Browsing by Subject "Roughness parameterization"

Now showing 1 - 1 of 1

Determining seafloor sediment geoacoustic and ripple parameters from simulated transmission loss data through Bayesian parallel tempering inference
(2021-12-06) Albritton, James Andrew; Wilson, Preston S.; Gunderson, Aaron M.
Geoacoustic inversion of shallow water transmission loss (TL) measurements can be a more convenient way to characterize the seafloor compared to coring or other direct measurements. The Bayesian inversion method of parallel tempering was applied to high-fidelity simulated TL data to determine the viability of inverting for a small parameter set characterizing a rippled seafloor. The algorithm inverts for bulk sediment density, sound speed, attenuation, and sediment ripple amplitude and wavelength. Ripple wavelengths ranging from 1–3.5 m were considered due to their impact on acoustic waves in the kilohertz frequency range. Parallel tempering overcame local entrapment issues encountered by traditional Markov Chain Monte Carlo Metropolis-Hastings sampling with multimodal solutions. Parallel tempering prevents entrapment through state-swapping between parallel inversion chains, which improves parameter space sampling while remaining unbiased. The ray-based model Bellhop was used to evaluate the forward solution. To evaluate the algorithm’s performance, simulated data sets were created using both finite element models and Bellhop, and were then inverted. The algorithm yielded marginal posterior probability distributions for each of the parameters, as well as information about parameter resolvability. It performed well for a range of ripple parameters, acoustic frequencies, waveguide ranges, and source locations. The specific results of each test case and potential ways to improve the overall accuracy and efficiency of the algorithm are discussed