PQM_functions.F90

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!> Piecewise quartic reconstruction functions
module pqm_functions
 
! This file is part of MOM6. See LICENSE.md for the license.
 
use regrid_edge_values, only : bound_edge_values, check_discontinuous_edge_values
 
implicit none ; private
 
public pqm_reconstruction, pqm_boundary_extrapolation, pqm_boundary_extrapolation_v1
 
real, parameter :: hneglect_dflt = 1.e-30 !< Default negligible cell thickness
 
contains
 
!> Reconstruction by quartic polynomials within each cell.
!!
!! It is assumed that the dimension of 'u' is equal to the number of cells
!! defining 'grid' and 'ppoly'. No consistency check is performed.
subroutine pqm_reconstruction( N, h, u, ppoly_E, ppoly_S, ppoly_coef, h_neglect )
  integer,              intent(in)    :: n !< Number of cells
  real, dimension(:),   intent(in)    :: h !< cell widths (size N)
  real, dimension(:),   intent(in)    :: u !< cell averages (size N)
  real, dimension(:,:), intent(inout) :: ppoly_e    !< Edge value of polynomial,
                                           !! with the same units as u.
  real, dimension(:,:), intent(inout) :: ppoly_s    !< Edge slope of polynomial,
                                           !! in the units of u over the units of h.
  real, dimension(:,:), intent(inout) :: ppoly_coef !< Coefficients of polynomial, mainly
                                           !! with the same units as u.
  real,       optional, intent(in)    :: h_neglect  !< A negligibly small width for
                                           !! the purpose of cell reconstructions
                                           !! in the same units as h
 
  ! Local variables
  integer   :: k                ! loop index
  real      :: h_c              ! cell width
  real      :: u0_l, u0_r       ! edge values (left and right)
  real      :: u1_l, u1_r       ! edge slopes (left and right)
  real      :: a, b, c, d, e    ! parabola coefficients
 
  ! PQM limiter
  call pqm_limiter( n, h, u, ppoly_e, ppoly_s, h_neglect )
 
  ! Loop on cells to construct the cubic within each cell
  do k = 1,n
 
    u0_l = ppoly_e(k,1)
    u0_r = ppoly_e(k,2)
 
    u1_l = ppoly_s(k,1)
    u1_r = ppoly_s(k,2)
 
    h_c = h(k)
 
    a = u0_l
    b = h_c * u1_l
    c = 30.0 * u(k) - 12.0*u0_r - 18.0*u0_l + 1.5*h_c*(u1_r - 3.0*u1_l)
    d = -60.0 * u(k) + h_c *(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
    e = 30.0 * u(k) + 2.5*h_c*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
    ! Store coefficients
    ppoly_coef(k,1) = a
    ppoly_coef(k,2) = b
    ppoly_coef(k,3) = c
    ppoly_coef(k,4) = d
    ppoly_coef(k,5) = e
 
  enddo ! end loop on cells
 
end subroutine pqm_reconstruction
 
!> Limit the piecewise quartic method reconstruction
!!
!! Standard PQM limiter (White & Adcroft, JCP 2008).
!!
!! It is assumed that the dimension of 'u' is equal to the number of cells
!! defining 'grid' and 'ppoly'. No consistency check is performed.
subroutine pqm_limiter( N, h, u, ppoly_E, ppoly_S, h_neglect )
  integer,              intent(in)    :: N !< Number of cells
  real, dimension(:),   intent(in)    :: h !< cell widths (size N)
  real, dimension(:),   intent(in)    :: u !< cell average properties (size N)
  real, dimension(:,:), intent(inout) :: ppoly_E !< Potentially modified edge values,
                                           !! with the same units as u.
  real, dimension(:,:), intent(inout) :: ppoly_S !< Potentially modified edge slopes,
                                           !! with the same units as u.
  real,       optional, intent(in)    :: h_neglect !< A negligibly small width for
                                           !! the purpose of cell reconstructions
                                           !! in the same units as h
  ! Local variables
  integer :: k            ! loop index
  integer :: inflexion_l
  integer :: inflexion_r
  real    :: u0_l, u0_r     ! edge values
  real    :: u1_l, u1_r     ! edge slopes
  real    :: u_l, u_c, u_r  ! left, center and right cell averages
  real    :: h_l, h_c, h_r  ! left, center and right cell widths
  real    :: sigma_l, sigma_c, sigma_r ! left, center and right van Leer slopes
  real    :: slope          ! retained PLM slope
  real    :: a, b, c, d, e
  real    :: alpha1, alpha2, alpha3
  real    :: rho, sqrt_rho
  real    :: gradient1, gradient2
  real    :: x1, x2
  real    :: hNeglect
 
  hneglect = hneglect_dflt ; if (present(h_neglect)) hneglect = h_neglect
 
  ! Bound edge values
  call bound_edge_values( n, h, u, ppoly_e, hneglect )
 
