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The objective of this study is to use non-destructive testing of corrosion on coated aluminium alloys using differential eddy current detection (DECD), with the aim of elucidating the relationship between the characteristics of corrosion defects and the detection signal.

Pitting corrosion defects of varying geometrical dimensions were fabricated on the surface of aluminium alloy plates, and their impedance signals were detected using DECD to investigate the influence of defect diameter, depth, corrosion products and coating thickness on the detection signals. Furthermore, finite element analysis was used to ascertain the eddy current distributions and detection signals under different parameters.

The size of the defect is positively correlated with the strength of the detection signal, with the defect affecting the latter by modifying the distribution and magnitude of the eddy current. An increase in the diameter and depth of corrosion defects will enhance the eddy current detection (ECD) signal. The presence of corrosion products in the corrosion defects has no significant effect on the eddy current signal. The presence of a coating results in a decrease in the ECD signal, with the magnitude of this decrease increasing with the thickness of the coating.

The objective is to provide experimental and theoretical references for the design of eddy current non-destructive testing equipment and eddy current testing applications.

Water lubrication is significant for its environmental friendliness. Composite journal bearing is liable to deform for the huge pressure of water film. This paper aims to study the influence of elastic deformation on how lubrication functions in water-lubricated journal bearings and to provide references for designing composite journal bearings.

The combination of computational fluid dynamics and fluid-structure interaction is adopted in this paper to study the lubrication performance of water-lubricated compliant journal bearings. The influences of elasticity modulus and Poisson’s ratio on load-carrying capacity and elastic deformation are studied for different rotational speeds. Predictions in this work are compared with the published experimental results, and the present work agrees well with the experimental results.

A reference whether elastic deformation should be considered for composite journal bearings is proposed under different working conditions. Besides, a reference to determine water-lubricated plain journal bearings dimensions under different loads and rotational speeds is developed with the effect of both elastic deformation and cavitation being accounted.

The present research provides references as to whether elastic deformation should be considered in operation and to determine compliant journal bearings’ dimensions in the design process.

The purpose of this paper is to develop a novel autonomous in‐pipe robot to perform the preventive point reparation for long‐distance offshore oil pipelines.

The autonomous in‐pipe robot performs online ultrasonic inspection for pipe wall thickness, and the original inspection data are stored in large capacity hard disk. Through the offline data analysis by the data analysts and the software tool, the pipeline health status is known. If server defects lie there, the in‐pipe robot is introduced into the pipeline once more to indicate the defect's location to the maintenance ship.

The laboratory tests and the field tests prove the feasibility and validity of the developed autonomous in‐pipe robot. Furthermore, the application of intelligent control techniques ensures the mission completion by the autonomous in‐pipe robot, which worked in the awful pipeline environment.

The developed autonomous in‐pipe robot helps eliminate lost production costs and pipeline downtime caused by leakages and guarantees the safe run of offshore oil pipelines.

For the application of the autonomous in‐pipe robot, there are no special requirements for maintained pipelines themselves, so it is applicable to the point reparation for most long‐distance welded offshore pipelines.

This purpose of this study was to investigate the effects of carbon fiber (CF) and/or glass fiber (GF) fillers on the tribological behaviors of ultrahigh-molecular-weight polyethylene (UHMWPE) composites to develop a high-performance water-lubricated journal bearing material.

Tribological tests were conducted using a pin-on-disc tribometer using polished GCr15 steel pins against the UHMWPE composite discs under dry conditions with a contact pressure of 15 MPa and a sliding speed of 0.15 m/s. Scanning electron microscopy, laser 3D micro-imaging profile measurements and energy-dispersive X-ray spectrometry were used to analyze the morphologies and elemental distributions of the worn surfaces.

The results showed that hybrid CF and GF fillers effectively improved the wear resistance of the composites. The fiber fillers decreased the contact area, promoted transfer from the polymers and decreased the interlocking and plowing of material pairs, which contributed to the reduction of both the friction coefficient and the wear rate.

The UHMWPE composite containing 12.5 Wt.% CF and 12.5 Wt.% GF showed the best wear resistance of 2.61 × 10⁻⁵ mm³/(N·m) and the lower friction coefficient of 0.12 under heavy loading. In addition, the fillers changed the worn surface morphology and the wear mechanism of the composites.

The purpose of this paper is to study the friction and wear properties of journal bearings under different working conditions.

Friction coefficient and wear losses of journal bearing under different working conditions have been determined by a bearing test rig. The worn surfaces of bearing were examined by scanning electron microscopy and laser three-dimensional micro-imaging profile measurements, and the tribological behavior and wear mechanisms were investigated.

The wear loss and friction coefficient of bearing under starting-stopping working condition is far greater than that of steady-state working conditions. In addition, the maximum wear loss under start-up and stop conditions is about 120 times of that under stable operating conditions. Under stable working conditions, the main wear forms of bearings are abrasive wear, under starting-stopping working conditions the main wear mechanisms of bearings are adhesion wear, abrasive wear and fatigue wear.

These research results have certain practical value for understanding the tribology behavior of journal bearings under different working conditions.

The purpose of this paper is to study the frictional behaviors of CuAl10Fe3 journal bearings sliding against chromium electroplated 42CrMo shafts and diamond-like carbon-coated 42CrMo shafts, respectively, under two different conditions and to compare the two kinds of friction pairs.

