Search

To solve the problems of chaotic information management and difficult traceability in the manufacturing process of transformer coils, a traceability and management method oriented towards the manufacturing process of transformer coils has been proposed. This method integrates industrial internet identification resolution and extension of Petri net modeling theory. A comprehensive identification and resolution framework for coil manufacturing processes has been constructed. In this manuscript, the authors proposed an industrial data-sharing space based on the producer-consumer model with unified coding identification. This enables information sharing for all resources, including personnel, machinery, materials, methods, environment, and measurements. A method for modeling extensible identification primitives of coil manufacturing process information was proposed, which formalizes the correlation and data structure of process information. A Petri net model for the comprehensive acquisition and integration of elemental information in coil manufacturing processes, as well as a mathematical model for quality traceability, were constructed, thereby forming a complete path for quality traceability information. Finally, based on the method proposed above, a software and hardware environment for identification and traceability for coil manufacturing was established. Taking a certain type of coil as an example, validation was carried out; the results indicate a significant enhancement in the production management and information traceability capabilities of the coil production workshop. This study provides reference and guidance for the process traceability management of power equipment manufacturing. [ABSTRACT FROM AUTHOR]

Timed event graphs (TEGs) are mathematical models for the dynamics of discrete systems. A TEG is a directed graph consisting of two kinds of nodes, called places and transitions, and directed arcs between places and transitions. Each place can contain tokens that move around by firings of transitions, which is determined by the holding times assigned to places. In the weighted timed event graphs (WTEGs), the weights are assigned to the arcs and these weights represent the number of the tokens consumed or produced by the firing of the adjacent transitions. Unlike usual timed event graphs, weights on arcs make it difficult to describe the evolution of systems in simple mathematical formulae. The main purpose of this paper is to derive max-plus algebraic evolution equations for unitary WTEGs. We focus on the numbers indicating how many times each transition fires to reach the original token configuration again. Such numbers are known as the minimal T-semiflow and are computed from arc weights. We expand the dimension of the firing time vector by dividing the original variables into several variables, but it does not depend on the number of tokens. We also show that max-plus coefficient matrices in the evolution equation provide important information about the dynamics of a unitary WTEG. For example, the nilpotency of the coefficient matrix in the highest order term means the liveness of the WTEG. In this case, the average cycle time of the WTEG is computed as the eigenvalue of a certain max-plus matrix. [ABSTRACT FROM AUTHOR]

In order to express the energy flow, motion flow, and control flow in wireless rechargeable sensor networks accurately and intuitively, and to maximize the charging benefit of MVs (mobile vehicles), a type of MTS-HACO (Mobile Transition Sequence Hybrid Ant Colony Optimization) is proposed. Firstly, node places are grouped according to the firing time of node's energy consumption transition to ensure that in each time slot, MV places only enable charging transitions for the node places with lower remaining lifetimes. Then, the FSOMCT (Firing Sequence Optimization of Mobile Charging Transition) problem is formulated under the constraints of MV places capacity, travelling arc weight, charging arc weight, and so on. The elite strategy and the Max–Min Ant Colony system are further introduced to improve the ant colony algorithm, while the improved FWA (fireworks algorithm) optimizes the path constructed by each ant. Finally, the optimal mobile charging transition firing sequence and charging times are obtained, ensuring that MVs have sufficient energy to return to the base station. Simulation results indicate that, compared with the periodic algorithm and the PE-FWA algorithm, the proposed method can improve charging benefit by approximately 48.7% and 26.3%, respectively. [ABSTRACT FROM AUTHOR]

The airport apron is a high-risk area for aircraft collisions due to its heavy operational load and high aircraft density. Currently, existing quantitative models for apron collision risk provide limited consideration and classification of risk areas. In response, this paper proposes a Petri net-based method for assessing aircraft collision risk. The method predicts the probability of aircraft reaching different areas at different times based on operational data, enabling the calculation of collision risks within the Petri net framework. This approach highlights areas with potential collision risks and provides a classification evaluation. Subsequently, aircraft path re-planning is carried out to reduce collision risks. The model simplifies the complex operations of the apron system, making the calculation process clearer. The results show that, during the mid-phase of aircraft taxiing, there is a significant deviation between the actual and ideal positions of aircraft. Areas with high taxiway occupancy are more prone to collision risks. On peak days, due to relatively high flight volumes, the frequency of collision risks is 14% higher than on regular days, with an average risk increase of 23.3%, and the risks are more concentrated. Therefore, reducing collision risks through path planning becomes more challenging. It is recommended to focus attention on areas with high taxiway occupancy during peak periods and carefully plan routes to ensure apron safety. [ABSTRACT FROM AUTHOR]

