Conv Supercritical
Overview
Supercritical convection in tubes models forced heat transfer when fluid pressure is above the critical point and properties vary sharply with temperature, especially near the pseudocritical region. In this regime, small changes in state can cause large shifts in density, heat capacity, and transport properties, so conventional single-phase correlations can become unreliable. The functions in this category provide empirical Nusselt-number models for turbulent upward internal flow at supercritical conditions, most often for water-cooled channels used in power and process equipment. For background on the thermodynamic regime, see supercritical fluid.
The shared framework is dimensionless internal convection with correction factors for property variation across the wall and bulk fluid states. All correlations estimate Nu from combinations of Reynolds and Prandtl numbers, typically in power-law form, while some add multiplicative terms such as (\rho_w/\rho_b)^a, (\mu_w/\mu_b)^b, or heat-capacity modifiers to capture near-critical behavior. In design studies, this set is usually applied as a model family: engineers compare several correlations across the same operating window to quantify uncertainty and detect sensitivity to pseudocritical crossing, high heat flux, or deteriorated heat-transfer conditions.
Implementation is based on the Python ht library, specifically ht.conv_supercritical. The ht package provides vetted thermal-engineering correlations with consistent APIs, which makes these methods easy to use in spreadsheets, calculators, and scripted parameter sweeps.
NU_BRINGER_SMITH, NU_GORBAN, NU_MCADAMS, and NU_SHITSMAN are compact forms that rely mainly on Re and one or two Pr definitions. These are practical for baseline estimates, quick screening, and cross-checks when detailed wall/bulk property sets are not yet available. NU_GORBAN is historically important but often treated cautiously in modern comparisons, while NU_MCADAMS remains a simple reference-like form derived from classic turbulent-tube behavior. NU_BRINGER_SMITH and NU_SHITSMAN are likewise useful as lightweight bounds in early-stage studies.
NU_BISHOP, NU_SWENSON, NU_MOKRY, NU_XU, NU_ZHU, NU_GUPTA, NU_ORNATSKY, and NU_PETUKHOV explicitly account for wall-to-bulk property ratios and are typically preferred when temperature gradients are strong. These tools differ in which corrections they emphasize (density, viscosity, conductivity, or mixed Prandtl treatments), but all target improved fidelity in supercritical pipe-flow prediction. They are commonly used in thermal-hydraulic rating for heated channels, especially when evaluating normal versus deteriorated heat-transfer trends under changing mass flux and heat flux.
NU_JACKSON, NU_YAMAGATA, NU_KITOH, NU_GRIEM, NU_KRASN_PROTO, NU_KRASNOSH_PROTO, and NU_KRASNOSHCHEKOV add more structured handling of pseudocritical and heat-capacity effects. NU_JACKSON and NU_YAMAGATA incorporate regime-dependent exponents or factors tied to T_b, T_w, and T_{pc} behavior; NU_KITOH and NU_GRIEM include additional sensitivity to enthalpy and flux-related conditions. NU_KRASN_PROTO and NU_KRASNOSH_PROTO represent two category entries for the Krasnoshchekov-Protopopov style formulation, while NU_KRASNOSHCHEKOV applies a related but distinct corrected baseline form. Together, these functions are most useful for higher-fidelity comparative modeling when property data and operating-state definitions are well characterized.
NU_BISHOP
Calculate Nusselt number for supercritical pipe flow using the Bishop correlation.
Excel Usage
=NU_BISHOP(Re, Pr, rho_w, rho_b, D, x)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk properties and averaged heat capacity (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).D(float, optional, default: null): Tube diameter (m).x(float, optional, default: null): Axial distance along the tube (m).
Returns (float): Nusselt number with wall fluid properties (-).
Example 1: Bishop correlation example
Inputs:
| Re | Pr | rho_w | rho_b | D | x |
|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.01 | 1.2 |
Excel formula:
=NU_BISHOP(100000, 1.2, 330, 290, 0.01, 1.2)
Expected output:
265.362
Example 2: Bishop correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 0.9 |
Excel formula:
=NU_BISHOP(80000, 0.9)
Expected output:
166.506
Example 3: Bishop correlation with density ratio
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 150000 | 1.4 | 350 | 300 |
Excel formula:
=NU_BISHOP(150000, 1.4, 350, 300)
Expected output:
419.337
Example 4: Bishop correlation with entry correction
Inputs:
| Re | Pr | rho_w | rho_b | D | x |
|---|---|---|---|---|---|
| 250000 | 1.1 | 400 | 320 | 0.02 | 2 |
Excel formula:
=NU_BISHOP(250000, 1.1, 400, 320, 0.02, 2)
Expected output:
597.428
Python Code
Show Code
from ht.conv_supercritical import Nu_Bishop as ht_Nu_Bishop
def Nu_Bishop(Re, Pr, rho_w=None, rho_b=None, D=None, x=None):
"""
Calculate Nusselt number for supercritical pipe flow using the Bishop correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk properties and averaged heat capacity (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
D (float, optional): Tube diameter (m). Default is None.
x (float, optional): Axial distance along the tube (m). Default is None.
Returns:
float: Nusselt number with wall fluid properties (-).
"""
try:
return ht_Nu_Bishop(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b, D=D, x=x)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_BRINGER_SMITH
Calculate Nusselt number for near-supercritical flow using the Bringer-Smith correlation.
