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This paper aims to explore the influence of applied pressure on the tribological properties of the friction component in a wet multi-disc clutch during the running-in process.

The running-in evolutionary was explored in terms of global friction performance. The variation of friction torque and mean COF of the initial 300 engagement cycles was obtained by full-scale tests. Finally, an optical microscope was used to detect the wear characteristics of friction surfaces.

The applied pressure showed a significant influence on the tribological behaviors of wet clutches during the running-in process. The mean COF decreased and then increases with the increase of the applied pressure. A higher applied pressure contributed to more asperity summits being sheared, thus resulting in a smoother surface. Considering a suitable wore performance, properly applied pressure is necessary.

The results provide theoretical guidance for selecting the optimal applied pressure in the running-in of wet clutches.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2022-0256/

Parameter identification of photovoltaic (PV) modules plays a vital role in modeling PV systems. This study aims to propose a novel hybrid approach to identify the seven parameters of the two-diode model of PV modules with high accuracy.

The proposed hybrid approach combines an improved particle swarm optimization (IPSO) algorithm with an analytical approach. Three parameters are optimized using IPSO, whereas the other four are analytically determined. To improve the performance of IPSO, three improvements are adopted, that is, evaluating the particles with two evaluation functions, adaptive evolutionary learning and adaptive mutation.

The performance of proposed approach is first verified by comparing with several well-established algorithms for two case studies. Then, the proposed method is applied to extract the seven parameters of CSUN340-72M under different operating conditions. The comprehensively experimental results and comparison with other methods verify the effectiveness and precision of the proposed method. Furthermore, the performance of IPSO is evaluated against that of several popular intelligent algorithms. The results indicate that IPSO obtains the best performance in terms of the accuracy and robustness.

An improved hybrid approach for parameter identification of the two-diode model of PV modules is proposed. The proposed approach considers the recombination saturation current of the p–n junction in the depletion region and makes no assumptions or ignores certain parameters, which results in higher precision. The proposed method can be applied to the modeling and simulation for research and development of PV systems.

The purpose of this study is to reduce the gloss of the surface of silk fabrics, by treating the fabrics with tea and matting agent, to imitate the aging and retro effects of silk artefacts.

Silk fabrics were treated with different processing techniques. The aged appearance and surface gloss of the silk fabrics were characterised by sensory analysis, measurement of reflectivity, scanning electron microscopy, measurement of brightness and chroma to identify the influential factors.

The application of matting agent on silk fabrics could reduce the lustre of silk fabrics. Treated with matting agent and tea pigments, silk fabrics could be “aged” to achieve retro effects within a relatively short period of time. A number of other factors and mechanisms that affect the reflectivity of the silk fabrics were also identified.

There is no definite index to evaluate the antique effect of fabrics.

The method developed through this study provided a simple and practical solution to achieving aging and retro effects on silk fabrics.

The method for reducing the lustre of silk fabrics by treating them with matting agent is novel and the finding of the relationships among reflectivity and brightness and chroma is original.