Surface integrity in metal machining - Part II: Functional performance

Material removal operations play a pivotal role in the manufacture of key components, required for engineering systems to operate safely and efficiently under ever more advanced functional requirements and over extended life cycles. To further step up the loading capability of machined parts, fundamental understanding of how of machining-induced features can influence the performance of advanced materials under complex service conditions is necessary over finer temporal and spatial scales. As discussed in Part I of this review, when engineering surfaces are generated by material removal processes, a wide range of physical mechanisms (e.g. mechanical, thermal, chemical and their combinations) drive the characteristics of workpiece surface integrity. In Part II of this review, the interplay between the metallurgical and micro-mechanical condition induced by material removal processes and their in-service response will be thoroughly explored, by a critical analysis of the state-of-the-art in the field. Specifically, attention is focused on recent advances made towards the understanding of the mechanisms determining the resistance of machined surface to fatigue crack nucleation (Section 2), corrosion and stress-corrosion cracking (Section 3), and wear (Section 4). Furthermore, the impact of relevant post-machining treatments on the in-service behaviour of machined surfaces is analysed, and the possible strategies for the enhancement of the functional performance of machined surfaces are presented (Section 5). Finally, the current research gaps and the prospective challenges in understanding the in-service behaviour of machined surfaces are critically discussed, providing an interpretation of the possible directions of future scientific development of this field

Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping

Information about urban land use is important for urban planning and sustainable development. The emergence of geospatial big data (GBD), increased the availability of remotely sensed (RS) data and the development of new methods for data integration to provide new opportunities for mapping types of urban land use. However, the modes of RS and GBD integration are diverse due to the differences in data, study areas, classifiers, etc. In this context, this study aims to summarize the main methods of data integration and evaluate them via a case study of urban land use mapping in Hangzhou, China. We first categorized the RS and GBD integration methods into decision-level integration (DI) and feature-level integration (FI) and analyzed their main differences by reviewing the existing literature. The two methods were then applied for mapping urban land use types in Hangzhou city, based on urban parcels derived from the OpenStreetMap (OSM) road network, 10 m Sentinel-2A images, and points of interest (POI). The corresponding classification results were validated quantitatively and qualitatively using the same testing dataset. Finally, we illustrated the advantages and disadvantages of both approaches via bibliographic evidence and quantitative analysis. The results showed that: (1) The visual comparison indicates a generally better performance of DI-based classification than FI-based classification; (2) DI-based urban land use mapping is easy to implement, while FI-based land use mapping enables the mixture of features; (3) DI-based and FI-based methods can be used together to improve urban land use mapping, as they have different performances when classifying different types of land use. This study provides an improved understanding of urban land use mapping in terms of the RS and GBD integration strategy

Lifetime estimation of enameled wires under accelerated thermal aging using curve fitting methods

Estimating the lifetime of enameled wires using the conventional/standard test method requires a significant amount of time that can endure up to thousands of testing hours, which could considerably delay the time-To-market of a new product. This paper presents a new approach that estimates the insulation lifetime of enameled wire, employed in electrical machines, using curve fitting models whose computation is rapid and accurate. Three curve fit models are adopted to predict the insulation resistance of double-coated enameled magnet wire samples, with respect to their aging time. The samples' mean time-To-failure is estimated, and performance of the models is apprised through a comparison against the conventional 'standard method' of lifetime estimation of the enameled wires. The best prediction accuracy is achieved by a logarithmic curve fit approach, which gives an error of 0.95% and 1.62% when its thermal index is compared with the conventional method and manufacturer claim respectively. The proposed approach provides a time-saving of 67% (83 days) when its computation time is compared with respect to the 'standard method' of lifetime estimation

Lightweight verification and fine-grained access control in named data networking based on schnorr signature and hash functions

Named Data Networking (NDN) is a new kind of architecture for future Internet, which is exactly satisfied with the rapidly increasing mobile requirement and information-depended applications that dominate today's Internet. However, the current verification-data accessed system is not safe enough to prevent data leakage because no strongly method to resist any device or user to access it. We bring up a lightweight verification based on hash functions and a fine-grained access control based on Schnorr Signature to address the issue seamlessly. The proposed scheme is scalable and protect data confidentiality in a NDN network

Impact of CO2 activation on the structure, composition, and performance of Sb/C nanohybrid lithium/sodium-ion battery anodes

Antimony (Sb) has been regarded as one of the most promising anode materials for both lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs) and attracted much attention in recent years. Alleviating the volumetric effect of Sb during charge and discharge processes is the key point to promote Sb-based anodes to practical applications. Carbon dioxide (CO2) activation is applied to improve the rate performance of the Sb/C nanohybrid anodes caused by the limited diffusion of Li/Na ions in excessive carbon components. Based on the reaction between CO2 and carbon, CO2 activation can not only reduce the excess carbon content of the Sb/C nanohybrid but also create abundant mesopores inside the carbon matrix, leading to enhanced rate performance. Additionally, CO2 activation is also a fast and facile method, which is perfectly suitable for the fabrication system we proposed. As a result, after CO2 activation, the average capacity of the Sb/C nanohybrid LIB anode is increased by about 18 times (from 9 mA h g−1 to 160 mA h g−1) at a current density of 3300 mA g−1. Moreover, the application of the CO2-activated Sb/C nanohybrid as a SIB anode is also demonstrated, showing good electrochemical performance

