A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory’s Monte Carlo Application Toolkit (MCATK) and examples of it’s use are shown for both super-critical and sub-critical systems.
Making sense of data is complex, and the knowledge and skills required to understand "Big Data" - and many open data sources - go beyond those taught in traditional introductory statistics courses. The Mobilize project has created and implemented a course for secondary students, Introduction to Data Science (IDS), that aims to develop computational and statistical thinking skills so that students can access and analyze data from a variety of traditional and non-traditional sources. Although the course does not directly address open source data, such data are used in the curriculum, and an outcome of the project is to develop skills and habits of mind that allow students to use open source data to understand their community. This paper introduces the course and describes some of the challenges in its implementation.
The Monte Carlo Application ToolKit (MCATK) is a component-based software library designed to build specialized applications and to provide new functionality for existing general purpose Monte Carlo radiation transport codes. We will describe MCATK and its capabilities along with presenting some verification and validations results.
The Monte Carlo Application Toolkit (MCATK) provides solution options for problems with time varying properties in mesh geometries and simple solid bodies. The paper describes the toolkit’s mechanism for handling time varying problems focusing on managing the particle population. The included results show the robustness of this approach for systems with varying degrees of criticality without user intervention.
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