For the past few decades, the most common type of deep-penetration (shielding)problem simulated using Monte Carlo methods has been the source-detector problem,in which a response is calculated at a single location in space. Traditionally,the nonanalog Monte Carlo methods used to solve these problems have requiredsignificant user input to generate and sufficiently optimize the biasing parametersnecessary to obtain a statistically reliable solution. It has been demonstrated thatthis laborious task can be replaced by automated processes that rely on a deterministicadjoint solution to set the biasing parameters – the so-called hybrid methods.The increase in computational power over recent years has also led to interest inobtaining the solution in a region of space much larger than a point detector. In thisthesis, we propose two methods for solving problems ranging from source-detectorproblems to more global calculations – weight windows and the Transform approach.These techniques employ some of the same biasing elements that have been usedpreviously; however, the fundamental difference is that here the biasing techniquesare used as elements of a comprehensive tool set to distribute Monte Carlo particlesin a user-specified way. The weight window achieves the user-specified Monte Carloparticle distribution by imposing a particular weight window on the system, withoutaltering the particle physics. The Transform approach introduces a transforminto the neutron transport equation, which results in a complete modification of theparticle physics to produce the user-specified Monte Carlo distribution.These methods are tested in a three-dimensional multigroup Monte Carlo code.For a basic shielding problem and a more realistic one, these methods adequatelysolved source-detector problems and more global calculations. Furthermore, theyconfirmed that theoretical Monte Carlo particle distributions correspond to the simulatedones, implying that these methods can be used to achieve user-specified MonteCarlo distributions. Overall, the Transform approach performed more efficientlythan the weight window methods, but it performed much more efficiently for source-detectorproblems than for global problems.
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Hybrid Monte Carlo/Deterministic Methods for Radiation Shielding Problems.