Characterization And Optimization Of A Tensioned Metastable Fluid Nuclear Particle Sensor Using Laser Based Profilimetry

PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON NUCLEAR ENGINEERING - 2014, VOL 5(2014)

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摘要
State of the art neutron detectors lack capabilities required by the fields of homeland security, health physics, and even for direct in-core nuclear power monitoring. A new system being developed at Purdue's Metastable Fluid and Advanced Research Laboratory in conjunction with S/A Labs, LLC provides capabilities the state of the art lacks, and simultaneously with beta (beta) and gamma (gamma) blindness, high (> 90% intrinsic) efficiency(1) for neutron/alpha spectroscopy and directionality, simple detection mechanism, and lowered electronic component dependence. This system, the Tensioned Metastable Fluid Detector (TMFD) [3], provides these capabilities despite its vastly reduced cost and complexity compared with equivalent present day systems. Fluids may be placed at pressures lower than perfect vacuum (i.e. negative) [4, 5], resulting in tensioned metastable states. These states may be induced by tensioning fluids just as one would tension solids. The TMED works by cavitation nucleation of bubbles resulting from energy deposited by charged ions or laser photon pileup heating of fluid molecules which are placed under sufficiently tensioned (negative) pressure states of metastability. The charged ions may be created from neutron scattering, or from energetic charged particles such as alphas, alpha recoils, fission fragments, etc. A methodology has been created to profile the pressures in these chambers by lasing, called Laser Induced Cavitation (LIC), for verification of a multiphysics simulation of the chambers. The methodology and simulation together have lead to large efficiency gains in the current Acoustically Tensioned Metastable Fluid Detector (ATMFD) system. This paper describes in detail the LIC methodology and provides background on the simulation it validates.
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关键词
Metastable Fluids, Neutron Detection
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