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• W1567802578 abstract "Abstract : Propagation and reverberation of acoustic fields in shallow water depend strongly on the spatial variability of seabed geoacoustic parameters, and lack of knowledge of seabed variability is often a limiting factor in acoustic modeling applications. However, direct sampling (e.g., coring) of vertical and lateral variability is expensive and laborious, and long-range inversion methods can fail to provide sufficient resolution. For proper quantitative examination of variability, parameter uncertainty must be quantified first which can be particularly challenging for large data sets, and in range-dependent and/or dispersive seabed environments. A long-term goal of this work is to substantially advance Bayesian inversion methodology to allow automated analysis of large and complex data sets. These advances will allow mesoscale spatial variability of seabed sediments to be quantified in two and three dimensions. In addition, understanding acoustic dispersion in seabed sediments is of significant interest to the acoustical oceanography community. Obtaining meaningful inferences on low-frequency dispersion is a challenging inverse problem since estimates can strongly depend on the spatial structure (layering) of the sediment and multiple competing physical theories exist that can predict similar dispersion regimes. Further, direct sampling is currently not possible for low frequencies (hundreds of Hertz). Recent advances in Bayesian inversion (Dettmer et al. 2010, 2012a; Holland and Dettmer 2012) allow inferences on complex environments (arbitrary and unknown layering) and advanced physical theories (acoustics of dispersive media and spherical reflection coefficients). A long-term goal is to further understanding of such complex systems and develop a quantitative methodology for understanding and discrimination of physical dispersion theories." @default.
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• W1567802578 date "2013-09-30" @default.
• W1567802578 modified "2023-09-25" @default.
• W1567802578 title "Automated Geoacoustic Inversion and Uncertainty: Meso-Scale Seabed Variability in Shallow Water Environments" @default.
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