Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02

References

• Sato T. Niita K, Matsuda N, et al. Particle and Heavy Ion Transport code System, PHITS, version 2.52. J Nucl Sci Technol. 2013;50:913–923.
   Web of Science ®Google Scholar
• Iwamoto Y, Sato T, Hashimoto S, et al. Benchmark study of the recent version of the PHITS code. J Nucl Sci Technol. 2017;54:617–635.
   Web of Science ®Google Scholar
• Furuta T, Ishikawa KL, Fukunishi N, et al. Implementation of OpenMP and MPI hybrid parallelization to Monte Carlo dose simulation for particle therapy. IFMBE Proc. 2012;39:2099–2102.
   Google Scholar
• Kai T, Maekawa F, Kosako K, et al. DCHAIN-SP 2001: high energy particle induced radioactivity calculation code. Tokai, Japan: Japan Atomic Energy Research Institute; 2001. ( JAERI-Data/Code 2001-016). [ in Japanese]
   Google Scholar
• X-5 Monte Carlo Team. MCNP - a general N-particle transport code, verion 5, volume I: overview and theory. Los Alamos, USA: Los Alamos National Laboratory; 2003. ( LA-UR-03-1987).
   Google Scholar
• Theis C, Buchegger KH, Brugger M, et al. Interactive three-dimensional visualization and creation of geometries for Monte Carlo calculations. Nucl Instrum Meth A. 2006;562:827–829.
   Web of Science ®Google Scholar
• Furuta T, Sato T, Han MC, et al. Implementation of tetrahedral-mesh geometry in Monte Carlo radiation transport code PHITS. Phys Med Biol. 2017;62:4798–4810.
   PubMed Web of Science ®Google Scholar
• Wu YC, Song J, Zheng HQ, et al. CAD-based Monte Carlo program for integrated simulation of nuclear system SuperMC. Ann Nucl Energy. 2015;82:161–168.
   Web of Science ®Google Scholar
• Sato T, Niita K, Matsuda N, et al. Overview of particle and heavy ion transport code system PHITS. Ann Nucl Energy. 2015;82:110–115.
   Web of Science ®Google Scholar
• Sato T, Niita K, Iwamoto Y, et al. Recent improvements of particle and heavy ion transport code system: PHITS. EPJ Web Conf. 2017;153:06008.
   Google Scholar
• Hirayama H, Namito Y, Bielajew AF, et al. The EGS5 code system. Menlo Park, USA and Tsukuba, Japan: SLAC National Accelerator Laboratory and High Energy Accelerator Research Organization; 2005. ( SLAC-R-730 and KEK Report 2005-8).
   Google Scholar
• Nara Y, Otuka H, Ohnishi A, et al. Relativistic nuclear collisions at 10A GeV energies from p+Be to Au+Au with the hadronic cascade model. Phys Rev C. 2000;61:024901.
   Web of Science ®Google Scholar
• Niita K, Chiba S, Maruyama T, et al. Analysis of the (N,xN') reactions by quantum molecular-dynamics plus statistical decay model. Phys Rev C. 1995;52:2620–2635.
   PubMed Web of Science ®Google Scholar
• Ogawa T, Sato T, Hashimoto S, et al. Energy-dependent fragmentation cross sections of relativistic C-12. Phys Rev C. 2015;92: 024614.
   Web of Science ®Google Scholar
• Ogawa T, Hashimoto S, Sato T. Development of general nuclear resonance fluorescence model. J Nucl Sci Technol. 2016;53:1766–1773.
   Web of Science ®Google Scholar
• Noda S, Hashimoto S, Sato T, et al. Improvement of photonuclear reaction model below 140 MeV in the PHITS code. J Nucl Sci Technol. 2015;52:57–62.
   Web of Science ®Google Scholar
• Abe S, Sato T. Implementation of muon interaction models in PHITS. J Nucl Sci Technol. 2016;54:101–110.
   Web of Science ®Google Scholar
• Ogawa T, Sato T, Hashimoto S, et al. Development of a reaction ejectile sampling algorithm to recover kinematic correlations from inclusive cross-section data in Monte-Carlo particle transport simulations. Nucl Instrum Meth A. 2014;763:575–590.
   Web of Science ®Google Scholar
• Abe S, Sato T. Soft error rate analysis based on multiple sensitive volume model using PHITS. J Nucl Sci Technol. 2016;53:451–458.
   Web of Science ®Google Scholar
• Furihata S. Statistical analysis of light fragment production from medium energy proton-induced reactions. Nucl Instrum Meth B. 2000;171:251–258.
   Web of Science ®Google Scholar
• Ogawa T, Hashimoto S, Sato T, et al. Development of gamma de-excitation model for prediction of prompt gamma-rays and isomer production based on energy-dependent level structure treatment. Nucl Instrum Meth B. 2014;325:35–42.
   Web of Science ®Google Scholar
• Taya T, Kataoka J, Kishimoto A, et al. Optimization and verification of image reconstruction for a Compton camera towards application as an on-line monitor for particle therapy. J Instrum. 2017;12:P07015.
   Web of Science ®Google Scholar
• Shibata K, Iwamoto O, Nakagawa T, et al. JENDL-4.0: a new library for nuclear science and engineering. J Nucl Sci Technol. 2011;48:1–30.
   Web of Science ®Google Scholar
• Sihver L, Kohama A, Iida K, et al. Current status of the “Hybrid Kurotama model” for total reaction cross sections. Nucl Instrum Meth B. 2014;334:34–39.
   Web of Science ®Google Scholar
• Sato T, Kataoka R, Yasuda H, et al. Air shower simulation for WASAVIES: warning system for aviation exposure to solar energetic particles. Radiat Prot Dosim. 2014;161:274–278.
   PubMed Web of Science ®Google Scholar
• Minomo K, Washiyama K, Ogata K. Deuteron-nucleus total reaction cross sections up to 1 GeV. J Nucl Sci Technol. 2017;54:127–130.
   Web of Science ®Google Scholar
• Boudard A, Cugnon J, David JC, et al. New potentialities of the Liege intranuclear cascade model for reactions induced by nucleons and light charged particles. Phys Rev C. 2013;87:014606.
   Web of Science ®Google Scholar
• Hashimoto S, Iwamoto Y, Sato T, et al. New approach to description of (d,xn) spectra at energies below 50 MeV in Monte Carlo simulation by intra nuclear cascade code with Distorted Wave Born Approximation. Nucl Instrum Meth B. 2014;333:27–41.
   Web of Science ®Google Scholar
• Shiiba T, Kuga N, Kuroiwa Y, et al. Evaluation of the accuracy of mono-energetic electron and beta-emitting isotope dose-point kernels using particle and heavy ion transport code system: PHITS. Appl Radiat Isot. 2017;128:199–203.
   PubMed Web of Science ®Google Scholar
• Cullen DE, Hubbell JH, Kissel LD. EPDL97: the evaluated photon data library, '97 version. UCRL-50400, 6, Rev. 5. Livermore, USA: Lawrence Livermore National Laboratory; 1997.
   Google Scholar
• Kai T, Yokoya A, Ukai M, et al. Thermal equilibrium and prehydration processes of electrons injected into liquid water calculated by dynamic Monte Carlo method. Radiat Phys Chem. 2015;115:1–5.
   Web of Science ®Google Scholar
• Nikjoo H, Emfietzoglou D, Liamsuwan T, et al. Radiation track, DNA damage and response-a review. Rep Prog Phys. 2016;79:116601.
   PubMed Web of Science ®Google Scholar
• Kai T, Yokoya A, Ukai M, et al. Cross sections, stopping powers, and energy loss rates for rotational and phonon excitation processes in liquid water by electron impact. Radiat Phys Chem. 2015;108:13–17.
   Web of Science ®Google Scholar
• Geissel H, Scheidenberger C, Malzacher P, et al. ATIMA. Darmstadt, Germany: GSI. Available from: http://web-docs.gsi.de/∼weick/atima/ accessed on Sep. 15, 2017.
   Google Scholar
• Yang ZY, Tsai PE, Lee SC, et al. Inter-comparison of dose distributions calculated by FLUKA, GEANT4, MCNP, and PHITS for proton therapy. EPJ Web Conf. 2017;153:04011.
   Google Scholar
• Butts JJ, Katz R. Theory of RBE for heavy ion bombardment of dry enzymes and viruses. Radiat Res. 1967;30:855–871.
   PubMed Web of Science ®Google Scholar
• PHITS website. Tokai, Japan: JAEA. Available from: http://phits.jaea.go.jp/ accessed on Sep. 15, 2017.
   Google Scholar
• Ayachit U. The paraview guide: a parallel visualization application. Clifton Park, USA: Kitware; 2015.
   Google Scholar
• International Commission on Radiological Protection. Adult reference computational phantoms, ICRP Publication 110. Ann. ICRP. 2009;39(2).
   Google Scholar
• Sato T, Kase Y, Watanabe R, et al. Biological dose estimation for charged-particle therapy using an improved PHITS code coupled with a microdosimetric kinetic model. Radiat Res. 2009;171:107–117.
   PubMed Web of Science ®Google Scholar
• Endo A, Yamaguchi Y, Eckerman KF. Nuclear decay data for dosimetry calculations – revised data of ICRP publication 38. Tokai, Japan: Japan Atomic Energy Research Institute; 2005. ( JAERI 1347).
   Google Scholar
• International Commission on Radiological Protection. Nuclear decay data for dosimetric calculations, ICRP publication 107. Ann. ICRP. 2008; 38(3).
   Google Scholar
• Verbeke JM, Hagmann C, Wright D. Simulation of neutron and gamma ray emission from fission and photofission. Livermore, USA: Lawrence Livermore National Laboratory; 2014. ( UCRL-AR-228518).
   Google Scholar
• Phase-space database for external beam radiotherapy. Vienna, Austria: IAEA. Available from: https://www-nds.iaea.org/phsp/ accessed on Sep. 15, 2017.
   Google Scholar
• Endo A, Sato T. Analysis of linear energy transfers and quality factors of charged particles produced by spontaneous fission neutrons from Cf-252 and Pu-244 in the human body. Radiat Prot Dosim. 2013;154:142–147.
   PubMed Web of Science ®Google Scholar
• Schneider W, Bortfeld T, Schlegel W. Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. Phys Med Biol. 2000;45:459–478.
   PubMed Web of Science ®Google Scholar
• Panchal A. Extensible radiation therapy research platform & viewer for DICOM & DICOM RT. dicompyler. Available from: http://www.dicompyler.com/ accessed on Sep. 15, 2017.
   Google Scholar
• Yeom YS, Jeong JH, Han MC, et al. Tetrahedral-mesh-based computational human phantom for fast Monte Carlo dose calculations. Phys Med Biol. 2014;59:3173–3185.
   PubMed Web of Science ®Google Scholar