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Modeling The Temperature of a Calorimeter at Clab : Considering a Thermodynamic Model of The Temperature Evolution of The Calorimeter System 251Ekman, Johannes January 2021 (has links)
It is important to know the heat generated due to nuclear decay in the final repository for spent nuclear fuel. In Sweden, the heating powers generated in spent nuclear fuels are currently measured in the calorimeter System 251 at the Clab facility, Oskarshamn. In order to better measure, and increase understanding, of the temperature measurements in the calorimeter, a simple thermodynamic model of its temperature evolution was developed. The model was described as a system of ordinary differential equations, which were solved, and the solution was applied to calibration measurements of the calorimeter. How precise the model is, how its parameters affect the model, et cetera, are addressed. How the temperature evolution of the system changes as the values of parameters in the model are changed is addressed. The mass correction of the calorimeter could be estimated from this model, which validated the established mass correction of the calorimeter. How the measurement results from the calorimeter would be affected if the volume of the calorimeter was changed was also considered. Additionally, gamma radiation escape from the calorimeter without being detected as heat in the calorimeter. The gamma escape energy fraction was estimated by SERPENT simulations of the calorimeter, as a function of the initial photon energy. The gamma escape was also estimated for different values of the radius of System 251.
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Phase Unwrapping MRI Flow Measurements / Fasutvikning av MRT-flödesmätningarLiljeblad, Mio January 2023 (has links)
Magnetic resonance images (MRI) are acquired by sampling the current of induced electromotiveforce (EMF). EMF is induced due to flux of the net magnetic field from coherent nuclear spins with intrinsic magnetic dipole moments. The spins are excited by (non-ionizing) radio frequency electromagnetic radiation in conjunction with stationary and gradient magnetic fields. These images reveal detailed internal morphological structures as well as enable functional assessment of the body that can help diagnose a wide range of medical conditions. The aim of this project was to unwrap phase contrast cine magnetic resonance images, targeting the great vessels. The maximum encoded velocity (venc) is limited to the angular phase range [-π, π] radians. This may result in aliasing if the venc is set too low by the MRI personnel. Aliased images yield inaccurate cardiac stroke volume measurements and therefore require acquisition retakes. The retakes might be avoided if the images could be unwrapped in post-processing instead. Using computer vision, the angular phase of flow measurements as well as the angular phase of retrospectively wrapped image sets were unwrapped. The performances of three algorithms were assessed, Laplacian algorithm, sequential tree-reweighted message passing and iterative graph cuts. The associated energy formulation was also evaluated. Iterative graph cuts was shown to be the most robust with respect to the number of wraps and the energies correlated with the errors. This thesis shows that there is potential to reduce the number of acquisition retakes, although the MRI personnel still need to verify that the unwrapping performances are satisfactory. Given the promising results of iterative graph cuts, next it would be valuable to investigate the performance of a globally optimal surface estimation algorithm.
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