Excel Usage
=NU_BRINGER_SMITH(Re, Pr)
Re(float, required): Reynolds number with reference properties (-).Pr(float, required): Prandtl number with wall properties (-).
Returns (float): Nusselt number with reference temperature properties (-).
Example 1: Bringer-Smith example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_BRINGER_SMITH(100000, 1.2)
Expected output:
208.176
Example 2: Bringer-Smith lower Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 50000 | 1 |
Excel formula:
=NU_BRINGER_SMITH(50000, 1)
Expected output:
110.43
Example 3: Bringer-Smith mid Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 200000 | 0.8 |
Excel formula:
=NU_BRINGER_SMITH(200000, 0.8)
Expected output:
284.037
Example 4: Bringer-Smith higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 800000 | 1.5 |
Excel formula:
=NU_BRINGER_SMITH(800000, 1.5)
Expected output:
1167.11
Python Code
Show Code
from ht.conv_supercritical import Nu_Bringer_Smith as ht_Nu_Bringer_Smith
def Nu_Bringer_Smith(Re, Pr):
"""
Calculate Nusselt number for near-supercritical flow using the Bringer-Smith correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with reference properties (-).
Pr (float): Prandtl number with wall properties (-).
Returns:
float: Nusselt number with reference temperature properties (-).
"""
try:
return ht_Nu_Bringer_Smith(Re=Re, Pr=Pr)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_GORBAN
Calculate Nusselt number for supercritical flow using the Gorban correlation.
Excel Usage
=NU_GORBAN(Re, Pr)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Gorban correlation example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_GORBAN(100000, 1.2)
Expected output:
182.537
Example 2: Gorban correlation lower Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 40000 | 1.1 |
Excel formula:
=NU_GORBAN(40000, 1.1)
Expected output:
80.861
Example 3: Gorban correlation mid Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 200000 | 0.9 |
Excel formula:
=NU_GORBAN(200000, 0.9)
Expected output:
352.59
Example 4: Gorban correlation higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 600000 | 1.4 |
Excel formula:
=NU_GORBAN(600000, 1.4)
Expected output:
898.779
Python Code
Show Code
from ht.conv_supercritical import Nu_Gorban as ht_Nu_Gorban
def Nu_Gorban(Re, Pr):
"""
Calculate Nusselt number for supercritical flow using the Gorban correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Gorban(Re=Re, Pr=Pr)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_GRIEM
Calculate Nusselt number for supercritical flow using the Griem correlation.
Excel Usage
=NU_GRIEM(Re, Pr, H)
Re(float, required): Reynolds number as defined by the correlation (-).Pr(float, required): Prandtl number as defined by the correlation (-).H(float, optional, default: null): Enthalpy of water when applicable (J/kg).
Returns (float): Nusselt number for supercritical pipe flow (-).
Example 1: Griem correlation example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_GRIEM(100000, 1.2)
Expected output:
275.482
Example 2: Griem correlation lower Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 60000 | 1 |
Excel formula:
=NU_GRIEM(60000, 1)
Expected output:
166.154
Example 3: Griem correlation with enthalpy
Inputs:
| Re | Pr | H |
|---|---|---|
| 150000 | 1.4 | 1600000 |
Excel formula:
=NU_GRIEM(150000, 1.4, 1600000)
Expected output:
361.133
Example 4: Griem correlation higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 400000 | 0.9 |
Excel formula:
=NU_GRIEM(400000, 0.9)
Expected output:
774.82
Python Code
Show Code
from ht.conv_supercritical import Nu_Griem as ht_Nu_Griem
def Nu_Griem(Re, Pr, H=None):
"""
Calculate Nusselt number for supercritical flow using the Griem correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number as defined by the correlation (-).
Pr (float): Prandtl number as defined by the correlation (-).
H (float, optional): Enthalpy of water when applicable (J/kg). Default is None.
Returns:
float: Nusselt number for supercritical pipe flow (-).
"""
try:
return ht_Nu_Griem(Re=Re, Pr=Pr, H=H)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_GUPTA
Calculate Nusselt number for supercritical flow using the Gupta correlation.
Excel Usage
=NU_GUPTA(Re, Pr, rho_w, rho_b, mu_w, mu_b)
Re(float, required): Reynolds number with wall properties (-).Pr(float, required): Prandtl number with wall properties (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).mu_w(float, optional, default: null): Viscosity at wall temperature (Pa*s).mu_b(float, optional, default: null): Viscosity at bulk temperature (Pa*s).
Returns (float): Nusselt number with wall fluid properties (-).
Example 1: Gupta correlation example
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.0008 | 0.0009 |
Excel formula:
=NU_GUPTA(100000, 1.2, 330, 290, 0.0008, 0.0009)
Expected output:
186.201
Example 2: Gupta correlation with bulk and wall properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_GUPTA(80000, 1.1)
Expected output:
144.414
Example 3: Gupta correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 200000 | 0.9 | 360 | 310 | 0.0007 | 0.00085 |
Excel formula:
=NU_GUPTA(200000, 0.9, 360, 310, 0.0007, 0.00085)
Expected output:
275.904
Example 4: Gupta correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 500000 | 1.5 | 380 | 320 | 0.0006 | 0.00075 |
Excel formula:
=NU_GUPTA(500000, 1.5, 380, 320, 0.0006, 0.00075)
Expected output:
947.852
Python Code
Show Code
from ht.conv_supercritical import Nu_Gupta as ht_Nu_Gupta
def Nu_Gupta(Re, Pr, rho_w=None, rho_b=None, mu_w=None, mu_b=None):
"""
Calculate Nusselt number for supercritical flow using the Gupta correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with wall properties (-).
