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A Monte Carlo Primer - A Practical Approach to Radiation Transport (Hardcover, 2002 ed.)
Loot Price: R5,950
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A Monte Carlo Primer - A Practical Approach to Radiation Transport (Hardcover, 2002 ed.)
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This book introduces the reader to the use of Monte Carlo methods
for solving practical problems in radiation transport, and will
also serve as a reference work for practitioners in the field. It
assumes the reader has a general knowledge of calculus and
radiation physics, and a knowledge of Fortran programming, but
assumes no prior knowledge of stochastic methods or statistical
physics. The subject is presented by a combination of theoretical
development and practical calculations. Because Monte Carlo methods
are closely linked to the use of computers, from the beginning the
reader is taught to convert the theoretical constructs developed in
the text into functional software for use on a personal computer.
Example problems provide the reader with an in-depth understanding
of the concepts presented and lead to the production of a unique
learning tool, a probabilistic framework code that models in a
simple manner the features of production of Monte Carlo transport
codes. This framework code is developed in stages such that every
function is understood, tested, and demonstrated - random sampling,
generating random numbers, implementing geometric models, using
variance reduction, tracking particles in a random walk, testing
the thoroughness with which the problem phase space is sampled,
scoring detectors, and obtaining estimates of uncertainty in
results. Advanced topics covered include criticality, correlated
sampling, adjoint transport, and neutron thermalization. Monte
Carlo codes can produce highly precise wrong answers. The
probability of this occurring is increased if production codes are
run as opaque, black boxes' of software. This text attempts to make
Monte Carlo into acomprehensible, usable tool for solving practical
transport problems. It is suitable for advanced undergraduate and
graduate students and researchers who wish to expand their
knowledge of the Monte Carlo technique.
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