This paper introduces software patterns (registration, acquire-release, and cache awareness) and data structures (Petri net, finite state machine, and protocol flag array) to support the coordinated execution of software activities (also called "components" or "agents"). Moreover, it presents and tests an implementation for Petri nets that supports real-time execution in shared memory for deployment inside one individual robot and separates event firing and handling, enabling distributed deployment between multiple robots. Experimental validation of the introduced patterns and data structures is performed within the context of activities for task execution, control and perception, and decision making for an application on coordinated navigation. [ABSTRACT FROM AUTHOR]

This paper addresses the one-dimensional cutting stock problem, focusing on minimizing total stock usage. Most procedures that deal with this problem reside on linear programming methods, heuristics, metaheuristics, and hybridizations. These methods face drawbacks like handling only low-complexity instances or requiring extensive parameter tuning. To address these limitations we develop a Petri-net model to construct cutting patterns. Using the filtered beam search algorithm, the reachability tree of the Petri net is constructed level by level from its root node to find the best solution, pruning the nodes that worsen the solution as the search progresses through the tree. Our algorithm is compared with the Least Lost Algorithm and the Generate and Solve algorithm over five datasets of instances. These algorithms share some characteristics with ours and have proven to be effective and efficient. Experimental results demonstrate that our algorithm effectively finds optimal and near-optimalsolutions for both low and high-complexity instances. These findings confirm that Petri nets are suitable for modeling and solving the one-dimensional cutting stock problem. [ABSTRACT FROM AUTHOR]

This survey paper explores Petri Net tools relevant to concurrent, non-deterministic, stochastic, and parallel systems. It begins with a brief introduction to Petri Nets, discussing their formalism, properties, and variants. The paper then examines several Petri Net tools, including the Oris Tool, Tapaal Tool, and Color Petri Net (CPN) Tool, detailing their modeling capabilities and presenting the results obtained from the problems addressed. [ABSTRACT FROM AUTHOR]

Objective. The purpose of the study is to use artificial intelligence tools to optimize and model the automated organization of work at a mass service enterprise. Method. The research is based on the use of a Petri net as a modeling tool, as well as mathematical hardware that makes it possible to implement simulation models of subsystems and conduct additional research on GPSS artificial intelligence models. Result. To process the results of the modeling process, the Petri net modeling method was used and a network activity model graph was developed. The modeling process used with the Petri Net application allows such functions to be described more clearly. The principles of modeling systems based on the GPSS language and Petri nets are considered. Conclusion. It is advisable to use the language devices GPSS and SP, which provide information support for the activities of a mass service enterprise, modeling the structural organization and information flows.

Nowadays, applying additive manufacturing (AM) technologies into a supply chain (SC) permits realization of the so-called “demand chains” and transformation of conventional production to mass customization. However, integration of AM technologies within an SC indicates the need to support managers’ decision about such an investment. Therefore, this work develops a Petri net-based decision support model that determines the changes in an SC by adopting AM and improving customer-perceived value (CPV), based on a case study regarding a real-life metal production process. The basis for building such a model is the supply chain operation reference model (SCOR), focusing on CPV, due to the need for redesigning the SC starting from the customer instead of the company. To achieve the research objective, this work introduces a novel verification methodology for a Petri net-based decision model. The research results show that applying the developed model, which is based on the selected characteristics of the production process and parameters describing the potential integration of AM within the SC, allows managers to perceive a scenario in the form of graphical models about positive or negative impacts of introducing AM into the SC. The managers find the Petri net-based decision support model presented in this paper a beneficial tool to support the implementation of changes in an SC and show the potential increase in customer satisfaction thanks to the integration of AM within an SC.

