Physical simulations are widely used to recreate the motions of everyday objects, and elastic rods---long and thin deformable bodies---are an important computer animation primitive. In computer graphics, many simulation models have been developed to produce plausible animations, but many of these methods can also accomplish tasks beyond creating visualizations. This thesis demonstrates how simulation methods for animation of slender rods can be used in other applications. First, we describe physically based methods for simultaneous generation of animation and sound for deformable rods. We introduce an efficient acoustic radiation method based on dipoles, and show how to tie it to common elastic rod simulation frameworks. We present several examples of our results, including challenging scenes involving thousands of highly coupled frictional contacts. We then show how elastic rods can improve yarn geometry synthesis techniques. Prior work can generate virtual fiber curves for specific types of yarn, but does not account for how these curves deform as yarns collide. We introduce macro-fibers, elastic rods that represent groups of fibers in a yarn. We split existing yarn curves into macro-fibers and run a short relaxation simulation to allow them to rearrange locally. We show how the resulting curves can be used to predict yarn deformation in the context of knitted fabrics. By following the paths of the macro-fibers, we can generate fiber assemblies for rendering that more closely resemble the structure of actual cloth than prior work. Finally, we propose a method for tracking yarn paths through computed tomography (CT) scans of real fabrics. Existing methods are either designed for low-curvature yarn configurations, tend to fail around yarn crossings, or rely on identifying individual fibers within a pattern. Our algorithm finds ridges---chains of high-density voxels that approximate fibers---to guide centerline placement without explicitly identifying fibers, and is robust to arbitrary yarn arrangements. By reconstructing the yarn paths within these volumetric scans, we are more prepared to quantitatively validate and calibrate yarn-level cloth simulations.