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The purpose of this study is to investigate the contact models for contact and vibration features of cylindrical roller bearings (CRBs). CRBs are important parts of rotating machinery. The contact deformation between the roller and the raceway is an essential research topic for the CRBs. The contact deformation between the roller and the raceway can greatly affect vibration characteristics and fatigue life of the CRBs. In this investigation, six different methods are adopted to calculate the contact deformation, contact area width and contact stress between the roller and raceways of a CRB.

In this paper, the contact deformations and the contact stiffnesses between the roller and the raceway of a CRB obtained by various well-known empirical methods (Lundberg’s, Palmgren’s, Houpert’s, Cheng’s and Hertzian methods) are directly compared with those by the finite element (FE) method. A two degree-of-freedom (2 DOF) dynamic model of the CRB is applied to investigate the effects of the contact stiffness obtained by different line contact deformation calculation methods on the vibration characteristics, such as the root mean square (RMS), the peak to peak (PTP), the crest factor and the kurtosis of the displacement, velocity and acceleration of the inner raceway.

The computational results show that different calculation methods for the contact deformations between rollers and raceways have significant effects on the vibrations of the CRB. It is found that that the differences of computational results obtained by Palmgren’s and Lundberg’s models with respect to the FE method are smaller than those by the other three methods, i.e. Houpert’s, Cheng’s and Hertzain models. The amplitude and peak frequency of the frequency response functions from Palmgren’s method are much more similar to those from the finite element method. The above results indicate that Palmgren’s method is a better calculation method for predicting the contact deformations and dynamics of the CRBs.

This work adopts six different methods to calculate the contact deformation, contact area width and contact stress between the roller and raceways of a CRB. Moreover, a vibration model of a CRB is used to investigate the effect of contact stiffness obtained by the above methods on the vibrations of the CRB. The works can give some guidance for the accurate analytical method for calculating the contact deformations between rollers and raceways and the vibrations of the CRB.

The purpose of this paper is to propose a multi-scale extended grey target decision method for dealing with multi-attribute decision-making problems with interval grey numbers whose value distribution information is asymmetrical.

First, the whitenization weight function (WWF) was adopted to show the value distribution information of interval grey numbers. The definitions of kernel, degree of greyness, relative kernel and whitenization standard deviation of interval grey numbers were given based on the WWF. Then, the relative kernel grey target and whitenization standard deviation grey target were constructed to take full advantage of the owned decision information. Finally, the relative bull’s-eye coefficient was proposed to rank the preference order of all alternatives.

The relative bull’s-eye coefficient reflects the influence of the decision information on decision results with respect to the mean level and value distribution of attribute values. Thus, the decision-maker could set the return and risk adjustment coefficient according to their preferences and select the optimal alternative with a high expected return and low risk.

The paper considers the valve distribution information of interval grey numbers, and a novel definition for kernels, degrees of greyness, relative kernels and whitenization standard deviations, which are given based on the WWF. The paper not only considers the influence of mean levels of decision information over decision results, but also takes the value distribution information into account.

This paper aims to anticipate the possible development direction of WAAM. For large-scale and complex components, the material loss and cycle time of wire arc additive manufacturing (WAAM) are lower than those of conventional manufacturing. However, the high-precision WAAM currently requires longer cycle times for correcting dimensional errors. Therefore, new technologies need to be developed to achieve high-precision and high-efficiency WAAM.

This paper analyses the innovations in high-precision WAAM in the past five years from a mechanistic point of view.

Controlling heat to improve precision is an effective method. Methods of heat control include reducing the amount of heat entering the deposited interlayer or transferring the accumulated heat out of the interlayer in time. Based on this, an effective and highly precise WAAM is achievable in combination with multi-scale sensors and a complete expert system.

Therefore, a development direction for intelligent WAAM is proposed. Using the optimised process parameters based on machine learning, adjusting the parameters according to the sensors’ in-process feedback, achieving heat control and high precision manufacturing.

This study investigates how online sellers can leverage platform-based technologies to mitigate product returns through the lens of affordance actualization theory. We conceptualize four categories of platform-based technologies and theorize how their affordances influence consumer perceptions and behaviors, leading to reduced return rates.

We develop a research model grounded in affordance actualization theory and test our hypotheses using a unique longitudinal dataset from a leading e-commerce platform. We employ panel data analysis with seller fixed effects and conduct various robustness checks to ensure the reliability of our findings. We also examine the synergistic effects among different platform-based technologies and explore their varying impacts across product types and seller characteristics.

The strategic actualization of pricing, marketing, product presentation and customer service technology affordances significantly reduces product return rates. The return-mitigating effects are stronger for low-reputation sellers and high-price, high-complexity products, highlighting the contingent value of technology affordances in managing returns. Besides, we find evidence of synergistic effects among different platform-based technologies, particularly for complex products and less reputable sellers.

This study extends affordance actualization theory to the e-commerce context and uncovers the mechanisms and boundary conditions for platform-based technologies to mitigate product returns. We contribute to the literature by offering a novel theoretical perspective and granular insights into the role of technology in shaping a critical operational outcome in online retailing.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.

A core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.

A two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.

The results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.

The proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.