Search results

This study aims to enhance the lubrication performance of thrust bearings. The influence of columnar convex–concave compound microtexture on bearing performance is investigated

Based on the compound microtexture model of thrust bearings, considering surface roughness and turbulent effect, the variation of lubrication characteristics with the change in the compound microtexture parameters is studied.

The results indicate that, compared with circular microtexture, the maximum pressure of compound microtexture of thrust bearings increases by 7.42%. Optimal bearing performance is achieved when the internal microtexture depth is 0.02 mm. Turbulent flow states and surface roughness lead to a reduction in the optimal depth. The maximum pressure and load-carrying capacity of the bearing decrease as the initial angle increases, whereas the friction coefficient increases with the increase in the initial angle. The lubrication performance is best for bearings with a circumferential parallel arrangement of microtexture.

The novel composite microtexture with columnar convex-concave is proposed, and the computational model of thrust bearings is set. The influence of surface roughness and turbulent flow on the bearing performance should be considered for better conforming with engineering practice. The effect of microtexture depth, arrangement method and distribution position on the lubrication performance of the compound microtexture thrust bearing is investigated, which is of great significance for improving tribology, thrust bearings and surface microtexture theory.

The purpose of this study is to numerically investigate the geometric influence of different corrugation profiles (rectangular, trapezoidal and triangular) of varying heights on the flow and the natural convection heat transfer process over isothermal plates.

This work is an extension and finalization of previous studies of the leading author. The numerical methodology was proposed and experimentally validated in previous studies. Using OpenFOAM® and other free and open-source numerical-computational tools, three-dimensional numerical models were built to simulate the flow and the natural convection heat transfer process over isothermal corrugation plates with variable and constant heights.

The influence of different geometric arrangements of corrugated plates on the flow and natural convection heat transfer over isothermal plates is investigated. The influence of the height ratio parameter, as well as the resulting concave and convex profiles, on the parameters average Nusselt number, corrected average Nusselt number and convective thermal efficiency gain, is analyzed. It is shown that the total convective heat transfer and the convective thermal efficiency gain increase with the increase of the height ratio. The numerical results confirm previous findings about the predominant effects on the predominant impact of increasing the heat transfer area on the thermal efficiency gain in corrugated surfaces, in contrast to the adverse effects caused on the flow. In corrugations with heights resulting in concave profiles, the geometry with triangular corrugations presented the highest total convection heat transfer, followed by trapezoidal and rectangular. For arrangements with the same area, it was demonstrated that corrugations of constant and variable height are approximately equivalent in terms of natural convection heat transfer.

The results allowed a better understanding of the flow characteristics and the natural convection heat transfer process over isothermal plates with corrugations of variable height. The advantages of the surfaces studied in terms of increasing convective thermal efficiency were demonstrated, with the potential to be used in cooling systems exclusively by natural convection (or with reduced dependence on forced convection cooling systems), including in technological applications of microelectronics, robotics, internet of things (IoT), artificial intelligence, information technology, industry 4.0, etc.

To the best of the authors’ knowledge, the results presented are new in the scientific literature. Unlike previous studies conducted by the leading author, this analysis specifically analyzed the natural convection phenomenon over plates with variable-height corrugations. The obtained results will contribute to projects to improve and optimize natural convection cooling systems.

Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

This study comprehensively examines entropy generation and thermosolutal performance of a ternary hybrid nanofluid in a partially active porous cabinet. The purpose of this study is to comprehend the intricate phenomena of double diffusion by investigating the dispersion behavior of Al₂O₃, CuO, and Ag nanoparticles in water.

The cabinet design consists of two horizontal walls and two curved walls with the lower border divided into a heated and concentrated region of length b and the remaining sections are adiabatic. The vertical borders are cold and low concentration, while the upper border is adiabatic. Two cavity configurations such as convex and concave are considered. A uniform porous medium is taken within the ternary hybrid nanofluid. This has been characterized by the Brinkman-extended Darcy model. Thermosolutal phenomena are governed by the Navier-Stokes equations and are solved by adopting a higher-order compact scheme.

The present study focuses on exploring the influence of several well-defined parameters, including Rayleigh number, Darcy number, Lewis number, Buoyancy ratio number, nanoparticle volume concentration and heater size. The results indicate that the ternary hybrid nanofluid outperforms both the mono and hybrid nanofluids in all considered aspects.

This study brings forth a significant contribution by uncovering novel flow features that have previously remained unexplored. By addressing a well-defined problem, the work provides valuable insights into the enhancement of thermal transport, with direct implications for diverse engineering devices such as solar collectors, heat exchangers and microelectronics.

This paper examines the effect of market knowledge on market success of product innovativeness and the moderating role of absorptive capacity. We separated market knowledge into market diversity and market significance components and examined their effects on radical product innovation performance.

This paper adopted the secondary database study. Excluding cases with missing values of main variables, a total of 1,219 Taiwanese manufacturing firms from the Third Taiwan Technology Innovation Survey (TTIS3) database were used to test the hypotheses. A moderated hierarchical regression approach was utilized to analyze the data.

