High performance polyethylene nanocomposite fibers

A high density polyethylene (HDPE) matrix was melt compounded with 2 vol% of dimethyldichlorosilane treated fumed silica nanoparticles. Nanocomposite fibers were prepared by melt spinning through a co-rotating twin screw extruder and drawing at 125°C in air. Thermo-mechanical and morphological properties of the resulting fibers were then investigated. The introduction of nanosilica improved the drawability of the fibers, allowing the achievement of higher draw ratios with respect to the neat matrix. The elastic modulus and creep stability of the fibers were remarkably improved upon nanofiller addition, with a retention of the pristine tensile properties at break. Transmission electronic microscope (TEM) images evidenced that the original morphology of the silica aggregates was disrupted by the applied drawing

Deep-Learning-Based Onset Time Precision in Acoustic Emission Non-Destructive Testing

To investigate the actual health status and mechanical properties of structural materials, both direct and/or indirect investigation procedures can be used. The acoustic emission (AE) method is a non-destructive indirect structural health monitoring method based on the analysis of the elastic wave propagation inside the material under study induced during cracks and micro-cracks coalescence, opening, and formation process. To capture reliable ultrasonic elastic waveform data, piezoelectric sensors are typically employed which are directly and firmly fixed and attached to the specimen under study. For identifying the region of crack formation, thus the position of structural damage in its early stage, at least four sensors must be employed simultaneously. Furthermore, the identification of the onset time is crucial to accomplishing this task. In this study, the authors proposed a deep-learning-based solution based on a U-net architecture for identifying onset time with a method attempting to overcome the existing limitations of traditional threshold-based methods. The onset time precision obtained with this artificial intelligence-based (AI) paradigm is discussed on an acknowledged dataset available in the literature based on Pencil Lead Break (PLB) data, commonly used as a benchmark in the AE field. Finally, the method is tested on some real AE signals acquired during laboratory testing of reinforced concrete specimens. The results demonstrated the actual potential of the proposed AI-based method in future real-time monitoring real- world applications

Chromosome numbers for the Italian flora: 10

In this contribution, new chromosome data regarding two taxonomically critical genera of the Italian fora, namely Plantago and Sesleria, are presented. All the specimens analysed in this paper were collected in the Italian territory and include three chromosome counts for Plantago (P. albicans, P. crassifolia, and P. subulata) and two counts for Sesleria (S. caerulea and S. nitida)

Control of quantum interference in molecular junctions: Understanding the origin of Fano and anti- resonances

We investigate within a coarse-grained model the conditions leading to the appearance of Fano resonances or anti-resonances in the conductance spectrum of a generic molecular junction with a side group (T-junction). By introducing a simple graphical representation (parabolic diagram), we can easily visualize the relation between the different electronic parameters determining the regimes where Fano resonances or anti-resonances in the low-energy conductance spectrum can be expected. The results obtained within the coarse-grained model are validated using density-functional based quantum transport calculations in realistic T-shaped molecular junctions.Comment: 5 pages, 5 figure

Impact of PWM Voltage Waveforms in High-Speed Drives: A Survey on High-Frequency Motor Models and Partial Discharge Phenomenon

The insulation system’s dielectric of the electric motor is very often subjected to severe electrical stress generated by the high dv/dt seen at the machine’s terminals. The electrical stress and high reflected wave transient overvoltage are even more evident in case of high-speed machines fed by high-frequency (HF) converters featuring very fast wide-bandgap devices. They are promoting the occurrence of partial discharges and consequently accelerate ageing. As this is serious issue and the main cause of the drive failure, it is important to analyse and characterise the surges at the motor terminals. Several HF models of motors have been proposed in the literature for this purpose. This article presents a survey on HF motor models, which is crucial in understanding and studying the most critical parameter identification and overvoltage mitigation techniques. Moreover, it offers a comparison of the models’ main features as well as a comparison with the experimental voltage waveform at motor terminals. A general overview of the partial discharge (PD) phenomenon is also provided, as it is favoured by HF operation and together with HF motor modelling provides key insights to the insulation ageing issue. In particular, an analysis of the effects of PWM waveform affecting insulation is given, as well as useful methods for developing strategies for the inspection and maintenance of winding insulation