Decompression algorithm: Difference between revisions

A decompression algorithm is used to calculate the decompression stops needed for a particular dive profile to prevent decompression sickness when diving. The algorithm can be used to generate decompression tables or be implemented in dive computer software.

Deterministic Models

Deterministic decompression models are a rule based approach to calculating decompression. These models work from the idea that "excessive" supersaturation in various tissues is "unsafe" (resulting in decompression sickness). They usually contain multiple depth and tissue dependent rules. These rules are revised by qualitative judgement. There is no objective mathematical way of evaluating the rules or overall risk.

Probabilistic Models

Probabilistic decompression models are designed to calculate the risk (or probability) of decompression sickness (DCS) occurring on a given decompression profile. These models can vary the decompression stop depths and times to arrive at a final decompression schedule that assumes a specified probability of DCS occurring. The model does this while minimizing the total decompression time. This process can also work in reverse allowing one to calculate the probability of DCS for any decompression schedule.

Bubble Models

Bubble decompression models are a rule based approach to calculating decompression. These models work from the idea that microscopic bubble nuclei always exist in water and tissues that contain water and that by predicting/ controlling the bubble growth, one can avoid decompression sickness.

References

• Lippmann, John; Mitchell, Simon (2005). Deeper into Diving (2nd ed.). Melbourne, Australia: J L Publications. ISBN 0-9752290-1-X. Section 2 chapters 13–24 pages 181–350

Further reading

• Powell, Mark (2008). Deco for Divers. Southend-on-Sea: Aquapress. ISBN 1-905492-07-3.