Pr (float): Prandtl number with wall properties (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
mu_w (float, optional): Viscosity at wall temperature (Pa*s). Default is None.
mu_b (float, optional): Viscosity at bulk temperature (Pa*s). Default is None.
Returns:
float: Nusselt number with wall fluid properties (-).
"""
try:
return ht_Nu_Gupta(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b, mu_w=mu_w, mu_b=mu_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_JACKSON
Calculate Nusselt number for supercritical flow using the Jackson correlation.
Excel Usage
=NU_JACKSON(Re, Pr, rho_w, rho_b, Cp_avg, Cp_b, T_b, T_w, T_pc)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).Cp_avg(float, optional, default: null): Average heat capacity between wall and bulk temperatures (J/kg/K).Cp_b(float, optional, default: null): Heat capacity at bulk temperature (J/kg/K).T_b(float, optional, default: null): Bulk temperature (K).T_w(float, optional, default: null): Wall temperature (K).T_pc(float, optional, default: null): Pseudocritical temperature at pressure (K).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Jackson correlation example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_JACKSON(100000, 1.2)
Expected output:
252.372
Example 2: Jackson correlation with property corrections
Inputs:
| Re | Pr | rho_w | rho_b | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 2100 | 2000 | 650 | 700 | 640 |
Excel formula:
=NU_JACKSON(100000, 1.2, 330, 290, 2100, 2000, 650, 700, 640)
Expected output:
267.743
Example 3: Jackson correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|---|
| 200000 | 0.9 | 350 | 300 | 2300 | 2100 | 620 | 680 | 640 |
Excel formula:
=NU_JACKSON(200000, 0.9, 350, 300, 2300, 2100, 620, 680, 640)
Expected output:
419.564
Example 4: Jackson correlation higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 400000 | 1.1 |
Excel formula:
=NU_JACKSON(400000, 1.1)
Expected output:
753.072
Python Code
Show Code
from ht.conv_supercritical import Nu_Jackson as ht_Nu_Jackson
def Nu_Jackson(Re, Pr, rho_w=None, rho_b=None, Cp_avg=None, Cp_b=None, T_b=None, T_w=None, T_pc=None):
"""
Calculate Nusselt number for supercritical flow using the Jackson correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
Cp_avg (float, optional): Average heat capacity between wall and bulk temperatures (J/kg/K). Default is None.
Cp_b (float, optional): Heat capacity at bulk temperature (J/kg/K). Default is None.
T_b (float, optional): Bulk temperature (K). Default is None.
T_w (float, optional): Wall temperature (K). Default is None.
T_pc (float, optional): Pseudocritical temperature at pressure (K). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Jackson(
Re=Re,
Pr=Pr,
rho_w=rho_w,
rho_b=rho_b,
Cp_avg=Cp_avg,
Cp_b=Cp_b,
T_b=T_b,
T_w=T_w,
T_pc=T_pc,
)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_KITOH
Calculate Nusselt number for supercritical flow using the Kitoh correlation.
Excel Usage
=NU_KITOH(Re, Pr, H, G, q)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).H(float, optional, default: null): Enthalpy of water when applicable (J/kg).G(float, optional, default: null): Mass flux of the fluid (kg/m^2/s).q(float, optional, default: null): Heat flux to the wall (W/m^2).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Kitoh correlation example
Inputs:
| Re | Pr | H | G | q |
|---|---|---|---|---|
| 100000 | 1.2 | 1300000 | 1500 | 5000000 |
Excel formula:
=NU_KITOH(100000, 1.2, 1300000, 1500, 5000000)
Expected output:
331.802
Example 2: Kitoh correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_KITOH(80000, 1.1)
Expected output:
235.656
Example 3: Kitoh correlation mid Reynolds number
Inputs:
| Re | Pr | H | G | q |
|---|---|---|---|---|
| 200000 | 0.9 | 1800000 | 1200 | 3000000 |
Excel formula:
=NU_KITOH(200000, 0.9, 1800000, 1200, 3000000)
Expected output:
570.322
Example 4: Kitoh correlation higher Reynolds number
Inputs:
| Re | Pr | H | G | q |
|---|---|---|---|---|
| 450000 | 1.4 | 2200000 | 1700 | 6000000 |
Excel formula:
=NU_KITOH(450000, 1.4, 2200000, 1700, 6000000)
Expected output:
416.26
Python Code
Show Code
from ht.conv_supercritical import Nu_Kitoh as ht_Nu_Kitoh
def Nu_Kitoh(Re, Pr, H=None, G=None, q=None):
"""
Calculate Nusselt number for supercritical flow using the Kitoh correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
H (float, optional): Enthalpy of water when applicable (J/kg). Default is None.
G (float, optional): Mass flux of the fluid (kg/m^2/s). Default is None.
q (float, optional): Heat flux to the wall (W/m^2). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Kitoh(Re=Re, Pr=Pr, H=H, G=G, q=q)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_KRASN_PROTO
Calculate Nusselt number for supercritical flow using the Krasnoshchekov-Protopopov correlation.
