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Fast neutron transmission and tomography simulation using Monte Carlo techniques for the examination of large industrial and biological objects.

Tabatabaian, Zinat. (1997) Fast neutron transmission and tomography simulation using Monte Carlo techniques for the examination of large industrial and biological objects. Doctoral thesis, University of Surrey (United Kingdom)..

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Elemental analysis of substances made of heavy elements and detection of light elements in heavy matrices are difficult by means of photon transmission techniques. Neutrons have been used in this work, taking unique advantage of their absorption and scattering properties, to detect the structure of industrial and biological objects made of strongly-neutron scattering or absorbing materials, or to study objects combining of high and low neutron cross section materials. The most convenient matrices and impurities amenable to neutron inspection were searched by obtaining expressions for minimum detectable mass and length fraction of elements in an object. Formulae to calculate the minimum required number of neutrons to detect an impurity in a matrix have also been developed. The optimum sample thickness to be investigated with a minimum number of neutrons is likewise derived. Calculations have been carried out for the minimum detectable mass fraction of hydrogen in a number of sample matrices of industrial interest and of elements in a water matrix highlighting the differences with photon attenuation measurements. Results are presented for three neutron energies cold (0.001 eV), thermal (0.025 eV), and fast (14 MeV); concentrations in the parts per million range are demonstrated. Fast neutrons were used because of their high penetration ability, in order to study bulk industrial and biological samples and for their adequacy in detection of light elements such as H, C, N and O in large objects. An attempt to simulate fast neutron transmission tomographs of biological samples was made using the MORSE-CGA Monte-Carlo code. The code was used to calculate transmission of multienergetic U-235 fast fission neutron source in a complex geometry for industrial and biological applications. A fast neutron collimator for radiography, a collimator for brain tomography and a tomography chamber were simulated to design a technique to estimate the effect of scattered neutrons in practical tomography. The macroscopic cross section and mean free path of neutrons for the media of the heterogeneous matrices were also obtained by using microscopic cross sections of elements from the DLC-100G package. Using a multienergetic source provided an opportunity to determine the optimum neutron energy for examination of objects. The analysis required establishing a technique to calculate the fraction of neutrons in each energy group for the 100 group structure of the DLC-100G package. Finally the simulated neutron tomographic images were reconstructed by using the neutron transmission data for different angles of the object, and reconstructing them by the filtered back projection technique. In non-destructive evaluation of medical organs by fast neutron simulation tomography the simulated tomography of prototype biological objects were able to distinguish brain in skull, bone-marrow in bone and bone in soft tissue with good contrast up to 0.42. These results are valuable to identify developing cystic lesions and daughter cyst within the marrow vascular spaces, solid bony tumors, aberrant masses in the facial bone, tumor in spine or other bone marrow abnormalities. In studying component characterisation of industrial objects non-destructively by fast neutron tomography a 3mm diameter duct containing engine-oil was detected at 40 cm depth inside an aluminium combustion engine with a remarkable contrast of 0.35. The minimum detectable mass of oil in aluminium for an optimum neutron energy was 0.1mg/g with a similar result for iron.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors :
Date : 1997
Contributors :
Depositing User : EPrints Services
Date Deposited : 09 Nov 2017 12:18
Last Modified : 09 Nov 2017 14:47

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