2016
DOI: 10.1016/j.proeng.2016.06.423
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Importance of Increased Knowledge on Reliability of District Heating Pipes

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Cited by 18 publications
(6 citation statements)
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References 30 publications
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“…Senouci et al developed an ANN base model to predict oil and gas pipeline failures for various failure types as well as mechanical operational and corrosion with an average validity of 92 % [42]. Sharma employed RNN in combination with a long Environmental and Climate Technologies ____________________________________________________________________________ 2020 / 24 302 short-term memory (LSTM) for predictive maintenance and asset management in oil and gas industry [43].…”
Section: Discussionmentioning
confidence: 99%
“…Senouci et al developed an ANN base model to predict oil and gas pipeline failures for various failure types as well as mechanical operational and corrosion with an average validity of 92 % [42]. Sharma employed RNN in combination with a long Environmental and Climate Technologies ____________________________________________________________________________ 2020 / 24 302 short-term memory (LSTM) for predictive maintenance and asset management in oil and gas industry [43].…”
Section: Discussionmentioning
confidence: 99%
“…In paper [4], three groups of factors that cause wear of pipelines of central heating systems were considered, namely physical, environmental and operational. Recommendations for preventing damage to pipelines are given.…”
Section: Engineeringmentioning
confidence: 99%
“…Furthermore, high temperature-sustaining materials (i.e., steel) must be used for the network [14], including heat exchangers, valves and instrumentations. Moreover, integration in the network is suitable only for high temperature sources, thus limiting the possibility of renewables exploitation [15,16].…”
Section: Introductionmentioning
confidence: 99%