Star formation occurs in molecular clouds, which contain networks of filamentary structures. These networks are becoming increasingly visible due to higher resolution telescope imaging. However, the properties of these filamentary structures, as well as their role in star formation, are not yet well understood. In this project, we measure the physical properties, such as the width, length, and density of filaments within a simulated molecular cloud and determine how they correlate with star formation. Additionally, we examine how those properties change over time as stars form. We use the Computational Ridge Identification with SCMS for Python (CRISPy) package to identify density ridges within a simulated molecular cloud. In the simulation, regions of high density are converted into sink particles, which represent stars or star systems. From the ridges, we obtain filamentary spines, which we cut into segments about 0.25pc long. A profile of the filament is generated for each segment using RadFil, a package for building filament radial density profiles. We fit the profiles with Gaussian and Plummer functions, as well as a two component Gaussian function. We show that the majority of segments are best fit by a two-component function. The majority of filaments within 0.05pc of a sink particle are also best fit by a two-component function. This was consistent through multiple timesteps of the simulation, ranging over about 900,000 years. Additionally, the narrower of the two Gaussians has a width of about 0.08pc, and the wider of the two Gaussians has a width of about 0.35 pc. These results indicate that filaments have a characteristic width of ~0.1 pc, which is consistent with recent observational results.