Stochastic Colored Petri Nets Research Articles

Refined Oil Loading and Unloading Process Risk Assessment using Stochastic Colored Petri Nets Integrated with Risk Factors

Refined Oil Loading and Unloading Process Risk Assessment using Stochastic Colored Petri Nets Integrated with Risk Factors

Modeling and performance analysis of emergency response process for hydrogen leakage and explosion accidents

To address concerns associated with the initial response process following hydrogen refueling station leakage and explosion accidents, this research introduces the utilization of stochastic colored Petri nets for dynamic modeling of the emergency response procedure. Through the construction of a process model for responding to hydrogen leakage and explosion accidents at refueling stations, the model's effectiveness is assessed using an Isomorphic Markov chain (MC) analysis approach, followed by simulation and analysis of the emergency response procedure. Furthermore, the performance of the emergency process in managing hydrogen leakage and explosion accidents at refueling stations is evaluated, considering place occupancy probabilities and transition utilization probabilities. By optimizing the timing of transitions, critical stages in the process for handling hydrogen leakage and explosion accidents at hydrogen refueling stations are identified, and recommendations for process enhancement are proposed. The findings reveal that continuous hydrogen leakage conditions and the phase involving the summoning of rescue personnel are prone to information congestion. The timely arrival of the on-site manager and the prompt reporting of incident details emerge as pivotal actions within the emergency response process for hydrogen refueling station leakage and combustion incidents. These actions wield substantial influence over the efficacy of emergency response and mitigation, underscoring their significance as primary areas for improvement.

Simulation models based on Petri nets for the analysis of maintenance and repair processes of complex technical systems

The presented review analyzes the approaches and methods of using simulation models in the maintenance and repair organization of the complex technical objects and systems. The development of the concept of "Industry 4.0" and the Internet of things involves the transition from periodic and preventive maintenance to predictive maintenance based on the study of processes during the object operation. It is shown that system models based on Petri nets are convenient for describing and analyzing technological processes and equipment maintenance. The effectiveness of timed stochastic colored Petri nets for virtual tests in the design of maintenance and repair procedures in complex systems is revealed. The use of hierarchical Petri nets allows building complex models that describe interrelated processes. A general model based on a hierarchical network is proposed to study the processes of deterioration and degradation of the technical object aggregates and elements and to form a predictive maintenance strategy. The model includes a Gantt chart of production tasks, a set of active and reserve units, maintenance and repair modules. The examples of simulation models on Petri nets for various technical systems are considered. Solutions for flexible production systems, railway bridges, offshore wind turbines, an aircraft fleet, a group of robotic vehicles, and a complex of computer equipment of an enterprise are given. The models of various maintenance strategies are considered and the generality of the models based on hierarchical Petri nets is shown. The article formulates methodological principles for constructing hierarchical networks to simulate the operation and maintenance of technical systems. The article analyzes known software tools for the implementation of timed stochastic colored Petri nets. The summary concludes that the use of simulation models on Petri nets is promising for organizing maintenance and repair of complex technical objects and systems.

Evaluating the Safety Control Scheme of Railway Centralized Traffic Control (CTC) System with Coloured Petri Nets

The Centralized Traffic Control (CTC) system plays an important role in ensuring safe and efficient rail transportation operations. It is mainly responsible for the implementation and adjustment of the train operation schedule through the automatic control of the station signalling equipment. The major task of the CTC system is to achieve a high rail transportation operation efficiency under the precondition of safety. For this purpose, it is necessary to select appropriate safety control schemes for the CTC system. In this paper, a formal approach is proposed to quantitatively evaluate the operation efficiencies of the CTC system with respect to different safety control schemes. The proposed approach adopts stochastic coloured Petri nets as the means of description for the system model, and evaluates the operation efficiency of the CTC system based on the data collected during the simulation of the system model. To exemplify the proposed approach, the safety control scheme of prohibiting a passenger train from passing a freight train through adjacent rail tracks between two adjacent stations is studied. The results of the case study show the feasibility of the proposed approach.

Qualitative and Quantitative Safety Evaluation of Train Control Systems (CTCS) With Stochastic Colored Petri Nets

Currently qualitative as well as quantitative safety analysis of railway systems are usually conducted through Fault Tree Analysis (FTA) and Event Tree Analysis (ETA). FTA and ETA display the causalities and consequences of hazards or accidents by means of linear event sequences, which makes it difficult to incorporate non-linear relationships such as feedback. The repair of failure system components is not considered in traditional FTA and ETA. Moreover, quantitative safety evaluation by FTA and ETA requires that failure events should be statistically independent. Considering these issues, we propose an approach of conducting qualitative as well as quantitative safety evaluation of the CTCS-3 with stochastic Coloured Petri Nets (CPNs). The hierarchical CPN model of the CTCS-3 takes the scenarios, movement of trains, the failure and repair of system components into account. The occurrence times of hazardous events of a CTCS-3 system is quantitatively evaluated with the numerical data collected during the simulation of the system model. The evaluation results demonstrate the feasibility of the proposed approach.

