Copy-paste solutions for common thermodynamic tasks. Every code block defines its own fluid and can run independently in Python after pip install neqsim. The phase-envelope plotting block also requires matplotlib.

Table of Contents

Creating Fluids

Create Natural Gas

from neqsim import jneqsim

fluid = jneqsim.thermo.system.SystemSrkEos(298.15, 50.0)
fluid.addComponent("nitrogen", 0.02)
fluid.addComponent("CO2", 0.01)
fluid.addComponent("methane", 0.85)
fluid.addComponent("ethane", 0.06)
fluid.addComponent("propane", 0.03)
fluid.addComponent("n-butane", 0.02)
fluid.addComponent("n-pentane", 0.01)
fluid.setMixingRule("classic")

The constructor uses kelvin and bara. Component amounts are relative mole amounts; they do not need to sum to one. Set the mixing rule after all components are added.

Create Oil with a Characterized Plus Fraction

from neqsim import jneqsim

fluid = jneqsim.thermo.system.SystemPrEos(333.15, 200.0)
fluid.addComponent("nitrogen", 0.5)
fluid.addComponent("CO2", 2.0)
fluid.addComponent("methane", 45.0)
fluid.addComponent("ethane", 8.0)
fluid.addComponent("propane", 5.0)
fluid.addComponent("n-butane", 3.0)
fluid.addComponent("n-pentane", 2.0)
fluid.addComponent("n-hexane", 2.0)

# Arguments: relative mole amount, molar mass (kg/mol), density (g/cm3).
# Use a terminal numeric label before default Pedersen characterization.
fluid.addPlusFraction("C7", 32.5, 0.220, 0.82)
fluid.setMixingRule("classic")
fluid.getCharacterization().getLumpingModel().setNumberOfPseudoComponents(12)
fluid.getCharacterization().characterisePlusFraction()
fluid.setMultiPhaseCheck(True)

addTBPfraction(...) creates one specified pseudo-component. Use addPlusFraction(...) followed by characterisePlusFraction() when a residual fraction is to be split and lumped. Although addPlusFraction(...) accepts a name containing +, the current default Pedersen characterization parser does not safely parse that name. Use a numeric terminal carbon label such as C7 when calling characterisePlusFraction().

Create a CO₂-Water Fluid with CPA

from neqsim import jneqsim

fluid = jneqsim.thermo.system.SystemSrkCPAstatoil(298.15, 100.0)
fluid.addComponent("CO2", 0.95)
fluid.addComponent("methane", 0.03)
fluid.addComponent("water", 0.02)
fluid.setMixingRule(10)

CPA is useful when association, especially water, matters. Validate the selected model and binary interaction parameters against data for the composition and conditions of interest.

Flash Calculations

This complete example runs TP, constant-enthalpy PH, and constant-entropy PS flashes from the same initial natural-gas state. Enthalpy and entropy passed to PHflash and PSflash are total-system values in J and J/K.

from neqsim import jneqsim

def make_fluid():
    gas = jneqsim.thermo.system.SystemSrkEos(298.15, 50.0)
    gas.addComponent("nitrogen", 0.02)
    gas.addComponent("CO2", 0.01)
    gas.addComponent("methane", 0.85)
    gas.addComponent("ethane", 0.06)
    gas.addComponent("propane", 0.03)
    gas.addComponent("n-butane", 0.02)
    gas.addComponent("n-pentane", 0.01)
    gas.setMixingRule("classic")
    return gas

tp_fluid = make_fluid()
tp_ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(tp_fluid)
tp_ops.TPflash()
tp_fluid.initProperties()
print(f"TP phases: {tp_fluid.getNumberOfPhases()}")

ph_fluid = make_fluid()
ph_ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(ph_fluid)
ph_ops.TPflash()
ph_fluid.initProperties()
initial_enthalpy_j = ph_fluid.getEnthalpy("J")
ph_fluid.setPressure(30.0, "bara")
ph_ops.PHflash(initial_enthalpy_j)
print(f"PH temperature: {ph_fluid.getTemperature() - 273.15:.2f} °C")

ps_fluid = make_fluid()
ps_ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(ps_fluid)
ps_ops.TPflash()
ps_fluid.initProperties()
initial_entropy_j_per_k = ps_fluid.getEntropy("J/K")
ps_fluid.setPressure(20.0, "bara")
ps_ops.PSflash(initial_entropy_j_per_k)
print(f"PS temperature: {ps_fluid.getTemperature() - 273.15:.2f} °C")

