Cloud-based digital twinning for structural health monitoring using deep learning

Digital Twin technology has recently gathered pace in the engineering communities as it allows for the convergence of the real structure and its digital counterpart throughout their entire life-cycle. With the rapid development of supporting technologies, including machine learning, 5G/6G, cloud computing, and Internet of Things, Digital Twin has been moving progressively from concept to practice. In this paper, a Digital Twin framework based on cloud computing and deep learning for structural health monitoring is proposed to efficiently perform real-time monitoring and proactive maintenance. The framework consists of structural components, device measurements, and digital models formed by combining different sub-models including mathematical, finite element, and machine learning ones. The data interaction among physical structure, digital model, and human interventions are enhanced by using cloud computing infrastructure and a user-friendly web application. The feasibility of the proposed framework is demonstrated via case studies of damage detection of model bridge and real bridge structures using deep learning algorithms, with high accuracy of 92%

On the cooperative relaying strategies for multi-core wireless Network-on-Chip

Recently, hybrid wired-wireless Network-on-Chip (WiNoC) has been proposed as a suitable communication fabric to provide scalability and satisfy high performance demands of the exascale era of modern multi/many-core System-on-Chip (SoC) design. A well accepted low-latency wireless communication fabric for WiNoCs is millimeter wave (mm-Wave). However, the wireless channel of mm-Wave is lossy due to free space signal radiation with both dielectric propagation loss (DPL) and molecular absorption attenuation (MAA). This is exacerbated for edge situated cores and in macro-chips embodying thousands of cores. To this end, this paper proposes efficient relaying techniques to improve the signal strength of the wireless channel in the WiNoCs using on-chip networking approaches under the realistic SoC channel conditions. First, we propose a realistic relay communication channel for the WiNoCs to characterise both MAA and DPL which have drastic effect on the performance. We then derive and show that the channel capacity for a single-relay WiNoC employing Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying protocols increases by up to 20% and 25%, respectively, compared to the conventional direct transmission. The AF protocol outperforms the DF mode for shorter transmissions between the relay and the destination cores, while the reverse is observed in other conditions. A hybrid protocol is then proposed to exploit the performance advantages of both relaying protocols to address the unbalanced distance between the cores, providing the maximal channel capacity close to the cutset bound. Finally, our approach is further validated in multi-relay WiNoCs where the communications of the remote cores is assisted by multiple intermediate cores along with the details of associated realistic channel model in emerging many-core SoCs

Digital twin for 5G and beyond

Although many countries have started the initial phase of rolling out 5G, it is still in its infancy with researchers from both academia and industry facing the challenges of developing to its full potential. With the support of Artificial Intelligence, development of digital transformation through the notion of a ‘Digital Twin’ has been taking off in many industries such as smart manufacturing, oil & gas, constructions, bio-engineering, and automotive. However, Digital Twins remain relatively new for 5G networks, despite the obvious potential in helping develop and deploy the complex 5G environment. This paper looks into these topics and discusses how Digital Twin could be a powerful tool to fulfil the potentials of 5G networks and beyond

Practical Evaluation of Stateful NAT64/DNS64 Translation

It is often suggested that the approach to IPv6 transition is dual-stack deployment; however, it is not feasible in certain environments. As Network Address Translation -- Protocol Translation (NAT-PT) has been deprecated, stateful NAT64 and DNS64 RFCs have been published, supporting only IPv6-to-IPv4 translation scenario. Now the question of usability in the real world arises. In this paper, we systematically test a number of widely used application-layer network protocols to find out how well they traverse Ecdysis, the first open source stateful NAT64 and DNS64 implementation. We practically evaluated 18 popular protocols, among them HTTP, RDP, MSNP, and IMAP, and discuss the shortcomings of such translations that might not be apparent at first sight

A framework for execution of computational chemistry codes in grid environments

International audienceGrid computing is a promising technology for computational chemistry, due to the large volume of calculations involved in appplications such as molecular modeling, thermochemistry and other types of systematic studies. Difficulties in using computational chemistry codes in grid environments arise, however, from the fact that the application software is complex, requiring substantial effort to be installed on different platforms. Morever, these codes depend upon task-dependent sets of data files to be present at the execution nodes. Aiming to improve the usability of different quantum chemistry codes in the distributed, heterogeneous environments found in computational grids, we describe a framework capable of handling the execution of different codes on different platforms. This framework can be divided into three independent parts, one dealing with the mapping of a calculation to a set of codes and the construction of execution environments, one dealing with the management of grid resources, and one that takes care of the heterogeneity of the environment. The suitability of this framework to tackle typical quantum chemistry calculations is discussed and illustrated by a model application