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This study aims to develop a high-performance nanofluid that can be used in titanium alloys machining. Titanium alloys are difficult-to-cut materials and difficult to be lubricated. This study explored the lubrication performance of various carbon nanoparticles in water-based lubricants for titanium alloys.

The lubricating and antiwear properties of the developed cutting fluid were tested by a tribo-tester. The lubricant performance was evaluated through friction coefficient, wear volume and surface quality. The lubrication mechanism was analyzed through surface morphology, wettability and bonding analysis.

The lubricating performance of four kinds of carbon nanoparticles on titanium alloys was tested and the results showed that single-layer graphene had the smallest COF and wear volume. The interaction between nanoparticles and debris was an important factor that influenced the lubrication performance of nanoparticles for titanium alloy. Moreover, the hybrid nanofluid with graphene and spherical graphite in a ratio of 1:2 achieved a balance between lubricating performance and price, making it the optimal choice.

The developed lubricant containing carbon nanoparticles that can lubricate titanium alloys effectively has great potential in machining titanium alloy as a high-performance cutting fluid in the future.

This paper fulfills an identified need for water-based lubricant for titanium alloys considering the bad tribological properties.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0124/

The outbreak of the COVID-19 pandemic led to the rise of online learning in Hong Kong. Online learning was identified as the only solution to meet students’ learning needs in the higher education sector during this chaotic period. This research aims to explore students’ perceptions of online teaching and learning from home under a health emergency via a comparison of undergraduate and postgraduate students’ experiences.

A total of 174 postgraduate students and 286 undergraduate students in various universities and colleges in Hong Kong were surveyed in this study.

The results show that postgraduate students generally gave more positive feedback on individual and environmental prerequisites, alongside pedagogical and institutional support, and were more motivated in online classes as compared to undergraduate students. Undergraduate students considered the shift to online education in light of the COVID-19 pandemic to be timely and rated their level of discipline with respect to online learning higher than did postgraduate students.

This study enables educators to better understand the first-hand experiences of students across different levels of study in Hong Kong, as well as to examine the possibility of establishing online education as a more prevalent mode of study in the future. The COVID-19 pandemic has educated us on the significance of being well-prepared to ensure quality education continues when emergencies and disturbances arise.

The purpose of this study is to optimize the operational efficiency of the entire system by developing a reasonable maintenance strategy for wind turbines that improves component reliability and safety while reducing maintenance costs.

A hybrid incomplete preventive maintenance (PM) model based on boundary intensity process is established to give dynamic PM intervals for wind turbines using an iterative method with reliability as a constraint; the selection method of PM and replacement is given based on the cost-effectiveness ratio, which in turn determines the optimal number of PM for wind turbines.

The reliability is used to obtain the components’ maintenance cycle, and the cost-effectiveness ratio is used to select the number of maintenance times, thus, getting the optimal maintenance strategy. The validity of this paper’s method is verified by arithmetic cases, which provides a new method for formulating a reasonable PM strategy for wind turbines.

The wind turbine preventive maintenance strategy for Boundary intensity process proposed in this paper can scientifically formulate the maintenance strategy, optimize the cost-effectiveness per unit of time of the wind power generation system, and solve the problems of difficulty in formulating a reasonable maintenance strategy for the wind turbine components and high operation and maintenance costs.

In this paper, the authors describe the failure pattern by a Boundary intensity process, establish a hybrid incomplete PM model by introducing a failure intensity increment factor and an age reduction factor and establish a maintenance strategy optimization model with comprehensive consideration of reliability and cost-effectiveness ratio. Finally, the validity of the model in this paper is verified by arithmetic case analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0153/