Reading Properties

Run a flash and initProperties() before reading physical properties. The no-argument getDensity() is based on the EoS phase volumes without Peneloux correction. getDensity("kg/m3") uses initialized physical-property densities and corrected volume fractions.

from neqsim import jneqsim

fluid = jneqsim.thermo.system.SystemSrkEos(298.15, 50.0)
fluid.addComponent("nitrogen", 0.02)
fluid.addComponent("CO2", 0.01)
fluid.addComponent("methane", 0.85)
fluid.addComponent("ethane", 0.06)
fluid.addComponent("propane", 0.03)
fluid.addComponent("n-butane", 0.02)
fluid.addComponent("n-pentane", 0.01)
fluid.setMixingRule("classic")

ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(fluid)
ops.TPflash()
fluid.initProperties()

print(f"Temperature: {fluid.getTemperature() - 273.15:.2f} °C")
print(f"Pressure: {fluid.getPressure():.2f} bara")
print(f"EoS density: {fluid.getDensity():.2f} kg/m³")
print(f"Corrected density: {fluid.getDensity('kg/m3'):.2f} kg/m³")
print(f"Molar mass: {fluid.getMolarMass('g/mol'):.2f} g/mol")
print(f"Z-factor: {fluid.getZ():.4f}")
print(f"Enthalpy: {fluid.getEnthalpy('kJ/kg'):.2f} kJ/kg")
print(f"Entropy: {fluid.getEntropy('J/kgK'):.2f} J/(kg·K)")
print(f"Cp: {fluid.getCp('kJ/kgK'):.4f} kJ/(kg·K)")
print(f"Cv: {fluid.getCv('kJ/kgK'):.4f} kJ/(kg·K)")
print(f"Sound speed: {fluid.getSoundSpeed('m/s'):.2f} m/s")
print(f"Viscosity: {fluid.getViscosity('cP'):.4f} cP")
print(
    "Thermal conductivity: "
    f"{fluid.getThermalConductivity('W/mK'):.4f} W/(m·K)"
)

if fluid.hasPhaseType("gas"):
    gas = fluid.getPhase("gas")
    print(f"Gas density: {gas.getDensity('kg/m3'):.2f} kg/m³")
    print(f"Gas viscosity: {gas.getViscosity('cP'):.4f} cP")
    print(f"Gas mole fraction: {gas.getBeta():.4f}")

for component_index in range(fluid.getNumberOfComponents()):
    component = fluid.getComponent(component_index)
    name = str(component.getComponentName())
    print(
        f"{name}: z={component.getz():.4f}, "
        f"Tc={component.getTC():.1f} K, "
        f"Pc={component.getPC():.1f} bara"
    )

Bulk properties of a multiphase system are mixture-level quantities. Read the named phase when a phase-specific value is required.

