An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel

In this paper, we investigate two experimental datasets of laminar hypersonic flows, in vibrational and reactive non-equilibrium, over a double-cone geometry, acquired in CUBRC's LENS-XX expansion tunnel. These datasets have yet to be modeled accurately. A previous paper suggested that this could partly be due to mis-specified inlet conditions. The authors of this paper solved a Bayesian inverse problem to infer the inlet conditions of the LENS-XX test-section and found that in one case they lay outside the uncertainty bounds specified in the experimental dataset. However, the inference was performed using approximate surrogate models. In this paper, we revisit the experimental datasets and perform inversions for the tunnel test-section inlet conditions with a Navier-Stokes simulator. The inversion is deterministic and provides uncertainty bounds on the inlet conditions under a Gaussian assumption. We find that deterministic inversion yields inlet conditions that are at variance with what was stated in the experiments. We also assess the usefulness of the uncertainty bounds provided by the Gaussian approximation of the true posterior distribution, and find it marginally useful for the inter-quartile range. We also present an \emph{a posteriori} method to check the validity of the Gaussian assumption for the posterior distribution. This paper contributes to ongoing work on the assessment of datasets from challenging experiments conducted in extreme environments, where the experimental apparatus is pushed to the margins of its design and performance envelopes.