  ! Make discontinuous edge values monotonic (thru averaging)
  call check_discontinuous_edge_values( n, u, ppoly_e )
 
  ! Loop on interior cells to apply the PQM limiter
  do k = 2,n-1
 
    !if ( h(k) < 1.0 ) cycle
 
    inflexion_l = 0
    inflexion_r = 0
 
    ! Get edge values, edge slopes and cell width
    u0_l = ppoly_e(k,1)
    u0_r = ppoly_e(k,2)
    u1_l = ppoly_s(k,1)
    u1_r = ppoly_s(k,2)
 
    ! Get cell widths and cell averages (boundary cells are assumed to
    ! be local extrema for the sake of slopes)
    h_l = h(k-1)
    h_c = h(k)
    h_r = h(k+1)
    u_l = u(k-1)
    u_c = u(k)
    u_r = u(k+1)
 
    ! Compute limited slope
    sigma_l = 2.0 * ( u_c - u_l ) / ( h_c + hneglect )
    sigma_c = 2.0 * ( u_r - u_l ) / ( h_l + 2.0*h_c + h_r + hneglect )
    sigma_r = 2.0 * ( u_r - u_c ) / ( h_c + hneglect )
 
    if ( (sigma_l * sigma_r) > 0.0 ) then
      slope = sign( min(abs(sigma_l),abs(sigma_c),abs(sigma_r)), sigma_c )
    else
      slope = 0.0
    endif
 
    ! If one of the slopes has the wrong sign compared with the
    ! limited PLM slope, it is set equal to the limited PLM slope
    if ( u1_l*slope <= 0.0 ) u1_l = slope
    if ( u1_r*slope <= 0.0 ) u1_r = slope
 
    ! Local extremum --> flatten
    if ( (u0_r - u_c) * (u_c - u0_l) <= 0.0) then
      u0_l = u_c
      u0_r = u_c
      u1_l = 0.0
      u1_r = 0.0
      inflexion_l = -1
      inflexion_r = -1
    endif
 
    ! Edge values are bounded and averaged when discontinuous and not
    ! monotonic, edge slopes are consistent and the cell is not an extremum.
    ! We now need to check and encorce the monotonicity of the quartic within
    ! the cell
    if ( (inflexion_l == 0) .AND. (inflexion_r == 0) ) then
 
      a = u0_l
      b = h_c * u1_l
      c = 30.0 * u(k) - 12.0*u0_r - 18.0*u0_l + 1.5*h_c*(u1_r - 3.0*u1_l)
      d = -60.0 * u(k) + h_c *(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
      e = 30.0 * u(k) + 2.5*h_c*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
      ! Determine the coefficients of the second derivative
      ! alpha1 xi^2 + alpha2 xi + alpha3
      alpha1 = 6*e
      alpha2 = 3*d
      alpha3 = c
 
      rho = alpha2 * alpha2 - 4.0 * alpha1 * alpha3
 
      ! Check whether inflexion points exist
      if (( alpha1 /= 0.0 ) .and. ( rho >= 0.0 )) then
 
        sqrt_rho = sqrt( rho )
 
        x1 = 0.5 * ( - alpha2 - sqrt_rho ) / alpha1
        x2 = 0.5 * ( - alpha2 + sqrt_rho ) / alpha1
 
        ! Check whether both inflexion points lie in [0,1]
        if ( (x1 >= 0.0) .AND. (x1 <= 1.0) .AND. &
             (x2 >= 0.0) .AND. (x2 <= 1.0) ) then
 
          gradient1 = 4.0 * e * (x1**3) + 3.0 * d * (x1**2) + 2.0 * c * x1 + b
          gradient2 = 4.0 * e * (x2**3) + 3.0 * d * (x2**2) + 2.0 * c * x2 + b
 