All journal bearing samples underwent 24 h running-in and repeatability verification. Then, the journal bearing friction experiments were carried out under two different conditions. After testing, the torques, friction coefficients, power consumptions and other parameters were obtained.

The pair of CuAl10Fe3 journal bearing and diamond-like carbon–coated shaft could drive greater load to start up than the pair of CuAl10Fe3 journal bearing and chromium electroplated 42CrMo shaft, but it had greater power consumption during the steady running period under the identical condition. With the changing of specific pressure or rotational speed, the friction coefficients had different variations. The frictional oscillations appeared at 32 rotations per minute under heavy loads for both kinds of pairs, the oscillation frequencies were equal to rotational frequency of the test shaft and the oscillation amplitude for diamond-like carbon coating was much greater.

These results have guiding significance for practical industrial applications.

Ball grid array (BGA) package is prone to failure issues in a thermal vibration-coupled environment, such as deformation and fracture of solder joints. To predict the minimum equivalent stress of solder joints more accurately and optimize the solder joint structure, this paper aims to compare the machine learning method with response surface methodology (RSM).

This paper introduced a machine learning algorithm using Grey Wolf Optimization (GWO) Support Vector Regression (SVR) to optimize solder joint parameters. The solder joint height, spacing, solder pad diameter and thickness were the design variables, and minimizing the equivalent stress of solder joint was the optimization objective. The three dimensional finite element model of the printed circuit board assembly was verified by a modal experiment, and simulations were conducted for 25 groups of models with different parameter combinations. The simulation results were employed to train GWO-SVR to build a mathematical model and were analyzed using RSM to obtain a regression equation. Finally, GWO optimized these two methods.

The results show that the optimization results of GWO-SVR are closer to the simulation results than those of RSM. The minimum equivalent stress is decreased by 8.528% that of the original solution.

This study demonstrates that GWO-SVR is more precise and effective than RSM in optimizing the design of solder joints.

The purpose of this study was to solve the problem of most woven-fabric self-lubricating bearings that find it difficult to function at temperatures above 320°C, by designing a new type of new nuclear joint bearing. The results of this study will help designers to achieve accurate stress distribution, displacement deformation, fatigue life and damage of bearings. All of these can be a guide for designing self-lubricating joint bearings.

Finite element analysis is undertaken to simulate the new design bearings. To get the most appropriate and accurate results, the room temperature simulation (Simulation A), the modulus of elasticity that changes with temperature (Simulation B) and the thermal-structure-coupled simulation (Simulation C) are compared. The fatigue simulation is conducted to verify whether the self-lubricating method is reasonable and whether the bearing can function for over 60 years in an enclosed environment.

Stress distribution and displacement deformation of joint bearing can be accurately achieved via the thermal-structure coupled simulation. Work life and damage results have been achieved via the fatigue analysis, and the suggested working loads can be calculated via safety factors.

The newly designed joint bearing in which the graphite is laid on the outside of the inner ring functions and self-lubricates at temperatures above 320°C.

Despite recent organizational behavior studies have witnessed considerable progress in abusive supervision research; some demerits for both theory and methodology still remain in the past years. To clarify the current state of knowledge in the field, this study aims to analyze the current state of theories and methods on abusive supervision and provides a detailed future research agenda.

This paper conducted a literature review for both theory and methodology of the abusive supervision research using a content analysis of 134 publications.

For the theory part, this paper summarized the theories that had been applied to explain the relationship between abusive supervision and its consequences as well as antecedents. For the methodology part, this paper outlined some critical issues regarding country of origin, research design, measurement, analysis strategy and also summarized with a discussion of the relationship between methodological issues and article impact. Finally, this paper concluded by presenting an agenda for future abusive supervision research regarding both theory and methodology.

First, this paper summarizes the main theories, antecedents and consequences often used in abusive supervision research to allow scholars to carry out theoretically driven research investigating abusive supervision in the future. Second, through a content analysis of the methods sections of abusive supervision research in the samples (i.e. country of origin, research design, measurement and analytical procedures), this paper identified the potential reasons underlying the inconsistency in the conclusions of abusive supervision research and provide some guidance for future empirical studies. Third, based on the qualitative review, this paper provides an agenda for future research investigating abusive supervision by developing a content-specific theoretical framework to benchmark abusive supervision research against other research related to leadership and offers an accurate response to scholars’ criticisms of abusive supervision research.

We have proposed and implemented AgentMatcher, an architecture for match‐making in e‐Business applications. It uses arc‐labeled and arc‐weighted trees to match buyers and sellers via our novel similarity algorithm. This paper adapts the architecture for match‐making between learners and learning objects (LOs). It uses the Canadian Learning Object Metadata (CanLOM) repository of the eduSource e‐Learning project. Through AgentMatcher’s new indexing component, known as Learning Object Metadata Generator (LOMGen), metadata is extracted from HTML LOs for use in CanLOM. LOMGen semi‐automatically generates the LO metadata by combining a word frequency count and dictionary lookup. A subset of these metadata terms can be selected from a query interface, which permits adjustment of weights that express user preferences. Web‐based pre‐filtering is then performed over the CanLOM metadata kept in a relational database. Using an XSLT (Extensible Stylesheet Language Transformations) translator, the pre‐filtered result is transformed into an XML representation, called Weighted Object‐Oriented (WOO) RuleML (Rule Markup Language). This is compared to the WOO RuleML representation obtained from the query interface by AgentMatcher’s core Similarity Engine. The final result is presented as a ranked LO list with a user‐specified threshold.