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The microcutting performance of the ¹⁰B/Al composite is significantly poor because of the existence of hard boron particles. The effects of cutting parameters, including uncut chip thickness and cutting speed, on the material removal mechanism and surface generation are investigated to improve the surface quality.

The 2D finite element model, which includes a rigid cutting tool, a reinforced phase, a matrix and a dense layer, is established. The effects of uncut chip thickness on material removal mechanism and surface generation are analyzed from a probabilistic perspective. The relationship between the uncut chip thickness and the probability in which the machined surface will have a better surface quality is constructed. A Gaussian distribution formula is applied to describe the machined surface quality.

Two representative particle-removal modes, namely, cutting-through and pulling-out modes, are observed. For cutting-through mode, when the relative cutting location is small, better surface quality is obtained. For pulling-out mode, the quality of the machined surface gradually improves because the further increase of the relative cutting location reduces the height of the generated pit and scratches. The microcutting at high cutting speed tends to suppress the scratch phenomenon. The best surface quality will be obtained at small uncut chip thickness and high cutting speed.

The surface quality generated in microcutting of the ¹⁰B/Al composite can be improved by optimizing the cutting parameters and controlling the particle-removal modes based on the proposed Gaussian distribution formula.

This paper aims to study the relationship between leakage flux coefficient and the coreless axial magnetic field permanent magnet synchronous generator (AFPMSG) size and obtain the expressions of leakage flux coefficient.

In this paper, a magnetic circuit model of coreless AFPMSG is proposed. Four kinds of leakage permeances of permanent magnet (PM) are considered, and the expression of no-load leakage flux coefficient is obtained. Solving the integral region of leakage permeances by generator size, which improves the accuracy of the solution.

Finite element method and magnetic circuit method are used to obtain the no-load leakage flux coefficient and its variation trend charts with the change of pole arc coefficient, air gap length and PM thickness. The average errors of the two methods are 2.835%, 0.84% and 1.347%, respectively. At the same time, the results of single-phase electromotive force obtained by magnetic circuit method, three dimensional finite element method and prototype experiments are 19.36 V, 18.82 V and 19.09 V, respectively. The results show that the magnetic circuit method is correct in calculating the no-load leakage flux coefficient.

The special structure of the coreless AFPMSG is considered in the presented equivalent magnetic circuit and equations, and the equations in this paper can be applied for leakage flux evaluating purposes and initial parameter selection of the coreless AFPMSG.

The aim of the paper is to propose a simple and effective calculation method for a three-side protected steel beam temperature field.

The calculation model is based on temperature increment equation of EN1993-1-2 and the Fourier's law to calculate the conductive heat flux. The ABAQUS heat transfer simulation is used to establish temperatures and heat flux database at the joints. The ratio of simulation and calculated heat flux is predicted by evolutionary regression and gradient boosting method.

Combined evolutionary regression analysis (CERA) including both linear and polynomial regression reduce the residual of mean square error (MSE) by 7.1% compared to linear regression analysis (linear evolutionary regression analysis (LERA)). The evolutionary regression analysis (ERA) effectively reduces the temperature discrepancy with increase of evolution numbers. Gradient boosting predicts the k value and temperatures with the least residual of MSE. The average residual of MSE is 53.23 °C for the upper flange, 16.18 °C for the web and 19.44 °C for the lower flange.

This paper proposed an effective and fast temperature distribution model for the three-side protected steel beam combining machine learning methods to converge the conductive heat flux between specimens. A novel ERA able to fit output data with multiple inputs with explainable equations is proposed and validated by effectively converging the conductive heat flux to simulation results.

This study aims to explore the determinants of green electronics purchase intention in Malaysia by extending existing knowledge on green consumer behavior and contributing to the field of sustainable consumption.

A quantitative research approach was adopted, with data collected from 250 Malaysian consumers. The proposed model was tested using partial least squares structural equation modeling to assess the relationships between various determinants and green purchase intention.

The results demonstrate that perceived consumer effectiveness, green advertising and monetary cost positively affect environmental attitudes, which subsequently influence green purchase intention. The study also identifies that brand image and information quality significantly enhance green brand trust (GBT), leading to stronger intentions to engage in green purchasing. Additionally, it finds that environmental knowledge and environmental concern shape perceived behavioral control, which further impacts green purchasing intention.

The study focuses on Malaysian consumers, which may limit the generalizability of the findings to other cultural contexts. Future research could expand the scope to include cross-cultural comparisons to validate the model in different settings.

By providing insights into the key factors driving consumers’ intention to purchase green electronics, the study offers valuable guidance for marketers and manufacturers to develop targeted strategies that promote sustainable consumption and capitalize on the growing demand for green products in Malaysia.

This study is unique in measuring the influence of green attitude, GBT and perceived behavioral control on green purchase intention specifically within the electronics sector, offering a novel contribution to the literature on sustainable consumer behavior.

This study aimed to design a user-participatory methodology to investigate the post-occupancy sustainability of reused historical buildings and to apply it to a case study.

This study was designed in four stages. In the first stage, the sustainability parameters and sub-parameters were determined in the reused historical buildings based on the literature. The second stage included a field study in which the current situation of the study area was analysed, and the users were reached using the survey technique. In the third stage, the data obtained from the user participation were analysed with importance performance analysis (IPA) and an IPA matrix was created. The fourth stage included an evaluation of the results of the analysis and the development of recommendations.

IPA is a supportive method for ensuring the sustainable use of historic buildings. According to the data obtained from the IPA, it was seen that the functional sustainability of the building was achieved to a great extent. At the same time, there were deficiencies in technical and environmental sustainability. In terms of aesthetic sustainability, it was observed that the importance and performance values given by the users were generally consistent with each other.

The originality of this study is that the performance of the reused historical buildings in the process of use was monitored with appropriate parameters, and a user-participated method was proposed that allows improvement suggestions to be developed in line with the results obtained.