Compute local properties of materials (density, viscosity, etc.) from geometry, equation of state and reference properties of materials. More...
Namespaces | |
module | mod_linearized_enthalpy_functions |
Temperature-Enthalpy functions for the Linearized Enthalpy method. | |
module | mod_material_properties_boundary_conditions |
Boundary conditions related routines for materials. | |
module | fields_material_properties |
Local properties of material defined on cells or faces. | |
module | mod_temperature_enthalpy_functions |
Temperature-Enthalpy functions for the Apparent Heat Capacity method. | |
module | variables_material_properties |
Declaration of local properties of the materials involved in the simulation (density, conductivity, viscosity, etc.) | |
Classes | |
type | type_material_reference_properties::material_reference_properties |
Definition of the reference properties of a material. More... | |
Functions | |
subroutine, public | mod_compute_material_properties::compute_material_properties () |
Compute local material properties. | |
subroutine | mod_compute_material_properties::compute_property_sutherland_law (temperature, material_law, local_field) |
Compute a material property \( X \) according to a sutherland law of the temperature : | |
subroutine | mod_compute_material_properties::compute_property_polynomial_temperature_nist_law (temperature, material_law, local_field) |
Compute a material property \( X \) according to a polynomial law of the temperature proposed by refprop NIST: | |
subroutine | mod_compute_material_properties::compute_property_polynomial_temperature_law (temperature, material_law, local_field) |
Compute a material property \( X \) according to a polynomial law of the temperature : | |
subroutine | mod_compute_material_properties::compute_property_neural_network (pressure, temperature, material_law, reference_pressure, local_field) |
Compute a material property \( X \) according to a neural_network function of the pressure and the temperature : | |
subroutine | mod_predict_material_properties::predict_material_properties () |
Compute time extrapolation of material properties. | |
Compute local properties of materials (density, viscosity, etc.) from geometry, equation of state and reference properties of materials.
Compute local properties of materials (density, viscosity, etc.) from geometry, equation of state and reference properties of materials.
┌───────────────┐ │ Temperature │ │ Concentration │ │ etc. │ └───────────────┘ ↓ ┌───────────────┐ ┏━━━━━━━━━━━━━┓ ┌──────────────┐ │ Reference │ ┃ Equation of ┃ │ Geometry │ │ properties of │ ───────>┃ state ┃ <─────── │ (e.g. volume │ │ materials │ ┃ (EoS) ┃ │ faction) │ └───────────────┘ ┗━━━━━━━━━━━━━┛ └──────────────┘ ↓ ┌───────────────┐ │ Local │ │ properties of │ │ materials │ └───────────────┘
Non-exhaustive list of reference properties:
When multiple materials are involved in the simulation, the properties ( \( \rho, \mu, C_{p}, \lambda, etc.) \) are locally computed from the volume fraction of materials \( f_i \) (possibly smoothed) according to the following formula:
\[ \phi = \sum_{i=1}^{n} \phi_{i} f_{i} \]
where \( \phi_{i} \) denotes any property of material \( i \) such as density or conductivity.
Depending on the modeling, density may vary linearly with temperature and species concentration \( C_i \):
\[ \rho = \rho_0(1 - \beta_T(T - T_0) + \sum_{i=1}^{m} \beta_{C_i} (C_i - C_{i_0})) \]
When driving pressure is considered (defined as \( \nabla p^* = \nabla p - \rho_0 \bf{g} \)), previous equation reads:
\[ \rho = \rho_0(- \beta_T(T - T_0) + \sum_{i=1}^{m} \beta_{C_i} (C_i - C_{i_0})) \]
anonymous enum |
anonymous enum |
Enumaration associated to the equation of stage.
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private |
Compute a material property \( X \) according to a neural_network function of the pressure and the temperature :
\[ X^{*,n+1}(p^*,T^*) =\alpha(w^n \cdot X^{*,n} + b^n) \]
with \( \alpha \) the activation function (could be sigmoid or tanh), \( X^*, p^*,T^* \) respectively the dimensional computed field, pressure and temperature, \( w^n, X^{*,n}, b^n \) the weights, dimensionless field and bias at neural network layer \( n \).
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private |
Compute a material property \( X \) according to a polynomial law of the temperature :
\[ X(T) =\sum_{i=0}^{4} a_i T^i + a_5 T^5 \]
with \( p \) the degree of the polynom and \( T \) the temperature field.
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private |
Compute a material property \( X \) according to a polynomial law of the temperature proposed by refprop NIST:
\[ X(T) =\sum_{i=0}^{p-2} a_i (T/1000)^i + a_{p-1} (T/1000)^{-2} \]
with \( p \) the degree of the polynom and \( T \) the temperature field.
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private |
Compute a material property \( X \) according to a sutherland law of the temperature :
\[ X(T) = X^* \Big( \frac{T}{T^*} \Big)^{3/2} \frac{T^* + S}{T + S} \]
with \( X^* \), \( T^* \), \( S \), the coefficients of the law material_lawcoef = [ \( X^* \), \( T^* \), \( S \)]