Mine Burial Expert System for Change of MIW Doctrine

Abstract

Mine impact burial models such as IMPACT25, IMPACT28, and IMPACT35 have been used in the MIW community in an attempt to calculate the percentage of impact burial for sea mines. Until recently the models have been deterministic, using parameters such as sediment type, air and sea trajectories, drop angle, and mine type to calculate the percentage of burial. These models have been relatively effective in calculating impact burial, but little attention has been given to the temporal effects on mine burial, known as scour burial. Another shortfall of the deterministic modeling approach is the inability to capture the stochastic nature of the input parameters. To address these issues the John Hopkins University - Applied Physics Laboratory (JHU-APL), in conjunction with the NRL has developed the Mine Burial Expert System (MBES). The MBES is a Bayesian network of physics based, deterministic models, observational data, and expert opinion. It provides the opportunity to give input parameters as probability density tables (PDTs) and receive a burial percentage as an output distribution. This allows its user to capture the variability of input parameters and converge them into variability in the burial prediction, providing valuable risk data to the mine countermeasure (MCM) Commander. The MBES has been incorporated into the Environmental Post Mission Analysis (EPMA) tool for Naval Oceanographic Office (NAVO), which could give the MCM planners an idea of the confidence level of its predictions. To understand how the variability and confidence levels can be used and how it may affect current doctrine, a series of tests have been run through the MBES. A thorough review of the results can have a significant effect on future use of the system and subsequent changes to MIW doctrine. In particular, current doctrinal sediment categories are not sufficient in capturing the resolution of the MBES predictions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2011
Accession Number
ADA552264

Entities

People

  • Christopher M. Beuligmann

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Boats
  • Civil War
  • Computer Programs
  • Countermeasures
  • Expert Systems
  • Explosives
  • International Law
  • Naval Mines
  • Naval Operations
  • Navy
  • Physics
  • Physics Laboratories
  • Probability
  • Probability Distributions
  • United States

Readers

  • Coastal Oceanography
  • Computational Modeling and Simulation
  • Naval Mine Countermeasure Systems Development.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference