DETERMINING THE CONCENTRATION OF BASE SOLUTION BASED ON GAMMA TRANSITION TECHNIQUE COMBINED WITH MONTE CARLO SIMULATION AND ARTIFICIAL NEUTRAL NETWORK: PRELIMINARY RESULTS
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Abstract
This study proposes an approach based on Monte Carlo simulation data of gamma transmission measurements combined with an artificial neural network (ANN) model to determine the percentage concentration of base solutions. The simulated data was used to evaluate the relationship between R (the ratio of the area under the transmission peak for the solution relative to that of water) and the concentration of base solution with different energies in the range of 60 – 667 keV. The average reduction of R has a minimum value of 0.0024 at 662 keV and a maximum value of 0.0063 at 60 keV. This result indicates that the measurement sensitivity is more favored in the low-energy case. The ANN model was trained by using the simulated data and then used to predict the concentration of the base solution. The study results show that the proposed approach is feasible for determining the concentration of base solutions. The relative deviations between ANN predictions and reference concentrations are less than 5% for the solution concentrations in the range of 4% to 50%. The preliminary results play an important role in developing a useful non-destructive method to determine the concentration of base solutions.
Keywords
base solution, concentration, gamma transmission, Monte Carlo, NaI(Tl)
Article Details
References
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