Variance reduction for collimated gamma detector geometry in Serpent

The potential of modeling the photon transport in passive gamma emission tomography (PGET) with Serpent is restricted by the computational demand of the simulation using conventional particle tracking routines. However, the analog tracking process can be altered to improve the computational efficiency of the Monte Carlo simulation. In this thesis, a variance reduction scheme utilizing splitting and modified direction sampling is developed and implemented in Serpent. The implementation is verified in a simple test geometry and the method is demonstrated in a PGET gamma-radiation transport. As a result, a factor of 13 or greater improvement was successfully obtained compared to the analog simulation. On the contrary, further development would be required to provide a user interface for input parameter adjustments needed for any generalizations of the method

PGET Monte Carlo simulations using Serpent

Since 2017, over 100 spent nuclear fuel assemblies at the Finnish nuclear power plants have been imaged with the Passive Gamma Emission Tomography (PGET) device in preparation of the implementation of PGET in the safeguards infrastructure of the Finnish geological repository. In order to increase understanding of the PGET method and guide its further development, we have recently implemented PGET in Serpent, a widely-used neutron and photon transport Monte Carlo simulation code. We will discuss the major aspects of this implementation and illustrate the usefulness of the simulations with a few examples. The PGET device as used in the measurements (which was developed under the guidance of IAEA and is approved for safeguards inspections) was implemented in a very realistic way based on its technical drawings. The simulation produces sinograms in user-defined energy windows as well as the uncertainty on these sinograms. Tomographic images are then reconstructed using the exact same algorithm as used for the measured data. A dedicated variance reduction scheme was implemented, increasing the computational efficiency by about a factor of 30. The simulation of the PGET response at one angular measurement position for 1 billion primary photons takes a few hours on a single 40-core node. The 1-sigma uncertainty in the highest intensity sinogram pixels is about a few percent. Aiming at improving the imaging of VVER-440 assemblies, we have simulated assemblies containing one or a few missing fuel rods or having only one emitting rod (the other rods being present but not emitting) in various well-chosen places, configurations that are not accessible in practice. The single-emitting rod results show in great detail those parts of the sinogram that contain most of the information for the particular rod position. How this information might be used for obtaining better images, especially of the central region of a fuel assembly, will be discussed

PGET Monte Carlo simulations using Serpent

Since 2017, over 100 spent nuclear fuel assemblies at the Finnish nuclear power plants have been imaged with the Passive Gamma Emission Tomography (PGET) device in preparation of the implementation of PGET in the safeguards infrastructure of the Finnish geological repository. In order to increase understanding of the PGET method and guide its further development, we have recently implemented PGET in Serpent, a widely-used neutron and photon transport Monte Carlo simulation code. We will discuss the major aspects of this implementation and illustrate the usefulness of the simulations with a few examples. The PGET device as used in the measurements (which was developed under the guidance of IAEA and is approved for safeguards inspections) was implemented in a very realistic way based on its technical drawings. The simulation produces sinograms in user-defined energy windows as well as the uncertainty on these sinograms. Tomographic images are then reconstructed using the exact same algorithm as used for the measured data. A dedicated variance reduction scheme was implemented, increasing the computational efficiency by about a factor of 30. The simulation of the PGET response at one angular measurement position for 1 billion primary photons takes a few hours on a single 40-core node. The 1-sigma uncertainty in the highest intensity sinogram pixels is about a few percent. Aiming at improving the imaging of VVER-440 assemblies, we have simulated assemblies containing one or a few missing fuel rods or having only one emitting rod (the other rods being present but not emitting) in various well-chosen places, configurations that are not accessible in practice. The single-emitting rod results show in great detail those parts of the sinogram that contain most of the information for the particular rod position. How this information might be used for obtaining better images, especially of the central region of a fuel assembly, will be discussed

Evaluating the viability of Serpent in Passive Gamma Emission Tomography (PGET) radiation transport simulations

Passive Gamma Emission Tomography (PGET) has been developed for verification of spent nuclear fuel. To reliably detect missing or substituted fuel pins, verification processes with advanced image reconstruction and classification algorithms are developed. High-fidelity PGET simulations could provide valuable information for the development, and they need accurate modelling of spent nuclear fuel, gamma-radiation, and detector response. This thesis studies the viability of Monte Carlo particle transport code Serpent for PGET modelling, and the objective is to evaluate the viability of gamma-radiation transport in this application. A two-phased analog photon transport was used to simulate flux sinograms. To meet the available time-frame, the transport was divided into two consequent phases and it was benchmarked against a normal one-phased photon transport. The method was consistent with the reference calculation and an efficiency improvement of several factors was obtained. Results were visualized as flux sinograms, from which filtered back projection reconstructions were performed. Simulated reconstructed images were compared to experimental data to qualitatively estimate the performance of the simulation. Results of the simulations were physically sensible, but the framework has to be developed further. To have a fully capable simulation framework, the performance of the radiation transport has to be further increased to make it suitable for simulations of large populations of flux sinograms. The detector response was not simulated in this study, and it has to be implemented to obtain realistic results. Furthermore, once the framework is ready, the simulation has to be validated against other codes or experimental data