          ! Check whether one of the gradients is inconsistent
          if ( (gradient1 * slope < 0.0) .OR. &
               (gradient2 * slope < 0.0) ) then
            ! Decide where to collapse inflexion points
            ! (depends on one-sided slopes)
            if ( abs(sigma_l) < abs(sigma_r) ) then
              inflexion_l = 1
            else
              inflexion_r = 1
            endif
          endif
 
        ! If both x1 and x2 do not lie in [0,1], check whether
        ! only x1 lies in [0,1]
        elseif ( (x1 >= 0.0) .AND. (x1 <= 1.0) ) then
 
          gradient1 = 4.0 * e * (x1**3) + 3.0 * d * (x1**2) + 2.0 * c * x1 + b
 
          ! Check whether the gradient is inconsistent
          if ( gradient1 * slope < 0.0 ) then
            ! Decide where to collapse inflexion points
            ! (depends on one-sided slopes)
            if ( abs(sigma_l) < abs(sigma_r) ) then
              inflexion_l = 1
            else
              inflexion_r = 1
            endif
          endif
 
        ! If x1 does not lie in [0,1], check whether x2 lies in [0,1]
        elseif ( (x2 >= 0.0) .AND. (x2 <= 1.0) ) then
 
          gradient2 = 4.0 * e * (x2**3) + 3.0 * d * (x2**2) + 2.0 * c * x2 + b
 
          ! Check whether the gradient is inconsistent
          if ( gradient2 * slope < 0.0 ) then
            ! Decide where to collapse inflexion points
            ! (depends on one-sided slopes)
            if ( abs(sigma_l) < abs(sigma_r) ) then
              inflexion_l = 1
            else
              inflexion_r = 1
            endif
          endif
 
        endif ! end checking where the inflexion points lie
 
      endif ! end checking if alpha1 != 0 AND rho >= 0
 
      ! If alpha1 is zero, the second derivative of the quartic reduces
      ! to a straight line
      if (( alpha1 == 0.0 ) .and. ( alpha2 /= 0.0 )) then
 
          x1 = - alpha3 / alpha2
          if ( (x1 >= 0.0) .AND. (x1 <= 1.0) ) then
 
            gradient1 = 4.0 * e * (x1**3) + 3.0 * d * (x1**2) + 2.0 * c * x1 + b
 
            ! Check whether the gradient is inconsistent
            if ( gradient1 * slope < 0.0 ) then
              ! Decide where to collapse inflexion points
              ! (depends on one-sided slopes)
              if ( abs(sigma_l) < abs(sigma_r) ) then
                inflexion_l = 1
              else
                inflexion_r = 1
              endif
            endif ! check slope consistency
 
          endif
 
      endif ! end check whether we can find the root of the straight line
 
    endif ! end checking whether to shift inflexion points
 
    ! At this point, we know onto which edge to shift inflexion points
    if ( inflexion_l == 1 ) then
 
      ! We modify the edge slopes so that both inflexion points
      ! collapse onto the left edge
      u1_l = ( 10.0 * u_c - 2.0 * u0_r - 8.0 * u0_l ) / (3.0*h_c + hneglect )
      u1_r = ( -10.0 * u_c + 6.0 * u0_r + 4.0 * u0_l ) / ( h_c + hneglect )
 
      ! One of the modified slopes might be inconsistent. When that happens,
      ! the inconsistent slope is set equal to zero and the opposite edge value
      ! and edge slope are modified in compliance with the fact that both
      ! inflexion points must still be located on the left edge
      if ( u1_l * slope < 0.0 ) then
 
        u1_l = 0.0
        u0_r = 5.0 * u_c - 4.0 * u0_l
        u1_r = 20.0 * (u_c - u0_l) / ( h_c + hneglect )
 
      elseif ( u1_r * slope < 0.0 ) then
 
        u1_r = 0.0
        u0_l = (5.0*u_c - 3.0*u0_r) / 2.0
        u1_l = 10.0 * (-u_c + u0_r) / (3.0 * h_c + hneglect)
 
      endif
 
    elseif ( inflexion_r == 1 ) then
 
      ! We modify the edge slopes so that both inflexion points
      ! collapse onto the right edge
      u1_r = ( -10.0 * u_c + 8.0 * u0_r + 2.0 * u0_l ) / (3.0 * h_c + hneglect)
      u1_l = ( 10.0 * u_c - 4.0 * u0_r - 6.0 * u0_l ) / (h_c + hneglect)
 
