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@article{154832,
        author = {Manjunath S V and S. K. Maharana and Abdul Sharief},
        title = {Bayesian Inference of Volume Fraction of Vapor Formed During Nucleate Boiling Phenomenon of Water Undergoing Phase Change over Two Heated Cylinders in Tandem Arrangement},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {411-418},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154832},
        abstract = {Fluid flow and heat transfer phenomena through cylinders are common in fluid dynamics. Fluid flow interaction, vortex dynamics, interferences in flow and engineering applications such as compact heat exchangers, nuclear reactor fuel rods and hot-wire anemometry are of major research interest . The main objective is to determine the conditional probability of VF forming around a heated cylinder's surface while it is submerged in water. The flow is calculated using the RANS equations. In the dataset of VF, Bayesian inference was utilized to calculate the prior, likelihood, and posterior probabilities for a given condition. A new value of probability is substituted for the VF at a given region around the heated cylinder. As a result, it's fascinating to observe how Bayesian inference performs on a multivariate dataset. The validity of the findings is made against the literature. The nucleate boiling phenomenon that originates at the surface of a heated cylinder is significantly influenced by cylinder rotation. Using a sample collected using Markov Chain Monte Carlo and Variational Inference methods; the inference methodology was able to detect a statistically significant difference of 0.4 between the means of VFs when the cylinder is at rest and when the same cylinder is rotating.},
        keywords = {Bayesian Inference, Film Boiling, k-ε Turbulence Model, RANS, Volume Fraction.},
        month = {},
        }