design_brinkman.f90

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! Implements the `brinkman_design_t` type.
module brinkman_design
  use num_types, only: rp, sp
  use field, only: field_t
  use json_module, only: json_file
  use mapping_handler, only: mapping_handler_t
  use coefs, only: coef_t
  use adjoint_fluid_pnpn, only: adjoint_fluid_pnpn_t
  use scratch_registry, only: neko_scratch_registry
  use fld_file_output, only: fld_file_output_t
  use point_zone_registry, only: neko_point_zone_registry
  use point_zone, only: point_zone_t
  use mask_ops, only: mask_exterior_const
  use neko_config, only: neko_bcknd_device
  use device, only: device_memcpy, host_to_device
  use design, only: design_t
  use math, only: rzero
  use simulation_m, only: simulation_t
  use json_module, only: json_file
  use simple_brinkman_source_term, only: simple_brinkman_source_term_t
  use vector, only: vector_t
  use math, only: copy
  use device_math, only: device_copy
  use field_registry, only: neko_field_registry
  use neko_ext, only: field_to_vector, vector_to_field
  use optimization_ic, only: set_optimization_ic
  use field_math, only: field_rzero
  use json_utils, only: json_get, json_get_or_default, json_extract_object
  use utils, only: neko_error
  implicit none
  private
 
  type, extends(design_t), public :: brinkman_design_t
     private
 
     ! TODO
     ! in the future make this a derived type of a `design_variable`
     ! type, public, extends(design_variable_t) :: brinkman_design_t
     type(field_t), pointer :: design_indicator
 
     ! TODO
     ! NOTE: Tim, right now we only have the brinkman term
     ! in the future we may map to other coeeficients for other equations...
     ! in which case this should be a field list
     !
     ! or as I describe below, we also have multiple constraints,
     ! so a list-of-lists may be the correct way forward
     type(field_t), pointer :: brinkman_amplitude
 
     ! NOTE:
     ! again, we have to be so clear with nomenclature.
     ! If we have an objective function F.
     ! I also like to use \rho to describe the design_indicator
     !
     ! and let's say, for completness, we're doing conjugate heat transfer,
     ! so we have to map
     ! to 3 coefficients, \chi, C and \kappa.
     !
     ! then we will perform 3 mapping,
     ! \rho -> \chi
     ! \rho -> C
     ! \rho -> \kappa
     !
     ! Then during the forward/adjoint looping there will be an additional
     ! object, the "objective_function" object that will be responsible for
     ! computing the sensitivity of the objective function with respect to the
     ! coefficients
     ! ie,
     ! dF/d\chi, dF/dC and dF/d\kappa
     !
     ! What I'm calling "sensitivity" here, is the sensitivity with respect to
     ! the design indicator
     ! so dF/d\rho
     !
     ! so the proceedure "map_backwards" will take in the field list
     ! dF/d\chi, dF/dC and dF/d\kappa
     !and chain rule it's way back to
     ! dF/d\rho
     ! and store it here          v
     type(field_t), pointer :: sensitivity
     ! have a field list here
     ! type(filed_list_t), public :: constraint_sensitivity
     ! HOWEVER !
     ! What is a bit confusing to me... is how we'll deal with constraints.
     !
     ! Because in principle we could have constraints C1, C2, C3 etc
     ! Implying we also want dC1/d\rho, dC2/d\rho etc
     ! So this "sensitivity" should also be a list...
     !
     ! So I bet you'll have a nice abstract way of constructing this in the
     ! future but I think a sort of list-of-lists would be nice.
     !
     ! For F:
     ! \rho -> \tild{\rho} -> \chi
     ! \rho -> \tild{\rho} -> C
     ! \rho -> \tild{\rho} -> \kappa
     !
     ! For C1:
     ! \rho -> \tild{\rho}  (eg for a volume constraint or so)
     !
     ! For C2:
     ! \rho -> \tild{\rho}  (for something else)
     !
     ! etc..
     !
     ! So now we have multiple instances of the "objective" type,
     ! each for F, C1, C2 etc
     ! each of them can pass their dF\d_coefficents to the design
     ! and we continue from there.
     !
     ! perhaps even the "objective" type is defined as a list of objectives.
 
