mod_mof2d_minimization_reconstruction Module Reference

Functions/Subroutines
pure subroutine, public	mof2d_symmetric_minimization_reconstruction (polygon, ref_centroid1, ref_centroid2, ref_volume1, ref_volume2, angle, normal, residual1, residual2, polygon1, polygon2)
	Find the MOF linear reconstruction in a convex cell using a minimization algorithm.
pure subroutine, public	mof2d_minimization_reconstruction (polygon, ref_centroid, ref_volume, angle, normal, residual, polygon_full, polygon_empty)
	Find the MOF linear reconstruction in a convex cell using a minimization algorithm.
pure double precision function	mof2d_symmetric_derivative (centroid1, centroid2, ref_centroid1, ref_centroid2, s0, s1, angle, ref_volume1, ref_volume2)
	Compute the derivative of the symmetric objective function(any coordinate system)
pure double precision function	mof2d_derivative (centroid, ref_centroid, s0, s1, angle, ref_volume)
	Compute the derivative of the objective function(any coordinate system)
pure double precision function	mof2d_cart_symmetric_derivative (centroid1, centroid2, ref_centroid1, ref_centroid2, s0, s1, angle, ref_volume1, ref_volume2)
	Compute the derivative of the symmetric objective function in Cartesian.
pure double precision function	mof2d_cart_derivative (centroid, ref_centroid, s0, s1, angle, ref_volume)
	Compute the derivative of the objective function in Cartesian.
pure double precision function	mof2d_axisym_derivative (centroid, ref_centroid, s0, s1, angle, ref_volume)
	Analytic derivative in axisymmetric.
pure double precision function	mof2d_axisym_symmetric_derivative (centroid1, centroid2, ref_centroid1, ref_centroid2, s0, s1, angle, ref_volume1, ref_volume2)
	Analytic derivative in axisymmetric using symmetric reconstruction.
pure double precision function, dimension(2, 2)	tensor_product (p1, p2)
	Tensor product of two vectors.

Variables
double precision, parameter	tau = 4d0*acos(0d0)
double precision, parameter	pi = 2d0*acos(0d0)
integer, parameter	max_iter_zoom = 120
double precision, parameter	tol_angle_low = 5d-2

Function/Subroutine Documentation

mof2d_axisym_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_axisym_derivative ( double precision, dimension(2), intent(in) centroid, double precision, dimension(2), intent(in) ref_centroid, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume )

private

Analytic derivative in axisymmetric.

Reference: Lemoine A. (2020) Analytic Gradient for the Moment-of-Fluid Method in Axisymmetric and on General Polyhedrons in Any Dimension

mof2d_axisym_symmetric_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_axisym_symmetric_derivative ( double precision, dimension(2), intent(in) centroid1, double precision, dimension(2), intent(in) centroid2, double precision, dimension(2), intent(in) ref_centroid1, double precision, dimension(2), intent(in) ref_centroid2, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume1, double precision, intent(in) ref_volume2 )

private

Analytic derivative in axisymmetric using symmetric reconstruction.

Reference: Lemoine A. (2020) Analytic Gradient for the Moment-of-Fluid Method in Axisymmetric and on General Polyhedrons in Any Dimension

mof2d_cart_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_cart_derivative ( double precision, dimension(2), intent(in) centroid, double precision, dimension(2), intent(in) ref_centroid, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume )

private

Compute the derivative of the objective function in Cartesian.

mof2d_cart_symmetric_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_cart_symmetric_derivative ( double precision, dimension(2), intent(in) centroid1, double precision, dimension(2), intent(in) centroid2, double precision, dimension(2), intent(in) ref_centroid1, double precision, dimension(2), intent(in) ref_centroid2, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume1, double precision, intent(in) ref_volume2 )

private

Compute the derivative of the symmetric objective function in Cartesian.

mof2d_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_derivative ( double precision, dimension(2), intent(in) centroid, double precision, dimension(2), intent(in) ref_centroid, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume )

private

Compute the derivative of the objective function(any coordinate system)

mof2d_symmetric_derivative()

pure double precision function mod_mof2d_minimization_reconstruction::mof2d_symmetric_derivative ( double precision, dimension(2), intent(in) centroid1, double precision, dimension(2), intent(in) centroid2, double precision, dimension(2), intent(in) ref_centroid1, double precision, dimension(2), intent(in) ref_centroid2, double precision, dimension(2), intent(in) s0, double precision, dimension(2), intent(in) s1, double precision, intent(in) angle, double precision, intent(in) ref_volume1, double precision, intent(in) ref_volume2 )

private

Compute the derivative of the symmetric objective function(any coordinate system)

tensor_product()

pure double precision function, dimension(2,2) mod_mof2d_minimization_reconstruction::tensor_product ( double precision, dimension(2), intent(in) p1, double precision, dimension(2), intent(in) p2 )

private

Tensor product of two vectors.

Variable Documentation

max_iter_zoom

integer, parameter mod_mof2d_minimization_reconstruction::max_iter_zoom = 120

private

pi

double precision, parameter mod_mof2d_minimization_reconstruction::pi = 2d0*acos(0d0)

private

tau

double precision, parameter mod_mof2d_minimization_reconstruction::tau = 4d0*acos(0d0)

private

tol_angle_low

double precision, parameter mod_mof2d_minimization_reconstruction::tol_angle_low = 5d-2

private