Modeling Complex System Using T-subnet based Hierarchical Petri Nets

2009 ◽  
Vol 4 (9) ◽  
Author(s):  
Zhijian Wang ◽  
Dingguo Wei
2021 ◽  
Author(s):  
M.V. Pirogov

Complex artificial purposeful systems and their software and hardware are characterized not only by achievements, but also disadvantages leading to significant losses. Modern automation tools do not fully cope with the existing problems. To solve the problems of complex systems, new effective tools are needed, new modeling technology. This technology should cover all significant aspects of the problem area. It seems that such technology should be based on radical modeling and the universal language of radical schemes RADICAL. A radical is a system characterized by both active (working) and passive states. Being connected with each other radicals form schemes of radicals. These schemes are constructions of the RADICAL language. In the aggregate, these schemes realize radical environment – radical model of united problem area of complex system. That is, the problem area is represented by a single global scheme of radicals. The work with such a scheme is carried out using the universal language of radical schemes RADICAL, applicable to the problem area of any complex system by constructing sections of the RADICAL language, expressed by the schemes of radicals. The purpose of the work is to consider the use of radical schemes for the implementation of the structures of sections (sequences of sections) of the RADICAL language when modeling complex system. The results of the work are descriptions of some typical schemes of radicals intended for the implementation of the section structures of the RADICAL language when modeling complex purposeful systems. Something significant sequences of sections are considered. The practice of using of structures of cross-sections of the media of radicals, expressed by the schemes of radicals, indicates the expediency of they use for radical modeling of problem areas of complex purposeful systems, for the development and modification of software and information support of such systems.


Author(s):  
Feng Ye ◽  
Guo-xing Lan ◽  
Ye-quan Cai ◽  
Ying-chao Zhang
Keyword(s):  

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thangamani Gurunathan

PurposeThe purpose of this paper to present a practical and systematic approach to estimate the availability of a process plant using generalized stochastic Petri nets (GSPNs). The actual live problem at a fluid catalytic cracking unit (FCCU) of a refinery is used to demonstrate this approach.Design/methodology/approachA majority of models used for estimation of availability of a complex system are based on the assumptions that the failure of the system is associated with only a few states, and the system does not face different operating conditions, repair actions and common-cause failures. In reality, this is often not the case. Therefore, it is necessary to construct more sophisticated models without such assumptions. In this paper, an attempt has been made to model interaction of component failures, partial failures of components and common-cause failures.FindingsThe superiority of this approach over other modeling approaches such as fault tree and Markov analysis is demonstrated. The proposed GSPN is a promising tool that can be conveniently used to model and analyze any complex systems.Practical implicationsGSPN was used to model the reactor-regenerator section of FCCU, which is quite a large system, which shows the strength of modeling capability. The use of Petri nets (PNs) for modeling complex systems for the purpose of availability assessment is demonstrated in this paper. Sensitivity analysis was also carried out for various subsystem/components.Originality/valueNo similar work has been conducted for FCCU using GSPN as per literature incorporating different operating conditions and common-cause failures. The understanding and usage of PNs require a steep learning curve for the practitioners, and this paper provides an approach to estimate availability measures for the complex system.


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