     ! Let's say way have a chain of two mappings
 
     ! This is still up for discussion where the mapping will eventually live.
     ! Maybe it makes more sense to keep the design as clean as possible,
     ! and then the resposibility of converting the design into coefficients
     ! used in the PDE being solved would be the responsibility of the module
     ! used for solving the PDE, ie, the simulation.
     ! Then the simulation would responsiblity for asking "do we have a scalar?"
     ! ok, let me figure out how to map this design into a coeffient in the
     ! scalar equation.
     !
     ! I guess then the mapping backwards gets confusing to me.
     ! anyway, for now, let's keep things how they are and I suppose the
     ! intention is to have different types of designs for different types of
     ! problems.
 
     type(mapping_handler_t) :: mapping
 
     class(point_zone_t), pointer :: optimization_domain
     logical :: if_mask
 
     ! TODO
     ! you also had logicals for convergence etc,
     ! I feel they should live in "problem"
 
     ! afield writer would be nice too
     type(fld_file_output_t), private :: output
 
   contains
 
     ! ----------------------------------------------------------------------- !
     ! Initializations
 
     generic, public :: init => init_from_json_sim, init_from_components
     procedure, pass(this), public :: init_from_json_sim => &
          brinkman_design_init_from_json_sim
     procedure, pass(this), public :: init_from_components => &
          brinkman_design_init_from_components
 
     procedure, pass(this) :: get_values => brinkman_design_get_design
 
     procedure, pass(this) :: get_x => brinkman_design_get_x
     procedure, pass(this) :: get_y => brinkman_design_get_y
     procedure, pass(this) :: get_z => brinkman_design_get_z
 
     procedure, pass(this) :: update_design => brinkman_design_update_design
 
     ! design_indicator -> filtering -> chi
     ! and ultimately handle mapping different coeficients!
     procedure, pass(this) :: map_forward => brinkman_design_map_forward
     ! d_design_indicator <- d_filtering <- d_chi
     ! and ultimately handle mapping different coeficients!
     procedure, pass(this) :: map_backward => brinkman_design_map_backward
     ! TODO
     ! maybe it would have been smarter to have a "coeficient" type,
     ! which is just a scalar field and set of mappings going from
     ! design_indicator -> coeficient and their corresponding chain rules
     ! maybe also some information about what equation they live in...
 
     ! a writer being called from outside would be nice
     procedure, pass(this) :: write => brinkman_design_write
 
     procedure, pass(this) :: free => brinkman_design_free
     ! TODO
     ! I'm not sure who owns the optimizer...
     ! but it would make sense to have it in here so you provide it
     ! with dF/d_design_indicator and it updates itself.
     ! procedure, pass(this) :: update => brinkman_design_update_design
  end type brinkman_design_t
 
contains
 
  subroutine brinkman_design_init_from_json_sim(this, parameters, simulation)
    class(brinkman_design_t), intent(inout) :: this
    type(json_file), intent(inout) :: parameters
    type(simulation_t), intent(inout) :: simulation
    type(json_file) :: json_subdict
    character(len=:), allocatable :: domain_name, domain_type
 
    ! Initialize the optimization domain
    if (parameters%valid_path('optimization.domain')) then
       call json_get(parameters, 'optimization.domain.type', domain_type)
       select case (trim(domain_type))
       case ('point_zone')
          this%if_mask = .true.
          call json_get(parameters, 'optimization.domain.zone_name', &
               domain_name)
          this%optimization_domain => &
               neko_point_zone_registry%get_point_zone(domain_name)
 
       case default
          call neko_error('brinkman design only supports point_zones for&
          & optimization domain types')
 
       end select
    else
       this%if_mask = .false.
    end if
 
    ! Initialize and inject into the simulation
    call this%init_from_components(simulation)
 
    ! Initialize the mapper
    associate(coef => simulation%neko_case%fluid%c_Xh, &
         gs => simulation%neko_case%fluid%gs_Xh)
      call this%mapping%init_base(coef)
      call this%mapping%add(parameters, 'optimization.design.mapping')
 
      if (parameters%valid_path(&
           'optimization.design.initial_distribution')) then
         call json_extract_object(parameters, &
              'optimization.design.initial_distribution', json_subdict)
         call set_optimization_ic(this%design_indicator, coef, gs, &
              json_subdict)
      else
         call field_rzero(this%design_indicator)
      end if
    end associate
 