      ! One of the modified slopes might be inconsistent. When that happens,
      ! the inconsistent slope is set equal to zero and the opposite edge value
      ! and edge slope are modified in compliance with the fact that both
      ! inflexion points must still be located on the right edge
      if ( u1_l * slope < 0.0 ) then
 
        u1_l = 0.0
        u0_r = ( 5.0 * u_c - 3.0 * u0_l ) / 2.0
        u1_r = 10.0 * (u_c - u0_l) / (3.0 * h_c + hneglect)
 
      elseif ( u1_r * slope < 0.0 ) then
 
        u1_r = 0.0
        u0_l = 5.0 * u_c - 4.0 * u0_r
        u1_l = 20.0 * ( -u_c + u0_r ) / (h_c + hneglect)
 
      endif
 
    endif ! clause to check where to collapse inflexion points
 
    ! Save edge values and edge slopes for reconstruction
    ppoly_e(k,1) = u0_l
    ppoly_e(k,2) = u0_r
    ppoly_s(k,1) = u1_l
    ppoly_s(k,2) = u1_r
 
  enddo ! end loop on interior cells
 
  ! Constant reconstruction within boundary cells
  ppoly_e(1,:) = u(1)
  ppoly_s(1,:) = 0.0
 
  ppoly_e(n,:) = u(n)
  ppoly_s(n,:) = 0.0
 
end subroutine pqm_limiter
 
!> Reconstruction by parabolas within boundary cells.
!!
!! The following explanations apply to the left boundary cell. The same
!! reasoning holds for the right boundary cell.
!!
!! A parabola needs to be built in the cell and requires three degrees of
!! freedom, which are the right edge value and slope and the cell average.
!! The right edge values and slopes are taken to be that of the neighboring
!! cell (i.e., the left edge value and slope of the neighboring cell).
!! The resulting parabola is not necessarily monotonic and the traditional
!! PPM limiter is used to modify one of the edge values in order to yield
!! a monotonic parabola.
!!
!! It is assumed that the size of the array 'u' is equal to the number of cells
!! defining 'grid' and 'ppoly'. No consistency check is performed here.
subroutine pqm_boundary_extrapolation( N, h, u, ppoly_E, ppoly_coef )
  integer,              intent(in)    :: n !< Number of cells
  real, dimension(:),   intent(in)    :: h !< cell widths (size N)
  real, dimension(:),   intent(in)    :: u !< cell averages (size N)
  real, dimension(:,:), intent(inout) :: ppoly_e    !< Edge value of polynomial,
                                           !! with the same units as u.
  real, dimension(:,:), intent(inout) :: ppoly_coef !< Coefficients of polynomial, mainly
                                           !! with the same units as u.
  ! Local variables
  integer       :: i0, i1
  real          :: u0, u1
  real          :: h0, h1
  real          :: a, b, c, d, e
  real          :: u0_l, u0_r
  real          :: u1_l, u1_r
  real          :: slope
  real          :: exp1, exp2
 
  ! ----- Left boundary -----
  i0 = 1
  i1 = 2
  h0 = h(i0)
  h1 = h(i1)
  u0 = u(i0)
  u1 = u(i1)
 
  ! Compute the left edge slope in neighboring cell and express it in
  ! the global coordinate system
  b = ppoly_coef(i1,2)
  u1_r = b *(h0/h1)     ! derivative evaluated at xi = 0.0,
                        ! expressed w.r.t. xi (local coord. system)
 
  ! Limit the right slope by the PLM limited slope
  slope = 2.0 * ( u1 - u0 )
  if ( abs(u1_r) > abs(slope) ) then
    u1_r = slope
  endif
 
  ! The right edge value in the boundary cell is taken to be the left
  ! edge value in the neighboring cell
  u0_r = ppoly_e(i1,1)
 
  ! Given the right edge value and slope, we determine the left
  ! edge value and slope by computing the parabola as determined by
  ! the right edge value and slope and the boundary cell average
  u0_l = 3.0 * u0 + 0.5 * u1_r - 2.0 * u0_r
 
  ! Apply the traditional PPM limiter
  exp1 = (u0_r - u0_l) * (u0 - 0.5*(u0_l+u0_r))
  exp2 = (u0_r - u0_l) * (u0_r - u0_l) / 6.0
 
  if ( exp1 > exp2 ) then
    u0_l = 3.0 * u0 - 2.0 * u0_r
  endif
 
  if ( exp1 < -exp2 ) then
    u0_r = 3.0 * u0 - 2.0 * u0_l
  endif
 
  ppoly_e(i0,1) = u0_l
  ppoly_e(i0,2) = u0_r
 
  a = u0_l
  b = 6.0 * u0 - 4.0 * u0_l - 2.0 * u0_r
  c = 3.0 * ( u0_r + u0_l - 2.0 * u0 )
 
