GradientVector

Gradient of the coupled tensor buffer returned as a stacked torch tensor.

GradientVector computes the spatial gradient of a scalar buffer and returns a torch tensor with components $var element = document.getElementById("moose-equation-068b1a9b-3e3c-442c-9aa8-e6635910d3b3");katex.render("(\\partial_x u, \\partial_y u, \\partial_z u)", element, {displayMode:false,throwOnError:false});$ stacked along the trailing dimension. When "input_is_reciprocal" = true, the input is treated as already in reciprocal space.

Overview

The gradient is computed spectrally using FFTs as

$var element = document.getElementById("moose-equation-2b485274-42fb-4f64-bcde-ed9ca23e9246");katex.render("\\nabla u = \\mathcal{F}^{-1}\\{ i \\, \\mathbf{k} \\, \\mathcal{F}\\{u\\}\\}.", element, {displayMode:true,throwOnError:false});$

In 2D/1D, the unused components are zero.

Example Input File Syntax

[TensorComputes<<<{"href": "../../syntax/TensorComputes/index.html"}>>>]
  [Initialize<<<{"href": "../../syntax/TensorComputes/Initialize/index.html"}>>>]
    [grad_c]
      type = GradientVector<<<{"description": "Gradient of the coupled tensor buffer returned as a stacked torch tensor.", "href": "GradientVector.html"}>>>
      buffer<<<{"description": "The buffer this compute is writing to"}>>> = grad_c
      input<<<{"description": "Input buffer name"}>>> = c
    []
  []
[]

Input Parameters

bufferThe buffer this compute is writing to
C++ Type:std::string
Controllable:No
Description:The buffer this compute is writing to
inputInput buffer name
C++ Type:std::string
Controllable:No
Description:Input buffer name

Required Parameters

input_is_reciprocalFalseInput buffer is already in reciprocal space
Default:False
C++ Type:bool
Controllable:No
Description:Input buffer is already in reciprocal space

Optional Parameters

control_tagsAdds user-defined labels for accessing object parameters via control logic.
C++ Type:std::vector<std::string>
Controllable:No
Description:Adds user-defined labels for accessing object parameters via control logic.
enableTrueSet the enabled status of the MooseObject.
Default:True
C++ Type:bool
Controllable:No
Description:Set the enabled status of the MooseObject.

Advanced Parameters

Input Files

(test/tests/typed_tensors/gradient_vector.i)

(test/tests/typed_tensors/gradient_vector.i)

[Domain]
  dim = 3
  nx = 20
  ny = 10
  nz = 5
  mesh_mode = DUMMY
  device_names = cpu
[]

[TensorComputes]
  [Initialize]
    [c]
      type = ParsedCompute
      buffer = c
      extra_symbols = true
      expression = 'sin(x*8*pi)+cos(y*4*pi)+sin(z*2*pi)'
    []
    [grad_c]
      type = GradientVector
      buffer = grad_c
      input = c
    []
  []
[]

[Problem]
  type = TensorProblem
  print_debug_output = true
[]

[Executioner]
  type = Transient
  num_steps = 1
[]

[TensorOutputs]
  [xdmf]
    type = XDMFTensorOutput
    buffer = 'c grad_c'
    file_base = gradient
    output_mode = 'NODE NODE'
    enable_hdf5 = true
  []
[]

(test/tests/typed_tensors/gradient_vector.i)

[Domain]
  dim = 3
  nx = 20
  ny = 10
  nz = 5
  mesh_mode = DUMMY
  device_names = cpu
[]

[TensorComputes]
  [Initialize]
    [c]
      type = ParsedCompute
      buffer = c
      extra_symbols = true
      expression = 'sin(x*8*pi)+cos(y*4*pi)+sin(z*2*pi)'
    []
    [grad_c]
      type = GradientVector
      buffer = grad_c
      input = c
    []
  []
[]

[Problem]
  type = TensorProblem
  print_debug_output = true
[]

[Executioner]
  type = Transient
  num_steps = 1
[]

[TensorOutputs]
  [xdmf]
    type = XDMFTensorOutput
    buffer = 'c grad_c'
    file_base = gradient
    output_mode = 'NODE NODE'
    enable_hdf5 = true
  []
[]

Overview
Example Input File Syntax
Input Parameters
Input Files