    ! Map to the Brinkman amplitude
    call this%map_forward()
 
  end subroutine brinkman_design_init_from_json_sim
 
  subroutine brinkman_design_free(this)
    class(brinkman_design_t), intent(inout) :: this
 
    call this%free_base()
    call this%brinkman_amplitude%free()
    call this%design_indicator%free()
    call this%sensitivity%free()
 
  end subroutine brinkman_design_free
 
  subroutine brinkman_design_init_from_components(this, simulation)
    class(brinkman_design_t), intent(inout) :: this
    type(simulation_t), intent(inout) :: simulation
    integer :: n, i
    type(simple_brinkman_source_term_t) :: forward_brinkman, adjoint_brinkman
 
    associate(dof => simulation%neko_case%fluid%dm_Xh)
 
      call neko_field_registry%add_field(dof, "design_indicator", .true.)
      call neko_field_registry%add_field(dof, "brinkman_amplitude", .true.)
      call neko_field_registry%add_field(dof, "sensitivity", .true.)
 
    end associate
 
    this%design_indicator => &
         neko_field_registry%get_field("design_indicator")
    this%brinkman_amplitude => &
         neko_field_registry%get_field("brinkman_amplitude")
    this%sensitivity => &
         neko_field_registry%get_field("sensitivity")
 
    ! TODO
    ! this is where we steal basically everything in
    ! brinkman_source_term regarding loading initial fields
    ! for now, make it a cylinder by hand
    this%design_indicator = 0.0_rp
    this%brinkman_amplitude = 0.0_rp
    this%design_indicator%x = 0.0_rp
 
    n = this%design_indicator%dof%size()
    ! This is probably getting fixed in tim's PR anyway, otherwise I'll fix it.
    do i = 1, n
       this%design_indicator%x(i,1,1,1) = 0.0_rp
    end do
 
    ! again this will be handled better in the future...
    if (neko_bcknd_device .eq. 1) then
       call device_memcpy(this%design_indicator%x, &
            this%design_indicator%x_d, n, &
            host_to_device, sync = .false.)
    end if
 
    ! TODO
    ! Regarding masks and filters,
    ! I suppose there are two ways of thinking about it:
    ! 1) Mask first, then filter
    ! 2) filter first, then mask
    !
    ! Each one can be used to achieve different results, and when we do complex
    ! non-linear filter cascades the choice here has implications for exactly
    ! how we define "minimum size control".
    !
    ! On top of this, I've only ever used spatial convolution filters before,
    ! not PDE based filters.
    ! With these filters you need to think of how your domain is "padded" when
    ! you move the kernel over the boundary. Again, you can achieve different
    ! effects depending on the choice of padding.
    ! I don't really know if there's a similar implication for PDE based
    ! based filters, I bet there is. (We should ask Niels and Casper) I bet it
    ! means we need to consider the boundary of the mask as the boundary we
    ! enforce to be Nuemann, not the boundary of the computational domain.
    ! That sounds REALLY hard to implement...I hope it doesn't come down to
    ! that.
    !
    ! We can always change this decision later, but I'm going with (1)
    ! mask first, then filter.
    ! The reason being, one of the purposes of the filtering is to avoid sharp
    ! interfaces, if we filter first then mask there's a chance we have a sharp
    ! interface on the boundary of the optimization domain.
    ! if we mask first then filter, at least all the boundaries will be smooth.
    if (this%if_mask) then
       call mask_exterior_const(this%design_indicator, &
            this%optimization_domain, 0.0_rp)
    end if
 
    ! a field writer would be nice to output
    ! - design indicator (\rho)
    ! - mapped design (\chi)
    ! - sensitivity (dF/d\chi)
    ! TODO
    ! do this properly with JSON
    ! TODO
    ! obviously when we do the mappings properly, to many coeficients,
    ! we'll also have to modify this
    call this%output%init(sp, 'design', 3)
    call this%output%fields%assign_to_field(1, this%design_indicator)
    call this%output%fields%assign_to_field(2, this%brinkman_amplitude)
    call this%output%fields%assign_to_field(3, this%sensitivity)
 
    call this%init_base(n)
 
    ! init the simple brinkman term for the forward problem
    call forward_brinkman%init_from_components( &
         simulation%fluid%f_x, &
         simulation%fluid%f_y, &
         simulation%fluid%f_z, &
         this%brinkman_amplitude, &
         simulation%fluid%u, &
         simulation%fluid%v, &
         simulation%fluid%w, &
         simulation%fluid%c_Xh)
    ! append brinkman source term to the forward problem
    call simulation%fluid%source_term%add(forward_brinkman)
 