  ! The quartic is reduced to a parabola in the boundary cell
  ppoly_coef(i0,1) = a
  ppoly_coef(i0,2) = b
  ppoly_coef(i0,3) = c
  ppoly_coef(i0,4) = 0.0
  ppoly_coef(i0,5) = 0.0
 
  ! ----- Right boundary -----
  i0 = n-1
  i1 = n
  h0 = h(i0)
  h1 = h(i1)
  u0 = u(i0)
  u1 = u(i1)
 
  ! Compute the right edge slope in neighboring cell and express it in
  ! the global coordinate system
  b = ppoly_coef(i0,2)
  c = ppoly_coef(i0,3)
  d = ppoly_coef(i0,4)
  e = ppoly_coef(i0,5)
  u1_l = (b + 2*c + 3*d + 4*e)      ! derivative evaluated at xi = 1.0
  u1_l = u1_l * (h1/h0)
 
  ! Limit the left slope by the PLM limited slope
  slope = 2.0 * ( u1 - u0 )
  if ( abs(u1_l) > abs(slope) ) then
    u1_l = slope
  endif
 
  ! The left edge value in the boundary cell is taken to be the right
  ! edge value in the neighboring cell
  u0_l = ppoly_e(i0,2)
 
  ! Given the left edge value and slope, we determine the right
  ! edge value and slope by computing the parabola as determined by
  ! the left edge value and slope and the boundary cell average
  u0_r = 3.0 * u1 - 0.5 * u1_l - 2.0 * u0_l
 
  ! Apply the traditional PPM limiter
  exp1 = (u0_r - u0_l) * (u1 - 0.5*(u0_l+u0_r))
  exp2 = (u0_r - u0_l) * (u0_r - u0_l) / 6.0
 
  if ( exp1 > exp2 ) then
    u0_l = 3.0 * u1 - 2.0 * u0_r
  endif
 
  if ( exp1 < -exp2 ) then
    u0_r = 3.0 * u1 - 2.0 * u0_l
  endif
 
  ppoly_e(i1,1) = u0_l
  ppoly_e(i1,2) = u0_r
 
  a = u0_l
  b = 6.0 * u1 - 4.0 * u0_l - 2.0 * u0_r
  c = 3.0 * ( u0_r + u0_l - 2.0 * u1 )
 
  ! The quartic is reduced to a parabola in the boundary cell
  ppoly_coef(i1,1) = a
  ppoly_coef(i1,2) = b
  ppoly_coef(i1,3) = c
  ppoly_coef(i1,4) = 0.0
  ppoly_coef(i1,5) = 0.0
 
end subroutine pqm_boundary_extrapolation
 
 
!> Reconstruction by parabolas within boundary cells.
!!
!! The following explanations apply to the left boundary cell. The same
!! reasoning holds for the right boundary cell.
!!
!! A parabola needs to be built in the cell and requires three degrees of
!! freedom, which are the right edge value and slope and the cell average.
!! The right edge values and slopes are taken to be that of the neighboring
!! cell (i.e., the left edge value and slope of the neighboring cell).
!! The resulting parabola is not necessarily monotonic and the traditional
!! PPM limiter is used to modify one of the edge values in order to yield
!! a monotonic parabola.
!!
!! It is assumed that the size of the array 'u' is equal to the number of cells
!! defining 'grid' and 'ppoly'. No consistency check is performed here.
subroutine pqm_boundary_extrapolation_v1( N, h, u, ppoly_E, ppoly_S, ppoly_coef, h_neglect )
  integer,              intent(in)    :: n !< Number of cells
  real, dimension(:),   intent(in)    :: h !< cell widths (size N)
  real, dimension(:),   intent(in)    :: u !< cell averages (size N)
  real, dimension(:,:), intent(inout) :: ppoly_e    !< Edge value of polynomial,
                                           !! with the same units as u.
  real, dimension(:,:), intent(inout) :: ppoly_s    !< Edge slope of polynomial,
                                           !! in the units of u over the units of h.
  real, dimension(:,:), intent(inout) :: ppoly_coef !< Coefficients of polynomial, mainly
                                           !! with the same units as u.
  real,       optional, intent(in)    :: h_neglect  !< A negligibly small width for
                                           !! the purpose of cell reconstructions
                                           !! in the same units as h.
  ! Local variables
  integer :: i0, i1
  integer :: inflexion_l
  integer :: inflexion_r
  real    :: u0, u1, um
  real    :: h0, h1
  real    :: a, b, c, d, e
  real    :: ar, br, beta
  real    :: u0_l, u0_r
  real    :: u1_l, u1_r
  real    :: u_plm
  real    :: slope
  real    :: alpha1, alpha2, alpha3
  real    :: rho, sqrt_rho
  real    :: gradient1, gradient2
  real    :: x1, x2
  real    :: hneglect
 
