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A Development of Architecture for Risk Area Prediction System

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Parallel and Distributed Computing, Applications and Technologies (PDCAT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 931))

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Abstract

Risk area prediction system is a kind of safety management system that suggesting risk level to worker or humans resideing in chemical plant. This system is calculating safety distances based event consequence analysis according to API RP 581, EIGA Doc 75 standards, reference manual Bevi risk assessments. Safety distance could be estimated by calculating in sequential order of release module, dispersion module, and fire and explosion module. So, it needs to consider how to connect between each modules. Also, additional modules have to be developed to help derive safety distance and risk area from calculated results of fire or explosion effect modules. This paper introduce consequence analysis modules for estimating risk area from chemical plant data and chemical properties and architecture of connecting each modules. And risk gradation as a new risk expression concept will be provided for offering risk level to workers in chemical plant.

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Author information

Authors and Affiliations

  1. Korea Gas Safety Corporation, Eumseong, Republic of Korea

    Ugiwyeon Lee & Jeongseok Oh

Authors
  1. Ugiwyeon Lee
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  2. Jeongseok Oh
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Corresponding author

Correspondence to Jeongseok Oh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    Jong Hyuk Park

  2. School of Computer Science, University of Adelaide, Adelaide, SA, Australia

    Hong Shen

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Yunsick Sung

  4. School of ICT, Griffith University, Gold Coast, Australia

    Hui Tian

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© 2019 Springer Nature Singapore Pte Ltd.

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Lee, U., Oh, J. (2019). A Development of Architecture for Risk Area Prediction System. In: Park, J., Shen, H., Sung, Y., Tian, H. (eds) Parallel and Distributed Computing, Applications and Technologies. PDCAT 2018. Communications in Computer and Information Science, vol 931. Springer, Singapore. https://doi.org/10.1007/978-981-13-5907-1_31

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  • DOI: https://doi.org/10.1007/978-981-13-5907-1_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5906-4

  • Online ISBN: 978-981-13-5907-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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