From a695a29e9d94d722f7c06a00ecdc3d9889af69df Mon Sep 17 00:00:00 2001 From: Daiane Iglesia Dolci <63597005+Ig-dolci@users.noreply.github.com> Date: Mon, 29 Jan 2024 15:47:35 +0000 Subject: [PATCH] Update docs/notebooks/burger.ipynb Co-authored-by: James R. Maddison --- docs/notebooks/burger.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/notebooks/burger.ipynb b/docs/notebooks/burger.ipynb index 91b75be..5920336 100644 --- a/docs/notebooks/burger.ipynb +++ b/docs/notebooks/burger.ipynb @@ -37,7 +37,7 @@ "## Burger's equation solver\n", "The sensitivity computation is performed by first solving the forward problem, and then using the forward solution to solve the adjoint problem. \n", "\n", - "To solve forward and adjoint solvers, we implement `BurgersEquation` class that execute the forward and adjoint solvers. In addition, the `BurgersEquation` has the `copy_data` that copies the data from one storage type to another, and `adjoint_initial_condition` that sets the adjoint initial condition.\n", + "To solve the forward and adjoint problems, we define a `BurgersEquation` class that can be used to compute the forward and adjoint solutions. In addition, the `BurgersEquation` class defines a `copy_data` method that copies the data from one storage type to another, and an `adjoint_initial_condition` method that initializes the adjoint.\n", "\n", "The forward Burger's equation is discretised using the Finite Element Method (FEM). We use continuous first-order Lagrange basis functions to discretise the spatial domain. The backward finite difference method is employed to discretise the equations in time.\n", "\n",