Specific Filters Applied in Nuclear Medicine Services

In Nuclear Medicine, radioiodine, in various chemical forms, is a key tracer used in diagnostic practices and/or therapy. Due to its high volatility, medical professionals may incorporate radioactive iodine during the preparation of the dose to be administered to the patient. In radioactive iodine therapy doses ranging from 3.7 to 7.4GBq per patient are employed. Thus, aiming at reducing the risk of occupational contamination, we developed a low cost filter to be installed at the exit of the exhaust system where doses of radioactive iodine are fractionated, using domestic technology. The effectiveness of radioactive iodine retention by silver impregnated silica [10%] crystals and natural activated carbon was verified using radiotracer techniques. The results showed that natural activated carbon is effective for I2 capture for a large or small amount of substrate but its use is restricted due to its low flash point (150º C). Besides, when poisoned by organic solvents, this flash point may become lower, causing explosions if absorbing large amounts of nitrates. To hold the CH3I gas, it was necessary to increase the volume of natural activated carbon since it was not absorbed by SiO2 + Ag crystals. We concluded that, for an exhaust flow range of (306 4) m3/h, a double stage filter using SiO2 + Ag in the first stage and natural activated carbon in the second is sufficient to meet radiological safety requirements.

Artificial Neural Network and Neutron Aplication in a Volume Fraction Calculation in Annular and Stratified Multiphase System

Multiphase flows, type oil–water-gas are very common among different industrial activities, such as chemical industries and petroleum extraction, and its measurements show some difficulties to be taken. Precisely determining the volume fraction of each one of the elements that composes a multiphase flow is very important in chemical plants and petroleum industries. This work presents a methodology able to determine volume fraction on Annular and Stratified multiphase flow system with the use of neutrons and artificial intelligence, using the principles of transmission/scattering of fast neutrons from a 241Am-Be source and measurements of point flow that are influenced by variations of volume fractions. The proposed geometries used on the mathematical model was used to obtain a data set where the thicknesses referred of each material had been changed in order to obtain volume fraction of each phase providing 119 compositions that were used in the simulation with MCNP-X –computer code based on Monte Carlo Method that simulates the radiation transport. An artificial neural network (ANN) was trained with data obtained using the MCNP-X, and used to correlate such measurements with the respective real fractions. The ANN was able to correlate the data obtained on the simulation with MCNP-X with the volume fractions of the multiphase flows (oil-water-gas), both in the pattern of annular flow as stratified, resulting in a average relative error (%) for each production set of: annular (air= 3.85; water = 4.31; oil=1.08); stratified (air=3.10, water 2.01, oil = 1.45). The method demonstrated good efficiency in the determination of each material that composes the phases, thus demonstrating the feasibility of the technique.