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|Title: ||Combining qualitative and quantitative reasoning to support hazard identification by computer|
|Authors: ||McCoy, Stephen A.|
|Keywords: ||HAZOP Emulation|
|Issue Date: ||1999|
|Publisher: ||© Stephen McCoy|
|Abstract: ||This thesis investigates the proposition that use must be made of quantitative
information to control the reporting of hazard scenarios in automatically generated
HAZOP is a successful and widely accepted technique for identification of process
hazards. However, it requires an expensive commitment of time and personnel near
the end of a project. Use of a HAZOP emulation tool before conventional HAZOP
could speed up the examination of routine hazards, or identify deficiencies I in the
design of a plant.
Qualitative models of process equipment can efficiently model fault propagation in
chemical plants. However, purely qualitative models lack the representational power
to model many constraints in real plants, resulting in indiscriminate reporting of
In the AutoHAZID computer program, qualitative reasoning is used to emulate
HAZOP. Signed-directed graph (SDG) models of equipment are used to build a graph
model of the plant. This graph is searched to find links between faults and
consequences, which are reported as hazardous scenarios associated with process
variable deviations. However, factors not represented in the SDG, such as the fluids in
the plant, often affect the feasibility of scenarios.
Support for the qualitative model system, in the form of quantitative judgements to
assess the feasibility of certain hazards, was investigated and is reported here. This
thesis also describes the novel "Fluid Modelling System" (FMS) which now provides
this quantitative support mechanism in AutoHAZID. The FMS allows the attachment
of conditions to SDG arcs. Fault paths are validated by testing the conditions along
their arcs. Infeasible scenarios are removed.
In the FMS, numerical limits on process variable deviations have been used to assess
the sufficiency of a given fault to cause any linked consequence. In a number of case
studies, use of the FMS in AutoHAZID has improved the focus of the automatically
generated HAZOP results.
This thesis describes qualitative model-based methods for identifying process hazards
by computer, in particular AutoHAZID. It identifies a range of problems where the
purely qualitative approach is inadequate and demonstrates how such problems can be
tackled by selective use of quantitative information about the plant or the fluids in it.
The conclusion is that quantitative knowledge is' required to support the qualitative
reasoning in hazard identification by computer.|
|Description: ||A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.|
|Appears in Collections:||PhD Theses (Chemical Engineering)|
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