  hneglect = hneglect_dflt ; if (present(h_neglect)) hneglect = h_neglect
 
  ! ----- Left boundary (TOP) -----
  i0 = 1
  i1 = 2
  h0 = h(i0)
  h1 = h(i1)
  u0 = u(i0)
  u1 = u(i1)
  um = u0
 
  ! Compute real slope and express it w.r.t. local coordinate system
  ! within boundary cell
  slope = 2.0 * ( u1 - u0 ) / ( ( h0 + h1 ) + hneglect )
  slope = slope * h0
 
  ! The right edge value and slope of the boundary cell are taken to be the
  ! left edge value and slope of the adjacent cell
  a = ppoly_coef(i1,1)
  b = ppoly_coef(i1,2)
 
  u0_r = a          ! edge value
  u1_r = b / (h1 + hneglect) ! edge slope (w.r.t. global coord.)
 
  ! Compute coefficient for rational function based on mean and right
  ! edge value and slope
  if (u1_r /= 0.) then ! HACK by AJA
    beta = 2.0 * ( u0_r - um ) / ( (h0 + hneglect)*u1_r) - 1.0
  else
    beta = 0.
  endif ! HACK by AJA
  br = u0_r + beta*u0_r - um
  ar = um + beta*um - br
 
  ! Left edge value estimate based on rational function
  u0_l = ar
 
  ! Edge value estimate based on PLM
  u_plm = um - 0.5 * slope
 
  ! Check whether the left edge value is bounded by the mean and
  ! the PLM edge value. If so, keep it and compute left edge slope
  ! based on the rational function. If not, keep the PLM edge value and
  ! compute corresponding slope.
  if ( abs(um-u0_l) < abs(um-u_plm) ) then
    u1_l = 2.0 * ( br - ar*beta)
    u1_l = u1_l / (h0 + hneglect)
  else
    u0_l = u_plm
    u1_l = slope / (h0 + hneglect)
  endif
 
  ! Monotonize quartic
  inflexion_l = 0
 
  a = u0_l
  b = h0 * u1_l
  c = 30.0 * um - 12.0*u0_r - 18.0*u0_l + 1.5*h0*(u1_r - 3.0*u1_l)
  d = -60.0 * um + h0 *(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
  e = 30.0 * um + 2.5*h0*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
  alpha1 = 6*e
  alpha2 = 3*d
  alpha3 = c
 
  rho = alpha2 * alpha2 - 4.0 * alpha1 * alpha3
 
  ! Check whether inflexion points exist. If so, transform the quartic
  ! so that both inflexion points coalesce on the left edge.
  if (( alpha1 /= 0.0 ) .and. ( rho >= 0.0 )) then
 
    sqrt_rho = sqrt( rho )
 
    x1 = 0.5 * ( - alpha2 - sqrt_rho ) / alpha1
    if ( (x1 > 0.0) .and. (x1 < 1.0) ) then
      gradient1 = 4.0 * e * (x1**3) + 3.0 * d * (x1**2) + 2.0 * c * x1 + b
      if ( gradient1 * slope < 0.0 ) then
        inflexion_l = 1
      endif
    endif
 
    x2 = 0.5 * ( - alpha2 + sqrt_rho ) / alpha1
    if ( (x2 > 0.0) .and. (x2 < 1.0) ) then
      gradient2 = 4.0 * e * (x2**3) + 3.0 * d * (x2**2) + 2.0 * c * x2 + b
      if ( gradient2 * slope < 0.0 ) then
        inflexion_l = 1
      endif
    endif
 