Model-based dependability evaluation of a Wireless Communication System in a Virtually Coupled Train Set

A new paradigm based on the concept of virtual coupling of train sets is being elaborated to provide innovative solutions so as to increase efficiency, operational flexibility, line capacity, competitiveness among market players and quality of consumer experience. Train-to-Train (T2T) and Train-to-Ground (T2G) wireless communications will be the backbone for the implementation of the virtual coupling functionalities. In the present paper, we perform a model-based dependability analysis of the wireless communication system under virtual coupling operation. Namely, Stochastic Colored Petri Net (SCPN) models are developed to depict the exchanges of the various information needed under virtual coupling operation. Dependability evaluation is then performed by means of simulation. In particular, the impact of various communication parameters is scrutinized while taking into account different operational scenarios. The obtained results allow the identification of the most impacting aspects on dependability analysis and provide valuable inputs to support the technological choices in terms of communication to implement virtual coupling.

Interdependent Healthcare Critical Infrastructure Analysis in a Spatiotemporal Environment: A Case Study

During an urban flooding scenario, Healthcare Critical Infrastructure (HCI) represents a critical and essential resource. As the flood levels rise and the existing HCI facilities struggle to keep up with the pace, the under-preparedness of most urban cities to address this challenge becomes evident. Due to the disruptions in the interdependent Critical Infrastructures (CI) network (i.e., water supply, communications, electricity, transportation, etc.), during an urban flooding event, the operations at the healthcare CI facilities are inevitably affected. Hence, there is a need to identify cascading CI failure scenarios to visualize the propagation of failure of one CI facility to another CI, which can impact vast geographical areas. The goal of this work is to develop an interdependent HCI simulation model in a spatiotemporal environment to understand the dynamics in real-time and model the propagation of cascading CI failures in an interdependent HCI network. The model is developed based on a real-world cascading CI failure case study on an interdependent HCI network during the flood disaster event in December 2015 at Chennai, TamilNadu, India. The interdependencies between the CI networks are modeled by using the Stochastic Colored Petri Net (SCPN) based modeling approach. SCPN is used to model a real-word process that occurs in parallel or concurrently. Furthermore, a geographic information system-based interface is integrated with the simulation model, to visualize the dynamic behavior of the interdependent HCI SCPN simulation model in a spatiotemporal environment. Such a dynamic simulation model can assist the decision-makers and emergency responders to rapidly simulate ‘what if’ kind of scenarios and consequently respond rapidly.

Modeling and Performance Analysis of Cognitive Radio Networks Using Stochastic Timed Colored Petri Nets

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.

Maintenance Process Simulation Based Maintainability Evaluation by Using Stochastic Colored Petri Net

Maintainability is a critical design characteristic of products. Maintainability evaluation plays an important role in maintainability design. Existing maintainability evaluation approaches neglect logistic effects on system maintainability. In this paper, tuples of stochastic colored petri nets (SCPN) are used to express the constituents of a maintenance process; and the maintenance process model is developed based on the SCPN. Approaches for calculating the required maintenance resources are proposed according to the state equation of the SCPN, and a method for calculating maintenance time is proposed by using an SCPN based discrete-event simulation. Finally, the line maintenance of a wheel steering system is used as a case study to illustrate the application and effectiveness of our proposed approaches. The work discussed herein provides a maintainability evaluation methodology based on the maintenance task demonstration that is conducted on the digital mockup of products. The approaches can be applied in the design stage when there are no physical mockups, and the maintainability design can be carried on concurrently with the development of products.

STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL

Abstract. The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.

STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL

The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.

Coloured stochastic Petri nets modelling for the reliability and maintenance analysis of multi-state multi-unit systems

Purpose – The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs. Design/methodology/approach – The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size. Findings – Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system. Research limitations/implications – The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered. Practical implications – The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies. Originality/value – The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

Attack Composition Model Based on Generalized Stochastic Colored Petri Nets

Attack modeling plays an important role in network security analysis and assessment. A Generalized Stochastic Colored Petri Net(GSCPN) model for attack composition is proposed. To each attack, a GSCPN model is constructed to describe the relation of components graphically. Operators to construct attack composition from known ones as blocks are defined formally. The algorithm to construct a composite attack is delivered, and the structural complexity of combination model is measured also. On this basis, the time cost of vulnerabilities is assessed. The network example validates further the effectiveness of the proposed composition model and calculation method.

