查看更多>>摘要：Assessment of cybersecurity in power system automation (PSA) requires a framework to study and analyze the complex relationships between the cyber-based control systems and power systems. A production system is not ideal or available for such assessment due to potential impacts and disruptions. In this paper,1 we propose a framework constituents of power system, process network, communication network, automation network, and enterprize network for cybersecurity assessment in PSA. Both real and virtual components supportability are incorporated in the framework for covering good enough functionalities of power systems maintaining hardware diversity and scalability. A specific instance of the proposed framework, Virtual Operational Technology Network (VOTNet), is presented explaining simulated and emulated systems such as programmable logic controllers (PLCs), network devices, computing systems, software, and tools. The VOTNet consists of a centralized control center deployed with computing devices, an emulated communication network, a substation control center, and power systems. We evaluate and assess the VOTNet for cybersecurity and scalability issues and its cyber-physical impacts under different cyberattacks such as unauthorized access, denial of service (DoS), modbus protocol scanning and data reading, data manipulation/injection, and session hijacking. We also present risk assessment and mitigation against all the demonstrated attacks. Situational awareness and coordination under cyberattacks are also demonstrated. Finally, the usefulness of a virtual testbed in terms of different research applications and lessons learnt from its usage are also presented.
查看更多>>摘要：This paper presents an approach towards computationally efficient discrete-event-simulation designed to take advantage of high-performance computing architecture. We demonstrate how computational efficiency combined with large computing capacity enables quantification and mapping of stochastic system performance across a computationally challenging multidimensional parameter space requiring several million individual DES instances. An open-pit mine bulk materials handling system case study is presented to demonstrate the approach. A dispatching heuristic controlling the operation of the trucking system can be optimised through the selection of values for four control parameters. The multidimensional space represented by these control parameters is exhaustively mapped and visualised to provide insight into the relationships between combinations of parameters and system performance. The extensive data generated is ultimately used within a hyper-heuristic to determine near-optimal values for the dispatching heuristic control parameters.
Alaoui, El Arbi AbdellaouiTekouabou, Stephane Cedric KoumetioMaleh, YassineNayyar, Anand...
26页
查看更多>>摘要：The communication protocols of wireless networks have experienced great advances in recent years, specifically with the evolution of new technologies such as the Internet of Things (IoT). However, certain problems remain unsolved, in particular for wireless networks, and more specifically for DTN networks, which represent a major challenge in terms of DTN routing. This paper aims to design an intelligent routing system based on machine learning techniques, the use of which represents another possibility to classify bundles that have arrived at the destination successfully or not. These networks occasionally carry out an evaluation which makes it possible to choose the type of routing corresponding to a given situation. It then minimizes the unnecessary information of the entries and performs the classification of the data. Despite the problems cited, our challenge is to design an intelligent routing mechanism that is able to classify bundles that have arrived and those that have not arrived at their destination. The smart routing system uses machine learning as a main tool to design our system. Indeed, various Machine Learning techniques, such as Bagging and Boosting, have been used to classify whether bundles have arrived at their destination successfully or not. Machine Learning now enables us to learn directly from data rather than human expertise, resulting in higher accuracy. We utilized the SMOTE technique to balance the two groups of data, which allows us to collect the equal amount of samples for each class. We also included techniques for interpreting complicated Machine Learning Models to understand the reasoning for model decisions, such as SHAP values. Results show an overall accuracy of 80% for the Random Forest (RF) and ExtraTrees Classifier (ET).
查看更多>>摘要：It is challenging to ascertain a correct composition of an envisaged Distributed Cyber-Physical System (DCPS) with the user and physical interfaces and requisite interactions. The gap in understanding the user's ideation and designer's manifestation in the early stages of the System Development Life Cycle (SDLC) results in requirement errors. These requirement errors result in a higher cost due to rework if discovered in later phases of the SDLC. Hence, there is a need to incorporate dynamic models as system prototypes to facilitate early visibility of the designer's manifestation to the user community in the requirement engineering phase of SDLC.This paper is an attempt to fill this gap. This paper presents a framework to construct and validate DCPS composition as a rapid prototype. The idea is to facilitate effective communication among the user and developer community. The framework uses Reference net formalism extended with GUI enhancements to achieve the wire-frame implementation of the DCPS prototype under investigation. A containment management scenario in the COVID-19 context illustrates the applicability of the presented framework. The execution of end-to-end scenarios spanning multiple user interfaces with simulated sensors, actuators, and environmental operations within a distributed setup gives a realistic feel of the system operations and dynamics. The presented approach facilitates early validation, identification, and rectification of requirement errors through multiple refinement cycles. In our understanding, this work has not been suggested earlier.
