Browsing by Author "Modarres, Mohammed"
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Item Application of Goal Tree-Success Tree Model as the Knowledge- Base of Operator Advisory Systems.(1987) Kim, I.S.; Modarres, Mohammed; ISRThe most important portion of an expert system development is the articulation of knowledge by the expert and its satisfactory formulation in a suitable knowledge representation scheme for mechanization by a computer. A "deep knowledge" approach called Goal Tree-Success Tree model is devised to represent complex dynamic domain knowledge. This approach can hierarchically model the underlying principles of a given process domain (for example nuclear power plant operations domain). The Goal Tree-Success Tree can then be used to represent the knowledge-base and provide means of selecting an efficient search routine in the inference engine of an expert system.Item Application of Goal Tree-Success Tree Model as the Knowledge- Base of Operator Advisory Systems.(1986) Kim, I.S.; Modarres, Mohammed; ISRThe most important portion of an expert system development is the articulation of knowledge by the expert and its satisfactory formulation in a suitable knowledge representation scheme for mechanization by a computer. A "deep knowledge" approach called Goal Tree-Success Tree model is devised to represent complex dynamic domain knowledge. This approach can hierarchically model the underlying principles of a given process domain (for example nuclear power plant operations domain). The Goal Tree-Success Tree can then be used to represent the knowledge-base and provide means of selecting an efficient search routine in the inference engine of an expert system. A prototype expert system has been developed to demonstrate the method. This expert system models the operation of a typical feedwater system used in the pressurized water reactors. The expert system is modeled for real-time operations if an interface between plant parameters , the expert system is established. The real-time operation provides an ability to quickly remedy minor-disturbances that can quickly lead to system malfunction or trip.Item A Correlation Model to Analyze Dependent Variables.(1986) Dezfuli, H.; Modarres, Mohammed; ISRIn this paper a methodology is formulated to study the dependency between two variables. Statistical correlation coefficient between two variables is used as a measure of the degree of dependency. The method of bootstrap technique is employed to account for the statistical uncertainty in the correlation coefficient that is estimated from available data. A computer program entitled correlation coefficient generafor (CCG) is developed to perform the analysis. An example is also presented to demonstrate the methodology. The objective of this example is to determine the dependency between specific actions of control room operator of a nuclear power plant. The methodology and the CCG code are very effective and easy to use.Item Gotres: An Expert System for Fault Detection and Analysis.(1988) Chung, Donald T.; Modarres, Mohammed; ISRThis paper describes a deep-knowledge expert system shell for diagnosing faults in process operations. The expert program shell is called GOTRES (GOal TRee Expert System) and uses a goal tree- success tree deep-knowledge structure to model its knowledge- base. To demonstrate GOTRES, we have built an on-line fault diagnosis expert system for an experimental nuclear reactor facility using this shell. The expert system is capable of diagnosing fault conditions using system goal tree as well as utilizing accumulated operating knowledge to predict plant causal and temporal behaviors. The GOTRES shell has also been used for root-cause detection and analysis in a nuclear plant.Item A Method of Alarm System Analysis in Process Plants with the Aid of an Expert Computer System.(1985) Modarres, Mohammed; Cadman, T.; ISRDesign and improvement of alarm systems in process plants has been given considerable attention recently. A methodology is presented in this paper which can be used as an aid in the design of new alarm systems or in the improvement of existing alarm systems. The methodology is incorporated in a computer software into which expert knowledge of a given process plant can be entered and used to select a proper alarm system.Item A Method of Fault Diagnosis: Presentation of a Deep Knowledge System.(1987) Chung, Donald T.; Modarres, Mohammed; ISRIn fault diagnostic expert systems, the knowledge can be either shallow (experience-based) or deep (function-based). This paper presents a deep-knowledge expert system for fault detection in process operations and control domain. The structure used for modelling deep-knowledge is called Goal-Tree-Success Tree. An expert system shell has been built for applying this deep- knowledge model utilizing the logic based language PROLOG. An example, applying this deep-knowledge model and the developed expert system shell, is also presented.Item A Method of Fault Diagnosis: Presentation of a Deep Knowledge System.(1986) Chung, Donald T.; Modarres, Mohammed; ISRIn fault diagnostic expert systems, the knowledge can be either shallow (experience-based) or deep (function-based). This paper presents a deep-knowledge expert system for fault detection in process operations and control domain. The structure used for modelling deep-knowledge is called Goal-Tree Success Tree. An expert system shell has been built for applying this deep- knowledge model utilizing the logic based language PROLOG. An example, applying this deep-knowledge model and the developed expert system shell, is also presented.Item A Method of Fault Diagnosis: Presentation of a Deep-Knowledge System.(1987) Chung, Donald T.; Modarres, Mohammed; ISRThe purpose of this paper is to present an expert system shell (GOTRES) that utilizes a deep knowledge model which is based on specific plant goals. In this method, the principles of process operations and control are organized in a hierarchial tree structure. This method of modelling knowledge is known as Goal Tree-Success Tree (GTST) [12].Item A Model-Based Approach to On-Line Process Disturbance Management: The Models.(1988) Kim, I.S.; Modarres, Mohammed; Hunt, R.N.M.; ISRA methodology is proposed which can be used to design real-time expert systems for on-line process disturbance management. This methodology encompasses diverse functional aspects that are required for an effective process disturbance management: 1) intelligent process monitoring and alarming, 2) on-line sensor data validation and sensor conflict resolution, 3) on-line hardware failure diagnosis, and 4) real-time corrective measure synthesis. Accomplishment of these functions is made possible through the integrated application of the various models, goal- tree success-tree, process monitor tree, sensor failure diagnosis, and hardware failure diagnosis models. This paper presents and discusses the various models along with the overall algorithm of the methodology. The application of the methodology to a target process, a typical main feedwater system of a nuclear power plant which employs a complex control mechanism, will be presented in a companion paper.Item Probabilistic Risk Assessment: A Look at the Role of Artificial Intelligence.(1987) Wang, J.; Modarres, Mohammed; Hunt, R.N.M.; ISR