  endif
 
  if (( alpha1 == 0.0 ) .and. ( alpha2 /= 0.0 )) then
 
    x1 = - alpha3 / alpha2
    if ( (x1 >= 0.0) .and. (x1 <= 1.0) ) then
      gradient1 = 3.0 * d * (x1**2) + 2.0 * c * x1 + b
      if ( gradient1 * slope < 0.0 ) then
        inflexion_l = 1
      endif
    endif
 
  endif
 
  if ( inflexion_l == 1 ) then
 
    ! We modify the edge slopes so that both inflexion points
    ! collapse onto the left edge
    u1_l = ( 10.0 * um - 2.0 * u0_r - 8.0 * u0_l ) / (3.0*h0 + hneglect)
    u1_r = ( -10.0 * um + 6.0 * u0_r + 4.0 * u0_l ) / (h0 + hneglect)
 
    ! One of the modified slopes might be inconsistent. When that happens,
    ! the inconsistent slope is set equal to zero and the opposite edge value
    ! and edge slope are modified in compliance with the fact that both
    ! inflexion points must still be located on the left edge
    if ( u1_l * slope < 0.0 ) then
 
      u1_l = 0.0
      u0_r = 5.0 * um - 4.0 * u0_l
      u1_r = 20.0 * (um - u0_l) / ( h0 + hneglect )
 
    elseif ( u1_r * slope < 0.0 ) then
 
      u1_r = 0.0
      u0_l = (5.0*um - 3.0*u0_r) / 2.0
      u1_l = 10.0 * (-um + u0_r) / (3.0 * h0 + hneglect )
 
    endif
 
  endif
 
  ! Store edge values, edge slopes and coefficients
  ppoly_e(i0,1) = u0_l
  ppoly_e(i0,2) = u0_r
  ppoly_s(i0,1) = u1_l
  ppoly_s(i0,2) = u1_r
 
  a = u0_l
  b = h0 * u1_l
  c = 30.0 * um - 12.0*u0_r - 18.0*u0_l + 1.5*h0*(u1_r - 3.0*u1_l)
  d = -60.0 * um + h0 *(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
  e = 30.0 * um + 2.5*h0*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
    ! Store coefficients
  ppoly_coef(i0,1) = a
  ppoly_coef(i0,2) = b
  ppoly_coef(i0,3) = c
  ppoly_coef(i0,4) = d
  ppoly_coef(i0,5) = e
 
  ! ----- Right boundary (BOTTOM) -----
  i0 = n-1
  i1 = n
  h0 = h(i0)
  h1 = h(i1)
  u0 = u(i0)
  u1 = u(i1)
  um = u1
 
  ! Compute real slope and express it w.r.t. local coordinate system
  ! within boundary cell
  slope = 2.0 * ( u1 - u0 ) / ( h0 + h1 )
  slope = slope * h1
 
  ! The left edge value and slope of the boundary cell are taken to be the
  ! right edge value and slope of the adjacent cell
  a = ppoly_coef(i0,1)
  b = ppoly_coef(i0,2)
  c = ppoly_coef(i0,3)
  d = ppoly_coef(i0,4)
  e = ppoly_coef(i0,5)
  u0_l = a + b + c + d + e                  ! edge value
  u1_l = (b + 2*c + 3*d + 4*e) / h0         ! edge slope (w.r.t. global coord.)
 
  ! Compute coefficient for rational function based on mean and left
  ! edge value and slope
  if (um-u0_l /= 0.) then ! HACK by AJA
    beta = 0.5*h1*u1_l / (um-u0_l) - 1.0
  else
    beta = 0.
  endif ! HACK by AJA
  br = beta*um + um - u0_l
  ar = u0_l
 
  ! Right edge value estimate based on rational function
  if (1+beta /= 0.) then ! HACK by AJA
    u0_r = (ar + 2*br + beta*br ) / ((1+beta)*(1+beta))
  else
    u0_r = um + 0.5 * slope ! PLM
  endif ! HACK by AJA
 
  ! Right edge value estimate based on PLM
  u_plm = um + 0.5 * slope
 
  ! Check whether the right edge value is bounded by the mean and
  ! the PLM edge value. If so, keep it and compute right edge slope
  ! based on the rational function. If not, keep the PLM edge value and
  ! compute corresponding slope.
  if ( abs(um-u0_r) < abs(um-u_plm) ) then
    u1_r = 2.0 * ( br - ar*beta ) / ( (1+beta)*(1+beta)*(1+beta) )
    u1_r = u1_r / h1
  else
    u0_r = u_plm
    u1_r = slope / h1
  endif
 
