Simulation, Analysis, and Modeling (SAM)

Develop simulation, analysis, and modeling methods to identify and characterize SNM and facilities processing SNM.

Challenges of CNEC Thrust Areas

– SAM Thrust Lead
The Simulation, Analysis, and Modeling (SAM) team’s challenge problem is to develop methods that will enable the rapid localization of a radiation source in a cluttered, noisy urban environment. “Clutter” describes the heterogeneous nature of the environment: buildings attenuate radiation rapidly, while radiation tends to stream down streets with few interactions. “Noisy” describes the location- and time-dependent variations in the radiation background that results from variations in building materials and atmospheric conditions. The SAM team is developing deterministic (e.g., regression) and stochastic (e.g., Bayesian) methods to estimate the location and activity of a radiation source using a network of detectors deployed across an urban environment. They have developed a Bayesian Metropolis framework for estimating the distribution of probable source locations from the detector network, methods for propagating uncertainties in building composition and density onto the uncertainty in source location, and techniques for optimizing the configuration of the detector network. They have also developed deterministic radiation transport methods that use unstructured, tetrahedral spatial meshes and Monte Carlo radiation transport methods for estimating the sensitivity of responses to variations in the transport medium geometry. Furthermore, they are currently coupling deterministic transport calculations to Monte Carlo calculations to optimize their computational efficiency. These developments will enable efficient, high-fidelity simulations of urban source search scenarios, which will be used to develop and evaluate source localization algorithms.

Research Participants

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