Note

Go to the end to download the full example code.

Simulate a multi-zone HCCI engine#

Ansys Chemkin offers some idealized internal combustion (IC) engine models commonly used for fuel combustion and engine performance research. The Chemkin IC engine model is a specialized transient 0-D closed gas-phase reactor that mainly performs combustion simulation between the intake valve closing (IVC) and the exhaust valve opening (EVO), that is, when the engine cylinder resembles a closed chamber. The cylinder volume is derived from the piston motion as a function of the engine crank angle (CA) and engine parameters such as engine speed (RPM) and stroke. The energy equation is always solved and there are several wall heat transfer models specifically designed for engine simulations.

Note

For additional information on the Chemkin IC engine models, use the ansys.chemkin.core.manuals() method to view the online Theory manual.

The multi-zone homogeneous charged compression ignition (HCCI) model is mainly intended to address the temperature variation inside the cylinder caused by the wall heat transfer and the imperfect mixing of the in-cylinder gas mixture. In addition, the multi-zone HCCI engine model allows the introduction of non-uniform temperature and/or the equivalence ratio distribution of the gas mixture at the IVC.

This example shows how to set up and run the Chemkin multi-zone HCCI engine model. Many engine model-specific features, such as basic engine parameters, exhaust gas recirculation, and wall heat transfer, are applied to the engine simulation. This example also shows how to create initial distributions of zone size, temperature, and composition.

Import PyChemkin packages and start the logger#

from pathlib import Path

import matplotlib.pyplot as plt  # plotting
import numpy as np  # number crunching

import ansys.chemkin.core as ck  # Chemkin
from ansys.chemkin.core import Color

# Chemkin homogeneous charge compression ignition (HCCI) engine model (transient)
from ansys.chemkin.core.engines.HCCI import HCCIengine
from ansys.chemkin.core.logger import logger

# check working directory
current_dir = str(Path.cwd())
logger.debug("working directory: " + current_dir)
# set verbose mode
ck.set_verbose(True)
# set interactive mode for plotting the results
# interactive = True: display plot
# interactive = False: save plot as a PNG file
global interactive
interactive = True

Create a chemistry set#

The mechanism to load is the GRI 3.0 mechanism for methane combustion. This mechanism and its associated data files come with the standard Ansys Chemkin installation in the /reaction/data directory.

# set mechanism directory (the default Chemkin mechanism data directory)
data_dir = Path(ck.ansys_dir) / "reaction" / "data"
mechanism_dir = data_dir
# create a chemistry set based on the GRI mechanism
MyGasMech = ck.Chemistry(label="GRI 3.0")
# set mechanism input files
# including the full file path is recommended
MyGasMech.chemfile = str(mechanism_dir / "grimech30_chem.inp")
MyGasMech.thermfile = str(mechanism_dir / "grimech30_thermo.dat")
MyGasMech.tranfile = str(mechanism_dir / "grimech30_transport.dat")

Preprocess the chemistry set#

# preprocess the mechanism files
ierror = MyGasMech.preprocess()

Set up the fuel-air mixture#

You must set up the fuel-air mixture inside the engine cylinder right after the intake valve is closed. Here the x_by_equivalence_ratio() method is used. You create the fuelmixture and the air mixtures first. You then define the complete combustion product species and provide the additives composition if there is any. Finally, you set the equivalenceratio value to create the fuel-air mixture. In this case, the fuel mixture consists of methane, ethane, and propane as the simulated natural gas. Because HCCI engines generally run on lean fuel-air mixtures, the equivalence ratio is set to 0.8.

