The Use of Monte Carlo Simulation for Uncertainty Estimation in Gamma Densitometry Measurements

Abstract

Abstract Measurement uncertainty is increasingly seen as essential in quality assurance for industry. The uncertainty associated with a value of a physical quantity provides a quantitative measure of the reliability and trustworthiness of that value. The ISO Guide to the Expression of Uncertainty in Measurement (GUM), which provides international agreed recommendations for the evaluation of uncertainty, recommends an approach based on the propagation of distribution using Monte Carlo Simulation (MCS). Uncertainty in multiphase flow measurement results from the uncertainty in the fluid density, phase volume fraction and velocity measurements. In this work, the application of MCS as flow measurement uncertainty estimation method for gamma densitometry in multiphase flow is presented. A response database was obtained by pulling up Polyvinyl Chloride (PVC) ‘blobs’ in a static column of water/oil. Phase volume fractions and velocities measurement were obtained from the energy attenuation data of a caesium-137 radioisotope-based densitometer. MCS is then used to estimate the uncertainties in these measurements. We present preliminary results and demonstrates the simplicity and reliability of this approach to uncertainty assessment. We opined that this method is suited for radiation-based metering technique because of its reliance on randomness, as such it does capture the natural stochastic process inherent in the interaction of gamma rays and multiphase flow.