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This study aims to investigate mixed lubrication performances of stern bearing in a misaligned state considering turbulence and bearing deformation impacts.

A mixed lubrication model of stern bearing is established. The generalized average Reynolds equation governing the turbulent flow of lubricant is analyzed by considering the interaction of bearing elastic deformation, asperity contact pressure and film pressure. The bearing behaviors including minimum film thickness, hydrodynamic pressure, asperity friction force and frictional coefficient are studied under different models. The correctness of this model is verified by comparing it with that of the published data.

Numerical results indicate that elastic deformation noticeably decreases the maximum film pressure, the asperity contact force and the friction coefficient in the mixed lubrication stage. The effect of elastic deformation and turbulence reduces the transition speed from mixed to liquid lubrication.

This model includes both turbulence and bearing deformation impacts on journal bearing performances. It is expected that the numerical results can provide useful information to establish a stern bearing exposed to mixed lubrication conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0352/

This paper aims to extend understanding of how team creative potential translates into team creativity. Drawing on social exchange theories, the authors propose that reward interdependence produce cooperative intra-team interactions, which in turn enables aggregate levels of individual member creativity to translate into team creativity. Further, the authors propose that reward interdependence enhances this link indirectly by motivating collective norms around knowledge sharing.

Multi-source and multi-wave data was collected from 94 R&D teams in two large medical firms. At Time 1, team members assessed the degree of reward interdependence and knowledge sharing characterizing their team; team leaders rated each member’s individual creativity. Unit leaders reported on the team’s overall creativity at Time 2 (three months after Time 1).

The results indicate that the effect of aggregate member creativity (AMC) on team creativity is moderated by reward interdependence in such a way that when reward interdependence is high, AMC has stronger positive effects on team creativity. Furthermore, knowledge sharing, as motivated by reward interdependence, mediates this moderating effect.

By integrating the team design and team creativity literatures, this paper advances an interactive model in which team creative composition combines with reward interdependence and knowledge sharing to help team creativity.

This paper aims to report the tribological behavior of Ag nanoparticles/reduced graphene oxide nanocomposites (Ag/RGO NCs) and Ag nanoparticles (Ag NPs) as a green additive in oil with different concentration and under different friction conditions.

The Ag/RGO NCs and Ag NPs were both synthesized in a chemical reduction method. The diameter of silver nanoparticles implanted between RGO sheets was about 25 nm and that of silver sol was 70 nm. The morphology and structure of Ag/RGO NC were characterized by TEM, XRD and FTIR. The tribological properties of Ag/RGO NCs and Ag NPs as lubricant oil additive were evaluated by measuring the friction coefficients and wear of the surface in different condition which were tested on UMT-II.

The results indicated that both the additives improved the friction-reduced and anti-wear properties of paraffin oil, and Ag/RGO NCs has better tribological performance than Ag NPs. The excellent tribological properties were attributed to the special structure of Ag/RGO NC and the formation of tribofilm reducing the friction and wear on the shearing surfaces.

It is relatively difficult to observe the morphology of the lubricant film formed on the friction surface and to analyze the chemical composition at different depths of the lubricant film.

It is the first time for Ag/RGO NCs to be applied to improve the friction-reduced and anti-wear properties of lubricant oil as additive.

The purpose of this study is to investigate the relationship between sustainable leadership and sustainable project performance. Specifically, the study aims to examine the mediating role of knowledge integration, examining how knowledge integration within an organization influences project outcomes. In addition, the study seeks to explore the moderating role of top management knowledge values, examining how the values and beliefs of top management influence the relationship between sustainable leadership and project performance.

A three-wave survey of 392 employees working in construction sector projects in Pakistan used both hierarchical regression analysis and Hayes’ PROCESS macro method to evaluate the hypotheses.

The study results show that sustainable leadership positively relates to sustainable project performance and knowledge integration mediating this relationship. In addition, the top management knowledge value moderates the indirect effect of sustainable leadership on sustainable project performance via knowledge integration.

Although the model was tested using three-wave data, it is important to note that the data were obtained from a single source. Therefore, it is possible that common method bias may have influenced the results, and this cannot be disregarded.

Organizations seek to prioritize sustainability and integrate sustainability considerations into their project management processes. Organizations can achieve improved sustainable project performance by investing in sustainable leadership development, fostering a culture of knowledge sharing and learning, prioritizing top management support for sustainable performance and integrating sustainable considerations into project management processes.

The study’s grounding on organizational learning theory adds an original and valuable perspective to the relationship between sustainable leadership and sustainable project performance. This investigation is original, as it combines sustainable leadership, knowledge integration and the moderating role of top management knowledge value to understand their impact on sustainable project performance. This unique approach contributes to the literature by providing new insights into these relationships and mechanisms in the construction industry.

This paper aims to optimize the weighing control system and compensate weighing error for weighing control system of coal mine paste-filling weighing control system.

The process of the paste-filling weighing control system is analyzed and the mathematical model of the paste-filling material weight is established. Then, the back-propagation (BP) neural network is used to optimize the control system and compensate the weighing error.

