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The oil film thickness provides a key performance indicator of a ball bearing lubrication condition. This paper aims to propose an approach to calculate and measure the oil film thickness of the bearing.

On a specially designed test rig, measurement of the capacitance is used to monitor the oil film thickness of ball bearing. A corrected film thickness formula taking account of the influences of non-Newtonian shear thinning and thermal is introduced to predict the oil film thickness of ball bearing. And then the film thickness distribution and the corresponding capacitances are calculated.

Measurement and calculation of oil film thickness in a ball bearing are carried out under various rotating speeds and external loads. By comparing the calculated capacitances with measured results, it can be concluded that the calculated results obtained by the amended film thickness formula are much closer to the test findings than the classical computed values according to Hamrock–Dowson.

A new corrected film thickness formula is introduced in predicting oil film thickness of ball bearing and verified by the series of experiments according to capacitance method.

The impact of network centrality on innovation performance is inconclusive. The purpose of this paper is to examine how formal and informal institutions affect the influence of network centrality on firms’ innovation performance in emerging economies by integrating social network theory and institutional theory.

Multisource and lagged data from 234 technology-based entrepreneurial firms listed on the Chinese Growth Enterprise Market were leveraged to test a proposed research model.

Results suggest that formal institutions (marketization) positively moderate the relationship between network centrality and innovation performance, whereas informal institutions (social cohesion) negatively moderate this relationship. Moreover, formal and informal institutions have a strong joint impact on such relationship, that is, the effect of network centrality on innovation performance is most positive when marketization is high and social cohesion is low.

This empirical research provides new insights into whether and how firms can grasp the innovation benefits of network centrality by exploring institutional contingencies. It further sheds on light the scope of the network centrality–innovation issue by extending its research context to Chinese entrepreneurial firms.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

This paper aims to explore the influence of CO₂ partial pressure, flow rate and water cut on N80 steel corrosion behaviors in the displacement process of oil in glutenite reservoir by CO₂ injection.

A self-made 3 L high-temperature and high-pressure autoclave was used to conduct corrosion simulation experiments of N80 steel in different CO₂ partial pressures, flow rates and water cut (the independently developed oil and water mixing approach can ensure the uniform mixing of oil and water in experiments). Techniques like weight loss and surface analysis were used to analyze the corrosion behaviors of N80 steel under different conditions.

Results showed that the average corrosion rate of N80 steel accelerated at varying degrees with the increase of CO₂ partial pressure, flow rate and water cut. Excluding that the samples showed uniform corrosion under the two conditions of 0.5MPa CO₂ partial pressure and static corrosion, they displayed mesa attack corrosion under other conditions. Besides, with the increase of CO₂ partial pressure, the pH value of solution dropped and the matrix corrosion speed rose, hence leading to the increased Fe²⁺ and CO₃²⁻ concentration. Meanwhile, a lowered pH value improved the FeCO₃ critical supersaturation, thereby leading to an increased nucleation rate/growth rate and ultimately causing the decrease of the dimension of FeCO₃ crystallites formed on the surface of the samples.

The results can be helpful in targeted anti-corrosion measures for CO₂/oil/water corrosive environment.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.