From 2b8d7b7918f63c9ed550c9ec781c659e9fa9846d Mon Sep 17 00:00:00 2001 From: Niklas Heim Date: Wed, 27 Aug 2025 13:30:44 +0200 Subject: [PATCH] fix broken link in docs --- examples/fem-shapeopt/demo.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/fem-shapeopt/demo.ipynb b/examples/fem-shapeopt/demo.ipynb index 2b8b47d..617ccab 100644 --- a/examples/fem-shapeopt/demo.ipynb +++ b/examples/fem-shapeopt/demo.ipynb @@ -21,7 +21,7 @@ "\n", "## Introduction\n", "\n", - "In this notebook, we explore the optimization of a parametric structure made of a linear elastic material. The structure is parametrized by N bars, each of which has M piecewise linear segments. We seek the ideal configuration of the $y$-coordinates of the vertices that connect those bar segments. This notebook is based on the [2D topology optimization example](https://github.com/deepmodeling/jax-fem/tree/main/demos/topology_optimization) from `jax-fem`, but we solve the problem using a parametric approach instead.\n", + "In this notebook, we explore the optimization of a parametric structure made of a linear elastic material. The structure is parametrized by N bars, each of which has M piecewise linear segments. We seek the ideal configuration of the $y$-coordinates of the vertices that connect those bar segments. This notebook is based on the [2D topology optimization example](https://github.com/deepmodeling/jax-fem/blob/main/docs/source/learn/topology_optimization.ipynb) from `jax-fem`, but we solve the problem using a parametric approach instead.\n", "\n", "**That is, we use end-to-end automatic differentiation (AD) through several components to optimize the design variables directly with respect to (simulated) performance of the design.**\n", "\n",