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Title: Preliminary results coupling “Stochastic Mean Field” and “Boltzmann-Langevin One Body” models with Geant4

Abstract

Monte Carlo (MC) simulations are widely used for medical applications and nuclear reaction models are fundamental for the simulation of the particle interactions with patients in ion therapy. Therefore, it is of utmost importance to have reliable models in MC simulations for such interactions. Geant4 is one of the most used toolkits for MC simulation. However, its models showed severe limitations in reproducing the yields measured in the interaction of ion beams below 100 MeV/u with thin targets. For this reason, we interfaced two models, SMF (“Stochastic Mean Field”) and BLOB (“Boltzmann-Langevin One Body”), dedicated to simulate such reactions, with Geant4.

Authors:
 [1];  [2];  [3];  [4];  [2];  [1];  [5];  [4];  [2];  [4]
+ Show Author Affiliations
  1. Sapienza Univ. of Rome (Italy); National Inst. of Nuclear Physics (INFN), Rome (Italy)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  3. National Center for Radiation Protection and Computational Physics, Istituto Superiore di Sanit (Italy)
  4. National Inst. of Nuclear Physics (INFN), Catania (Italy)
  5. Univ. Paris-Saclay, Gif-sur-Yvette (France)
Publication Date:
Research Org.:
SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1598425
Grant/Contract Number:  
AC02-76SF00515
Resource Type:
Accepted Manuscript
Journal Name:
Physica Medica
Additional Journal Information:
Journal Volume: 67; Journal Issue: C; Journal ID: ISSN 1120-1797
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; Monte Carlo simulation; Nuclear reaction; Ion therapy; Hadron-therapy

Citation Formats

Mancini-Terracciano, C., Asai, M., Caccia, B., Cirrone, G.A.P., Dotti, A., Faccini, R., Napolitani, P., Pandola, L., Wright, D.H., and Colonna, M. Preliminary results coupling “Stochastic Mean Field” and “Boltzmann-Langevin One Body” models with Geant4. United States: N. p., 2019. Web. doi:10.1016/j.ejmp.2019.10.026.
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Mancini-Terracciano, C., Asai, M., Caccia, B., Cirrone, G.A.P., Dotti, A., Faccini, R., Napolitani, P., Pandola, L., Wright, D.H., & Colonna, M. Preliminary results coupling “Stochastic Mean Field” and “Boltzmann-Langevin One Body” models with Geant4. United States. https://doi.org/10.1016/j.ejmp.2019.10.026
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Mancini-Terracciano, C., Asai, M., Caccia, B., Cirrone, G.A.P., Dotti, A., Faccini, R., Napolitani, P., Pandola, L., Wright, D.H., and Colonna, M. Fri . "Preliminary results coupling “Stochastic Mean Field” and “Boltzmann-Langevin One Body” models with Geant4". United States. https://doi.org/10.1016/j.ejmp.2019.10.026. https://www.osti.gov/servlets/purl/1598425.
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@article{osti_1598425,
title = {Preliminary results coupling “Stochastic Mean Field” and “Boltzmann-Langevin One Body” models with Geant4},
author = {Mancini-Terracciano, C. and Asai, M. and Caccia, B. and Cirrone, G.A.P. and Dotti, A. and Faccini, R. and Napolitani, P. and Pandola, L. and Wright, D.H. and Colonna, M.},
abstractNote = {Monte Carlo (MC) simulations are widely used for medical applications and nuclear reaction models are fundamental for the simulation of the particle interactions with patients in ion therapy. Therefore, it is of utmost importance to have reliable models in MC simulations for such interactions. Geant4 is one of the most used toolkits for MC simulation. However, its models showed severe limitations in reproducing the yields measured in the interaction of ion beams below 100 MeV/u with thin targets. For this reason, we interfaced two models, SMF (“Stochastic Mean Field”) and BLOB (“Boltzmann-Langevin One Body”), dedicated to simulate such reactions, with Geant4.},
doi = {10.1016/j.ejmp.2019.10.026},
journal = {Physica Medica},
number = C,
volume = 67,
place = {United States},
year = {Fri Nov 01 00:00:00 EDT 2019},
month = {Fri Nov 01 00:00:00 EDT 2019}
}
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Publisher's Version of Record
https://doi.org/10.1016/j.ejmp.2019.10.026
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