Journal

William Oates

Bin, J. and Taira, K.

2015

A model for two-dimensional graphene-based thermoacoustic membranes is investigated analytically and numerically validated using Bayesian statistics in this study. The temperature and the pressure variables are first analytically determined in one-dimension by noticing that the magnitude of the pressure time derivative is small in the heat transfer equations and by taking advantage of the large disparity between the length scales. The one-dimensional findings are then extended to three-dimensions, where pressure fluctuation produced by the surface temperature variation is determined using an acoustic piston model. Through the one and three-dimensional model analysis, the dependence of acoustic pressure as a function of frequency is studied. The acoustic response with respect to the frequency shows different characteristics when assuming Dirichlet (temperature) or Neumann (heat flux) boundary conditions. The thermoacoustic model is validated with a graphene-on-paper loudspeaker using Bayesian statistical methods and a Delayed Rejection Adaptive Metropolis algorithm to identify model parameters and their uncertainty. The findings provide insights into the heat transport mechanisms associated with sound generation from thermally cycling thin conductive membranes at high frequencies.

Journal of Applies Psychics

117

6

064506

2/13/2015

https://aip.scitation.org/doi/10.1063/1.4908067

https://doi.org/10.1063/1.4908067