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A systematic approach on service life prediction of a model aerostat envelope
Affiliation:1. Department of Textile Technology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110 016, India;2. Department of Civil Engineering, National Institute of Technology Rourkela, Odisha, 769008, India;1. Institute for Problems of Chemical and Energetic Technologies, Siberian Branch of the Russian Academy of Sciences (IPCET SB RAS), Biysk 659322, Altai Krai, Russia;2. N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry, Siberian Branch of the Russian Academy of Sciences (NIOCh SB RAS), Novosibirsk 630090, Russia;3. OOO Elektromash, Novosibirsk, 630088 Russia;1. Institute of Fundamental Technological Research, PAS, Warsaw, Poland;2. Institute of Materials Science, University of Silesia, Katowice, Poland;3. Aichi Institute of Technology, Toyota-city, Japan;4. SMP Technologies Inc., Tokyo, Japan
Abstract:Lighter-than-air (LTA) helium aerostats are receiving renewed attention for scientific as well as defense applications. Designing of new and improved materials for this kind of structure that consistently survive in the harsh atmospheric condition is one of the critical issues. However, durability of a newly developed material, in the actual field of application, is often unknown. Field experiments to know about its service life take prolonged time. In this study, a systematic approach has been proposed to predict the in service weatherability of a model aerostat envelope. A reliability model with two stress types (UV radiation and temperature) has been achieved to predict the service life of a model aerostat envelope material concerning the gas permeability through the material. Accelerated aging tests at higher stress levels have been performed to obtain a life stress relationship from which service life of the material has been determined at the use level conditions. Validation of the proposed model has also been performed using the actual field test data. It will be worthy to apply this approach in various fields of application to predict the service life of newly developed materials before their commercialization.
Keywords:Service life prediction  Accelerated weathering  Natural weathering  Reliability model  Weibull distribution
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