Monte Carlo N-Particle Transport Code

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MCNP
Developer(s) LANL
Stable release
MCNP 6.1 / August 5, 2013; 3 years ago (2013-08-05)[1]
Preview release
MCNP 6.1.1beta / 24 June 2014; 2 years ago (2014-06-24)[2]
Written in Fortran 90
Operating system Cross-platform
Type Computational physics
License MCNPX Single-User Software License (proprietary)
Website mcnp.lanl.gov

Monte Carlo N-Particle Transport Code (MCNP) is a software package for simulating nuclear processes. It is developed by Los Alamos National Laboratory since at least 1957[3] with several further major improvements. It is distributed within the United States by the Radiation Safety Information Computational Center in Oak Ridge, TN and internationally by the Nuclear Energy Agency in Paris, France. It is used primarily for the simulation of nuclear processes, such as fission, but has the capability to simulate particle interactions involving neutrons, photons, and electrons among other particles. "Specific areas of application include, but are not limited to, radiation protection and dosimetry, radiation shielding, radiography, medical physics, nuclear criticality safety, detector design and analysis, nuclear oil well logging, accelerator target design, fission and fusion reactor design, decontamination and decommissioning."

Monte Carlo N-Particle eXtended[edit]

Monte Carlo N-Particle eXtended (MCNPX) was also developed at Los Alamos National Laboratory, and is capable of simulating particle interactions of 34 different types of particles (nucleons and ions) and 2000+ heavy ions at nearly all energies,[4] including those simulated by MCNP.

Both codes can be used to judge whether or not nuclear systems are critical and to determine doses from sources, among other things.

MCNP6 is a merger of MCNP5 and MCNPX.[5]

See also[edit]

Notes[edit]

  1. ^ "MCNP6.1 home Page". LANL. 5 August 2013. Archived from the original on March 30, 2012. Retrieved 7 August 2013. 
  2. ^ Tim Goorley. MCNP 6.1.1 - Beta Release Notes
  3. ^ Cashwell, E.D.; Everett, C.J. (1959). A Practical Manual on the Monte Carlo Method for Random Walk Problems (PDF). London: Pergamon Press. [dead link]
  4. ^ https://mcnpx.lanl.gov/opendocs/misc/FeaturesList.pdf
  5. ^ https://mcnp.lanl.gov

External links[edit]