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Molecular dynamics is an emerging simulation technique in the field of machining in recent years. Many researchers have tried to simulate different processing methods of various materials with the theory of molecular dynamics (MD), and some preliminary conclusions have been obtained. However, the application of MD simulation is more limited compared with traditional finite element model (FEM) simulation technique due to the complex modeling approach and long computation time. Therefore, more studies on the MD simulations are required to provide a reliable theoretical basis for the nanoscale interpretation of grinding process. This study investigates the crystal structures, dislocations, force, temperature and subsurface damage (SSD) in the grinding of iron-nickel alloy using MD analysis.

In this study the simulation model is established on the basis of the workpiece and single cubic boron nitride (CBN) grit with embedded atom method and Morse potentials describing the forces and energies between different atoms. The effects of grinding parameters on the material microstructure are studied based on the simulation results.

When CBN grit goes through one of the grains, the arrangement of atoms within the grain will be disordered, but other grains will not be easily deformed due to the protection of the grain boundaries. Higher grinding speed and larger cutting depth can cause greater impact of grit on the atoms, and more body-centered cubic (BCC) structures will be destroyed. The dislocations will appear in grain boundaries due to the rearrangement of atoms in grinding. The increase of grinding speed results in the more transformation from BCC to amorphous structures.

This study is aimed to study the grinding of Fe-Ni alloy (maraging steel) with single grit through MD simulation method, and to reveal the microstructure evolution within the affected range of SSD layer in the workpiece. The simulation model of polycrystalline structure of Fe-Ni maraging steel and grinding process of single CBN grit is constructed based on the Voronoi algorithm. The atomic accumulation, transformation of crystal structures, evolution of dislocations as well as the generation of SSD are discussed according to the simulation results.

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This paper studies the lateral stability regulation of intelligent electric vehicle (EV) based on model predictive control (MPC) algorithm.

Firstly, the bicycle model is adopted in the system modelling process. To improve the accuracy, the lateral stiffness of front and rear tire is estimated using the real-time yaw rate acceleration and lateral acceleration of the vehicle based on the vehicle dynamics. Then the constraint of input and output in the model predictive controller is designed. Soft constraints on the lateral speed of the vehicle are designed to guarantee the solved persistent feasibility and enforce the vehicle’s sideslip angle within a safety range.

The simulation results show that the proposed lateral stability controller based on the MPC algorithm can improve the handling and stability performance of the vehicle under complex working conditions.

The MPC schema and the objective function are established. The integrated active front steering/direct yaw moments control strategy is simultaneously adopted in the model. The vehicle’s sideslip angle is chosen as the constraint and is controlled in stable range. The online estimation of tire stiffness is performed. The vehicle’s lateral acceleration and the yaw rate acceleration are modelled into the two-degree-of-freedom equation to solve the tire cornering stiffness in real time. This can ensure the accuracy of model.

The literature on ‘mixed’ families (in which members are socially viewed as ‘different’ due to their varying ethnicities and/or nationalities) identifies several stakes of mixedness. One of them arises from childbirth, after which parents need to give name(s) to their offspring. How does the parent–child dyad understand the giving of names in their mixed family? What does naming children unveil regarding interpersonal interactions and the value of children within this social unit? The chapter delves into these questions through a case study of forenaming children in Filipino-Belgian families in Belgium. Interview data analysis reveals two modes of forenaming in these families: individualisation through single forenames and reinforcement of collective affiliation through compound forenames. Through the analytical framework of social relatedness, this chapter uncovers the way the act of naming a child bridges families based on biological and social ties, generations, and parents' nations of belonging in their transnational spaces. The complex process of naming reflects the power dynamics not only within the parental couple but also within the wider set of social relations. Although the use of forename(s) in everyday life and in legal terms differ, the value of children in the mixed families studied lies in their symbolic role as social bridges linking generations and non-biological relationships, the then and now, and the here and there.

The purpose of this paper is to propose policy recommendations that resort to the domestic market to achieve inclusive growth from an open perspective.

How will economic globalization based on domestic demand affect economic growth and income distribution in an open and large country? With the aim of discussing the mechanism of the impact of expanding domestic demand on the inclusive growth from an open perspective, this paper incorporates the Global Value Chains vs National Value Chains (GVC-NVC) competition, which is triggered by foreign investments attracted by the domestic demand scale into an endogenous growth model with “Schumpeterian Innovation.”

Theoretical analysis indicates the following findings: although domestic demand-based economic globalization can promote transnational inclusive growth across countries, it is not conducive to national (domestic) inclusive growth; the impacting effect of domestic demand scale on inclusive growth across countries is subject to the moderating effect of the development maturity of the labor market; and the impacting effect of domestic demand scale on national inclusive growth is subject to the joint moderating effect of the development maturity of the labor market and labor skill structure.

First, this paper examines the impact of domestic demand-based economic globalization on the inclusiveness of economic growth from an open perspective, which deepens the existing theory of intra-product specialization and inclusive growth. Second, the paper puts the sequential production process into Schumpeterian growth model and reveals the mechanism that domestic demand affects inclusive growth. Third, the study finds that the enhancement of labor market efficiency, transfer payments to low-skilled labor and the creation of a fair competitive market environment will contribute to the globalization of a domestic demand-oriented economy, which provides a policy-making basis for government sectors.