  ! Monotonize quartic
  inflexion_r = 0
 
  a = u0_l
  b = h1 * u1_l
  c = 30.0 * um - 12.0*u0_r - 18.0*u0_l + 1.5*h1*(u1_r - 3.0*u1_l)
  d = -60.0 * um + h1*(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
  e = 30.0 * um + 2.5*h1*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
  alpha1 = 6*e
  alpha2 = 3*d
  alpha3 = c
 
  rho = alpha2 * alpha2 - 4.0 * alpha1 * alpha3
 
  ! Check whether inflexion points exist. If so, transform the quartic
  ! so that both inflexion points coalesce on the right edge.
  if (( alpha1 /= 0.0 ) .and. ( rho >= 0.0 )) then
 
    sqrt_rho = sqrt( rho )
 
    x1 = 0.5 * ( - alpha2 - sqrt_rho ) / alpha1
    if ( (x1 > 0.0) .and. (x1 < 1.0) ) then
      gradient1 = 4.0 * e * (x1**3) + 3.0 * d * (x1**2) + 2.0 * c * x1 + b
      if ( gradient1 * slope < 0.0 ) then
        inflexion_r = 1
      endif
    endif
 
    x2 = 0.5 * ( - alpha2 + sqrt_rho ) / alpha1
    if ( (x2 > 0.0) .and. (x2 < 1.0) ) then
      gradient2 = 4.0 * e * (x2**3) + 3.0 * d * (x2**2) + 2.0 * c * x2 + b
      if ( gradient2 * slope < 0.0 ) then
        inflexion_r = 1
      endif
    endif
 
  endif
 
  if (( alpha1 == 0.0 ) .and. ( alpha2 /= 0.0 )) then
 
    x1 = - alpha3 / alpha2
    if ( (x1 >= 0.0) .and. (x1 <= 1.0) ) then
      gradient1 = 3.0 * d * (x1**2) + 2.0 * c * x1 + b
      if ( gradient1 * slope < 0.0 ) then
        inflexion_r = 1
      endif
    endif
 
  endif
 
  if ( inflexion_r == 1 ) then
 
    ! We modify the edge slopes so that both inflexion points
    ! collapse onto the right edge
    u1_r = ( -10.0 * um + 8.0 * u0_r + 2.0 * u0_l ) / (3.0 * h1)
    u1_l = ( 10.0 * um - 4.0 * u0_r - 6.0 * u0_l ) / h1
 
    ! One of the modified slopes might be inconsistent. When that happens,
    ! the inconsistent slope is set equal to zero and the opposite edge value
    ! and edge slope are modified in compliance with the fact that both
    ! inflexion points must still be located on the right edge
    if ( u1_l * slope < 0.0 ) then
 
      u1_l = 0.0
      u0_r = ( 5.0 * um - 3.0 * u0_l ) / 2.0
      u1_r = 10.0 * (um - u0_l) / (3.0 * h1)
 
    elseif ( u1_r * slope < 0.0 ) then
 
      u1_r = 0.0
      u0_l = 5.0 * um - 4.0 * u0_r
      u1_l = 20.0 * ( -um + u0_r ) / h1
 
    endif
 
  endif
 
  ! Store edge values, edge slopes and coefficients
  ppoly_e(i1,1) = u0_l
  ppoly_e(i1,2) = u0_r
  ppoly_s(i1,1) = u1_l
  ppoly_s(i1,2) = u1_r
 
  a = u0_l
  b = h1 * u1_l
  c = 30.0 * um - 12.0*u0_r - 18.0*u0_l + 1.5*h1*(u1_r - 3.0*u1_l)
  d = -60.0 * um + h1 *(6.0*u1_l - 4.0*u1_r) + 28.0*u0_r + 32.0*u0_l
  e = 30.0 * um + 2.5*h1*(u1_r - u1_l) - 15.0*(u0_l + u0_r)
 
  ppoly_coef(i1,1) = a
  ppoly_coef(i1,2) = b
  ppoly_coef(i1,3) = c
  ppoly_coef(i1,4) = d
  ppoly_coef(i1,5) = e
 
end subroutine pqm_boundary_extrapolation_v1
 
!> \namespace pqm_functions
!!
!! Date of creation: 2008.06.06
!! L. White
!!
!! This module contains routines that handle one-dimensionnal finite volume
!! reconstruction using the piecewise quartic method (PQM).
 
end module pqm_functions