This project was designed to demonstrate the use of the Radiation Detection Scenario Analysis Toolbox (RADSAT) radiation detection transport modeling package (developed in a previous NA-22 project) for specific radiation detection scenarios important to proliferation detection. RADSAT is founded on a 3-dimensional deterministic radiation transport solver capable of efficiently computing the radiation field at all points in complex, large-scale problems (e.g. buildings). These results are then coupled to a Monte Carlo detector response simulator. For this project Pacific Northwest National Laboratory (PNNL) staff applied RADSAT to two specific instruments and scenarios, in close collaboration with the developers of each technology. The first is a neutron-scatter camera for detection of concealed neutron-emitting sources developed at Sandia National Laboratories (SNL) and the second is a spent-fuel verification system for fuel assemblies in storage casks developed at Idaho National Laboratory (INL). To simulate detector responses, RADSAT uses a source modified version of Monte Carlo N-Particle Version 5 (MCNP5), which does not produce all of the information required to produce images for the scatter camera system. SNL models the scatter camera with Monte Carlo N-Particle-Politecnico di Milano (MCNP-PoliMi), which utilizes more accurate neutron elastic scattering physics and secondary gamma-ray production essential for modeling time-dependent events in multiple detectors. Therefore, RADSAT currently will not work for generating images for the scatter camera. However, it was demonstrated that RADSAT calculated the correct individual detector response, which indicates that RADSAT could be an appropriate tool for modeling neutron scatter cameras if MCNP-PoliMi were to be used as the RADSAT Monte Carlo detector response module. Incorporating MCNP-PoliMi into RADSAT in addition to MCNP5 would require a minimal amount of code development, testing, and quality assurance. In terms of computational run time, for very simple low scattering scenarios, RADSAT may not have a computational speed advantage over MCNP5, but for more complicated, larger, or highly scattering problems (which are probably more realistic), RADSAT may have computational run times shorter than MCNP5. For the simulation of the spent fuel cask gamma-ray scanner, the solution accuracies for the RADSAT simulations were reasonable (less than 15% different from experimental results) and comparable to the current standard (MCNPX) for all of the compared values for both full and empty assembly positions. RADSAT also ran 60% faster than Monte Carlo N-Particle eXtended (MCNPX), with both codes optimized for speed. In addition, the time to set up a RADSAT run is probably much less than the time to set up and optimize an MCNPX input deck with appropriate variance reduction, making the total time to solution even faster for RADSAT than just the computational run time advantage. v