Abstract
In order to reduce risks associated with Liquefied Natural Gas (LNG) production facilities, one approach is to provide real time and risk-based accident forecasting mechanisms and tools that will enable the early understanding of process deviations and link with possible accident scenarios. In this paper, process and fault modeling technique is presented to model causation models and link with accident scenarios using fault semantic networks (FSN). A forecasting algorithm is developed to identify and estimate safety measures for each operation step and process model element and validated with process condition.
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Gabbar, H.A. (2010). Fault Semantic Networks for Accident Forecasting of LNG Plants. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_44
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DOI: https://doi.org/10.1007/978-3-642-15390-7_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15389-1
Online ISBN: 978-3-642-15390-7
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