Hyperledger Fabric is a platform for permissioned blockchain networks that enables secure and auditable distributed data storage for enterprise applications. There is a growing interest in applications based on this platform, but its use requires the configuration of different blockchain parameters. Various configurations impact the system's non-functional qualities, especially performance and cost. In this article, we propose a Stochastic Petri Net to model the performance of the Hyperledger Fabric platform with different blockchain parameters, computer capacity, and transaction rates. We also present a set of case studies to demonstrate the feasibility of the proposed model. This model serves as a practical guide to help administrators of permissioned blockchain networks find the best performance for their applications. The proposed model allowed us to identify the block size that leads to a high mean response time (ranging from 1 to 25 seconds) caused by a change in the arrival rate. [ABSTRACT FROM AUTHOR]

Aiming at the problems of weak expressive ability and narrow scope of application in extended colored logical Petri net, timed colored logical Petri net is proposed. Firstly, instantiating colors and using variables to build expressions on directed edges enables the model to transmit complex data flows. Secondly, concepts such as global time and timestamp are introduced to add time constraints to transition enabling rules, so that the model can be used to simulate real-time systems. Thirdly, place restriction functions are defined and constraints on the output places are added to the transition enabling rules, so that the model can be applied to scenes with limited storage resources. Next, a matrix matching method based on logical transition input-output matrix is proposed, which can reduce the calculation cost of the enable decision of the logic input transition and simplify the calculation process of the enable decision of the logic output transition. Then, this paper redefines the enabling rules for three types of transitions and the mark updating methods for three types of places, in order to solve the problem that the semantics of the old model is not applicable to the new model. Finally, an example is given to illustrate that the new Petri net model has stronger expression ability and scope of application, and it can be applied to systems that transmit complex data flows, with limited storage resources, real-time and with batch processing selection structures.

As a typical information system, a cloud file system enables the storage, retrieval, and management of data on remote servers or server clusters. The reliable design of such systems is critical to ensure the security of data and availability of services. However, designing correct-by-construction systems is challenging due to the complexity of and concurrency inherent in cloud file systems. Further, existing works on cloud file system analysis often focus on specific systems or lack formal modeling and verification, leading to potential design flaws and security vulnerabilities. To address these issues, we propose MSCFS-RP, which is a formal analysis model based on colored Petri nets. Leveraging the strengths of colored Petri nets in representing diverse information types with colored tokens and defining explicit rules for concurrent interactions, our model captures the writing and reading processes of clients, meta servers, and clusters. With strong formalism and support for verification using CPN Tools, we rigorously evaluate key properties such as replication consistency under various scenarios. The results demonstrate that MSCFS-RP satisfies these properties, validating its effectiveness and trustworthiness in managing information within cloud storage systems. [ABSTRACT FROM AUTHOR]

For all the nuclear reactor systems, quantitative assessment of the accident management (AM) effects against long-term external hazards became one of the essential issues after the lesson learned from the Fukushima Daiichi Nuclear Power Plant accident. However, the influence from the safety systems' stochastic and dynamic shifting between multiple working states, which is related to the interaction with the adjacent components/systems in general, has not been accounted for yet. Therefore, this research aims to develop a dynamic probability risk assessment tool considering repairable multi-component interdependency for investigating the AM influences on the multi-state safety systems under long-term external hazards. Based on the newly proposed methodology in this research via integrating the Petri net (PN) model with the continuous Markov chain Monte Carlo (CMMC) method, a framework applying PN-CMMC methodology to a severe accident analysis code, SPECTRA, had been originally constructed. Different AM influences on the multi-state decay heat removal systems against long-term volcanic ashfall were also quantitatively confirmed, indicating that halving the repairing time is more influential in suppressing the core damage frequency than doubling the number of adjacent electricity support systems. Therefore, the PN-CMMC-SPECTRA framework can further assess the uncharted dynamic multi-state concerns, leading to a safer AM strategy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vehicular Ad-Hoc Networks have increased the opportunity to use Cognitive Radio (CR) to cope with spectrum scarcity and increase reliability. Despite all efforts to improve the reliability of CR-VANETs, there are no mathematical and scalable methods for modelling and evaluating CR-VANETs. This paper investigates the problem of assessing the reliability of a multi-hop and multi-channel CR-VANET in safety applications. Two formal and scalable methods, Boolean notation and the Petri Net model, are provided to model and evaluate the reliability of CR-VANET. We give a detailed simulation study with NS3 to support our theory. Our analytical and simulation results indicate the effectiveness of CR in increasing the reliability of VANET. By these results, one can evaluate the network's reliability and tune the network parameters for better reliability. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed research method is strictly aimed at further practical applications. The authors present the design technique aimed at the effective implementation of the modeled concurrent control system within the FPGA device. The main goal is the reduction in the logic resources of the destination FPGA by adequate modeling and optimization of the system. The proposed idea is illustrated by a real-life application of the photovoltaic control system implemented in the FPGA device from Xilinx (Artix-7 family). A novel design technique of a Petri net-based concurrent control system is proposed in this paper. The idea is oriented on the effective implementation of the system within the FPGA device. In order to reduce the resources of the targeted device, the concurrent control system is optimized by the use of the authors' techniques. The complete design flow is shown, including the modeling of the system by an interpreted Petri net, its further transformation to the hardware description language, adequate logic optimization, and final implementation within the destination FPGA. The presented method is explained by a case study example of the photovoltaic control system and compared with the already known technique. The performed experiments indicated a very high effectiveness of the proposed technique. It is shown that the photovoltaic control system designed according to the presented method reduces the logic resources of the destination FPGA device by up to 28%. [ABSTRACT FROM AUTHOR]