Excel Usage
=NU_KRASN_PROTO(Re, Pr, Cp_avg, Cp_b, k_w, k_b, mu_w, mu_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).Cp_avg(float, optional, default: null): Average heat capacity between wall and bulk temperatures (J/kg/K).Cp_b(float, optional, default: null): Heat capacity at bulk temperature (J/kg/K).k_w(float, optional, default: null): Thermal conductivity at wall temperature (W/m/K).k_b(float, optional, default: null): Thermal conductivity at bulk temperature (W/m/K).mu_w(float, optional, default: null): Viscosity at wall temperature (Pa*s).mu_b(float, optional, default: null): Viscosity at bulk temperature (Pa*s).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Krasnoshchekov-Protopopov example
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.62 | 0.52 | 0.0008 | 0.0009 |
Excel formula:
=NU_KRASN_PROTO(100000, 1.2, 330, 290, 0.62, 0.52, 0.0008, 0.0009)
Expected output:
228.853
Example 2: Krasnoshchekov-Protopopov bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_KRASN_PROTO(80000, 1.1)
Expected output:
186.725
Example 3: Krasnoshchekov-Protopopov mid Reynolds number
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 200000 | 0.95 | 2200 | 2050 | 0.68 | 0.58 | 0.0007 | 0.00082 |
Excel formula:
=NU_KRASN_PROTO(200000, 0.95, 2200, 2050, 0.68, 0.58, 0.0007, 0.00082)
Expected output:
336.777
Example 4: Krasnoshchekov-Protopopov higher Reynolds number
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 500000 | 1.4 | 2500 | 2200 | 0.75 | 0.65 | 0.0006 | 0.00075 |
Excel formula:
=NU_KRASN_PROTO(500000, 1.4, 2500, 2200, 0.75, 0.65, 0.0006, 0.00075)
Expected output:
931.323
Python Code
Show Code
from ht.conv_supercritical import Nu_Krasnoshchekov_Protopopov as ht_Nu_Krasnoshchekov_Protopopov
def Nu_Krasn_Proto(Re, Pr, Cp_avg=None, Cp_b=None, k_w=None, k_b=None, mu_w=None, mu_b=None):
"""
Calculate Nusselt number for supercritical flow using the Krasnoshchekov-Protopopov correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
Cp_avg (float, optional): Average heat capacity between wall and bulk temperatures (J/kg/K). Default is None.
Cp_b (float, optional): Heat capacity at bulk temperature (J/kg/K). Default is None.
k_w (float, optional): Thermal conductivity at wall temperature (W/m/K). Default is None.
k_b (float, optional): Thermal conductivity at bulk temperature (W/m/K). Default is None.
mu_w (float, optional): Viscosity at wall temperature (Pa*s). Default is None.
mu_b (float, optional): Viscosity at bulk temperature (Pa*s). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Krasnoshchekov_Protopopov(
Re=Re,
Pr=Pr,
Cp_avg=Cp_avg,
Cp_b=Cp_b,
k_w=k_w,
k_b=k_b,
mu_w=mu_w,
mu_b=mu_b,
)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_KRASNOSH_PROTO
Calculate Nusselt number for supercritical flow using the Krasnoshchekov-Protopopov correlation.
Excel Usage
=NU_KRASNOSH_PROTO(Re, Pr, Cp_avg, Cp_b, k_w, k_b, mu_w, mu_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).Cp_avg(float, optional, default: null): Average heat capacity between wall and bulk temperatures (J/kg/K).Cp_b(float, optional, default: null): Heat capacity at bulk temperature (J/kg/K).k_w(float, optional, default: null): Thermal conductivity at wall temperature (W/m/K).k_b(float, optional, default: null): Thermal conductivity at bulk temperature (W/m/K).mu_w(float, optional, default: null): Viscosity at wall temperature (Pa*s).mu_b(float, optional, default: null): Viscosity at bulk temperature (Pa*s).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Krasnoshchekov-Protopopov example
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.62 | 0.52 | 0.0008 | 0.0009 |
Excel formula:
=NU_KRASNOSH_PROTO(100000, 1.2, 330, 290, 0.62, 0.52, 0.0008, 0.0009)
Expected output:
228.853
Example 2: Krasnoshchekov-Protopopov bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_KRASNOSH_PROTO(80000, 1.1)
Expected output:
186.725
Example 3: Krasnoshchekov-Protopopov mid Reynolds number
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 200000 | 0.95 | 2200 | 2050 | 0.68 | 0.58 | 0.0007 | 0.00082 |
Excel formula:
=NU_KRASNOSH_PROTO(200000, 0.95, 2200, 2050, 0.68, 0.58, 0.0007, 0.00082)
Expected output:
336.777
Example 4: Krasnoshchekov-Protopopov higher Reynolds number
Inputs:
| Re | Pr | Cp_avg | Cp_b | k_w | k_b | mu_w | mu_b |
|---|---|---|---|---|---|---|---|
| 500000 | 1.4 | 2500 | 2200 | 0.75 | 0.65 | 0.0006 | 0.00075 |
Excel formula:
=NU_KRASNOSH_PROTO(500000, 1.4, 2500, 2200, 0.75, 0.65, 0.0006, 0.00075)
Expected output:
931.323
Python Code
Show Code
from ht.conv_supercritical import Nu_Krasnoshchekov_Protopopov as ht_Nu_Krasnoshchekov_Protopopov
def Nu_Krasnosh_Proto(Re, Pr, Cp_avg=None, Cp_b=None, k_w=None, k_b=None, mu_w=None, mu_b=None):
"""
Calculate Nusselt number for supercritical flow using the Krasnoshchekov-Protopopov correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
Cp_avg (float, optional): Average heat capacity between wall and bulk temperatures (J/kg/K). Default is None.
