    "        {\n",
+    "            \"case\": label,\n",
+    "            \"max zone mass residual\": maximum_mass,\n",
+    "            \"max zone element residual\": maximum_element,\n",
+    "            \"full energy residual\": abs(case[\"fullEnergyBalanceRelativeResidual\"]),\n",
+    "            \"omitted C fraction\": case[\"omittedElementFractions\"][\"C\"],\n",
+    "            \"omitted H fraction\": case[\"omittedElementFractions\"][\"H\"],\n",
+    "            \"omitted O fraction\": case[\"omittedElementFractions\"][\"O\"],\n",
+    "            \"omitted N fraction\": case[\"omittedElementFractions\"][\"N\"],\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "validation_table = pd.DataFrame(validation_rows).set_index(\"case\")\n",
+    "display(validation_table.style.format(\"{:.3e}\"))\n",
+    "\n",
+    "assert validation_table[\"max zone mass residual\"].max() < 1.0e-7\n",
+    "assert validation_table[\"max zone element residual\"].max() < 1.0e-7\n",
+    "assert validation_table[\"full energy residual\"].max() < 1.0e-6\n",
+    "assert validation_table[[\n",
+    "    \"omitted C fraction\",\n",
+    "    \"omitted H fraction\",\n",
+    "    \"omitted O fraction\",\n",
+    "    \"omitted N fraction\",\n",
+    "]].to_numpy().max() < 1.0e-6\n",
+    "print(\"Seven/five conservation, energy, and default projection gates passed.\")\n"
+   ],
+   "id": "342b7321d8af"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "Maximum sweep omitted-element fraction: 3.247241e-04\nMaximum sweep energy residual: 1.788856e-07\nRise/fall CO response occurs with positive useful heat at 30% and 20% load.\n"
+    }
+   ],
+   "source": [
+    "sweep_cases = results[\"constant_air_optional_entrainment_hypothesis\"]\n",
+    "maximum_sweep_omission = max(\n",
+    "    max(case[\"omittedElementFractions\"].values())\n",
+    "    for case in sweep_cases\n",
+    ")\n",
+    "maximum_sweep_energy_residual = max(\n",
+    "    abs(case[\"fullEnergyBalanceRelativeResidual\"])\n",
+    "    for case in sweep_cases\n",
+    ")\n",
+    "co_by_load = {\n",
+    "    case[\"fuelLoadFraction\"]: case[\"coMassRateKgPerHour\"]\n",
+    "    for case in sweep_cases\n",
+    "}\n",
+    "useful_heat_by_load = {\n",
+    "    case[\"fuelLoadFraction\"]: case[\"usefulHeatToOilW\"]\n",
+    "    for case in sweep_cases\n",
+    "}\n",
+    "\n",
+    "assert maximum_sweep_omission < 1.0e-3\n",
+    "assert maximum_sweep_energy_residual < 1.0e-6\n",
+    "assert co_by_load[0.3] > co_by_load[0.4]\n",
+    "assert co_by_load[0.2] < co_by_load[0.3]\n",
+    "assert useful_heat_by_load[0.3] > 0.0\n",
+    "assert useful_heat_by_load[0.2] > 0.0\n",
+    "\n",
+    "print(f\"Maximum sweep omitted-element fraction: {maximum_sweep_omission:.6e}\")\n",
+    "print(f\"Maximum sweep energy residual: {maximum_sweep_energy_residual:.6e}\")\n",
+    "print(\"Rise/fall CO response occurs with positive useful heat at 30% and 20% load.\")\n"
+   ],
+   "id": "e66ab7363c10"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "<pandas.io.formats.style.Styler object at 0x7f3e39237ad0>",
+      "text/html": "<style type=\"text/css\">\n</style>\n<table id=\"T_10858\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th id=\"T_10858_level0_col0\" class=\"col_heading level0 col0\" >Mechanism species</th>\n      <th id=\"T_10858_level0_col1\" class=\"col_heading level0 col1\" >Omitted H atom mol/s</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_10858_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_10858_row0_col0\" class=\"data row0 col0\" >H2O2</td>\n      <td id=\"T_10858_row0_col1\" class=\"data row0 col1\" >7.911012e-05</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_10858_row1_col0\" class=\"data row1 col0\" >OH</td>\n      <td id=\"T_10858_row1_col1\" class=\"data row1 col1\" >2.634008e-05</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_10858_row2_col0\" class=\"data row2 col0\" >HNO</td>\n      <td id=\"T_10858_row2_col1\" class=\"data row2 col1\" >2.310688e-08</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_10858_row3_col0\" class=\"data row3 col0\" >HO2</td>\n      <td id=\"T_10858_row3_col1\" class=\"data row3 col1\" >1.673490e-08</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_10858_row4_col0\" class=\"data row4 col0\" >H</td>\n      <td id=\"T_10858_row4_col1\" class=\"data row4 col1\" >7.924073e-10</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n      <td id=\"T_10858_row5_col0\" class=\"data row5 col0\" >HNCO</td>\n      <td id=\"T_10858_row5_col1\" class=\"data row5 col1\" >1.594103e-11</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n      <td id=\"T_10858_row6_col0\" class=\"data row6 col0\" >NH2</td>\n      <td id=\"T_10858_row6_col1\" class=\"data row6 col1\" >3.732450e-12</td>\n    </tr>\n    <tr>\n      <th id=\"T_10858_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n      <td id=\"T_10858_row7_col0\" class=\"data row7 col0\" >HCN</td>\n      <td id=\"T_10858_row7_col1\" class=\"data row7 col1\" >6.806796e-14</td>\n    </tr>\n  </tbody>\n</table>\n"