The supervisory control of Petri nets aims to enforce the undesired behavior as unreachable by designing a set of control places. This work presents a set cover approach to design maximally permissive supervisors. For each first-met bad marking, an integer linear programming problem is developed to obtain a control place to prohibit it. An objective function is formulated to make the maximal number of first-met bad markings forbidden. Then, we develop a set covering approach to minimize the number of selected control places. The proposed approach can guarantee the maximal permissiveness of the obtained supervisor and provide a trade-off between structural complexity and computational cost. Several examples are considered to validate the proposed method. [ABSTRACT FROM AUTHOR]

This document is a special issue of the journal "Mathematics in Engineering, Science & Aerospace" that focuses on advances in mathematical modeling and its applications. The issue covers a diverse range of topics including reliability, operation research, multi-objective optimization, machine learning, fluid dynamics, software reliability, numerical analysis, and supply chain. The articles included in this collection have been peer-reviewed and cover various domains. Some specific topics discussed in the articles include simulating wave solutions using trigonometric B-spline functions, innovation diffusion models, adaptability of origami structures, effects of voltage unbalanced on induction motors, job-shop scheduling problems, support vector machines, spectral methods for solving partial differential equations, blood flow in stenosed arteries, predator-prey cooperation dynamics, software reliability growth models, entropy measures for intuitionistic fuzzy sets, stability of chemically reacting flows, Petri net modeling of signaling pathways, and system reliability analysis. The authors express gratitude to the contributors and reviewers, as well as the editorial board of the journal. [Extracted from the article]

Internet of Things has become a common paradigm for various domains. To meet a user's complex requirement, we should compose multiple IoT devices (IoT services) to provide comprehensive services to the user. However, these services usually coexist, which is likely to lead to conflicts. Moreover, each user may have different kinds of needs. Suppose that in a smart home there are more than one person, a conflict may occur when they request the same service in this environment. Actually, even though they request different IoT services, among which if there exists function impact or QoS impact, a conflict could still occur. In this paper, we propose to employ high-level Petri nets to detect conflicts among IoT services. We first model the formal methods for conflict policies. Then, we present a Petri nets-based mechanism for modeling and detecting conflicts. Finally, we expand the previous model and use high-level Petri nets for handling fuzzy IoT conflict policies modeling and reasoning. The experimental results show that the proposed approach performs well in accuracy. [ABSTRACT FROM AUTHOR]

The mechatronic industry is currently subject to huge changes challenging it to offer products matching individual customer requirements at competitive prices. The design of such products calls for sophisticated and complex components integration following different technologies. Since we are on the cusp of the Fourth Industrial Revolution, in which the world of mechatronic production, network connectivity, the Internet of Things, and cyber-physical systems are correlated, the complexity of these systems increases exponentially, and we are talking about advanced mechatronic systems. To assist these changes, various methods, sweeping all project phases, are used by business houses. Predictive dependability assessment in the earlier design stage is considered a powerful metric used to evaluate the performances of different kinds of mechatronic products before the production phase. Altogether, dependability analysis ties the design directly to the desired functionality, operability, and integrity of the system. This paper explores an approach to assessing the dependability attributes, reliability, availability, and maintainability (RAM), of repairable mechatronic systems based on timed colored Petri nets and a Monte Carlo simulation, integrating simultaneously diverse components technologies: mechanical, electronic, and software. The proposed approach is tested taking the case of a regenerative braking system. The methodology appears to be efficient for evaluating predictive RAM indicators (MTTFF, MTTR, MTBF...) for the whole system and for each individual component separately. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces software patterns (registration, acquire-release, and cache awareness) and data structures (Petri net, finite state machine, and protocol flag array) to support the coordinated execution of software activities (also called “components” or “agents”). Moreover, it presents and tests an implementation for Petri nets that supports real-time execution in shared memory for deployment inside one individual robot and separates event firing and handling, enabling distributed deployment between multiple robots. Experimental validation of the introduced patterns and data structures is performed within the context of activities for task execution, control and perception, and decision making for an application on coordinated navigation.

Long-duration human space missions require intelligent regenerative life support systems that can recycle resources and automatically manage failures. This paper explores using Petri nets to model the reliability and complex interactions of such closed-loop systems. An architecture consisting of primary systems, backups, and consumable reserves is outlined. The automation system that controls everything is described. Petri nets can capture concurrency, failure modes, redundancy, and dynamic behavior. A modular modeling methodology is presented to develop hierarchical Petri net models that scale in fidelity. Elementary fragments represent failures and redundancy. Subsystem modules can be substituted for more detailed models. Analysis and simulation assess system reliability and failure response. This supports designing ultra-reliable systems to safely sustain human life in space.

The object of the research is the channels of information transmission during the control of the information-analytical decision-making system. The development of high technologies and computing capabilities ensures the evolutionary development of smart technologies and socio-cyber-physical systems on the one hand. On the other hand, it forms the integration of targeted (mixed) attacks with the possibility of integration with social engineering methods. In addition, mobile technologies significantly increase the possibilities of data transmission speed. However, this only provides the authentication service, which does not provide a full range of security services. Under such conditions, an urgent task at the decision-making stage is the use of auxiliary systems that ensure the adequacy of decisions and the promptness of their adoption. The proposed mathematical model of the information and analytical system allows to calculate the main technical characteristics of information transmission channels and identify their possible failures. The use of an information and analytical system simplifies the decision-making process, allows to increase the reliability of such decisions due to an increase in the level of automation. Increasing the level of automation in the decision-making process removes subjective factors and the decision depends on the availability of information. Therefore, the reliability of the information transmission channels of the information and analytical system significantly affects the quality of the decisions made. The developed model allows to ensure the required level of reliability of information transmission channels. The obtained results are explained by determining the dependence between the parameters of the information and analytical system and their influence on the quality of information transmission through channels. The results of the study can be used in practice when considering systems with a limited number of states during operation. [ABSTRACT FROM AUTHOR]

Serious games are becoming a more commonly utilized tool in training, education, and learning. On the other hand, Petri nets, a well-known formalism for process modeling, seem to be a promising tool for describing learning activity scenarios for serious games and virtual environments. Thanks to their graphical form and easy-to-understand nature, it can be assumed that participants from different backgrounds should be able to understand and use Petri nets for their scenarios. A present study presented here investigates how this assumption corresponds to reality. In the study, a short explanation of Petri nets and a set of related tasks were given to a sample of 31 participants (n = 31). The participants were students of Computer Science (16) and Humanities (15). The results collected and statistically analyzed demonstrate both similarities and distinctions in the reactions to problem-solving assignments among individuals in the two groups. These findings and their analysis have been condensed and presented in visual form. [ABSTRACT FROM AUTHOR]

