One of the important thing in the mitigation of accidents in nuclear power plant accidents is time management. The accidents should be resolved as soon as possible in order to prevent the core melting and the release ...
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One of the important thing in the mitigation of accidents in nuclear power plant accidents is time management. The accidents should be resolved as soon as possible in order to prevent the core melting and the release of radioactive material to the environment. In this case, operators should follow the emergency operating procedure related with the accident, in step by step order and in allowable time. Nowadays, the advanced main control rooms are equipped with computer-based procedures (CBPs) which is make it easier for operators to do their tasks of monitoring and controlling the reactor. However, most of the CBPs do not include the time remaining display feature which informs operators of time available for them to execute procedure steps and warns them if the they reach the time limit. Furthermore, the feature will increase the awareness of operators about their current situation in the procedure. This paper investigates this issue. The simplified of emergency operating procedure (EOP) of steam generator tube rupture (SGTR) accident of PWR plant is applied. In addition, the sequence of actions on each step of the procedure is modelled using multilevel flow modelling (MFM) and influenced propagation rule. The prediction of action time on each step is acquired based on similar case accidents and the Support Vector Regression. The derived time will be processed and then displayed on a CBP user interface.
This paper presents a goal based methodology for HAZOP studies in which a functional model of the plant is used to assist in a functional decomposition of the plant starting from the purpose of the plant and continuin...
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This paper presents a goal based methodology for HAZOP studies in which a functional model of the plant is used to assist in a functional decomposition of the plant starting from the purpose of the plant and continuing down to the function of a single node, e.g. a pipe section. This approach leads to nodes with simple functions such as liquid transport, gas transport, liquid storage, gas-liquid contacting etc. From the functions of the nodes the selection of relevant process variables and deviation variables follows directly. The knowledge required to perform the pre-meeting HAZOP task of dividing the plant along functional lines is that of chemical unit operations and transport processes plus a some familiarity with the plant a hand. Thus the preparatory work may be performed by a chemical engineer with just an introductory course in risk assessment. The goal based methodology lends itself directly for implementation into a computer aided reasoning tool for HAZOP studies to perform root cause and consequence analysis. Such a tool will facilitate finding causes far away from the site of the deviation. A Functional HAZOP Assistant is proposed and investigated in a HAZOP study of an industrial scale Indirect Vapour Recompression Distillation pilot Plant(IVa RDi P) at the DTU-Dept. of Chemical and Biochemical Engineering. The study shows that the goal based methodology using a functional approach provides a very efficient paradigm for facilitating HAZOP studies and for enabling reasoning to reveal potential hazards in safety critical operations.
The aim of this paper is to present an intelligent software tool, using Artificial Intelligence (AI) techniques, which allows the execution of an alarm analysis, during the remote sensing activity of complex plants. T...
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ISBN:
(纸本)1843394685
The aim of this paper is to present an intelligent software tool, using Artificial Intelligence (AI) techniques, which allows the execution of an alarm analysis, during the remote sensing activity of complex plants. The AI component allows to identify all the primary faults of the system, discriminating them from the side effect alarms. In other words this tool shows which alarms are directly connected to primary faults and which alarms are consequential effects of the primary ones. The core of the software is an algorithm which uses a knowledge ontology and a set of alarm propagation rules, which are both based on a multilevel flow modelling (MFM) paradigm. The algorithm has been tested implementing a rule based expert system (RBES) referred to an existing water plant. The main features of the water plant have been identified and all the main components and their possible alarm states have been analyzed to carry out the knowledge base.
Facing a growing complexity of industrial plants, we recognise the need for qualitative modelling methods capturing functional and causal complexity in a human-centred way. The present paper presents actant modelling ...
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Facing a growing complexity of industrial plants, we recognise the need for qualitative modelling methods capturing functional and causal complexity in a human-centred way. The present paper presents actant modelling as a functional modelling method rooted in linguistics and semiotics. Actant modelling combines actant models from linguistics with multilevel flow modelling (MFM). Thus the semantics of MFM functions is developed further and given an interpretation in terms of actant functions. The present challenge is to provide coherence between seemingly different categories of knowledge. Yet the gap between functional and causal modelling methods can be bridged. Actant modelling provides an open and provisional, but in no way exhaustive or final answer as to how teleological concepts like goals and functions relate to causal concepts. As the main focus of the paper an actant model of an extraction plant is presented. It is shown how the actant model merges functional and causal knowledge in a natural way. (C) 1999 Elsevier Science Ltd. All rights reserved.
In industrial plant projects much of the design knowledge is lost. Design documents typically concentrate on implementation-oriented structural information that is required to construct the plant. The documents to a g...
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In industrial plant projects much of the design knowledge is lost. Design documents typically concentrate on implementation-oriented structural information that is required to construct the plant. The documents to a great extent lack the functional knowledge representing the original design intentions, formed mainly during the conceptual design stage, and information on the design process. As a result, the design documents do not contain answers to questions about the purpose of the design. One typically cannot find any justifications for the design decisions, e.g. the selection of one of several apparently sufficiently good alternatives. Yet both kinds of information have proven to be important for effective co-operation of designers within a project, for succeeding projects, and for the operation and maintenance of the resulting plant. This thesis addresses the problem of structuring, recording, and transferring the design knowledge between designers and from the designers to the end users. The proposed solution is to introduce formal knowledge representations powerful enough to express the relevant concepts of the domain into the design process. With these representations and supporting tools we aim to structure and record the functional design knowledge at design time. multilevel flow modelling is used to capture the functional knowledge of the plant. The resulting conceptual model is utilised for structuring the informal design knowledge related to both the designed artefact and the design process. Based on two validating industrial cases, the approach seems able to capture this design knowledge in industrial plant projects. On-line presentation of the functional knowledge to the plant operators is discussed. Our work emphasises the consistent presentation of the conceptual model created by the designers to the operators during the training sessions, in the user interfaces and alarm systems of the plant's automation systems, and in the on-line documentation sys
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