Search results

This paper aims to investigate the effects of inhomogeneities on the rolling contact fatigue (RCF) life in elastohydrodynamically lubricated (EHL) point contacts.

A numerical model for predicting the RCF life of inhomogeneous materials in EHL contacts was established by combining the EHL model and the inclusion model through the eigen-displacement and then connecting to the RCF life model through the subsurface stresses. Effects of the type, size, location and orientation of a single inhomogeneity and the distribution of multiple inhomogeneities on the RCF life were investigated.

The RCF life of a half-space containing manganese sulfide (MnS) inhomogeneity or the mixed inhomogeneity of aluminium oxide (Al₂O₃) and calcium oxide (CaO) was longer than that for the case of Al₂O₃ inhomogeneity. For a single ellipsoidal MnS inhomogeneity, increases of its semi-axis length and decreases of its horizontal distance between the inhomogeneity and the contact center shortened the RCF life. Furthermore, the relationship between the depth of a single MnS inhomogeneity and the RCF life was found. For the half-space containing multiple inhomogeneitites, the RCF life decreased remarkably compared with the homogeneous half-space and showed discreteness.

This paper implements the prediction of the RCF life of inhomogeneous materials under EHL condition.

As a high-performance engineering plastic, polyimide (PI) is widely used in the aerospace, electronics and automotive industries. This paper aims to review the latest progress in the tribological properties of PI-based composites, especially the effects of nanofiller selection, composite structure design and material modification on the tribological and mechanical properties of PI-matrix composites.

The preparation technology of PI and its composites is introduced and the effects of carbon nanotubes (CNTs), carbon fibers (CFs), graphene and its derivatives on the mechanical and tribological properties of PI-based composites are discussed. The effects of different nanofillers on tensile strength, tensile modulus, coefficient of friction and wear rate of PI-based composites are compared.

CNTs can serve as the strengthening and lubricating phase of PI, whereas CFs can significantly enhance the mechanical properties of the matrix. Two-dimensional graphene and its derivatives have a high modulus of elasticity and self-lubricating properties, making them ideal nanofillers to improve the lubrication performance of PI. In addition, copolymerization can improve the fracture toughness and impact resistance of PI, thereby enhancing its mechanical properties.

The mechanical and tribological properties of PI matrix composites vary depending on the nanofiller. Compared with nanofibers and nanoparticles, layered reinforcements can better improve the friction properties of PI composites. The synergistic effect of different composite fillers will become an important research system in the field of tribology in the future.

Relevant analyses are presented on the base of the compressible vortex method for simulating the development of two or three co-rotating vortices with different characteristic Mach numbers. The paper aims to discuss this issue.

In addition to having vorticity and dilatation properties, the vortex particles also carry density, enthalpy, and entropy. Taking co-rotating vortices in two-dimensional unsteady compressible flow for an example, truncation of unbounded domains via a nonreflecting boundary condition was considered in order to make the method computationally efficient.

For two identical vortices, the effect of the vortex Mach number on merging process is not evident; if two vortices have the same circulation rather than different radiuses, the vorticity and dilatation fields of the vortex under a vortex Mach number will be absorbed by the vortex under a higher vortex Mach number. For three vortices, if the original arrangement of the vortices is changed, the evolvement of the vorticity and dilatation fields is different.

The paper reveals new mechanism of the three co-rotating vortices by a feasible compressible vortex method.

An effective machine vision-based method for micro-crack detection of solar cell can economically improve the qualified rate of solar cells. However, how to extract features which have strong generalization and data representation ability at the same time is still an open problem for machine vision-based methods.

A micro-crack detection method based on adaptive deep features and visual saliency is proposed in this paper. The proposed method can adaptively extract deep features from the input image without any supervised training. Furthermore, considering the fact that micro-cracks can obviously attract visual attention when people look at the solar cell’s surface, the visual saliency is also introduced for the micro-crack detection.

Comprehensive evaluations are implemented on two existing data sets, where subjective experimental results show that most of the micro-cracks can be detected, and the objective experimental results show that the method proposed in this study has better performance in detecting precision.

First, an adaptive deep features extraction scheme without any supervised training is proposed for micro-crack detection. Second, the visual saliency is introduced for micro-crack detection.

This paper aims to improve the generalization capability of feature extraction scheme by introducing a micro-cracks detection method based on self-learning features. Micro-cracks detection of multicrystalline solar cell surface based on machine vision is fast, economical, intelligent and easier for on-line detection. However, the generalization capability of feature extraction scheme adopted by existed methods is limited, which has become an obstacle for further improving the detection accuracy.

A novel micro-cracks detection method based on self-learning features and low-rank matrix recovery is proposed in this paper. First, the input image is preprocessed to suppress the noises and remove the busbars and fingers. Second, a self-learning feature extraction scheme in which the feature extraction templates are changed along with the input image is introduced. Third, the low-rank matrix recovery is applied to the decomposition of self-learning feature matrix for obtaining the preliminary detection result. Fourth, the preliminary detection result is optimized by incorporating the superpixel segmentation. Finally, the optimized result is further fine-tuned by morphological postprocessing.