Cp_b (float, optional): Heat capacity at bulk temperature (J/kg/K). Default is None.
k_w (float, optional): Thermal conductivity at wall temperature (W/m/K). Default is None.
k_b (float, optional): Thermal conductivity at bulk temperature (W/m/K). Default is None.
mu_w (float, optional): Viscosity at wall temperature (Pa*s). Default is None.
mu_b (float, optional): Viscosity at bulk temperature (Pa*s). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Krasnoshchekov_Protopopov(
Re=Re,
Pr=Pr,
Cp_avg=Cp_avg,
Cp_b=Cp_b,
k_w=k_w,
k_b=k_b,
mu_w=mu_w,
mu_b=mu_b,
)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_KRASNOSHCHEKOV
Calculate Nusselt number for supercritical flow using the Krasnoshchekov correlation.
Excel Usage
=NU_KRASNOSHCHEKOV(Re, Pr, rho_w, rho_b, Cp_avg, Cp_b, T_b, T_w, T_pc)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).Cp_avg(float, optional, default: null): Average heat capacity between wall and bulk temperatures (J/kg/K).Cp_b(float, optional, default: null): Heat capacity at bulk temperature (J/kg/K).T_b(float, optional, default: null): Bulk temperature (K).T_w(float, optional, default: null): Wall temperature (K).T_pc(float, optional, default: null): Pseudocritical temperature at pressure (K).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Krasnoshchekov correlation example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_KRASNOSHCHEKOV(100000, 1.2)
Expected output:
234.829
Example 2: Krasnoshchekov correlation with property corrections
Inputs:
| Re | Pr | rho_w | rho_b | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|---|
| 120000 | 1.1 | 350 | 300 | 2100 | 2000 | 650 | 700 | 640 |
Excel formula:
=NU_KRASNOSHCHEKOV(120000, 1.1, 350, 300, 2100, 2000, 650, 700, 640)
Expected output:
275.091
Example 3: Krasnoshchekov correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|---|
| 220000 | 0.95 | 360 | 310 | 2300 | 2100 | 620 | 690 | 640 |
Excel formula:
=NU_KRASNOSHCHEKOV(220000, 0.95, 360, 310, 2300, 2100, 620, 690, 640)
Expected output:
413.04
Example 4: Krasnoshchekov correlation higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 300000 | 0.9 |
Excel formula:
=NU_KRASNOSHCHEKOV(300000, 0.9)
Expected output:
470.84
Python Code
Show Code
from ht.conv_supercritical import Nu_Krasnoshchekov as ht_Nu_Krasnoshchekov
def Nu_Krasnoshchekov(Re, Pr, rho_w=None, rho_b=None, Cp_avg=None, Cp_b=None, T_b=None, T_w=None, T_pc=None):
"""
Calculate Nusselt number for supercritical flow using the Krasnoshchekov correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
Cp_avg (float, optional): Average heat capacity between wall and bulk temperatures (J/kg/K). Default is None.
Cp_b (float, optional): Heat capacity at bulk temperature (J/kg/K). Default is None.
T_b (float, optional): Bulk temperature (K). Default is None.
T_w (float, optional): Wall temperature (K). Default is None.
T_pc (float, optional): Pseudocritical temperature at pressure (K). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Krasnoshchekov(
Re=Re,
Pr=Pr,
rho_w=rho_w,
rho_b=rho_b,
Cp_avg=Cp_avg,
Cp_b=Cp_b,
T_b=T_b,
T_w=T_w,
T_pc=T_pc,
)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_MCADAMS
Calculate Nusselt number for supercritical flow using the McAdams correlation.
Excel Usage
=NU_MCADAMS(Re, Pr)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: McAdams correlation example
Inputs:
| Re | Pr |
|---|---|
| 100000 | 1.2 |
Excel formula:
=NU_MCADAMS(100000, 1.2)
Expected output:
261.384
Example 2: McAdams correlation lower Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 50000 | 1 |
Excel formula:
=NU_MCADAMS(50000, 1)
Expected output:
139.567
Example 3: McAdams correlation mid Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 200000 | 0.8 |
Excel formula:
=NU_MCADAMS(200000, 0.8)
Expected output:
386.96
Example 4: McAdams correlation higher Reynolds number
Inputs:
| Re | Pr |
|---|---|
| 700000 | 1.5 |
Excel formula:
=NU_MCADAMS(700000, 1.5)
Expected output:
1355.57
Python Code
Show Code
from ht.conv_supercritical import Nu_McAdams as ht_Nu_McAdams
def Nu_McAdams(Re, Pr):
"""
Calculate Nusselt number for supercritical flow using the McAdams correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_McAdams(Re=Re, Pr=Pr)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_MOKRY
Calculate Nusselt number for supercritical flow using the Mokry correlation.