+     }
+    },
+    {
+     "output_type": "display_data",
+     "metadata": {},
+     "data": {
+      "text/plain": "                          item                                              value\n0                       Solver                                            Cantera\n1               Solver version                                              3.2.0\n2                    Mechanism                                         gri30.yaml\n3  Canonical mechanism SHA-256  3cb2078af590038e2f9d3f33a8079ac882e6c1a4701c70...\n4                      Species                                                 53\n5                    Reactions                                                325\n6         Qualification status                        Software demonstration only",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>item</th>\n      <th>value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Solver</td>\n      <td>Cantera</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Solver version</td>\n      <td>3.2.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Mechanism</td>\n      <td>gri30.yaml</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Canonical mechanism SHA-256</td>\n      <td>3cb2078af590038e2f9d3f33a8079ac882e6c1a4701c70...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Species</td>\n      <td>53</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Reactions</td>\n      <td>325</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Qualification status</td>\n      <td>Software demonstration only</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     }
+    }
+   ],
+   "source": [
+    "seven = results[\"seven_burners\"]\n",
+    "hydrogen_diagnostics = seven[\"elementProjectionDiagnostics\"][\"H\"]\n",
+    "omitted_hydrogen = hydrogen_diagnostics[\"omittedSpeciesMolAtomsPerSecond\"]\n",
+    "top_omitted = sorted(\n",
+    "    omitted_hydrogen.items(),\n",
+    "    key=lambda item: item[1],\n",
+    "    reverse=True,\n",
+    ")[:8]\n",
+    "omitted_table = pd.DataFrame(\n",
+    "    top_omitted,\n",
+    "    columns=[\"Mechanism species\", \"Omitted H atom mol/s\"],\n",
+    ")\n",
+    "display(omitted_table.style.format({\"Omitted H atom mol/s\": \"{:.6e}\"}))\n",
+    "\n",
+    "provenance = seven[\"provenance\"]\n",
+    "provenance_table = pd.DataFrame(\n",
+    "    {\n",
+    "        \"item\": [\n",
+    "            \"Solver\",\n",
+    "            \"Solver version\",\n",
+    "            \"Mechanism\",\n",
+    "            \"Canonical mechanism SHA-256\",\n",
+    "            \"Species\",\n",
+    "            \"Reactions\",\n",
+    "            \"Qualification status\",\n",
+    "        ],\n",
+    "        \"value\": [\n",
+    "            provenance[\"solver\"],\n",
+    "            provenance[\"solverVersion\"],\n",
+    "            provenance[\"mechanism\"],\n",
+    "            provenance[\"resolvedMechanismSha256\"],\n",
+    "            provenance[\"speciesCount\"],\n",
+    "            provenance[\"reactionCount\"],\n",
+    "            \"Software demonstration only\",\n",
+    "        ],\n",
+    "    }\n",
+    ")\n",
+    "display(provenance_table)\n"
+   ],
+   "id": "66a932647a5e"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Interpretation and limits\n",
+    "\n",
+    "- Seven and five active burners give similar total useful heat at equal total fuel and air, while the finite-rate zone loading changes CO slightly.\n",
+    "- The separate fixed-air sweep produces a CO rise and fall in both mass and concentration. This emerges from kinetics, local-air capture, residence volume, and heat transfer; no direct emissions factor or target curve is fitted.\n",
+    "- Positive useful oil heat persists through the high-CO 30% and 20% load points. Complete extinction is therefore not used to explain the response.\n",
+    "- Raw dry, reference-O2-corrected, and actual-mass results are all retained. Oxygen correction is not interpreted as physical CO destruction.\n",
+    "- CH4 and organic-carbon values are mechanism diagnostics, not VOC-instrument equivalents.\n",
+    "- The sweep's local-air capture relation, effective tube sink, chamber geometry, steady refractory, and GRI-Mech chemistry are assumptions. Spatial burner geometry and dynamic refractory storage are not resolved.\n",
+    "- Public C2 and extrapolative C1 comparisons exist in NeqSim, but licensed C3/C4 qualification data remain missing. Do not use this notebook for plant calibration, emissions compliance, safety certification, or heater design.\n"
+   ],
+   "id": "79e95c731027"
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "multi_burner_hot_oil_heater_co_emissions.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.12"
+  },
+  "execution": {
+   "mode": "fresh-process-no-zmq",
+   "note": "Managed validation runner blocks Jupyter ZeroMQ sockets."
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}