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State-based modelling in hazard identification
The signed directed graph (SDG) is the most commonly used type of model for automated hazard identification in chemical plants. Although SDG models are efficient in simulating the plant, they have some weaknesses, which are discussed here in relation to typical process industry examples. Ways to tac...
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| Main Authors: | , , |
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| Format: | Default Article |
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2006
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/2337 |
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| _version_ | 1818175662059421696 |
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| author | Stephen A. McCoy Dingfeng Zhou Paul Chung |
| author_facet | Stephen A. McCoy Dingfeng Zhou Paul Chung |
| author_sort | Stephen A. McCoy (7127738) |
| collection | Figshare |
| description | The signed directed graph (SDG) is the most commonly used type of model for automated hazard identification in chemical plants. Although SDG models are efficient in simulating the plant, they have some weaknesses, which are discussed here in relation to typical process industry examples. Ways to tackle these problems are suggested, and the view is taken that a state-based formalism is needed, to take account of the discrete components in the system, their connection together, and their behaviour over time. A strong representation for operations and actions is also needed, to make the models appropriate for modelling batch processes. A research prototype for HAZOP studies on batch plants (CHECKOP) is also presented, as an illustration of the suggested approach to modelling. |
| format | Default Article |
| id | rr-article-9403298 |
| institution | Loughborough University |
| publishDate | 2006 |
| record_format | Figshare |
| spelling | rr-article-94032982006-01-01T00:00:00Z State-based modelling in hazard identification Stephen A. McCoy (7127738) Dingfeng Zhou (7169084) Paul Chung (1250973) Artificial intelligence not elsewhere classified Other information and computing sciences not elsewhere classified model-based reasoning qualitative modelling simulation batch HAZOP Artificial Intelligence and Image Processing Information and Computing Sciences not elsewhere classified The signed directed graph (SDG) is the most commonly used type of model for automated hazard identification in chemical plants. Although SDG models are efficient in simulating the plant, they have some weaknesses, which are discussed here in relation to typical process industry examples. Ways to tackle these problems are suggested, and the view is taken that a state-based formalism is needed, to take account of the discrete components in the system, their connection together, and their behaviour over time. A strong representation for operations and actions is also needed, to make the models appropriate for modelling batch processes. A research prototype for HAZOP studies on batch plants (CHECKOP) is also presented, as an illustration of the suggested approach to modelling. 2006-01-01T00:00:00Z Text Journal contribution 2134/2337 https://figshare.com/articles/journal_contribution/State-based_modelling_in_hazard_identification/9403298 CC BY-NC-ND 4.0 |
| spellingShingle | Artificial intelligence not elsewhere classified Other information and computing sciences not elsewhere classified model-based reasoning qualitative modelling simulation batch HAZOP Artificial Intelligence and Image Processing Information and Computing Sciences not elsewhere classified Stephen A. McCoy Dingfeng Zhou Paul Chung State-based modelling in hazard identification |
| title | State-based modelling in hazard identification |
| title_full | State-based modelling in hazard identification |
| title_fullStr | State-based modelling in hazard identification |
| title_full_unstemmed | State-based modelling in hazard identification |
| title_short | State-based modelling in hazard identification |
| title_sort | state-based modelling in hazard identification |
| topic | Artificial intelligence not elsewhere classified Other information and computing sciences not elsewhere classified model-based reasoning qualitative modelling simulation batch HAZOP Artificial Intelligence and Image Processing Information and Computing Sciences not elsewhere classified |
| url | https://hdl.handle.net/2134/2337 |