Comprehensive evaluations are implemented on a data set which includes 120 testing images and corresponding human-annotated ground truth. Specifically, subjective evaluations show that the shape of detected micro-cracks is similar to the ground truth, and objective evaluations demonstrate that the proposed method has a high detection accuracy.

First, a self-learning feature extraction method which has good generalization capability is proposed. Second, the low-rank matrix recovery is combined with superpixel segmentation for locating the defective regions.

Assembly sequence planning (ASP) is a crucial job during assembly process design. However, it is still difficult to reuse the existing solution to solve a new ASP problem. In particular, with the rapid development of digital technologies, the reusable assembly information of an existing solution is not concentrated in one multimedia but dispersed in multiple heterogeneous multimedia, e.g. text, three-dimensional graphics, even images and videos. This paper aims to propose a multimedia case (MC)-based reasoning framework to solve ASP by reusing the existing solution whose assembly information is dispersed in multimedia.

The proposed framework is designed with the introduction of the MC. An MC seamlessly integrates the dispersed assembly information of an existing solution. Under the proposed concept and architecture, the assembly information of an existing solution is extracted to build assembly descriptors of multimedia. Therefore, the MC is captured by organizing the assembly descriptors of corresponding multimedia.

By means of the framework proposed, it is possible to reuse the existing solution whose assembly information is dispersed in multimedia to solve ASP. Moreover, the extraction method of assembly information can flexibly parse most of the multimedia. Finally, the MC has the capability to represent the existing solution by collecting dispersed assembly information.

The proposed framework can discover the similar existing solution and avoid the potential failures confronted in the past so that the feasibility of ASP result can be improved as much as possible.

The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

This paper aims to explore the damage mechanism of a lubricating film on the worn surface of solid self-lubricating composites under different loads.

By comparing the actual stress with the strength, it is possible to determine the approximate wear state of the lubricating film. To prove the validity of the mathematical model that can predict the initiation of micro cracks or even the failure of the lubricating film, M50-5 Wt.% Ag self-lubricating composites (MA) was prepared. Tribological tests of the composites against Si₃N₄ ceramic balls were conducted at room temperature from 2 to 8 N. The electron probe microanalysis images of the lubricating film verify the wear state of the lubricating film.

The study found that the back edge of the contact area is the most vulnerable to destruction. The tensile stress and the equivalent shear stress have a positive correlation with load and friction coefficient. When the load is 4 N, an intact lubricating film covers the worn surface because the tensile stress and the equivalent shear stress are below the tensile strength and the shear strength, respectively; under other working conditions, the lubricating film is destroyed.

This paper has certain theoretical guidance for the study of tribological properties of solid self-lubricating composites. Moreover, this mathematical model is appropriate to be applied for the other composites.

Integrating balance theory and social identify theory, this paper proposes a multilevel model to explain how abusive supervision climate of team impacts the relationship among team members as well as subordinates’ behavior towards their teammates, especially organizational citizenship behavior (OCB).

A survey was conducted to collect two-wave and multi-source data from 398 employees nested in 106 teams from Chinese high-technology companies. Hierarchical linear modeling was conducted to examine the theoretical model.

The results indicate that there is an inverted U-shape association between abusive supervision climate and subordinates’ OCB towards coworker; team member exchange (TMX) mediates their inverted U-shaped link. Furthermore, we confirm that coworker support plays a vitally moderating role upon the curvilinear link of abusive supervision climate (ASC)–TMX; specifically, when employees perceive low coworker support, negative relations between ASC and TMX will be stronger.

This study identifies team members’ advantageous and adverse relational response to shared threat of ASC and examines coworker support as a moderator of ASC, which provides valuable insights into when and why employees tend to cooperate with their teammates to jointly confront their leader’s abuse and highlights the importance of coworkers, thus enabling organizations to deeply understand the wider influences of ASC on interpersonal relationship between team members.

This study aims to improve disaster management. Social media, particularly microblog, has become a new platform for public opinion dissemination. However, few studies have been conducted to explore the structure of public opinions, the approaches for facilitating the spread of public opinions and the results of public opinion dissemination in the context of mobile internet for the purpose of improving disaster management.

This paper chooses Ebola as the research topic and extracts 14,735 Ebola-related data items from Sina Microblogs to examine the information nodes of public opinion and the characteristics of propagation paths on mobile internet. Particularly, nodes of public opinion between mobile terminals and non-mobile terminals are compared.

The results of this paper reveal the characteristics of public opinion propagation on mobile internet and verify the effectiveness of public opinion propagation on mobile internet. This study shows that public opinions propagate quickly, widely and efficiently and further generate great impacts on mobile internet.

The methods used in this study can be useful for the government agencies and other relevant organizations to monitor public opinions, identify issues and problems proactively and develop strategies in a more efficient manner to improve disaster management.

The results of this paper are helpful for related departments to monitor public opinions and to further improve disaster management.

This paper explores the mechanism of public opinion dissemination on mobile internet and further investigates how to improve disaster management through a case study related to Ebola.