@article{MAKHILLJEAS202015519094,
    title = {Bayesian Parameter Inference of Explosive Yields using
Markov Chain Monte Carlo Techniques},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {15},
    number = {5},
    pages = {1115-1126},
    year = {2020},
    issn = {1816-949x},
    doi = {jeasci.2020.1115.1126},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2020.1115.1126},
    author = {John},
    keywords = {Bayesian inference,nonlinear regression,explosive yield,Markov chain Monte Carlo,estimated,characteristics},
    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.}
    }