Browsing by Author "Geletu, Mesay"

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    Monte Carlo Simulation of Theratron Equinox 80" 60CO Radiotherapy Unit
    (Addis Ababa University, 2010-09) Geletu, Mesay; Bekele, Mulugeta (PhD)
    The BEAMnrc Monte Carlo package is used to simulate the 60Co beam from the \Theratron Equinox 80" 60Co radiotherapy unit. In modeling the 60Co unit a particular attention has been paid for the geometry and material construction of the 60Co source capsule, source housing, and the collimator assembly. The in uence of eld size on total photon spectra, scattered photon and electron spectra, (which is produced from the photon interaction with the materials surrounding the Cobalt source and collimator assembly), at the phantom surface (SSD equal to 80 cm) are studied. From our simulation the variation of total photon and scattered photon spectra with increasing eld size is caused by scattered photons from di erent parts of the 60Co radiothereapy unit. We also used BEAMnrc generated phase space les as beam source for DOSXYZnrc to calculate the percentage depth dose and compared with measured values
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    A New Approach to Compact Gravity Inversion Algorithm
    (Addis Ababa University, 2021-06-28) Geletu, Mesay; Lewi, Elias (PhD)
    The gravity method is one of the geophysical methods that has been used in a wider range of geophysical prospecting and investigations. One of the indispensable steps in this method is the inverse modelling of the measured data to estimate the subsurface density distribution and geometrical properties (e.g. shape and depth) of the causative bodies. Particularly, delineating localized and blocky geologic features, through the inversion of gravity data is an important goal in a range of geophysica l investigations and it is still a subject of interest and concern in the scientific communit y. Most conventional inversion algorithms generally yield smooth models with poor edge definition. These methods have difficulties in recovering non-smooth distributions that have sharp boundaries. The main objective of this thesis was then to develop and implement a gravity inversion algorithm that can produce compact and sharp images, aiming at recovering localized and blocky geologic features with varying geometric representations. In the course of the thesis work, this goal has been achieved by presenting a gravimetric inverse modelling method that has been tested to be effective. At the heart of the developed inversion method lies the usage of the 𝐿0-norm minimization of the objective function, which consists of data misfit and L0-norm stabilizing function, by an efficient iteratively reweighted least-squares (IRLS) algorithm. As a major contribution, the presented method incorporates three novel technical advancements. At first, the method incorporates an auto-adaptive regularization technique, which automatically determines a suitable regulariza t ion parameter, and a modified error weighting function that helps to improve both the stability and convergence of the method. The other advantage of the auto-adaptive regularization technique and error weighting matrix is that they are not wholly dependent on the known noise level. Because of that, the method can yield reasonable results even when the noise level of the data is not properly known. The other major contribution is the use of a new depth weighting function. The advantages of the newly proposed depth-weighting function can be summarized as follows: (I) It properly counteracts the gravity kernel decay, so that the inversion results can provide realistic depth information. (II) It avoids the selection of the depth weighting function parameters through trial and error, which was common in the traditional methods, through the usage of automated parameters selection techniques. Especially, this has a significant advantage when there is no prior depth informa t ion that helps to choose the optimum parameter in using the traditional depth weighting function. Furthermore, to achieve geologically plausible results and also reduce solution ambiguity, a physical parameter inequality constraint algorithm has been developed and employed to constrain the obtained density contrast values. Finally, the implementation of an effectively combined stopping criterion has been used to terminate the iterative inversion procedure, when geologically viable solutions are obtained. The proposed combined termination criteria are shown to outperform traditional termination criteria, used in most iterative geophysical invers ion algorithms, through the modeling of synthetic and published measured data To test the new method, forward and inverse modeling codes were written using Python programming in a Linux environment. The validity of the overall Python codes, and the practicality and efficiency of the presented inversion method were tested by inverting a number of synthetic data sets from geometrically complex bodies and field data sets from different geological settings. The results of the inversion confirmed the capability of the developed inversion method in producing geologically acceptable compact and sharp models that define the shape, location, and density distribution of the causative subsurface bodies. This proves, the reliability and effectiveness of the developed inversion method in practical applications to delineate sharp discontinuit ies and blocky features such as distinct layering or formation of localized bodies in the subsurface.