# create the fuel mixture
fuelmixture = ck.Mixture(MyGasMech)
# set fuel composition
fuelmixture.x = [("CH4", 0.9), ("C3H8", 0.05), ("C2H6", 0.05)]
# setting pressure and temperature is not required in this case
fuelmixture.pressure = 1.5 * ck.P_ATM
fuelmixture.temperature = 400.0
# create the oxidizer mixture: air
air = ck.Mixture(MyGasMech)
air.x = [("O2", 0.21), ("N2", 0.79)]
# setting pressure and temperature is not required in this case
air.pressure = 1.5 * ck.P_ATM
air.temperature = 400.0
# create the unburned fuel-air mixture
fresh = ck.Mixture(MyGasMech)
# products from the complete combustion of the fuel mixture and air
products = ["CO2", "H2O", "N2"]
# species mole fractions of added/inert mixture.
# can also create an additives mixture here
add_frac = np.zeros(MyGasMech.kk, dtype=np.double)  # no additives: all zeros
# mean equivalence ratio
equiv = 0.8
ierror = fresh.x_by_equivalence_ratio(
    MyGasMech, fuelmixture.x, air.x, add_frac, products, equivalenceratio=equiv
)
# check fuel-oxidizer mixture creation status
if ierror != 0:
    print("Error: Failed to create the fuel-oxidizer mixture.")
    exit()

# list the composition of the unburned fuel-air mixture
fresh.list_composition(mode="mole")

Specify pressure and temperature of the fuel-air mixture#

Since you are going to use the fresh fuel-air mixture to instantiate the engine object later, setting the mixture pressure and temperature is equivalent to setting the initial temperature and pressure of the engine cylinder.

fresh.temperature = 447.0
fresh.pressure = 1.065 * ck.P_ATM

Add EGR to the fresh fuel-air mixture#

Many engines have the configuration for exhaust gas recirculation (EGR). Chemkin engine models allow you to add the EGR mixture to the fresh fuel-air mixture entered the cylinder. If the engine you are modeling has EGR, you should have the EGR ratio, which is generally the volume ratio between the EGR mixture and the fresh fuel-air ratio. However, because you know nothing about the composition of the exhaust gas, you cannot simply combine these two mixtures. In this case, you use the get_egr_mole_fraction() method to estimate the major components of the exhaust gas from the combustion of the fresh fuel-air mixture. The threshold=1.0e-8 parameter tells the method to ignore any species with a mole fraction below the threshold value. Once you have the EGR mixture composition, use the x_by_equivalence_ratio() method a second time to re-create the fresh fuel-air mixture with the original fuelmixture and air mixtures along with the EGR composition you just got as the “additives”.

egr_ratio = 0.3
# compute the EGR stream composition in mole fractions
add_frac = fresh.get_egr_mole_fraction(egr_ratio, threshold=1.0e-8)
# recreate the initial mixture with EGR
ierror = fresh.x_by_equivalence_ratio(
    MyGasMech,
    fuelmixture.x,
    air.x,
    add_frac,
    products,
    equivalenceratio=equiv,
    threshold=1.0e-8,
)

# list the composition of the fuel+air+EGR mixture for verification
fresh.list_composition(mode="mole", bound=1.0e-8)

Set up the HCCI engine reactor#

Use the HCCIengine() method to create a multi-zone HCCI engine named MyMZEngine and make the new fresh mixture as the initial incylinder gas mixture at IVC. Set the nzones parameter to the number of zones in your multi-zone HCCI engine model.

# create a five-zone HCCI engine
numbzones = 5
MyMZEngine = HCCIengine(reactor_condition=fresh, nzones=numbzones)
# show initial gas composition inside the reactor
MyMZEngine.list_composition(mode="mole", bound=1.0e-8)

Set basic engine parameters#

Set the required engine parameters as shown in the following code. These engine parameters are used to describe the cylinder volume during the simulation. The starting_ca argument should be the crank angle corresponding to the cylinder IVC. The ending_ca is typically the EVC crank angle.

# cylinder bore diameter [cm]
MyMZEngine.bore = 12.065
# engine stroke [cm]
MyMZEngine.stroke = 14.005
# connecting rod length [cm]
MyMZEngine.connecting_rod_length = 26.0093
# compression ratio [-]
MyMZEngine.compression_ratio = 16.5
# engine speed [RPM]
MyMZEngine.rpm = 1000

# set other parameters
# simulation start CA [degree]
MyMZEngine.starting_ca = -142.0
# simulation end CA [degree]
MyMZEngine.ending_ca = 116.0

# list the engine parameters
MyMZEngine.list_engine_parameters()
print(f"engine displacement volume {MyMZEngine.get_displacement_volume()} [cm3]")
print(f"engine clearance volume {MyMZEngine.get_clearance_volume()} [cm3]")
print(f"number of zone(s) = {MyMZEngine.get_number_of_zones()}")

Set up the engine wall heat transfer model#

By default, the engine cylinder is adiabatic. You must set up a wall heat transfer model to include the heat loss effects in your engine simulation. Chemkin support three widely used engine wall heat transfer models. The models and their parameters follow.