    ! init the simple brinkman term for the adjoint
    call adjoint_brinkman%init_from_components( &
         simulation%adjoint_fluid%f_adj_x, &
         simulation%adjoint_fluid%f_adj_y, &
         simulation%adjoint_fluid%f_adj_z, &
         this%brinkman_amplitude, &
         simulation%adjoint_fluid%u_adj, &
         simulation%adjoint_fluid%v_adj, &
         simulation%adjoint_fluid%w_adj, &
         simulation%adjoint_fluid%c_Xh)
    ! append brinkman source term based on design
 
    select type (f => simulation%adjoint_fluid)
    type is (adjoint_fluid_pnpn_t)
       call f%source_term%add(adjoint_brinkman)
    class default
    end select
 
  end subroutine brinkman_design_init_from_components
 
 
  subroutine brinkman_design_map_forward(this)
    class(brinkman_design_t), intent(inout) :: this
 
    ! TODO, see previous todo about mask first, then mapping
    if (this%if_mask) then
       call mask_exterior_const(this%design_indicator, &
            this%optimization_domain, 0.0_rp)
    end if
 
    call this%mapping%apply_forward(this%brinkman_amplitude, &
         this%design_indicator)
 
  end subroutine brinkman_design_map_forward
 
  function brinkman_design_get_design(this) result(values)
    class(brinkman_design_t), intent(in) :: this
    type(vector_t) :: values
    integer :: n
 
    n = this%size()
    call values%init(n)
    call copy(values%x, this%design_indicator%x, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(values%x_d, this%design_indicator%x_d, n)
    end if
 
  end function brinkman_design_get_design
 
  function brinkman_design_get_x(this) result(x)
    class(brinkman_design_t), intent(in) :: this
    type(vector_t) :: x
    integer :: n
 
    n = this%size()
    call x%init(n)
    call copy(x%x, this%design_indicator%dof%x, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(x%x_d, this%design_indicator%dof%x_d, n)
    end if
 
  end function brinkman_design_get_x
 
  function brinkman_design_get_y(this) result(y)
    class(brinkman_design_t), intent(in) :: this
    type(vector_t) :: y
    integer :: n
 
    n = this%size()
    call y%init(n)
    call copy(y%x, this%design_indicator%dof%y, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(y%x_d, this%design_indicator%dof%y_d, n)
    end if
 
  end function brinkman_design_get_y
 
  function brinkman_design_get_z(this) result(z)
    class(brinkman_design_t), intent(in) :: this
    type(vector_t) :: z
    integer :: n
 
    n = this%size()
    call z%init(n)
    call copy(z%x, this%design_indicator%dof%z, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(z%x_d, this%design_indicator%dof%z_d, n)
    end if
 
  end function brinkman_design_get_z
 
  subroutine brinkman_design_update_design(this, values)
    class(brinkman_design_t), intent(inout) :: this
    type(vector_t), intent(inout) :: values
    integer :: n
 
    n = this%size()
    call copy(this%design_indicator%x, values%x, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(this%design_indicator%x_d, values%x_d, n)
    end if
 
    call this%map_forward()
 
    call copy(values%x, this%design_indicator%x, n)
    if (neko_bcknd_device .eq. 1) then
       call device_copy(values%x_d, this%design_indicator%x_d, n)
    end if
 
  end subroutine brinkman_design_update_design
 
  subroutine brinkman_design_map_backward(this, sensitivity)
    class(brinkman_design_t), intent(inout) :: this
    type(vector_t), intent(in) :: sensitivity
    type(field_t), pointer :: tmp_fld
    integer :: temp_indices(1)
 
    call neko_scratch_registry%request_field(tmp_fld, temp_indices(1))
 
    call vector_to_field(tmp_fld, sensitivity)
 
    call this%mapping%apply_backward(this%sensitivity, tmp_fld)
 
    ! TODO
    ! DELETE THIS LATER
    !
    ! When Abbas writes the interface for the optimization
    ! module this may be a moot point, because we would only really collect
    ! the sensitivity of the design variables inside the mask.
    !
    ! Note for Abbas,
    ! I'm NOT doing this because I'm too lazy and I just need masks so I can
    ! test something in the passive scalar.
    if (this%if_mask) then
       call mask_exterior_const(this%sensitivity, this%optimization_domain, &
            0.0_rp)
    end if
 
    call neko_scratch_registry%relinquish_field(temp_indices)
 
  end subroutine brinkman_design_map_backward
 
  subroutine brinkman_design_write(this, idx)
    class(brinkman_design_t), intent(inout) :: this
    integer, intent(in) :: idx
 
    call this%output%sample(real(idx, kind=rp))
 
  end subroutine brinkman_design_write
 
end module brinkman_design