Software Design Description for the Simulating Waves Nearshore Model (SWAN)

Abstract

Simulating WAves Nearshore (SWAN) is a third-generation numerical wave model developed for wave computations in coastal regions and inland waters. The model is based on an Ealerian formulation of the discrete spectral balance of action density that accounts for refractive propagation over arbitrary bathymetry and current fields. SWAN is driven by boundary conditions and local winds. The processes of wind generation, whitecapping, quadruplet wave-wave interactions, bottom dissipation, triad wave-wave interactions, and depth-induced wave breaking are represented explicitly, though SWAN does not account for diffraction. SWAN's numerical propagation scheme is implicit; thus the model is most efficient (relative to other models) when applied to cases with relatively high geographic resolution (i.e., cases of smaller scale). SWAN has been validated by comparisons with analytical solutions, and laboratory and field observations. SWAN is the state-of-the art phase-averaged coastal wave model (at the time of this writing). As a third-generation model, SWAN models propagation and dissipation explicitly. it also allows for simple integration of future developments in formulations for the physical processes mentioned above, as SWAN is a strictly and logically modular program.

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Document Details

Document Type
Technical Report
Publication Date
Nov 15, 2002
Accession Number
ADA409177

Entities

People

  • Erick Rogers
  • Kate V. Rushing
  • Richard Allard
  • Suzanne N. Carroll

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Birds
  • Boundary Layer
  • Cartesian Coordinates
  • Coastal Engineering
  • Coastal Regions
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Programming
  • Computer Programs
  • Diffraction
  • Geographic Regions
  • Grids
  • Mathematical Analysis
  • Operating Systems
  • Two Dimensional
  • Wave Propagation

Readers

  • Coastal Oceanography
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference