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Correct derivatives in Burgers equation (#389)

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* Correct derivatives in Burgers equation
This commit is contained in:
HGangloff
2024-12-09 13:13:07 +01:00
committed by GitHub
parent 5e36d1b618
commit 59c9a173b4
3 changed files with 5 additions and 5 deletions
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4
docs/source/_rst/tutorials/tutorial12/tutorial.rst
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@@ -132,8 +132,8 @@ parameter :math:`\nu`:
self.nu = nu
def equation(input_, output_):
return grad(output_, input_, d='x') +\
output_*grad(output_, input_, d='t') -\
return grad(output_, input_, d='t') +\
output_*grad(output_, input_, d='x') -\
self.nu*laplacian(output_, input_, d='x')

4
tutorials/tutorial12/tutorial.ipynb vendored
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@@ -161,8 +161,8 @@
" self.nu = nu \n",
" \n",
" def equation(input_, output_):\n",
" return grad(output_, input_, d='x') +\\\n",
" output_*grad(output_, input_, d='t') -\\\n",
" return grad(output_, input_, d='t') +\\\n",
" output_*grad(output_, input_, d='x') -\\\n",
" self.nu*laplacian(output_, input_, d='x')\n",
"\n",
" \n",

2
tutorials/tutorial12/tutorial.py vendored
View File

@@ -113,7 +113,7 @@ class Burgers1DEquation(Equation):
self.nu = nu
def equation(input_, output_):
return grad(output_, input_, d='x') + output_*grad(output_, input_, d='t') - self.nu*laplacian(output_, input_, d='x')
return grad(output_, input_, d='t') + output_*grad(output_, input_, d='x') - self.nu*laplacian(output_, input_, d='x')
super().__init__(equation)