LNG regasification via submerged combustion vaporizer — a PENG-ROBINSON process flowsheet
A real LNG-terminal regasification technology: fuel gas burns submerged in a water bath, and the hot combustion products bubbling through that bath transfer heat (via submerged tube coils) to vaporize the incoming LNG -- no new unit-op physics needed here, since this codebase's existing fired_heater already models exactly the energy balance this needs (Q_process = efficiency * Q_released from real fuel-gas combustion stoichiometry, then a duty-driven (P,H) flash on the process-side stream) and doesn't care whether that process stream starts liquid or vapor -- feeding it cryogenic liquid methane and specifying a target outlet temperature above its boiling point genuinely vaporizes it through the same mechanism. Honesty note: the water bath itself (its own thermal mass, the bubble-column heat-transfer coefficient, tube-coil geometry) isn't separately modeled -- the water bath is a heat-transfer PATH, not a separate energy-balance node, so representing it as fired_heater's existing efficiency-scaled duty transfer is honest, not a shortcut around missing physics (the same 'indirect utility duty stands in for the real mechanical path' posture already used by rotary_kiln's wall-temperature model elsewhere in this codebase).
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- Rigorous PENG-ROBINSON thermodynamics, solved by the same engine every simulation runs on.
- 1 unit operations modeled: SCV.
- Focus areas: LNG regasification, Submerged combustion, Cryogenics, Fired heater.
- Thermodynamics
- PENG-ROBINSON
- Components
- methane
- Unit operations
- SCV
Opens in a new tab, loaded straight into the app — no setup.
Read the step-by-step guideReproduce this exact result from Python — the real client.get_example() → run_and_wait() path, not a mockup.
from flowsim.sdk import FlowSimClient
client = FlowSimClient()
example = client.get_example("submerged-combustion-vaporizer")
sim = client.create_simulation(example["title"], example["flowsheet"])
result = client.run_and_wait(sim["id"])
print(result["status"]) # "converged"
streams = client.streams(sim["id"])Related models
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C3MR LNG liquefaction
A simplified APCI C3MR train: natural gas and the mixed refrigerant are precooled by a closed propane loop, liquefied to 120 K in a multi-stream main cryogenic exchanger against a closed N2/C1/C2/C3 refrigerant cycle, then let down to storage — LNG at ~115 K. Single-level precool and a single MCHE bundle (a real train uses three propane levels and two bundles); refrigerant charges are set via tear_specs.
Two-stage cascade (−100 °C)
Propylene + ethylene cascade: the ethylene loop condenses inside a heat exchanger against the evaporating propylene loop and serves a −100 °C load. Two coupled closed cycles. From the ChemSep casebook (Refrigeration_2-Stage-100C).
Three-stage cascade (−150 °C)
Propylene → ethylene → methane cascade to −150 °C: each colder loop condenses against the next-warmer loop’s evaporator. From the ChemSep casebook (Refrigeration_3-Stage-150C).
Four-stage cascade (≈−190 °C)
Propylene → ethylene → methane → nitrogen cascade reaching ≈81 K — four coupled closed loops, the full ChemSep cascade ladder (Refrigeration_4-Stage-190C). Air-separation-grade cold from stacked vapor-compression cycles.
TEALARC LNG liquefaction
A simplified Technip TEALARC train: two closed mixed-refrigerant loops — a heavy C1/C2/C3 precool MR that also cools itself in a 4-stream exchanger, and a light N2/C1/C2/C3 liquefaction MR — bring natural gas to 120 K before letdown to storage (LNG at ~115 K). Both circulations are set via tear_specs; the precool MR runs rich for pinch feasibility (screening fidelity). From the ChemSep casebook (TEALARC).