Journal of Engineering and Applied Sciences

Year: 2020
Volume: 15
Issue: 5
Page No. 1115 - 1126

Bayesian Parameter Inference of Explosive Yields using Markov Chain Monte Carlo Techniques

Authors : John Burkhardt

Abstract: A Bayesian parameter inference problem is conducted to estimate the explosive yield of the first atomic explosion at Trinity in New Mexico. Using data taken from archival film footage of the explosion and a physical model for the expansion characteristics of the resulting fireball, a yield estimate is made. In addition, the observed correlations between the yield and other parameters in the time-radius fireball expansion model are constructed. Bayesian results indicate that the estimated parameters are consistent with previous estimates and model predictions but possess some characteristics of significance which impact the radius-time fireball expansion model.

How to cite this article:

John Burkhardt , 2020. Bayesian Parameter Inference of Explosive Yields using Markov Chain Monte Carlo Techniques. Journal of Engineering and Applied Sciences, 15: 1115-1126.

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