Phase Envelopes

The named arrays contain temperature in K and pressure in bara. The cricondenbar and cricondentherm arrays are ordered [temperature, pressure, ...].

from neqsim import jneqsim
import matplotlib.pyplot as plt

fluid = jneqsim.thermo.system.SystemSrkEos(298.15, 50.0)
fluid.addComponent("methane", 0.80)
fluid.addComponent("ethane", 0.10)
fluid.addComponent("propane", 0.05)
fluid.addComponent("n-butane", 0.05)
fluid.setMixingRule("classic")

ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(fluid)
ops.calcPTphaseEnvelope()

dew_temperature_c = [value - 273.15 for value in list(ops.get("dewT"))]
dew_pressure_bara = list(ops.get("dewP"))
bubble_temperature_c = [value - 273.15 for value in list(ops.get("bubT"))]
bubble_pressure_bara = list(ops.get("bubP"))

cricondenbar = list(ops.get("cricondenbar"))
cricondentherm = list(ops.get("cricondentherm"))
print(
    f"Cricondenbar: {cricondenbar[1]:.2f} bara at "
    f"{cricondenbar[0] - 273.15:.2f} °C"
)
print(
    f"Cricondentherm: {cricondentherm[0] - 273.15:.2f} °C at "
    f"{cricondentherm[1]:.2f} bara"
)

plt.figure(figsize=(9, 5))
plt.plot(dew_temperature_c, dew_pressure_bara, label="Dew line")
plt.plot(bubble_temperature_c, bubble_pressure_bara, label="Bubble line")
plt.xlabel("Temperature (°C)")
plt.ylabel("Pressure (bara)")
plt.title("Pressure-temperature phase envelope")
plt.grid(True)
plt.legend()
plt.show()

Near critical points and for strongly associating or highly asymmetric mixtures, check convergence and compare with a validated fluid model or laboratory data.

Which EoS Should I Use?

Fluid or task Starting model Important qualification
Dry natural gas SRK or PR Validate density and calorific properties for the composition
Gas condensate PR or SRK Tune heavy-end characterization to PVT data
Black or volatile oil PR or SRK Characterize and tune C7+ before process studies
Dry CO₂-rich fluid PR, SRK, or a validated multiparameter model Check impurities and phase-boundary range
CO₂ with water CPA Validate water content, mutual solubility, and BIPs
Natural-gas reference properties GERG-2008 Use only supported components and validity ranges
LNG GERG-2008 or PR Validate cryogenic liquid density and phase equilibrium
Electrolytes and brines Electrolyte-CPA Define ions, salinity basis, and precipitation scope

Selection depends on fluid chemistry, properties of interest, conditions, available tuning data, and required uncertainty—not only the fluid label.

from neqsim import jneqsim

temperature_k = 288.15
pressure_bara = 70.0

srk_fluid = jneqsim.thermo.system.SystemSrkEos(
    temperature_k,
    pressure_bara,
)
pr_fluid = jneqsim.thermo.system.SystemPrEos(
    temperature_k,
    pressure_bara,
)
cpa_fluid = jneqsim.thermo.system.SystemSrkCPAstatoil(
    temperature_k,
    pressure_bara,
)
gerg_fluid = jneqsim.thermo.system.SystemGERG2008Eos(
    temperature_k,
    pressure_bara,
)

Export, Parse, and Clone

toJson() returns a nested response with conditions, properties, and composition. Values are serialized as objects containing value and unit; convert numeric strings explicitly.

import json
from neqsim import jneqsim

fluid = jneqsim.thermo.system.SystemSrkEos(298.15, 50.0)
fluid.addComponent("methane", 0.90)
fluid.addComponent("ethane", 0.07)
fluid.addComponent("propane", 0.03)
fluid.setMixingRule("classic")

ops = jneqsim.thermodynamicoperations.ThermodynamicOperations(fluid)
ops.TPflash()
fluid.initProperties()

json_text = str(fluid.toJson())
data = json.loads(json_text)
temperature = data["conditions"]["overall"]["temperature"]
print(f"Temperature: {float(temperature['value']):.2f} {temperature['unit']}")

fluid_copy = fluid.clone()
fluid_copy.setTemperature(300.0)
print(f"Original: {fluid.getTemperature():.2f} K")
print(f"Copy: {fluid_copy.getTemperature():.2f} K")

The clone is independent of the original, but recalculate its equilibrium and properties after changing temperature, pressure, composition, or model settings.

See Also