Fast and simple tuning rules of synchronous reference frame proportional-integral current controller

Synchronous reference frame proportional-integral (PI) current controller (CC) is considered the most well-established solution for the current regulation in electrical drives. However, the gain selection of the PI CC is still regarded to be poorly reported, particularly in relation to the effect of the inevitable execution time taken by the controller and inverter. Mostly, tuning process of PI CC is done by trial and error or using simple rules based on pole zero cancelation and pole placement methods which ignore time delays through the controller and inverter. Hence, PI CC delivers significantly different performance compared to the expected one during the digital implementation, especially if high bandwidth or low ratio between the switching and operational frequency are required. Therefore, this paper firstly addresses and analyses the common tuning rules of PI CC which ignore the existence of time delays followed by a rigorous analysis for PI CCs’ robustness to the influence of computational and modulation delays. Based on this analysis, generic recommendations have been proposed to select the PI CCs’ gains as a function of the electrical drive switching frequency considering the delay effect. A set of simple, generic, and fast tuning rules were derived that guarantee fast dynamic performance with reasonable stability margins. Moreover, the effects of model uncertainties on these developed rules have been analyzed and reported. Comprehensive experimental results are provided to prove the key analytical results of this study and to validate the proposed design recommendations

Federated learning algorithm based on knowledge distillation

Federated learning is a new scheme of distributed machine learning, which enables a large number of edge computing devices to jointly learn a shared model without private data sharing. Federated learning allows nodes to synchronize only the locally trained models instead of their own private data, which provides a guarantee for privacy and security. However, due to the challenges of heterogeneity in federated learning, which are: (1) heterogeneous model architecture among devices; (2) statistical heterogeneity in real federated dataset, which do not obey independent-identical-distribution, resulting in poor performance of traditional federated learning algorithms. To solve the problems above, this paper proposes FedDistill, a new distributed training method based on knowledge distillation. By introducing personalized model on each device, the personalized model aims to improve the local performance even in a situation that global model fails to adapt to the local dataset, thereby improving the ability and robustness of the global model. The improvement of the performance of local device benefits from the effect of knowledge distillation, which can guide the improvement of global model by knowledge transfer between heterogeneous networks. Experiments show that FedDistill can significantly improve the accuracy of classification tasks and meet the needs of heterogeneous users

Editorial: ‘One City, Many Tales’: COVID-19, perception, and the importance of contextualization

This introduction to the special issue summarizes the contributions from the five leading scholars in the field—their contribution to the conceptualization of such concepts as soft power, sharp power, image shaping, image reception, as well as methodological approaches. It highlights the importance of contextualizing their findings for a full understanding of the image of China in the media narratives examined. In doing so, the Introduction lays foundation for further investigations on the relationship between media coverage of health crisis and image construction as the world continues to fight against the virus

Investigation of fire protection performance and mechanical properties of thin-ply bio-epoxy composites

Hybrid composites composed of bio-based thin-ply carbon fibre prepreg and flameretardant mats (E20MI) have been produced to investigate the effects of laminate design on their fire protection performance and mechanical properties. These flame-retardant mats rely primarily on expandable graphite, mineral wool and glass fibre to generate a thermal barrier that releases incombustible gasses and protects the underlying material. A flame retardant (FR) mat is incorporated into the carbon fibre bio-based polymeric laminate and the relationship between the fire protection properties and mechanical properties is investigated. Hybrid composite laminates containing FR mats either at the exterior surfaces or embedded 2-plies deep have been tested by the limited oxygen index (LOI), vertical burning test and cone calorimetry. The addition of the surface or embedded E20MI flame retardant mats resulted in an improvement from a base line of 33.1% to 47.5% and 45.8%, respectively. All laminates passed the vertical burning test standard of FAR 25.853. Cone calorimeter data revealed an increase in the time to ignition (TTI) for the hybrid composites containing the FR mat, while the peak of heat release rate (PHRR) and total heat release (TTR) were greatly reduced. Furthermore, the maximum average rate of heat emission (MARHE) values indicated that both composites with flame retardant mats had achieved the requirements of EN 45545-2. However, the tensile strengths of laminates with surface or embedded flame-retardant mats were reduced from 1215.94 MPa to 885.92 MPa and 975.48 MPa, respectively. Similarly, the bending strength was reduced from 836.41 MPa to 767.03 MPa and 811.36 MPa, respectively

Fast frequency and phase lock of grid-connected TGS based on FIR filter

The thermoelectric generation system (TGS) has many advantages such as clean, no mechanical vibration and high reliability. When TGS is connected to the power grid, it requires that the frequency and phase are same as the power grid. It will take a number of working periods for the response time under the traditional method. A frequency and phase lock method with FIR filter will be introduced in the paper. It is based on the Capture and EPWM module of TMS320F28335. The phase lock can be carried out in one period. And the working frequency of TMS320F28335 is 150MHZ. Therefore, the speed of the whole operation is fast. The experimental results show that the method is feasible