Excel Usage
=NU_MOKRY(Re, Pr, rho_w, rho_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk properties and averaged heat capacity (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Mokry correlation example
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 100000 | 1.2 | 330 | 290 |
Excel formula:
=NU_MOKRY(100000, 1.2, 330, 290)
Expected output:
246.116
Example 2: Mokry correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1 |
Excel formula:
=NU_MOKRY(80000, 1)
Expected output:
165.091
Example 3: Mokry correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 200000 | 0.9 | 360 | 310 |
Excel formula:
=NU_MOKRY(200000, 0.9, 360, 310)
Expected output:
382.639
Example 4: Mokry correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 500000 | 1.5 | 380 | 320 |
Excel formula:
=NU_MOKRY(500000, 1.5, 380, 320)
Expected output:
1258.17
Python Code
Show Code
from ht.conv_supercritical import Nu_Mokry as ht_Nu_Mokry
def Nu_Mokry(Re, Pr, rho_w=None, rho_b=None):
"""
Calculate Nusselt number for supercritical flow using the Mokry correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk properties and averaged heat capacity (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Mokry(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_ORNATSKY
Calculate Nusselt number for supercritical flow using the Ornatsky correlation.
Excel Usage
=NU_ORNATSKY(Re, Pr_b, Pr_w, rho_w, rho_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr_b(float, required): Prandtl number with bulk fluid properties (-).Pr_w(float, required): Prandtl number with wall fluid properties (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Ornatsky correlation example
Inputs:
| Re | Pr_b | Pr_w | rho_w | rho_b |
|---|---|---|---|---|
| 100000 | 1.2 | 1.5 | 330 | 290 |
Excel formula:
=NU_ORNATSKY(100000, 1.2, 1.5, 330, 290)
Expected output:
276.635
Example 2: Ornatsky correlation bulk properties only
Inputs:
| Re | Pr_b | Pr_w |
|---|---|---|
| 80000 | 1 | 1.1 |
Excel formula:
=NU_ORNATSKY(80000, 1, 1.1)
Expected output:
192.398
Example 3: Ornatsky correlation mid Reynolds number
Inputs:
| Re | Pr_b | Pr_w | rho_w | rho_b |
|---|---|---|---|---|
| 200000 | 0.9 | 1.3 | 360 | 310 |
Excel formula:
=NU_ORNATSKY(200000, 0.9, 1.3, 360, 310)
Expected output:
384.971
Example 4: Ornatsky correlation higher Reynolds number
Inputs:
| Re | Pr_b | Pr_w | rho_w | rho_b |
|---|---|---|---|---|
| 450000 | 1.4 | 1.8 | 380 | 320 |
Excel formula:
=NU_ORNATSKY(450000, 1.4, 1.8, 380, 320)
Expected output:
1055.82
Python Code
Show Code
from ht.conv_supercritical import Nu_Ornatsky as ht_Nu_Ornatsky
def Nu_Ornatsky(Re, Pr_b, Pr_w, rho_w=None, rho_b=None):
"""
Calculate Nusselt number for supercritical flow using the Ornatsky correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr_b (float): Prandtl number with bulk fluid properties (-).
Pr_w (float): Prandtl number with wall fluid properties (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Ornatsky(Re=Re, Pr_b=Pr_b, Pr_w=Pr_w, rho_w=rho_w, rho_b=rho_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_PETUKHOV
Calculate Nusselt number for supercritical flow using the Petukhov correlation.
Excel Usage
=NU_PETUKHOV(Re, Pr, rho_w, rho_b, mu_w, mu_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).mu_w(float, optional, default: null): Viscosity at wall temperature (Pa*s).mu_b(float, optional, default: null): Viscosity at bulk temperature (Pa*s).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Petukhov correlation example
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.0008 | 0.0009 |
Excel formula:
=NU_PETUKHOV(100000, 1.2, 330, 290, 0.0008, 0.0009)
Expected output:
254.826
Example 2: Petukhov correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_PETUKHOV(80000, 1.1)
Expected output:
197.156
Example 3: Petukhov correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 200000 | 0.9 | 360 | 310 | 0.0007 | 0.00082 |
Excel formula:
=NU_PETUKHOV(200000, 0.9, 360, 310, 0.0007, 0.00082)
Expected output:
373.626
Example 4: Petukhov correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 450000 | 1.4 | 380 | 320 | 0.0006 | 0.00075 |
Excel formula:
=NU_PETUKHOV(450000, 1.4, 380, 320, 0.0006, 0.00075)
Expected output:
950.914
Python Code
Show Code
from ht.conv_supercritical import Nu_Petukhov as ht_Nu_Petukhov
def Nu_Petukhov(Re, Pr, rho_w=None, rho_b=None, mu_w=None, mu_b=None):
"""
Calculate Nusselt number for supercritical flow using the Petukhov correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
mu_w (float, optional): Viscosity at wall temperature (Pa*s). Default is None.
mu_b (float, optional): Viscosity at bulk temperature (Pa*s). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Petukhov(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b, mu_w=mu_w, mu_b=mu_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_SHITSMAN
Calculate Nusselt number for supercritical flow using the Shitsman correlation.
