Deep Thinking AI and Goldman's interconnected tissue theory coded in Python.
Deep Thinking AI and Diving
I've been testing AI in numerous fields, including decompression algorithms. I was "discussing" with "depth thinking" about Goldman's interconnected tissue decompression theory.
“Deep Thinking” coded an oversimplified example and produced an audio report of our conversation. Note that the audio is incredible. I took our conversation and transformed it into a podcast interview, which is impressive. The only bad thing is that my voice wasn’t used. Maybe I should upload it as well? I strongly recommend listening to understand what AI is capable of.
Evidently, the code is valid only for theoretical discussion; the code was based on:
Perfusion is still handled using the half-time concept.
Diffusion for peripheral compartments is modeled as proportional to the difference in pN2 between the peripheral and central compartments.
The central compartment's update now explicitly considers diffusion from the peripheral compartments.
Results:
Simulating dive with interconnected tissue model...
Time: 0 min, Depth: 0 m
Compartment Central: pN2 = 0.790 ATA
Compartment Peripheral1: pN2 = 0.790 ATA
Compartment Peripheral2: pN2 = 0.790 ATA
Time: 5 min, Depth: 30 m
Compartment Central: pN2 = 1.475 ATA
Compartment Peripheral1: pN2 = 0.920 ATA
Compartment Peripheral2: pN2 = 0.856 ATA
Time: 30 min, Depth: 30 m
Compartment Central: pN2 = 2.818 ATA
Compartment Peripheral1: pN2 = 1.608 ATA
Compartment Peripheral2: pN2 = 1.314 ATA
Time: 35 min, Depth: 0 m
Compartment Central: pN2 = 2.143 ATA
Compartment Peripheral1: pN2 = 1.620 ATA
Compartment Peripheral2: pN2 = 1.373 ATA
WARNING: Significant supersaturation in Central!
