A new method for identifying people by their odor is proposed. In this approach, subjects are characterized by a GC × GC-MS chromatogram of a sample of their hand odor. The method is based on the definition of a distance between odor chromatograms and the application of Bayesian hypothesis testing. Using a calibration panel of subjects for whom several odor chromatograms are available, the densities of the distance between chromatograms of the same person, and between chromatograms of different persons are estimated. Given the distance between a reference and a query chromatogram, the Bayesian framework provides an estimate of the probability that the corresponding two odor samples come from the same person. We tested the method on a panel that is fully independent from the calibration panel, with promising results for forensic applications.

Sensitivity of sonic boom propagation throughout a turbulent atmosphere is investigated. Three types of boom of same amplitude but different initial shapes: an ideal N-wave, a measured boom (NASA data for F-18) and a “low” boom (C25D mock-up) with increased rise time are studied. The atmosphere is supposed to be a quiescent and isothermal medium with a superposed synthetic velocity field with homogeneous and isotropic statistical properties satisfying a von Kármán energy spectrum. Using the “random field generation method,” the flow velocity turbulent field is governed by three independent parameters: a random matrix, an intensity parameter and a scale parameter (turbulence integral scale). The flow velocity is then used as a base flow for a in-house software called FLHOWARD designed to compute the propagation of acoustic shock waves in heterogeneous media. In order to reduce the number of simulations compared to a Monte-Carlo approach, the study is performed within the generalized chaos polynomial (gPC) framework. Various convergence tests have been performed to define the optimal discretization and gPC order. Stochastic evolution of selected metrics along a 1 km distance are investigated.

The propagation of sonic boom through kinematic turbulence is known to have an important impact on the noise perceived at the ground. In this work, a recent numerical method called FLHOWARD3D based on a one-way approach is used to simulate the propagation of classical and low-boom waveforms. Kinematic turbulence is synthesized following a von Kármán energy spectrum. Two- and three-dimensional (2D and 3D) simulations are compared to experimental measurements, and 2D simulations are found to be slightly less accurate than 3D ones but still consistent with experimental levels around 98% of the time. A stochastic study is carried out on the 2D simulation using the generalized polynomial chaos method with parameters of the von Kármán spectrum as uncertain parameters. Differences between the propagation of a classical N-wave and low booms are observed: the classical N-wave shows higher peak pressure and variations than low-boom signatures. The standard deviation for the peak pressure, the D-weighted sound exposure level (D-SEL), and the perceived level in dB (PLdB) metrics all show a linear increase with the distance, with a faster increase for the classical N-wave for the peak pressure and D-SEL and a similar increase between the different booms for PLdB. In general, it is found that low-boom waveforms show less sensitivity to turbulence.