Excel Usage
=NU_SHITSMAN(Re, Pr_b, Pr_w)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr_b(float, required): Prandtl number with bulk fluid properties (-).Pr_w(float, required): Prandtl number with wall fluid properties (-).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Shitsman correlation example
Inputs:
| Re | Pr_b | Pr_w |
|---|---|---|
| 100000 | 1.2 | 1.6 |
Excel formula:
=NU_SHITSMAN(100000, 1.2, 1.6)
Expected output:
266.117
Example 2: Shitsman correlation lower Reynolds number
Inputs:
| Re | Pr_b | Pr_w |
|---|---|---|
| 60000 | 1 | 1.3 |
Excel formula:
=NU_SHITSMAN(60000, 1, 1.3)
Expected output:
152.844
Example 3: Shitsman correlation mid Reynolds number
Inputs:
| Re | Pr_b | Pr_w |
|---|---|---|
| 200000 | 0.9 | 1.4 |
Excel formula:
=NU_SHITSMAN(200000, 0.9, 1.4)
Expected output:
368.083
Example 4: Shitsman correlation higher Reynolds number
Inputs:
| Re | Pr_b | Pr_w |
|---|---|---|
| 400000 | 1.3 | 1.7 |
Excel formula:
=NU_SHITSMAN(400000, 1.3, 1.7)
Expected output:
860.063
Python Code
Show Code
from ht.conv_supercritical import Nu_Shitsman as ht_Nu_Shitsman
def Nu_Shitsman(Re, Pr_b, Pr_w):
"""
Calculate Nusselt number for supercritical flow using the Shitsman correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr_b (float): Prandtl number with bulk fluid properties (-).
Pr_w (float): Prandtl number with wall fluid properties (-).
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Shitsman(Re=Re, Pr_b=Pr_b, Pr_w=Pr_w)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_SWENSON
Calculate Nusselt number for supercritical flow using the Swenson correlation.
Excel Usage
=NU_SWENSON(Re, Pr, rho_w, rho_b)
Re(float, required): Reynolds number with wall fluid properties (-).Pr(float, required): Prandtl number with wall properties and averaged heat capacity (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).
Returns (float): Nusselt number with wall fluid properties (-).
Example 1: Swenson correlation example
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 100000 | 1.2 | 330 | 290 |
Excel formula:
=NU_SWENSON(100000, 1.2, 330, 290)
Expected output:
217.928
Example 2: Swenson correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1 |
Excel formula:
=NU_SWENSON(80000, 1)
Expected output:
153.945
Example 3: Swenson correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 200000 | 0.9 | 360 | 310 |
Excel formula:
=NU_SWENSON(200000, 0.9, 360, 310)
Expected output:
348.029
Example 4: Swenson correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b |
|---|---|---|---|
| 500000 | 1.5 | 380 | 320 |
Excel formula:
=NU_SWENSON(500000, 1.5, 380, 320)
Expected output:
1114.67
Python Code
Show Code
from ht.conv_supercritical import Nu_Swenson as ht_Nu_Swenson
def Nu_Swenson(Re, Pr, rho_w=None, rho_b=None):
"""
Calculate Nusselt number for supercritical flow using the Swenson correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with wall fluid properties (-).
Pr (float): Prandtl number with wall properties and averaged heat capacity (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
Returns:
float: Nusselt number with wall fluid properties (-).
"""
try:
return ht_Nu_Swenson(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_XU
Calculate Nusselt number for supercritical flow using the Xu correlation.
Excel Usage
=NU_XU(Re, Pr, rho_w, rho_b, mu_w, mu_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk properties and averaged heat capacity (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).mu_w(float, optional, default: null): Viscosity at wall temperature (Pa*s).mu_b(float, optional, default: null): Viscosity at bulk temperature (Pa*s).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Xu correlation example
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.0008 | 0.0009 |
Excel formula:
=NU_XU(100000, 1.2, 330, 290, 0.0008, 0.0009)
Expected output:
289.133
Example 2: Xu correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_XU(80000, 1.1)
Expected output:
226.556
Example 3: Xu correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 200000 | 0.9 | 360 | 310 | 0.0007 | 0.00082 |
Excel formula:
=NU_XU(200000, 0.9, 360, 310, 0.0007, 0.00082)
Expected output:
380.01
Example 4: Xu correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | mu_w | mu_b |
|---|---|---|---|---|---|
| 450000 | 1.4 | 380 | 320 | 0.0006 | 0.00075 |
Excel formula:
=NU_XU(450000, 1.4, 380, 320, 0.0006, 0.00075)
Expected output:
1054.51
Python Code
Show Code
from ht.conv_supercritical import Nu_Xu as ht_Nu_Xu
def Nu_Xu(Re, Pr, rho_w=None, rho_b=None, mu_w=None, mu_b=None):
"""
Calculate Nusselt number for supercritical flow using the Xu correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk properties and averaged heat capacity (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
mu_w (float, optional): Viscosity at wall temperature (Pa*s). Default is None.
mu_b (float, optional): Viscosity at bulk temperature (Pa*s). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Xu(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b, mu_w=mu_w, mu_b=mu_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_YAMAGATA
Calculate Nusselt number for supercritical flow using the Yamagata correlation.
