Digital Twin-Oriented Complex Networked Systems based on Heterogeneous node features and interaction rules

This study proposes an extendable modelling framework for Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with a goal of generating networks that faithfully represent real systems. Modelling process focuses on (i) features of nodes and (ii) interaction rules for creating connections that are built based on individual node's preferences. We conduct experiments on simulation-based DT-CNSs that incorporate various features and rules about network growth and different transmissibilities related to an epidemic spread on these networks. We present a case study on disaster resilience of social networks given an epidemic outbreak by investigating the infection occurrence within specific time and social distance. The experimental results show how different levels of the structural and dynamics complexities, concerned with feature diversity and flexibility of interaction rules respectively, influence network growth and epidemic spread. The analysis revealed that, to achieve maximum disaster resilience, mitigation policies should be targeted at nodes with preferred features as they have higher infection risks and should be the focus of the epidemic control

Heterogeneous Feature Representation for Digital Twin-Oriented Complex Networked Systems

Building models of Complex Networked Systems (CNS) that can accurately represent reality forms an important research area. To be able to reflect real world systems, the modelling needs to consider not only the intensity of interactions between the entities but also features of all the elements of the system. This study aims to improve the expressive power of node features in Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with heterogeneous feature representation principles. This involves representing features with crisp feature values and fuzzy sets, each describing the objective and the subjective inductions of the nodes' features and feature differences. Our empirical analysis builds DT-CNSs to recreate realistic physical contact networks in different countries from real node feature distributions based on various representation principles and an optimised feature preference. We also investigate their respective disaster resilience to an epidemic outbreak starting from the most popular node. The results suggest that the increasing flexibility of feature representation with fuzzy sets improves the expressive power and enables more accurate modelling. In addition, the heterogeneous features influence the network structure and the speed of the epidemic outbreak, requiring various mitigation policies targeted at different people

Resilient Multi-Dimensional Consensus in Adversarial Environment

This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the healthy agents aim to reach an agreement within the convex hull of their initial states. Towards this end, this paper develops a resilient consensus algorithm, where each healthy agent sorts its received values on one dimension, computes two "middle points" based on the sorted values, and moves its state toward these middle points. We further show that the computation of middle points can be efficiently achieved by linear programming. Compared with the existing works, this approach has lower computational complexity. Assuming that the number of malicious agents is upper bounded, sufficient conditions on the network topology are then presented to guarantee the achievement of resilient consensus. Some numerical examples are finally provided to verify the theoretical results.Comment: arXiv admin note: substantial text overlap with arXiv:1911.1083

Effect of bias voltage on the tribological and sealing properties of rubber seals modified by DLC films

Diamond-like carbon (DLC) films were deposited on nitrile butadiene rubber (NBR) by the DC magnetron sputtering under different bias voltages. Raman spectra revealed that the variation of bias voltage could tune the carbon bond structure in DLC films. Both the hardness and Young's modulus increased with the increasing bias voltage. Tribological tests revealed that the DLC-coated NBR prepared at the bias voltage of -200 V exhibited low wear rate due to its high hardness. The sealing property was studied by evaluating the leakage rate of volatile liquid in a simple apparatus. All DLC films resulted in less leakage rate as compared to the raw rubber under large stress. The lowest leakage rate occurred in the DLC-coated NBR prepared with a bias voltage of -200 V, which was associated with the theoretical calculations (Persson's theory). It was attributed to the synergetic effects of the variations of the Young's modulus and root-mean-square (Rms) roughness. The low Young's modulus and Rms, controlled by regulating bias voltage, could enhance actual contact area and reduce the leakage rate

The investigation of microstructure, photocatalysis and corrosion resistance of c-doped ti–o films fabricated by reactive magnetron sputtering deposition with co₂ gas

By employing carbon dioxide as one source of reaction gases, carbon-doped Ti–O films were fabricated via reactive magnetron sputtering deposition. The chemical bonding configurations and microstructure of the films were analyzed by Raman spectrum and SEM, respectively. The effect of pH on the photocatalytic activities of the films was determined via evaluation of the decolorization rate of methyl orange under alkali, acid and neutrality conditions using UV light irradiation. Electrochemical impedance spectroscopy and potentiodynamic polarization tests were employed to determine the anti-corrosion properties. Compared with the C-free Ti–O film, the C-doped Ti–O films exhibit superior corrosion resistance. Furthermore, the results of the photodegradation experiment suggest that the C-doped Ti–O films have excellent photocatalytic activities and, for methyl orange, those with higher carbon content exhibit hyper-photodegradative effect under the alkali condition