  • dimensionless: [<a> <b> <c> <Twall>]

  • dimensional: [<a> <b> <c> <Twall>]

  • hohenburg: [<a> <b> <c> <d> <e> <Twall>]

There is also the in-cylinder gas velocity correlation (the Woschni correlation) that is associated with the engine wall heat transfer models. Here are the parameters of the Woschni correlation:

[<C11> <C12> <C2> <swirl ratio>]

You can also specify the surface areas of the piston head and the cylinder head for more precision heat transfer wall area. By default, both the piston head and the cylinder head surfaces are flat.

heattransferparameters = [0.035, 0.71, 0.0]
# set cylinder wall temperature [K]
t_wall = 400.0
MyMZEngine.set_wall_heat_transfer("dimensionless", heattransferparameters, t_wall)
# in-cylinder gas velocity correlation parameter (Woschni)
# [<C11> <C12> <C2> <swirl ratio>]
gv_parameters = [2.28, 0.308, 3.24, 0.0]
MyMZEngine.set_gas_velocity_correlation(gv_parameters)
# set piston head top surface area [cm2]
MyMZEngine.set_piston_head_area(area=124.75)
# set cylinder clearance surface area [cm2]
MyMZEngine.set_cylinder_head_area(area=123.5)

Set zonal properties#

By default, all zones in the multi-zone HCCI engine model have the same properties. You can artificially stratify the temperature and/or the equivalence ratio distribution in the cylinder at the IVC by utilizing the set_zonal methods of the HCCI object.

# zonal temperatures [K]
ztemperature = [447.5, 447.5, 447, 447, 447]
MyMZEngine.set_zonal_temperature(zonetemp=ztemperature)
# zonal volume fractions
zvolumefrac = [0.3, 0.25, 0.2, 0.2, 0.05]
MyMZEngine.set_zonal_volume_fraction(zonevol=zvolumefrac)
# wall heat transfer area fractions
zht_area = [0.0, 0.15, 0.2, 0.25, 0.4]
MyMZEngine.set_zonal_heat_transfer_area_fraction(zonearea=zht_area)
# zonal equivalence ratios
zphi = [equiv, equiv, equiv, equiv, equiv]
MyMZEngine.set_zonal_equivalence_ratio(zonephi=zphi)
# zonal EGR ratios
zegrr = [0.3, 0.3, 0.3, 0.35, 0.35]
MyMZEngine.set_zonal_egr_ratio(zoneegr=zegrr)
# set fuel "molar" composition
MyMZEngine.define_fuel_composition([("CH4", 0.9), ("C3H8", 0.05), ("C2H6", 0.05)])
# set oxidizer "molar' composition
MyMZEngine.define_oxid_composition([("O2", 0.21), ("N2", 0.79)])
# set products
MyMZEngine.define_product_composition(["CO2", "H2O", "N2"])
# set EGR composition in mole fractions
zadd = [add_frac, add_frac, add_frac, add_frac, add_frac]
MyMZEngine.define_additive_fractions(addfrac=zadd)

Set output options#

You can turn on the adaptive solution saving to resolve the steep variations in the solution profile. Here additional solution data points are saved for every 20*solver internal steps. You must include the set_ignition_delay() method for the engine model to report the ignition delay crank angle after the simulation is done. If method="T_inflection" is set, the reactor model treats the inflection points in the predicted gas temperature profile as the indication of an auto-ignition. You can choose a different auto-ignition definition.

Note

  • Type ansys.chemkin.core.show_ignition_definitions() to get the list of all available ignition delay time definitions in Chemkin.