Excel Usage
=NU_YAMAGATA(Re, Pr, Pr_pc, Cp_avg, Cp_b, T_b, T_w, T_pc)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk fluid properties (-).Pr_pc(float, optional, default: null): Prandtl number at the pseudocritical temperature (-).Cp_avg(float, optional, default: null): Average heat capacity between wall and bulk temperatures (J/kg/K).Cp_b(float, optional, default: null): Heat capacity at bulk temperature (J/kg/K).T_b(float, optional, default: null): Bulk temperature (K).T_w(float, optional, default: null): Wall temperature (K).T_pc(float, optional, default: null): Pseudocritical temperature at pressure (K).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Yamagata correlation example
Inputs:
| Re | Pr | Pr_pc | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|
| 100000 | 1.2 | 1.5 | 2080.845 | 2048.621 | 650 | 700 | 600 |
Excel formula:
=NU_YAMAGATA(100000, 1.2, 1.5, 2080.845, 2048.621, 650, 700, 600)
Expected output:
292.347
Example 2: Yamagata correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1 |
Excel formula:
=NU_YAMAGATA(80000, 1)
Expected output:
203.004
Example 3: Yamagata correlation mid Reynolds number
Inputs:
| Re | Pr | Pr_pc | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|
| 200000 | 0.9 | 1.2 | 2200 | 2100 | 620 | 680 | 640 |
Excel formula:
=NU_YAMAGATA(200000, 0.9, 1.2, 2200, 2100, 620, 680, 640)
Expected output:
270.924
Example 4: Yamagata correlation higher Reynolds number
Inputs:
| Re | Pr | Pr_pc | Cp_avg | Cp_b | T_b | T_w | T_pc |
|---|---|---|---|---|---|---|---|
| 450000 | 1.4 | 1.3 | 2400 | 2200 | 700 | 760 | 680 |
Excel formula:
=NU_YAMAGATA(450000, 1.4, 1.3, 2400, 2200, 700, 760, 680)
Expected output:
1374.86
Python Code
Show Code
from ht.conv_supercritical import Nu_Yamagata as ht_Nu_Yamagata
def Nu_Yamagata(Re, Pr, Pr_pc=None, Cp_avg=None, Cp_b=None, T_b=None, T_w=None, T_pc=None):
"""
Calculate Nusselt number for supercritical flow using the Yamagata correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk fluid properties (-).
Pr_pc (float, optional): Prandtl number at the pseudocritical temperature (-). Default is None.
Cp_avg (float, optional): Average heat capacity between wall and bulk temperatures (J/kg/K). Default is None.
Cp_b (float, optional): Heat capacity at bulk temperature (J/kg/K). Default is None.
T_b (float, optional): Bulk temperature (K). Default is None.
T_w (float, optional): Wall temperature (K). Default is None.
T_pc (float, optional): Pseudocritical temperature at pressure (K). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Yamagata(
Re=Re,
Pr=Pr,
Pr_pc=Pr_pc,
Cp_avg=Cp_avg,
Cp_b=Cp_b,
T_b=T_b,
T_w=T_w,
T_pc=T_pc,
)
except Exception as e:
return f"Error: {str(e)}"Online Calculator
NU_ZHU
Calculate Nusselt number for supercritical flow using the Zhu correlation.
Excel Usage
=NU_ZHU(Re, Pr, rho_w, rho_b, k_w, k_b)
Re(float, required): Reynolds number with bulk fluid properties (-).Pr(float, required): Prandtl number with bulk properties and averaged heat capacity (-).rho_w(float, optional, default: null): Density at wall temperature (kg/m^3).rho_b(float, optional, default: null): Density at bulk temperature (kg/m^3).k_w(float, optional, default: null): Thermal conductivity at wall temperature (W/m/K).k_b(float, optional, default: null): Thermal conductivity at bulk temperature (W/m/K).
Returns (float): Nusselt number with bulk fluid properties (-).
Example 1: Zhu correlation example
Inputs:
| Re | Pr | rho_w | rho_b | k_w | k_b |
|---|---|---|---|---|---|
| 100000 | 1.2 | 330 | 290 | 0.63 | 0.69 |
Excel formula:
=NU_ZHU(100000, 1.2, 330, 290, 0.63, 0.69)
Expected output:
240.146
Example 2: Zhu correlation bulk properties only
Inputs:
| Re | Pr |
|---|---|
| 80000 | 1.1 |
Excel formula:
=NU_ZHU(80000, 1.1)
Expected output:
186.796
Example 3: Zhu correlation mid Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | k_w | k_b |
|---|---|---|---|---|---|
| 200000 | 0.9 | 360 | 310 | 0.7 | 0.62 |
Excel formula:
=NU_ZHU(200000, 0.9, 360, 310, 0.7, 0.62)
Expected output:
398.964
Example 4: Zhu correlation higher Reynolds number
Inputs:
| Re | Pr | rho_w | rho_b | k_w | k_b |
|---|---|---|---|---|---|
| 450000 | 1.4 | 380 | 320 | 0.75 | 0.66 |
Excel formula:
=NU_ZHU(450000, 1.4, 380, 320, 0.75, 0.66)
Expected output:
1099.64
Python Code
Show Code
from ht.conv_supercritical import Nu_Zhu as ht_Nu_Zhu
def Nu_Zhu(Re, Pr, rho_w=None, rho_b=None, k_w=None, k_b=None):
"""
Calculate Nusselt number for supercritical flow using the Zhu correlation.
See: https://ht.readthedocs.io/en/latest/ht.conv_supercritical.html
This example function is provided as-is without any representation of accuracy.
Args:
Re (float): Reynolds number with bulk fluid properties (-).
Pr (float): Prandtl number with bulk properties and averaged heat capacity (-).
rho_w (float, optional): Density at wall temperature (kg/m^3). Default is None.
rho_b (float, optional): Density at bulk temperature (kg/m^3). Default is None.
k_w (float, optional): Thermal conductivity at wall temperature (W/m/K). Default is None.
k_b (float, optional): Thermal conductivity at bulk temperature (W/m/K). Default is None.
Returns:
float: Nusselt number with bulk fluid properties (-).
"""
try:
return ht_Nu_Zhu(Re=Re, Pr=Pr, rho_w=rho_w, rho_b=rho_b, k_w=k_w, k_b=k_b)
except Exception as e:
return f"Error: {str(e)}"Online Calculator