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This study aims to obtain a design scheme of the surface texture on mechanical seal with lower friction and leakage by comparing two common texture types: dimples and grooves.

An optimal free-form shape and an optimal circular shape were chosen by multi-objective optimization, and two types of grooves with different directions were chosen by a series of experiments. Then, the optimal free-form dimple, the optimal circular dimple, the groove perpendicular to the direction of movement (hereafter called groove-1) and the groove angled at 60° to the direction of movement (hereafter called groove-2) were compared by experiments under different loads.

The optimal free-form dimple shows a better performance in terms of a lower coefficient of friction (COF) and a lower leakage than the other shapes, especially for the high speed and low load conditions. The reduction rate of COF is up to 37.5%, and the leakage rate is reduced by about 12.5%. The dimples have a lower leakage than the grooves. The groove angled at 60° to the direction of movement is easier to pump the oil into the interface of the sealing face, leading to a lower friction but a higher leakage.

This study provides a feasible surface texture design scheme for improving the combination performance of mechanical seals.

The purpose of this study is to investigate the influence of groove shape on the hydrodynamic characteristics of a journal bearing.

The computational fluid dynamics model also takes into account the cavitation phenomena and thermal effect, which can illustrate the lubrication performance of a journal bearing.

The hydrodynamic simulations of the journal bearing with the different groove shapes are conducted under different operation conditions.

Based on the numerical analysis, the suggestions are presented for groove shape selection and can be used to the design of a journal bearing under the extreme operation condition.

The purpose of this paper is to provide a solution for Reynolds equation with both throttling term and reverse throttling term and provides a reference for changing damping of hydrostatic bearing.

The reverse throttling term is introduced into the Reynolds equation, and the adaptive damping factor is used in the Newton iteration method to improve convergence of numerical calculations. The static and dynamic performances of this bearing are numerically investigated by the finite-element method.

The results indicate that the reflux orifices lead to a decrease in load capacity at a high eccentricity ratio. Additionally, the mass inflow rate is increased; however, the additional inflow increase can be controlled by enhanced backpressure of the reflux orifice. Nevertheless, the bearing with the reflux orifice shows superiority in resisting high-frequency disturbances and enhances direct damping by 20% under a high backpressure.

This work presents an adaptive Newton damping iterative method for solving Reynolds equation with both throttling term and reverse throttling term. This work also provides a new idea for bearing structure design in improving damping.

The purpose of this paper is to examine the use of fused deposition modelling (FDM) models and finite element analysis (FEA) related to dysplastic hip orthopaedic surgery.

The study involved the use of Mimics and Abaqus softwares. Mimics was used to process the CT scan patient data to STL format before producing FDM models which were for before and after surgery. FEA was done to study the two different type of implant biomaterials used in dysplastic hip surgery.

The use of FDM pre models for preplanning of dysplastic hip surgery by orthopaedic surgeons and viewing of the surgery outcome via FDM post models. Different implant biomaterials used gave different results in reduction of stresses that were achieved.

This is original work involving patients in hospital, which got ethical approval and was funded by a university grant. The paper describes a new kind of research in the university.

As the grey systems theory has been used over the time in different economic areas, in the following, a short literature review will be put forward, starting from the usage of these theory in the supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, etc. The purpose of this paper is to identify some key studies from all the economic areas in which the grey systems can be used in order to open and to bring to the researchers new domains in which they can manifest their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Web of Science, a literature review has been performed for the economic grey systems applications developed over the time on both economic diagnosis and system’s forecasting. In addition, some hybrid grey systems theory – artificial intelligence techniques models have also been presented.

The grey systems theory has brought its contribution to numerous economic application from various fields such as: supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, firms’ bankruptcy, product development, consumer income, monetization ratio, etc.

The present paper identifies the some of the most representative examples in which the grey theory has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

Unlike other review papers written on the grey systems theory area, the present paper is only focusing on the economic applications in which this theory has been successfully used, bringing to the reader a general overview on this field and, in the same time, enabling new research perspectives.

The purpose of this paper is to identify smaller wear particles and improve the calculation speed, identify more abrasive particles and promote industrial applications.

This paper studies a new intelligent recognition method for equipment wear debris based on the YOLO V5S model released in June 2020. Nearly 800 ferrography pictures, 23 types of wear debris, about 5,000 wear debris were used to train and test the model. The new lightweight approach of wear debris recognition can be implemented in rapidly and automatically and also provide for the recognition of wear debris in the field of online wear monitoring.

An intelligent recognition method of wear debris in ferrography image based on the YOLO V5S model was designed. After the training, the GIoU values of the model converged steadily at about 0.02. The overall precision rate and recall rate reached 0.4 and 0.5, respectively. The overall MAP value of each type of wear debris was 40.5, which was close to the official recognition level of YOLO V5S in the MS COCO competition. The practicality of the model was approved. The intelligent recognition method of wear debris based on the YOLO V5S model can effectively reduce the sensitivity of wear debris size. It also has a good recognition effect on wear debris in different sizes and different scales. Compared with YOLOV. YOLOV, Mask R-CNN and other algorithms%2C, the intelligent recognition method based on the YOLO V5S model, have shown their own advantages in terms of the recognition effect of wear debris%2C the operation speed and the size of weight files. It also provides a new function for implementing accurate recognition of wear debris images collected by online and independent ferrography analysis devices.

To the best of the authors’ knowledge, the intelligent identification of wear debris based on the YOLO V5S network is proposed for the first time, and a large number of wear debris images are verified and applied.