Risk Assessment and Implementation of Impact Burial Prediction Algorithms for Detection of Bottom Sea Mines
Abstract
This paper presents a probabilistic approach to predicting the risk of encountering mines impact buried in mud seafloors. This approach is based on a stochastic interpretation of the sets of both the input and the output parameters used by the existing predictive software. The input parameters describe the variability in the environmental parameters of the layered sediments, as well as the dynamic parameters of the mine impacting the mud line. The output parameters are represented by several variables most relevant to the Navy mine hunting forces, i.e. height proud or percentage of surface area proud. Both sets of input parameters are described using their Gaussian distributions, derived from experimental observations. The stochastic output of the predictive impact burial model is evaluated using a Monte-Carlo simulation technique and compared with the diver measured data. The model displays a somewhat better performance, in statistical terms, as opposed to the deterministic evaluations. Previously observed tendencies to overestimate the height protruding, the final pitch in mud and to underestimate the surface area exposed are confirmed but with the added information from comparing the probability distributions. The model evaluated produces a somewhat more meaningful result for the decision making process of the MCM forces if exercised in the suggested Monte Carlo framework. Reference probability charts are developed providing a more accurate and easier to interpret model output that could be effectively utilized by the Navy Mine Counter-Measures (MCM) forces.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 13, 2004
- Accession Number
- ADA444543
Entities
People
- Andrei Abelev
- C. Barbu
- P. J. Valent
Organizations
- United States Naval Research Laboratory