This paper presents an innovative EGSPN (Editable Generalized Stochastic Petri Net) model, optimizing the size of GSPN (Generalized Stochastic Petri Net) while preserving its core benefits. Specifically, the EGSPN introduces a transition termed "editable transition," which allows for the establishment of any dynamic logic, thereby circumventing the intricacies associated with the EGSPN model structure. A Monte Carlo (MC) simulation technique is put forth for EGSPN analysis, enhanced by the integration of Sobol sequences with a Bayesian optimizer. This MC simulation approach, unbounded by any specific distribution constraints, exhibits accelerated convergence rates. To address the issue of preset sampling size, an adaptive sampling strategy rooted in confidence intervals has been proposed. By real‐time computation of margin of errors under varying confidence levels, simulations can be halted prior to reaching the preset sampling size. This method strikes a balance between reduced simulation time and maintained accuracy. The applicability and efficacy of the proposed method are further elucidated through a numerical example of a flight control system. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an inevitable part of construction and demolition (C&D) waste, muck has a dreadful environmental impact due its inadequate management by the traditional governance process. This paper therefore focuses on the management of muck generated from C&D waste by utilizing platform governance as an alternative process, which should more effectively contribute to China's circular economy. The study explores the feasibility of providing such a platform governance mode by using Petri net to compare the traditional governance process and platform governance process for the management of muck trucks, and by using Nanjing's muck smart supervision platform as a case study to assess the effectiveness of the platform governance mode. Results from Petri net simulation modeling reveal that the platform governance mode is more effective than the traditional mode, and from the case study it is found that the success of Nanjing's muck waste management can be attributed to the platform governance mode. The platform management approach can therefore contribute to the sustainability of muck waste governance, and is suitable as an integrated and effective management mode for current practices of muck waste management and resource recovery in China. The main finding from the study is that the platform governance mode significantly improves the efficiency of muck waste management as compared with the traditional governance mode and can therefore provide greater economic and environmental benefits as part of a circular economy. [ABSTRACT FROM AUTHOR]

The dynamic scheduling problem (DSP) in unreliable flexible manufacturing systems (UFMSs) with concurrency, conflicts, resource sharing, and sequential operations is a complex optimization problem that requires the use of efficient solution methodologies. The effectiveness of scheduling UFMSs relies on the quality of equipment maintenance. Currently, UFMSs with consistently large queues of parts awaiting service employ a repair-after-failure approach as a standard maintenance procedure. This method may require unexpected resources, incur costs, consume time, and potentially disrupt the operations of other UFMSs, either partially or fully. This study suggests using a predictive maintenance (PdM) strategy that utilizes the Internet of Things (IoT) to predict and avoid early mechanical equipment failures before they happen in UFMSs, thereby reducing unplanned downtime and enhancing reliability. Therefore, the objective of this paper is to construct timed Petri net (TPN) models using the IoT for the PdM configuration of mechanical equipment in the dynamic scheduling problem of UFMSs. This necessitates that users represent the specific problem using TPNs. The process of PN modeling requires the utilization of domain knowledge pertaining to the target problems as well as to machine information. However, it is important to note that the modeling rules for PNs are straightforward and limited in number. Consequently, the TPN model is applied to generate and formulate mixed-integer linear programming (MILP) instances accurately. This is done to identify the optimal production cycle time, which may be implemented in real-life scenarios. Several UFMS instances are used to demonstrate the applications and effectiveness of the proposed method. The computational results demonstrate that the proposed method shows superior solution quality, effectively solves instances for a total of 10 parts and 6 machines, and achieves a solution in a reasonable CPU time. [ABSTRACT FROM AUTHOR]

Aerial refueling is an extender of air combat capability that has received widespread attention with the development of the military field, particularly the mental workload of the pilot performing the aerial refueling task, as it is the key to the aerial refueling success rate. Therefore, this study analyzes the behavior of receiver aircraft pilots from rendezvous to the separation phase and constructs a mental workload model to improve the aerial refueling success rate. First, the time‐channel‐action unit network was constructed based on Petri net and multiple resource theory (MRT). Second, the mental workload evaluation model was constructed from three dimensions: conventional resource occupation, additional resource occupation, and time occupation. Finally, a simulated experiment was conducted, and the results showed that the mental workload obtained by the model constructed in this study exhibits a high positive correlation with subjective mental workload, pupil diameter, and blink rate, surpassing the accuracy of the traditional MRT model. [ABSTRACT FROM AUTHOR]

Abstract Internet of Things has become a common paradigm for various domains. To meet a user’s complex requirement, we should compose multiple IoT devices (IoT services) to provide comprehensive services to the user. However, these services usually coexist, which is likely to lead to conflicts. Moreover, each user may have different kinds of needs. Suppose that in a smart home there are more than one person, a conflict may occur when they request the same service in this environment. Actually, even though they request different IoT services, among which if there exists function impact or QoS impact, a conflict could still occur. In this paper, we propose to employ high-level Petri nets to detect conflicts among IoT services. We first model the formal methods for conflict policies. Then, we present a Petri nets-based mechanism for modeling and detecting conflicts. Finally, we expand the previous model and use high-level Petri nets for handling fuzzy IoT conflict policies modeling and reasoning. The experimental results show that the proposed approach performs well in accuracy.

