AAA: Muon imaging is one of the most promising non-invasive techniques for density structure scanning, specially for large objects reaching the kilometre scale. It has already interesting applications in different fields like geophysics or nuclear safety and has been proposed for some others like engineering or archaeology. One of the approaches of this technique is based on the well-known radiography principle, by reconstructing the incident direction of the detected muons after crossing the studied objects. In this case, muons detected after a previous forward scattering on the object surface represent an irreducible background noise, leading to a bias on the measurement and consequently on the reconstruction of the object mean density. Therefore, a prior characterization of this effect represents valuable information to conveniently correct the obtained results. Although the muon scattering process has been already theoretically described, a general study of this process has been carried out based on Monte Carlo simulations, resulting in a versatile tool to evaluate this effect for different object geometries and compositions. As an example, these simulations have been used to evaluate the impact of forward scattered muons on two different applications of muon imaging: archaeology and volcanology, revealing a significant impact on the latter case. The general way in which all the tools used have been developed can allow to make equivalent studies in the future for other muon imaging applications following the same procedure. KKKK: Models and simulations, Simulations methods and programs AAXXX PPPPP: 1709.05106

The short time Fourier transform (STFT) and continuous wavelet transform (CWT) cannot resolve slowly varying velocity at low velocity stage in most photonic Doppler velocimetry (PDV) data. A new analysis method based on Fourier transform is presented to overcome this shortcoming. Instead of extracting the frequency of interference signal for velocity analysis, the new method uses a modified Fourier transform to analysis the phase of signal, and converts phase to displacement or velocity. The validity of the proposed method is examined in experimental data of a plate-impact experiment, which distinguishes the elastic-plastic properties of Fe sample. The method not only uses all sampling points of the raw data, but also has a higher velocity resolutions especially for low velocity stage. The method is a supplement to STFT and CWT method.

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