The Naval Seafloor Evolution Architecture: A Platform for Predicting Dynamic Seafloor Roughness

Abstract

Predicting the temporal and spatial dynamics of seafloor roughness is important for understanding bottom boundary layer hydrodynamics. The Navy Seafloor Evolution Architecture (NSEA) is a platform for modeling the dynamic nature of the seafloor by combining hydrodynamic forcing information and observations from diverse sources. NSEA's three modules include a specification of hydrodynamic forcing, a seafloor evolution model, and a model to generate roughness realizations. It can be run in forward mode to predict seafloor roughness including the uncertainty from forcing information, or in inverse mode to estimate parameters from observed seafloor roughness. The model is demonstrated and shown to have good agreement with a field dataset of observed seafloor roughness. Similarly running in inverse mode, NSEA was demonstrated to predict the observed mean sediment grain size with good agreement. NSEA's modularity allows for a wide range of applications in hydrodynamic and acoustic modeling, and is built within an expandable framework that lends for coupling to such models with minimal effort.

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Document Details

Document Type
Technical Report
Publication Date
Jul 28, 2022
Accession Number
AD1183343

Entities

People

  • A. Penko
  • William S. Kearney

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Propagation
  • Acoustics
  • Bayesian Inference
  • Boundary Layer
  • Computational Fluid Dynamics
  • Computational Science
  • Data Science
  • Differential Equations
  • Earth Sciences
  • Fluid Mechanics
  • Gaussian Processes
  • Information Processing
  • Information Science
  • Partial Differential Equations
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Scattering
  • Statistical Algorithms
  • Statistical Inference
  • Stochastic Processes

Fields of Study

  • Environmental science

Readers

  • Coastal Oceanography
  • Computational Modeling and Simulation
  • Database Systems and Applications