AGGOUR

Computes the two-phase convective heat transfer coefficient for liquid-gas flow in a tube using the Aggour correlation. The model supports laminar and turbulent behavior and can include viscosity correction effects when wall viscosity is supplied.

The correlation is represented in Nusselt-form and converted to heat transfer coefficient form:

h = \frac{Nu\,k_l}{D}

where Nu is computed from flow regime-dependent expressions using liquid properties, geometry, and two-phase flow descriptors.

Excel Usage

=AGGOUR(m, x, alpha, D, rhol, Cpl, kl, mu_b, mu_w, L, turbulent)
  • m (float, required): Mass flow rate (kg/s).
  • x (float, required): Quality at the tube interval (-).
  • alpha (float, required): Void fraction in the tube (-).
  • D (float, required): Tube diameter (m).
  • rhol (float, required): Liquid density (kg/m^3).
  • Cpl (float, required): Liquid heat capacity at constant pressure (J/kg/K).
  • kl (float, required): Liquid thermal conductivity (W/m/K).
  • mu_b (float, required): Liquid viscosity at bulk conditions (Pa*s).
  • mu_w (float, optional, default: null): Liquid viscosity at wall temperature (Pa*s).
  • L (float, optional, default: null): Tube length (m).
  • turbulent (bool, optional, default: null): Force turbulent correlation selection (-).

Returns (float): Heat transfer coefficient (W/m^2/K).

Example 1: Aggour example

Inputs:

m x alpha D rhol Cpl kl mu_b
1 0.9 0.9 0.3 1000 2300 0.6 0.001

Excel formula:

=AGGOUR(1, 0.9, 0.9, 0.3, 1000, 2300, 0.6, 0.001)

Expected output:

420.935

Example 2: Laminar with viscosity correction

Inputs:

m x alpha D rhol Cpl kl mu_b mu_w L
0.2 0.1 0.2 0.02 998 4180 0.6 0.001 0.0012 2

Excel formula:

=AGGOUR(0.2, 0.1, 0.2, 0.02, 998, 4180, 0.6, 0.001, 0.0012, 2)

Expected output:

4158.46

Example 3: Forced turbulent regime

Inputs:

m x alpha D rhol Cpl kl mu_b turbulent
2 0.5 0.7 0.05 950 3900 0.55 0.0008 true

Excel formula:

=AGGOUR(2, 0.5, 0.7, 0.05, 950, 3900, 0.55, 0.0008, TRUE)

Expected output:

16366.8

Example 4: Longer tube length

Inputs:

m x alpha D rhol Cpl kl mu_b L
0.5 0.2 0.3 0.03 990 4100 0.58 0.0011 5

Excel formula:

=AGGOUR(0.5, 0.2, 0.3, 0.03, 990, 4100, 0.58, 0.0011, 5)

Expected output:

4524.48

Python Code

Show Code
from ht.conv_two_phase import Aggour as ht_Aggour

def Aggour(m, x, alpha, D, rhol, Cpl, kl, mu_b, mu_w=None, L=None, turbulent=None):
    """
    Calculate two-phase heat transfer coefficient using the Aggour correlation.

    See: https://ht.readthedocs.io/en/latest/ht.conv_two_phase.html

    This example function is provided as-is without any representation of accuracy.

    Args:
        m (float): Mass flow rate (kg/s).
        x (float): Quality at the tube interval (-).
        alpha (float): Void fraction in the tube (-).
        D (float): Tube diameter (m).
        rhol (float): Liquid density (kg/m^3).
        Cpl (float): Liquid heat capacity at constant pressure (J/kg/K).
        kl (float): Liquid thermal conductivity (W/m/K).
        mu_b (float): Liquid viscosity at bulk conditions (Pa*s).
        mu_w (float, optional): Liquid viscosity at wall temperature (Pa*s). Default is None.
        L (float, optional): Tube length (m). Default is None.
        turbulent (bool, optional): Force turbulent correlation selection (-). Default is None.

    Returns:
        float: Heat transfer coefficient (W/m^2/K).
    """
    try:
        return ht_Aggour(
            m=m,
            x=x,
            alpha=alpha,
            D=D,
            rhol=rhol,
            Cpl=Cpl,
            kl=kl,
            mu_b=mu_b,
            mu_w=mu_w,
            L=L,
            turbulent=turbulent,
        )
    except Exception as e:
        return f"Error: {str(e)}"

Online Calculator

Mass flow rate (kg/s).
Quality at the tube interval (-).
Void fraction in the tube (-).
Tube diameter (m).
Liquid density (kg/m^3).
Liquid heat capacity at constant pressure (J/kg/K).
Liquid thermal conductivity (W/m/K).
Liquid viscosity at bulk conditions (Pa*s).
Liquid viscosity at wall temperature (Pa*s).
Tube length (m).
Force turbulent correlation selection (-).