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R. Pompilio

Publications and source records attributed to R. Pompilio.

3 recordsLinked to original sources

Distillation and stripping pilot plants for the JUNO neutrino detector: design, operations and reliability

This paper describes the design, construction principles and operations of the distillation and stripping pilot plants tested at the Daya Bay Neutrino Laboratory, with the perspective to adapt this processes, system cleanliness and leak-tightness to the final full scale plants that will be used for the purification of the liquid scintillator used in the JUNO neutrino detector. The main goal of these plants is to remove radio impurities from the liquid scintillator while increasing its optical attenuation length. Purification of liquid scintillator will be performed with a system combining alumina oxide, distillation, water extraction and steam (or N2 gas) stripping. Such a combined system will aim at obtaining a total attenuation length greater than 20 m at 430 nm, and a bulk radiopurity for 238U and 232Th in the 10-15 to 10-17 g/g range. The pilot plants commissioning and operation have also provided valuable information on the degree of reliability of their main components, which will be particularly useful for the design of the final full scale purification equipment for the JUNO liquid scintillator. This paper describe two of the five pilot plants since the Alumina Column, Fluor mixing and the Water Extraction plants are in charge of the Chinese part of the collaboration.

physics.ins-det

GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6° x 4° area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. The inversion method allowed for integrating GOCE data with the a-priori information and regularization conditions through a Bayesian approach and a stochastic optimization. GIGJ fits the homogeneously distributed GOCE gravity data, characterized by high accuracy, with a ~1 mGal standard deviation of the residuals, compatible with the observation accuracy. Conversely to existing global models, GIGJ provides a site-specific subdivision of the crustal layers masses which uncertainties include estimation errors, associated to the gravimetric solution, and systematic uncertainties, related to the adoption of a fixed sedimentary layer. A consequence of this local rearrangement of the crustal layer thicknesses is a ~21% reduction and a ~24% increase of the middle and lower crust expected geoneutrino signal, respectively. Finally, the geophysical uncertainties of geoneutrino signals at JUNO produced by unitary uranium and thorium abundances distributed in the upper, middle and lower crust are reduced by 77%, 55% and 78%, respectively. The numerical model is available at http://www.fe.infn.it/u/radioactivity/GIGJ

physics.geo-ph

Charge reconstruction in large-area photomultipliers

Large-area PhotoMultiplier Tubes (PMT) allow to efficiently instrument Liquid Scintillator (LS) neutrino detectors, where large target masses are pivotal to compensate for neutrinos' extremely elusive nature. Depending on the detector light yield, several scintillation photons stemming from the same neutrino interaction are likely to hit a single PMT in a few tens/hundreds of nanoseconds, resulting in several photoelectrons (PEs) to pile-up at the PMT anode. In such scenario, the signal generated by each PE is entangled to the others, and an accurate PMT charge reconstruction becomes challenging. This manuscript describes an experimental method able to address the PMT charge reconstruction in the case of large PE pile-up, providing an unbiased charge estimator at the permille level up to 15 detected PEs. The method is based on a signal filtering technique (Wiener filter) which suppresses the noise due to both PMT and readout electronics, and on a Fourier-based deconvolution able to minimize the influence of signal distortions ---such as an overshoot. The analysis of simulated PMT waveforms shows that the slope of a linear regression modeling the relation between reconstructed and true charge values improves from $0.769 \pm 0.001$ (without deconvolution) to $0.989 \pm 0.001$ (with deconvolution), where unitary slope implies perfect reconstruction. A C++ implementation of the charge reconstruction algorithm is available online at http://www.fe.infn.it/CRA .

physics.ins-det