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ARG-US Remote Monitoring Systems: Use Cases and Applications in Nuclear Facilities and During Transportation
As highlighted in the Spring 2024 issue of Radwaste Solutions, researchers at the Department of Energy’s Argonne National Laboratory are developing and deploying ARG-US—meaning “Watchful Guardian”—remote monitoring systems technologies to enhance the safety, security, and safeguards (3S) of packages of nuclear and other radioactive material during storage, transportation, and disposal.
S. Fan, J. Rong, H. Zhang, Z. Zhao
Nuclear Science and Engineering | Volume 144 | Number 3 | July 2003 | Pages 219-226
Technical Paper | doi.org/10.13182/NSE03-A2355
Articles are hosted by Taylor and Francis Online.
The formation cross section of the nuclide production of proton-induced reactions with intermediate energy is important for a variety of applications. For instance, the mass and charge distribution of residual products produced in the spallation reactions needs to be studied because it can provide useful information for the disposal of nuclear waste and residual radioactivity generated by the spallation neutron target system. With our current work, we have developed the Many Stage Dynamical Model (MSDM) based on the Cascade-Exciton Model (CEM). By introducing Mshnik's recent work on the CEM code, the MSDM code and the Quantum Molecular Dynamics (QMD) plus Statistical Decay Model (SDM) (QMD+SDM) and QMD plus FISSION (QMD+FISSION) models are adopted; we use them to investigate the mass distribution of Nb, Au, and Pb of proton-induced reactions with energies from 100 MeV to 3 GeV. The agreement between the developed MSDM simulations and the measured data as well as the QMD+FISSION model are good in the energy range of 100 MeV to 3 GeV, and deviations mainly show up in the mass range of 90 to 140 in the high energy of protons incident on the Au and Pb target for the MSDM and QMD+FISSION model simulations. The QMD+SDM can reproduce only part of the spallation fragments and cannot reproduce the fission fragments of the measured data.