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Monte Carlo Modeling and Simulation

Monte Carlo M&S is the one which uses a model built based on statistical random sampling. The model typically does not represent time-varying relationships. Monte Carlo M&S is commonly used in disciplines such as Chemistry, Computational Engineering, Financial Probabilistic Modeling, Mathematics, Nuclear Engineering, (Computational, Nuclear, Statistical) Physics, and Reliability Engineering.

Gas Cloud Simulation

A simulation of how a gas cloud that has been observed approaching the supermassive black hole at the centre of the galaxy.

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Advanced Test Reactor Simulation

Advanced simulation capabilities can model reactors, such as INL's Advanced Test Reactor shown here, from atomic scales to full-sized reactor assemblies.

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Underwater EVA Simulation

Underwater simulation of extravehicular activity (EVA).

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Combat Simulation

A screen capture depicts a combat situation in a digital world during a command post exercise inside the Joint Multinational Simulations Center.

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Motorcycle Simulator

Testing motorcycle simulator at the Pentagon to get a feel for how the bike would handle some situations.

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Wake Turbulence Simulation

Wake turbulence simulation for an Airbus A340 on final approach, just before touchdown.

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Driving Conditions Simulator

View from the cockpit of the simulator. Multiple screens provide a view similar to what one would see in a snowplow on the road.

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Molecules Simulation

Dynamic computer simulations of molecular systems.

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Global Aerosols Simulation

This portrait of global aerosols was produced by a Goddard Earth Observing System Model, Version 5 (GEOS-5) simulation at a 10-kilometer resolution.

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Driving Simulation

Simulation for driving training.

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ACM SIGSIM

Special Interest Group (SIG) on SImulation and Modeling (SIM)

Monte Carlo Modeling and Simulation

Introduction

Books

Landau, D.P. and K. Binder (2005), A Guide to Monte Carlo Simulations in Statistical Physics, 2nd Edition, Cambridge University Press, Cambridge, UK.
Fishman, G.S. (1996), Monte Carlo: Concepts, Algorithms and Applications, Springer-Verlag, New York, NY.
Sadus, R.J. (1999), Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation, Elsevier, Burlington, MA.

Journals

Disciplines Using Monte Carlo M&S

Biology
Chemistry
Computational Engineering
Financial Probabilistic Modeling
Mathematics
Nuclear Engineering
Physics (Computational, Nuclear, Statistical)
Reliability Engineering
Statistics

Intended Uses / Objectives

Problem Solving based on statistical random sampling