Qingxian Zhang

Frequency spectrum analysis for spectrum stabilization in airborne gamma-ray spectrometer.

Abnormal multi-crystal spectral drifts often can be observed when power on the airborne gamma-ray spectrometer. Currently, these spectral drifts of each crystal are generally eliminated through manual adjustment, which is time-consuming and labor-ineffective. To realize this quick automatic spectrum stabilization of multi-crystal, a frequency spectrum analysis method for natural gamma-ray background spectrum is put forward in this paper to replace traditional spectrum stabilization method used characteristic peak. Based on the polynomial fitting of high harmonics in frequency spectrum and gamma-ray spectral drift, it calculates overall spectral drift of natural gamma-ray spectrum and adjusts the gain of spectrometer by this spectral drift value, thus completing quick spectrum stabilization in the power on stage of spectrometer. This method requires no manual intervention and can obtain the overall spectral drift value automatically under no time-domain pre-processing to the natural gamma-ray spectra. The spectral drift value calculated by this method has an absolute error less than five channels (1024 resolution) and a relative error smaller than 0.80%, which can satisfy the quick automatic spectrum stabilization requirement when power on the airborne gamma-ray spectrometer instead of manual operation.

Mapping of the lunar surface by average atomic number based on positron annihilation radiation from Chang’e‐1

A map of the average atomic number of lunar rock and soil can be used to differentiate lithology and soil type on the lunar surface. This paper establishes a linear relationship between the average atomic number of lunar rock or soil and the flux of position annihilation radiation (0.512‐MeV gamma‐ray) from the lunar surface. The relationship is confirmed by Monte Carlo simulation with data from lunar rock or soil samples collected by Luna (Russia) and Apollo (USA) missions. A map of the average atomic number of the lunar rock and soil on the lunar surface has been derived from the Gamma‐Ray Spectrometer data collected by Chang’e‐1, an unmanned Chinese lunar‐orbiting spacecraft. In the map, the higher average atomic numbers (ZA > 12.5), which are related to different types of basalt, are in the maria region; the highest ZA (13.2) readings are associated with Sinus Aestuum. The middle ZA (~12.1) regions, in the shape of irregular oval rings, are in West Oceanus Procellarum and Mare Frigoris, which seems to be consistent with the distribution of potassium, rare earth elements, and phosphorus as a unique feature on the lunar surface. The lower average atomic numbers (ZA < 11.5) are found to be correlated with the anorthosite on the far side of the Moon.

A hybrid method on sourceless sensitivity calculation for airborne gamma-ray spectrometer

The sensitivity calculation of airborne gamma-ray spectrometer (AGS) is usually performed by on-ground or in-flight calibration. However, both methods are cost-ineffective or not permissive, especially for artificial radioisotopes with short half-lives. Alternative to these methods is the Monte Carlo simulation, which has been widely applied over the last few decades. The greatest challenge to the practicability of the Monte Carlo simulation in the AGS calibration is its low computational efficiency for ensuring an acceptable reliability. This article proposes a hybrid numerical method for the sourceless AGS calibration by combining the deterministic point-kernel approach and the Monte Carlo simulation. This method is not only more efficient than the source-based calibration by an empirical method, but also independent of the source availability for on-ground or in-flight calibration. For a given soil test model, AGS sensitivities calculated by this hybrid method agree well with those obtained from the empirical method for the in-flight calibration.