  • The set_ignition_delay() method is required for the engine model to report the ignition delay time for each zone as well as the cylinder averaged ignition delay time derived from the cylinder averaged temperature profile.

  • By default, time/crank angle intervals for both print and save solution are 1/100 of the simulation duration, which in this case is \(dCA=(EVO-IVC)/100=2.58\). You can make the model report more frequently by using the ca_step_for_saving_solution() or the ca_step_for_printing_solution() method to set different interval values in the crank angle.

# set the number of crank angles between saving solution
MyMZEngine.ca_step_for_saving_solution = 0.5
# set the number of crank angles between printing solution
MyMZEngine.ca_step_for_printing_solution = 10.0
# turn on adaptive solution saving
MyMZEngine.adaptive_solution_saving(mode=True, steps=20)
# specify the ignition definitions
MyMZEngine.set_ignition_delay(method="T_inflection")

Set solver controls#

You can overwrite the default solver controls by using solver-related methods, such as those for tolerances.

# set tolerances in tuple: (absolute tolerance, relative tolerance)
MyMZEngine.tolerances = (1.0e-12, 1.0e-10)
# get solver parameters
atol, rtol = MyMZEngine.tolerances
print(f"Default absolute tolerance = {atol}.")
print(f"Default relative tolerance = {rtol}")
# turn on the force non-negative solutions option in the solver
MyMZEngine.force_nonnegative = True
# show solver and output options
# show the number of crank angles between printing solution
print(
    f"Crank angles between solution printing: "
    f"{MyMZEngine.ca_step_for_printing_solution}"
)
# show other transient solver setup
print(f"Forced non-negative solution values: {MyMZEngine.force_nonnegative}")

Display the added parameters (keywords)#

Use the showkeywordinputlines() method to verify that the preceding parameters are correctly assigned to the engine model.

MyMZEngine.showkeywordinputlines()

Run the simulation#

Use the run() method to start the multi-zone HCCI engine simulation.

runstatus = MyMZEngine.run()
# check run status
if runstatus != 0:
    # Run failed.
    print(Color.RED + ">>> Run failed. <<<", end=Color.END)
    exit()
# Run succeeded.
print(Color.GREEN + ">>> Run completed. <<<", end=Color.END)

Get the ignition delay crank angle from the solution#

Use the get_ignition_delay() method to extract the cylinder averaged ignition delay crank angle (CA) after the run is completed.

# get ignition delay "time"
delay_ca = MyMZEngine.get_ignition_delay()
print(f"Ignition delay CA = {delay_ca} [degree].")

Get the heat release crank angles#

The engine models also report the crank angles when the accumulated heat release reaches 10%, 50%, and 90% of the total heat release. Use the get_engine_heat_release_cas() method to extract these heat release crank angles (CA).

hr10, hr50, hr90 = MyMZEngine.get_engine_heat_release_cas()
print("Engine Heat Release Information:")
print(f"10% heat release CA = {hr10} [degree].")
print(f"50% heat release CA = {hr50} [degree].")
print(f"90% heat release CA = {hr90} [degree].\n")

Postprocess the solution =====================_== The postprocessing step parses the solution and packages the solution values at each time point into a mixture. There are two ways to access the solution profiles:

  • The raw solution profiles (value as a function of time) are available for time, temperature, pressure, volume, and species mass fractions.

  • The mixtures permit the use of all property and rate utilities to extract information such as viscosity, density, and mole fractions.

You can use the get_solution_variable_profile() method to get the raw solution profiles. You can get solution mixtures using either the get_solution_mixture_at_index() method for the solution mixture at a given time point or the get_solution_mixture() method for the solution mixture at a given time. (In this case, the mixture is constructed by interpolation.)

Note

  • For engine models, use the process_engine_solution() method to postprocess the solutions.

  • Use the getnumbersolutionpoints() method to get the size of the solution profiles before creating the arrays.

  • Use the get_ca() method to convert the time values reported in the solution to crank angles.

Postprocess the solution profiles in selected zone#

The solution of the multi-zone HCCI engine model contains the results of the individual zones plus the cylinder averaged results. This means that if there are n zones in the multi-zone engine model, there are (n+1) solution records: n zonal results and the cylinder averaged results.