Target assignment is the core part in the command and control process, and the optimization of the allocation mode is of great significance for improving the air defense and anti-missile combat capability. In order to improve the robustness, applicability, game antagonism and other combat performance of air defense and anti-missile target allocation, so as to cope with the current complex and changeable battlefield environment, this paper proposes the target allocation architecture establishment of multi-mode fusion, and adaptively improve the commercial order-type service mode. The improvement of three kinds of dispatching models, that are “dispatching order” “grabbing order” and “dispatching- grabbing order fusion”, are defined as military models. By using the US department of defense architecture framework (DoDAF) to establish a new target allocation architecture of “other allocation” “self-allocation”and “combination of other allocation and self-allocation”. With the introduction of Perti net model, the reachable map of Petri net model is constructed and analyzed. Through the simulation experiment platform, the complex combat scenario is constructed to verify the feasibility of the distribution strategy mechanism. The results show that each of the three strategies has its own advantages. The multi-strategy combination designed in this paper has greater advantages than the traditional single strategy in matching time, success rate and utility value.

A power distribution system is usually composed of a number of distribution substations and distribution lines, where the latter are fragile and often suffer from faults, leading to serious local power shortages. For all distribution substations, it is complex and costly to diagnose and locate faulty input lines from the multiple input lines of distribution substations. This paper reports a Petri net strategy to diagnose the faulty input lines to prevent local power shortages. The structure of a supervisor is proposed to detect and locate the faulty input lines by supervising the variations of power loads that are stored in a battery energy storage system. The stored power loads can be uninterruptedly distributed to the output lines during the fault diagnosis processes. Moreover, there are other auxiliary distribution substations that can urgently supply power loads to a distribution substation once the faulty input lines of the distribution substation are diagnosed. The local power shortages of the distribution substation are prevented during the fault diagnosis processes. In addition, the structures of power distribution systems and their control systems are formally defined by using Petri nets. The derivation processes of fault detection and location strategies are verified by the mathematical methods of Petri nets. Finally, a case study is presented.

The system deadlock problem of the flexible manufacturing system (FMS) needs to be solved urgently. Deadlocks may occur when resources are repeatedly requested by multiple working processes, where such competition causes a lack of resources, and the system cannot get into subsequent processes smoothly. In this paper, we build FMS by using a particular class of Petri Net (PN) model called a system of simple sequential processes with resources (S3PR) net, which features a high utilization rate of resources. When parts of resources are held by related processes and these processes wait for others to release resources to move on, a circular waiting situation occurs. Circular waiting is one of the conditions for system deadlocks occurring, where the system under this situation has a high probability of causing system deadlocks. The resources being held have to be released to break the waiting states. This paper develops a novel control transition-based deadlock recovery policy by combining graph theory and reachability graph analysis technique. The proposed approach firstly builds a subnet of the PN model called resource flow graph (RFG) and finds out all its hold and request circuits (HRCs), which may lead to a circular waiting situation. In addition, we design a new algorithm to obtain the minimal set of control transitions further. We introduce three PN models of FMS to demonstrate the proposed method. Through experimental results and comparison between related works, it is known that the proposed deadlock recovery uses fewer controllers and has the same performance.

Program deadlock detection plays an important role in ensuring the stability of software systems. In view of the high efficiency and low false alarm rate, dynamic deadlock analysis methods are widely studied. However, existing dynamic analysis methods use lock graph or its extended variants to model program behavior. Since there are information loss in existing lock graphs, deadlock false positives still exist. To solve the problem, a novel 2-stage dynamic deadlock analysis method is proposed. In the first stage, a Petri net model of the program is constructed by analyzing program running traces. Then, unfolding-based Petri net dead marking detection methods are used to identify potential program deadlocks. In the second stage, based on Petri net unfolding techniques, a deterministic program scheduling scheme that can be used for deadlock replay is derived for each potential deadlock. Each successfully replayed program deadlock is a real deadlock. It is shown that the proposed deadlock detection and replay method can eliminate more false positives compared to general dynamic methods, and the deadlock replay scheme is deterministic and easy to understand compared with existing random scheduling strategies.