Analysis of Effectiveness of Communication Overheads in the Parallel Computing System Using Stochastic Colored Petri Nets

In architectures of parallel computing system, which has a large number of processing nodes, communication overhead is an important metric to evaluate and minimize by improving computation speedup solutions. In this paper, we propose using Stochastic Colored Petri Net to give models of parallel computing multi-processing systems for analyzing and evaluating effectiveness of communication overheads to system performance.

Business Process Management System Modeling in the Virtual Enterprise Based on Stochastic Colored Petri Net

Traditional enterprise information systems have many defects, so business process management (BPM) system was applied to the virtual enterprise and virtual enterprise process model is established based on BPM system. The dominant enterprise and the member enterprises used BPM system for their own information management system in the virtual enterprise. The BPM system model of the virtual enterprise was divided into the formation process and the operation process. The analysis method based on stochastic colored Petri net(SCPN) was also presented which can be used to model and analyze the process model in order to obtain the system performance analysis data. The virtual enterprise resources utilization rate can be seen. The model extends the application area of BPM system and provides a reference for the construction and management of virtual enterprise.

Using Stochastic Colored Petri nets for Designing Multi-Purpose Plants

Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze multi-purpose plants. A simple approach is proposed to determine the utilization of shared resources and to reduce the equipment’s idle times. Three scenarios are presented to describe the proposed model. Generally, according to desire of a decision maker, different scenarios can be considered in the model to achieve to the expected design or plant configuration. The main characteristics of the proposed model are flexibility, the easiness of practical application and the simulation of the model in an easy way.

Colored stochastic Petri nets for modelling and analysis of multiclass retrial systems

Most retrial models assume that customers and servers are homogeneous. However, multiclass (or heterogeneous) retrial systems arise in various practical areas such as telecommunications and cellular mobile networks. Multiclass models are far more difficult for mathematical analysis than single class ones. So, explicit results are available only in few special cases. Actually, so far multiclass retrial systems have been analyzed only by means of queueing theory and almost all studies consider models with several customer’s classes and a service station consisting in one single server or multiple homogeneous (identic) servers and an infinite population size. In this paper, we propose an approach for modelling and analyzing finite-source retrial systems with several customer’s classes and server’s classes using the Colored Generalized Stochastic Petri Nets (CGSPNs). This high-level mathematical model is appropriate for describing and analyzing the performance of systems exhibiting concurrency and synchronization, possibly with heterogeneous components. Using a high-level formalism makes the description of the system easier, while preserving the possibility of obtaining exact performance results. We show how the main steady-state performance indices can be derived and we analyze the behaviour of heterogeneous retrial systems under two service disciplines. The numerical results are graphically displayed to illustrate the effect of system parameters and service discipline on the mean response time.

Coloured Petri nets and a dynamic reliability problem

One of the major problems of the system reliability calculation is an implementation of a dynamic behaviour. One way to show a possible representation of dynamic systems is by using coloured stochastic Petri nets (CSPNs). In this paper this approach is applied to one benchmark on the dynamic reliability taken from the literature. The system consists of a tank containing some liquid where the liquid level is controlled by suitable detectors acting on three hardware components that work independently. The modelled system is consequently used as an input for the calculation of the cumulative distribution functions and other characteristics (e.g. reliability of the system). As the next step, this benchmark will be modified. The first system modification is the maintenance action inclusion. The second one is the enhancement of the system by adding another process variable (the liquid temperature within the tank that is dependent on time). The CSPN approach is used to find a suitable representative scheme of these modifications.

Performance analysis of new stochastic colored Petri nets

While analyzing the system performance,the state space of stochastic Petri Nets increases exponentially with the accretion of the system scale,which causes the complexity of obtaining stabilization probability.Concerning this problem,we put forward a kind of Stochastic Colored Petri Net(SCPN),analyzed the limitary and reachable,and proved that SCPN is same as a continuous time Markov chain.At the same time,this article also analyzed the methods for modeling and quantitive performance analysis that the Stochastic Petri Nets(SPN)used.

Person-centred simulation of product development processes

In enterprises with multiple projects, product developers often fail to act according to project plans, even though the plans have been developed very thoroughly. The proposed person-centred simulation model can simulate more realistic courses of development projects. A major difference to existing models is the bounded rational decision making of the simulated product developers. The model was formally described by Timed Stochastic Coloured Petri Nets and was systematically verified using an analysis of variance. The results of a case study in a medium-sized enterprise show that the simulated project durations do not significantly differ from the historical data.