Physiological Event Prediction in Evaluations of Underwater Breathing Apparatus

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Physiological Event Prediction in Evaluations of Underwater Breathing Apparatus

Show simple item record Clarke, JR 2018-06-28T13:50:22Z 2018-06-28T13:50:22Z 2016
dc.identifier.govdoc AD1035602
dc.identifier.govdoc NEDU TR 16-04
dc.description Citation Status: Active; Citation Classification: Unclassified; Title Classification: Unclassified; Report Classification: Unclassified; Identifier Classification: Unclassified; Abstract Classification: Unclassified; Distribution Limitation(s): 01 - APPROVED FOR PUBLIC RELEASE; Information provided by the Department of Defense and the Defense Technical Information Center ( is considered public information and may be distributed or copied unless otherwise specified. Use of appropriate byline/photo/image credits is requested. en_US
dc.description.abstract This report describes the use of Predict, in-house designed prediction software. NEDU performance goals for underwater breathing apparatus (UBA) based on ventilatory flow rate have served the Navy well for decades. Nevertheless, gas density is a major determinant of respiratory loading at depth, based on both experimental evidence and simple models of fluid mechanics. An understanding of the influence of flow rate and gas density are vital to understanding the performance characteristics of UBA, and the probable tolerance of a diver to those influences. Over a decade ago NEDU developed a constant respiratory impedance model for determining acceptable pressure drops across UBA, and created software to predict the tolerance of divers to UBA under varying dive conditions. The so-called maximum respiratory impedance model was calibrated on Navy manned dive results, and this paper describes the use of that model and the associated Predict software to predict diver tolerance based on unmanned data. It is arguably a more complete approach compared to methods already in Navy use, and is particularly useful in estimating the risk of diving UBA made inadequate by design or accident. en_US
dc.description.sponsorship USN en_US
dc.language.iso en en_US
dc.publisher USN en_US
dc.subject Humans en_US
dc.subject divers en_US
dc.subject underwater breathing apparatus en_US
dc.subject diving equipment en_US
dc.subject impedance en_US
dc.subject high pressure en_US
dc.subject electrical resistance en_US
dc.subject unmanned en_US
dc.subject atmospheres en_US
dc.subject probability en_US
dc.subject measurement en_US
dc.subject fluid dynamics en_US
dc.subject software tools en_US
dc.subject test and evaluation en_US
dc.subject predictions en_US
dc.title Physiological Event Prediction in Evaluations of Underwater Breathing Apparatus en_US
dc.type Article en_US

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