To process the result of the zone number \(j\), \((1 \leq j \leq n)\), set the parameter value of zone_id to \(j\) when you call the engine postprocessor with the process_engine_solution() method. Otherwise, the cylinder averaged results are postprocessed by default, that is, when the zone_id parameter is omitted.

Note

Because The process_engine_solution() method can process only one set of results at a time (one zonal result or the cylinder averaged result), you must postprocess the zones one by one to obtain all solution data of the multi-zone simulation.

thiszone = 1
MyMZEngine.process_engine_solution(zone_id=thiszone)
plottitle = "Zone " + str(thiszone) + " Solution"
# get the number of solution time points
solutionpoints = MyMZEngine.getnumbersolutionpoints()
print(f"Number of solution points = {solutionpoints}.")
# get the time profile
timeprofile = MyMZEngine.get_solution_variable_profile("time")
# convert time to crank angle
ca_profile = np.zeros_like(timeprofile, dtype=np.double)
count = 0
for t in timeprofile:
    ca_profile[count] = MyMZEngine.get_ca(timeprofile[count])
    count += 1
# get the cylinder pressure profile
presprofile = MyMZEngine.get_solution_variable_profile("pressure")
presprofile *= 1.0e-6
# get the zonal volume profile
volprofile = MyMZEngine.get_solution_variable_profile("volume")
# create arrays for zonal mixture density and mixture specific heat capacity
denprofile = np.zeros_like(timeprofile, dtype=np.double)
viscprofile = np.zeros_like(timeprofile, dtype=np.double)
# loop over all solution time points
for i in range(solutionpoints):
    # get the zonal mixture at the time point
    solutionmixture = MyMZEngine.get_solution_mixture_at_index(solution_index=i)
    # get zonal gas density [g/cm3]
    denprofile[i] = solutionmixture.rho
    # get zonal mixture viscosity profile [g/cm-sec] or [Poise]
    viscprofile[i] = solutionmixture.mixture_viscosity() * 1.0e2

# post-process cylinder-averged solution
# do NOT set the zone_id parameter
MyMZEngine.process_average_engine_solution()
# get the cylinder volume profile
cylindervolprofile = MyMZEngine.get_solution_variable_profile("volume")
# create arrays for cylinder-averaged mixture density
cylinderdenprofile = np.zeros_like(timeprofile, dtype=np.double)
# loop over all solution time points
for i in range(solutionpoints):
    # get the zonal mixture at the time point
    solutionmixture = MyMZEngine.get_solution_mixture_at_index(solution_index=i)
    # get zonal gas density [g/cm3]
    cylinderdenprofile[i] = solutionmixture.rho

Plot the engine solution profiles#

Plot the zonal and the cylinder averaged profiles from the multi-zone HCCI engine simulation.

Note

You can get profiles of the thermodynamic and the transport properties by applying Mixture utility methods to the solution mixtures.

plt.subplots(2, 2, sharex="col", figsize=(12, 6))
plt.suptitle(plottitle, fontsize=16)
plt.subplot(221)
plt.plot(ca_profile, presprofile, "r-")
plt.ylabel("Pressure [bar]")
plt.subplot(222)
plt.plot(ca_profile, volprofile, "b-")
plt.plot(ca_profile, cylindervolprofile, "b--")
plt.ylabel("Volume [cm3]")
plt.legend(["Zone", "Cylinder"], loc="upper right")
plt.subplot(223)
plt.plot(ca_profile, denprofile, "g-")
plt.plot(ca_profile, cylinderdenprofile, "g--")
plt.xlabel("Crank Angle [degree]")
plt.ylabel("Mixture Density [g/cm3]")
plt.legend(["Zone", "Averaged"], loc="upper left")
plt.subplot(224)
plt.plot(ca_profile, viscprofile, "m-")
plt.xlabel("Crank Angle [degree]")
plt.ylabel("Mixture Viscosity [cP]")
# plot results
if interactive:
    plt.show()
else:
    plt.savefig("plot_multizone_HCCI_engine.png", bbox_inches="tight")

Gallery generated by Sphinx-Gallery