2023
DOI: 10.1007/s11696-023-03113-7
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Development of supervised machine learning model for prediction of TEG regeneration performance in natural gas dehydration

Amin Hedayati Moghaddam,
Abdellatif Mohammad Sadeq
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Cited by 2 publications
(1 citation statement)
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“…Teir study highlighted the importance of controlling BTEX emissions in natural gas dehydration units due to their harmful efects on human health, but could not integrate the two objectives simultaneously. Hedayati Moghaddam [33] and Moghaddam et al [34] investigated the performance of the wet natural gas dehydration process by absorption using liquid desiccant. Tazang et al [35] presented an approach to accurately model the solubilities of BTEX in triethylene glycol (TEG).…”
Section: Introductionmentioning
confidence: 99%
“…Teir study highlighted the importance of controlling BTEX emissions in natural gas dehydration units due to their harmful efects on human health, but could not integrate the two objectives simultaneously. Hedayati Moghaddam [33] and Moghaddam et al [34] investigated the performance of the wet natural gas dehydration process by absorption using liquid desiccant. Tazang et al [35] presented an approach to accurately model the solubilities of BTEX in triethylene glycol (TEG).…”
Section: Introductionmentioning
confidence: 99%