查看更多>>摘要：Evacuation route optimization is a crucial problem in emergency management of cruise ships. To solve a multi-route planning problem of evacuating all passengers and crews on cruise ships, this study proposes an improved artificial fish swarm algorithm (IAFSA). Different from the common single-route artificial fish swarm algorithm, IAFSA uses the entire swarm of fishes to simulate the behavior of all the passengers and crews during evacuation, and fishes works cooperatively to form a set of evacuation routes. The impact of crowding on speed is considered, waiting and distribution methods is introduced into the IAFSA to solve the crowd problem. Real cruise ship model and crowd distribution data are used for experiments. Simulation results demonstrate that IAFSA is a promising approach to solve the emergency evacuation route planning problem.
查看更多>>摘要：We propose inventory models that can be directly applied to the industrial field by adapting from the order-up-to policy and investigate how a die bank can be used to reduce inventory of finished goods and to improve customer responsiveness. This study was motivated by the cooperation with one leading semiconductor company in Korea that wishes to develop inventory-management policy for a die bank, a facility in which the intermediate and generic forms of fabricated wafers are stored. Our simulation experiments, implemented with Arena (R) software, show that a die bank makes the supply chain more responsive in adjusting demand changes by postponing the differentiation point of finished goods in the production process. We have sufficiently demonstrated the need for a die bank to the company through pilot tests, and laid a good foundation for the introduction of a die bank.
Manolakos, Dimitrios E.Pressas, Ioannis S.Papaefthymiou, Spyros
29页
查看更多>>摘要：Ring rolling is a near-net shape forming process that produces ring products with relatively good dimensional accuracy. Two main factors that lower the precision of the final products are the inability to determine the effects of elasticity and the thermal expansion of rolls during the process. This work focuses on the creation and evaluation of suitable finite element models of a ring rolling process based on available experimental data found in literature. Through these numerical models, the elastic and thermal deformations of the rolls were thoroughly studied and the deformation effect on the produced ring was predicted. A difference of a few millimeters was calculated on the outer and inner diameters of the ring as a result of the two effects, which is far greater than the annotation levels of these products. On the other hand, the effects of the tools' elasticity and thermal expansion of the ring rolling loads were proven negligible. Based on our analysis it was made clear that slight deformation deviations (thermal and elastic deformations) from the targeted values may cause instabilities to the process if the rolls fail to compensate for these deformations. Material combinations seem to influence the process. Regarding final dimensional deviations it can be concluded that thermo-elastic tool deformations are considerable in case of high product precision requirements.
查看更多>>摘要：Modelica is an object-oriented modeling language whose design and features facilitate the description of cyber-physical systems (CPS). Message passing communication (MPC), seen as the transmission of impulses of information between model components, eases the description of the discrete-event parts of CPS models. However, Modelica does not currently supports MPC. Modelica supports an equation-based component connection rationale, where Modelica tools automatically transform component connections into model equations, following a physical modeling approach. The differences between MPC and Modelica connections are analyzed. A proposal for supporting MPC in Modelica is presented, inspired by the coupled PDEVS model communication approach. The presented MPC proposal is based on the definition of structures to manage messages, named buffers, interface ports and communication channels. Also, an implementation of the proposed MPC mechanism in the form of a new free Modelica library, named MSGLib, is presented. MSGLib includes functionality to manage and dynamically store messages, and describe component communications. Two examples, a pick and place system and a robotic arm, are presented to demonstrate the use of the library, and its combination with other Modelica models.
查看更多>>摘要：With the sharp increase of passenger travel demands in an urban rail transit (URT) network, more and more stations suffer an over-saturated and congested situation during peak hours, which often leads to colossal passenger accumulation in platforms, especially in transfer platforms. Under this state, the passenger flow guidance is a useful method to release the passengers' pressure and balance the passenger accumulation imbalance. In order to calculate the passenger flow traveling data and the passenger flow guidance (PFG) time, a multi-agent simulation model is firstly established. And then, a two-phase integrated passenger flow assignment based on the backtracking algorithm (BA) is proposed for generating guidance information to minimize total passenger waiting time and release passenger congestion. Besides, a passenger compliance degree to the guidance information is defined to stimulate the passengers' response to the guidance information in the real world. Finally, a real-world example of the Chongqing subway network with five metro lines and 95 stations is implemented to verify the performance and effectiveness of the proposed method. The total passenger waiting time is decreased by 5.62% under the passenger flow guidance approach.
NSTL
Elsevier