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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Bayesian Parameter Inference of Explosive Yields using Markov Chain Monte Carlo Techniques

John Burkhardt
Page: 1115-1126 | Received 21 Sep 2022, Published online: 21 Sep 2022

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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. Bayesian Parameter Inference of Explosive Yields using Markov Chain Monte Carlo Techniques.
DOI: https://doi.org/10.36478/jeasci.2020.1115.1126
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2020.1115.1126