Without the BP neural network, the weighing error of the paste-filling control system is more than 3 per cent, whereas after optimization with the BP neural network, the weighing error is less than 1 per cent. With the simulation results, it is seen that the weighing error of the paste-filling control system decreases and the accuracy of the weighing control system improves and optimizes.

The method can be further used to improve the control precision of the coal mine paste-filling system.

The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

The purpose of this paper is to present an algorithm for determining the inner and outer loops of arbitrary parametric surfaces.

The algorithm considers two sub-algorithms: one for non-closed surfaces and another one for closed surfaces. The first sub-algorithm named by area positive and negative method (APNM), combines a curve discretization algorithm with the polygon direction judgment algorithm to judge the inner and outer loops of non-closed surfaces. The second sub-algorithm, called by cross-period number method (CPNM), combines a curve discretization algorithm with the periodicity of closed surfaces to judge the type of boundary loops.

The APNM can use less CPU time to determining the inner and outer loops of the non-closed parametric surfaces. The CPNM can also determine the inner and outer loops of closed parametric surfaces effectively. The judgment results of loops can ensure that the direction of meshes generated on these surfaces is right. And finally ensure the correctness of the numerical simulation results.

Several numerical examples presented have verified the robustness and efficiency of the proposed algorithm. Compared with the conventional algorithm, the more complex the model, the more time the APNM saves in the process of determining the inner and outer loops for non-closed surfaces. The CPNM is also a new method to determining the inner and outer loops for closed parametric surfaces. The single run-time of CPNM is very small and can reach the level of microseconds.

The purpose of the work reported in this paper is to prepare hybrid pigments fabricated by depositing pigment yellow 12 (PY12) on the surface of silica gel to improve the application performance of the resulting pigments. The particle size distribution, optical properties, thermal stability, water dispersibility and flowability of the pigments with and without silica gel modification were studied.

The hybrid pigments were synthesised with different amount of silica gel. The modified pigments were characterised by Fourier transforms infrared spectroscopy, X-ray diffraction, thermal analysis, scanning electron microscopy and transmission electron microscopy.

The particle size distribution of the modified pigments was found to have been altered significantly. This can be explained by the interaction between pigments and silica gel, which prevented self-aggregation of pigment particles and hence improved the properties of pigments.

Only silica supports and pigment yellow 12 were evaluated. Other pigments could also be studied.

Modification of pigment particles with smaller particle size can increase the efficiency of the modified pigment, in terms of colour shade and tinting strength, due to better particle size distribution.

The paper demonstrates that inorganic core can prevent self-aggregation of pigment particles, and the application properties of such pigment depend on the resulting degree of dispersion of pigment particles.

Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and measurement of regional science and technology innovation policy urgently require research attention.

In this paper, we use text mining and principal component analysis to analyze the classification and measurement of technology innovation policy based on data obtained from Zhongguancun Science Park.

The empirical results indicate that regional science and technology innovation policy can be divided into four types: authoritative, guiding, urgent and periodical. The key measurements are function type, intensity, resource supply, funding level and funding effectiveness.

A comparative analysis is performed to investigate the different types of regional science and technology innovation policy measurement. Additionally, the study’s limitations are discussed, and future research directions are proposed.

The paper proposed a fast procedure for solving the reliability-based robust design optimization (RBRDO) by modifying the RBRDO formulation and transforming it into a series of RBRDO subproblems. Then for each subproblem, the objective function, constraint function and reliability index are approximated using Taylor series expansion, and their approximate forms depend on the deterministic design vector rather than the random vector and the uncertain estimation in the inner loop of RBRDO can be avoided. In this way, it can greatly reduce the evaluation number of performance function. Lastly, the trust region method is used to manage the above sequential RBRDO subproblems for convergence.

As is known, RBRDO is nested optimization, where the outer loop updates the design vector and the inner loop estimate the uncertainties. When solving the RBRDO, a large evaluation number of performance functions are needed. Aiming at this issue, the paper proposed a fast integrated procedure for solving the RBRDO by reducing the evaluation number for the performance functions. First, it transforms the original RBRDO problem into a series of RBRDO subproblems. In each subproblem, the objective function, constraint function and reliability index caused are approximated using simple explicit functions that solely depend on the deterministic design vector rather than the random vector. In this way, the need for extensive sampling simulation in the inner loop is greatly reduced. As a result, the evaluation number for performance functions is significantly reduced, leading to a substantial reduction in computation cost. The trust region method is then employed to handle the sequential RBRDO subproblems, ensuring convergence to the optimal solutions. Finally, the engineering test and the application are presented to illustrate the effectiveness and efficiency of the proposed methods.

The paper proposes a fast procedure of solving the RBRDO can greatly reduce the evaluation number of performance function within the RBRDO and the computation cost can be saved greatly, which makes it suitable for engineering applications.

The standard deviation of the original objective function of the RBRDO is replaced by the mean and the reliability index of the original objective function, which are further approximated by using Taylor series expansion and their approximate forms depend on the deterministic design vector rather than the random vector. Moreover, the constraint functions are also approximated by using Taylor series expansion. In this way, the uncertainty estimation of the performance functions (i.e. the mean of the objective function, the constraint functions) and the reliability index of the objective function are avoided within the inner loop of the RBRDO.