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Statistical correlations and risk analyses techniques for a diving dual phase bubble model and data bank using

B R Wienke¹, T R O'Leary

¹Nuclear Weapons Technology/Simulation and Computing, Applied and Computational Physics Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. brw@lanl.gov <brw@lanl.gov>

Computers in Biology and Medicine

|March 29, 2008

Summary

The study links the Reduced Gradient Bubble Model (RGBM) with diving data, providing risk assessments for various dive profiles and gases. This advanced model is crucial for safe technical and scientific diving operations.

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Area of Science:

Diving Physiology and Decompression Theory
Computational Fluid Dynamics and Mathematical Modeling

Background:

The Reduced Gradient Bubble Model (RGBM) is a critical tool for understanding gas dynamics in divers.
Existing models require robust correlation with empirical data for accurate risk assessment.

Purpose of the Study:

To detail the LANL diving Reduced Gradient Bubble Model (RGBM), its dynamical principles, and its correlation with data.
To provide risk assessments for various diving scenarios using likelihood analysis.

Main Methods:

Utilized the LANL Data Bank for correlation with the RGBM.
Employed a modified Levenberg-Marquardt routine with an L2 error norm for data fitting.
Developed a Monte Carlo-like sampling scheme for numerical analysis and variance reduction.

Main Results:

Derived risk profiles for air, nitrox, helitrox, and mixed gas dives, including no-decompression limits and repetitive dive tables.
Validated the RGBM through application analyses including decompression meters, diver tables, and extreme exploration dives.
Established a first-time correlation between a dynamical bubble model and deep stop data.

Conclusions:

The RGBM has broad applications in recreational, technical, scientific, and commercial diving.
The developed methods offer alternatives to canonical approaches for estimating diving risk.
Supercomputing resources are essential for connecting dynamical models with real-world diving data.