Gürmen N M, Llewellyn A J, Gilbert R A, Egi S M
Department of Chemical Engineering at the University of South Florida, Tampa 33620, USA.
IEEE Trans Biomed Eng. 2001 Feb;48(2):185-93. doi: 10.1109/10.909639.
Decompression sickness (DCS) is the result of bubble formation in the body due to excessive/rapid reduction in the ambient pressure. Existing models relate the decompression stress either to the inert gas load or to the size of a single bubble in a tissue compartment. This paper presents a model that uses the gas exchange equations combined with bubble dissolution physics and population balance equations to produce a new mathematical framework for DCS modeling. This framework, the population balance model for decompression sickness (PBMDS), simulates the number of bubbles with their corresponding size distributions in a compartmental tissue array. The model has a modular structure that enables one to explore different modeling results with respect to key aspects of DCS, such as gas exchange, nucleation, and surface tension. The paper's goal is to present the derivation of PBMDS in detail, however, three simple application case studies are provided. The aim of these case studies is to suggest that PBMDS supplies additional information on bubble distribution while supporting the results from current practice.
减压病（DCS）是由于环境压力过度/快速降低导致体内形成气泡的结果。现有的模型将减压应力与惰性气体负荷或组织隔室中单个气泡的大小联系起来。本文提出了一个模型，该模型使用气体交换方程结合气泡溶解物理和群体平衡方程，为减压病建模生成一个新的数学框架。这个框架，即减压病群体平衡模型（PBMDS），模拟了隔室化组织阵列中具有相应大小分布的气泡数量。该模型具有模块化结构，使人们能够探索关于减压病关键方面的不同建模结果，如气体交换、成核和表面张力。本文的目标是详细介绍PBMDS的推导过程，不过，还提供了三个简单的应用案例研究。这些案例研究的目的是表明，PBMDS在支持当前实践结果的同时，还提供了关于气泡分布的额外信息。
