Open-source BOS tomography dataset of high-speed flow over a flight body

We present an open-source background-oriented schlieren dataset with 70 views of high-speed flow over a flight body. Sample analyses are performed using a neural implicit reconstruction technique (NIRT) with total variation regularization as well as data assimilation via the 3D compressible Euler equations. Limited data reconstructions based on nine views resolve sharp shocks that are consistent with the geometry, reproduce validation deflections with high fidelity, and exhibit minimal artifacts. Data assimilation recovers unmeasured fields, marking the first demonstration of 3D state estimation directly from experimental schlieren measurements. The NIRT also enables efficient uncertainty quantification, providing insight into well-resolved flow features and guiding design-of-experiments efforts. Public access to the data and code repositories is detailed at the end of this correspondence. Journal instruction requires a city and country for affiliations; however, these are missing in affiliation [1-3]. Please verify if the provided city and country are correct and amend if necessary. Department of Mechanical Engineering, Pennsylvania State University, University Park, USAAerospace Systems Directorate, Air Force Research Laboratory, Arnold Air Force Base, USA.Huntsville, USA.