The results revealed that the relationship between market diversity and radical product innovation performance is a predominantly positive concave downward curve. In contrast, the relationship between market significance and radical product innovation performance is a predominantly negative concave downward curve. Furthermore, the results also indicated that absorptive capacity has different moderating effects on the relationships between market diversity/significance and radical product innovation performance. Absorptive capacity enhances the negative effect of market significance but suppresses the positive effect of market diversity on radical product innovation performance.

This paper is the first research which contributes to examining the relationship between market knowledge and radical product innovation sale performance.

This study aims to investigate how gender diversity and remuneration of boards of directors’ influence earnings quality for Spanish-listed firms.

The sample includes 105 nonfinancial Spanish firms from 2013 to 2018, corresponding to an unbalanced panel of 491 firm-year observations. The primary empirical method uses a Tobit semiparametric estimator with firm- and industry-level fixed effects and an innovative set of measures for earnings quality developed by StarMine.

Results exhibit a positive correlation between increased gender diversity and a firm’s earnings quality, suggesting that a gender-balanced board of directors is associated with more transparent financial reporting and informative earnings. We also find a nonmonotonic, concave relationship between board remuneration and earnings quality. This indicates that beyond a certain point, excessive board compensation leads to more opportunistic manipulation of financial reporting with subsequent degradation of earnings quality.

This study only covers nonfinancial Spanish listed firms and is silent about how alternative board features’ influence earnings quality and their informativeness.

This study introduces measures of earnings quality developed by StarMine that have not been used in the empirical literature before as well as measures of board gender diversity applied to a suitable Tobit semiparametric estimator for fixed effects that improves the precision of results. In addition, while most of the literature focuses on Anglo-Saxon countries, this study discusses board gender diversity and board remuneration in the underexplored context of Spain. Moreover, the hand-collected data set comprising financial reports provides previously untested board features as well as a nonlinear relationship between remuneration and earnings quality that has not been thoroughly discussed before.

Current open innovation (OI) and external knowledge search (EKS) research primarily shows a positive linear relationship between EKS and innovation at an individual level. However, organizational scholarship argues that excessive EKS may harm innovation. This study combines the knowledge-based view (KBV) and attention-based view (ABV) to articulate a nonlinear theory of EKS and innovation at the individual level.

The authors constructed a multi-sourced dataset covering 59,798 USA pharmaceutical patents spanning from 1975 to 2014 and employed negative binomial fixed-effect models to examine theoretical hypotheses.

We find a significant concave curvilinear relationship between EKS and innovation quantity as well as innovation quality at an individual level. An individual’s knowledge breadth and depth moderate the relationship between EKS and innovation, such that the threshold at which EKS has diminishing returns for individual innovation is higher for inventors with a broad range of knowledge and those with deeper expertise in the domain where they are innovating.

Managers should guide inventors toward a moderate investment of time and effort in EKS and should caution against over searching. Besides, managers should recognize that an inventor’s capacity for EKS is determined in part by their breadth of knowledge across various domains as well as the depth of knowledge they have in the knowledge domain where they are innovating.

We provide both parties with a clearer understanding of when EKS can begin to deteriorate an individual’s innovation performance why that deterioration occurs, and we also highlight two individual-level knowledge characteristics to take into consideration when deciding when to cease the EKS process.

This study provides a novel holistic understanding of OI and knowledge management for policymakers and organizations to nourish innovation dynamism and make the best of knowledge stocks in the community, which in turn will create endless power for sustainable social change and inclusive development.

This study contributes to OI theory by highlighting the non-linear nature of the relationship between EKS and innovation on an individual level. This represents a fundamental shift in theory on EKS and individual innovation by suggesting a major rethinking of how the two concepts relate, revealing the dark side of EKS in knowledge management if inventors engage in excessive EKS. Likewise, our study’s incorporation of the ABV informs KBV scholarship by highlighting the role of the limited attentional capacity of individuals in firm knowledge management.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.

The performance of oil-filled pressure cores is very much affected by the corrugated diaphragm and the oil filling volume. The purpose of this paper is to show the effects of different corrugated diaphragms, different oil filling volumes and different treatments of the corrugated diaphragms on the performance of pressure sensors.

Pressure-sensitive cores with different diaphragm diameters, different diaphragm ripple numbers and different oil filling volumes are produced, and thermal cycling is introduced to improve the diaphragm performance, and finally the performance of each pressure-sensitive core is tested and the test data are analyzed and compared.

The experimental results show that the larger the diameter of the corrugated diaphragm used for encapsulation, the better the performance. For pressure-sensitive cores using smaller diameter corrugated diaphragms, the performance of one corrugation is better than that of two corrugations. When the number of corrugations and the diameter are the same size, the performance of the outer ring of the diaphragm with concave corrugations is better than that with convex corrugations. At the same time, the diaphragm after thermal cycling treatment and appropriate reduction of encapsulated oil filling can improve the performance of the pressure-sensitive core.

By exploring the effects of corrugated diaphragm and oil filling volume on the performance of oil-filled pressure cores, the design of oil-filled pressure sensors can be guided to improve sensor performance.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.