Dive computer decompression models and algorithms: philosophical and practical views

IF 0.4 Q4 Engineering UNDERWATER TECHNOLOGY Pub Date : 2018-07-01 DOI:10.3723/UT.35.051
S. Angelini
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引用次数: 2

Abstract

The functioning of diving decompression computers is based on predictive models that are made operational through algorithms. Relatively simple models can be constructed to manage diving decompression obligations with a high degree of confidence, as long as the dive profiles fall within the model’s ‘range of applicability’. The same degree of confidence cannot be assumed where dive profiles are outside of that range – for instance by diving deeper, or for longer or more frequently than what had been considered in the development of the model, or because of individual physiological particularities. A common method to deal with this is to increase the level of conservatism of the model by reducing inert gas load. Depending on the dive computer, this is achieved by allowing the diver to set predefined ‘personal levels’ or through ‘gradient factors’, which is a more transparent method of obtaining a reduced inert gas load at the end of a dive. This paper outlines models and algorithms in general, and then discusses gradient factors in further
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潜水计算机解压缩模型和算法:哲学和实用观点
潜水减压计算机的功能是建立在预测模型的基础上的,这些预测模型是通过算法实现的。只要潜水剖面在模型的“适用范围”内,就可以构建相对简单的模型,以高度的置信度来管理潜水减压义务。在潜水剖面超出该范围的情况下,例如潜水深度、潜水时间更长或潜水频率高于模型开发时所考虑的范围,或者由于个体生理特征,不能假设相同程度的置信度。解决这一问题的常用方法是通过减少惰性气体负荷来提高模型的保守性水平。根据潜水计算机的不同,这是通过允许潜水员设置预定义的“个人水平”或通过“梯度因子”来实现的,这是一种更透明的方法,可以在潜水结束时获得减少的惰性气体负荷。本文概述了模型和算法,然后进一步讨论了梯度因素
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UNDERWATER TECHNOLOGY
UNDERWATER TECHNOLOGY ENGINEERING, OCEAN-
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