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An electrorheological (ER) fluid comprises dielectric particles suspended in an insulating viscous medium. ER lubricants are considered smart lubricants. They have been applied in hydraulic valves, power transmission devices and damping systems. The purpose of this study is to investigate the performance of hydrostatic thrust bearing operating with ER lubricant.

Reynold’s equation was used to model the flow of the ER lubricant in the bearing. The continuous Bingham model was used to express the viscosity of the ER lubricant as a function of yielding stress, applied electric field and shear strain rate. The Reynolds equation is solved using the finite element method (weighted residual approach) to compute the film pressure as a primary variable and the lubricant flow rate, load-carrying capacity, stiffness and damping parameters as associated performance indices.

The effects of the pocket shape, compensating elements and ER lubricant on the bearing performance were investigated. The application of ER lubricant significantly enhanced the load-carrying capacity (48.2%), stiffness (49.8%) and damping (4.95%) of the bearings. Circular and triangular pocket bearings with constant-flow valves have been reported to provide better steady-state and rotor-dynamic performances, respectively.

This study presents the effect of an ER lubricant on the rotor-dynamic performance of hydrostatic thrust bearings with different pocket shapes.

This paper aims to describe an innovative recruitment campaign at HCL Technologies, India’s fourth largest information technology company. This campaign received media coverage in 60 national and international news outlets.

Using case study methodology, this paper explains how the unique process was carried out. Risks associated with the process are also identified.

It reveals that creative thinking and innovate practices can generate high social media engagement at a very low cost, while also fulfilling the task of recruitment. Managing risks inherent in the process is essential for reaping the rewards of this creative recruitment process.

The process described here can be emulated by other companies too. If executed well, rich dividends can be obtained at a modest cost. Companies can increase their engagement and brad equity at a low cost using this process.

The case study described here is unique in its approach toward recruitment and brand building.

An electrorheological (ER) fluid consists of dielectric particles blended in a nonconducting oil. ER lubricants are often considered smart lubricants. This paper aims to examine the steady state and dynamic response of multilobe journal bearings using an ER lubricant.

Reynold’s equation has been used to describe the lubricant flow in the journal-bearing clearance space. The Bingham model is used to characterize the nonlinear behavior of the lubricant. The solution of the Reynolds equation is obtained using the Newton–Raphson method, with gaseous cavitation in the fluid film numerically addressed by applying a mass-conserving algorithm. The effects of lobe geometry and the applied electric field are investigated on film pressure profile, fluid film thickness, direct stiffness and damping parameters. The equation of motion for journal center coordinates is solved using the fourth-order Runge–Kutta method, to predict journal center motion trajectories.

Using ER lubricant combined with two-lobe journal bearing significantly improved the minimum film thickness by 49.75%, the direct stiffness parameter by 132.18% and the damping parameter by 206.3%. However, the multilobe configuration was found to negatively impact the frictional powerloss of the bearing system. In the case of multilobe configurations of journal bearings using ER lubricant, linear motion journal trajectories are observed to be reduced and exhibit increased stability.

This study presents the effect of an ER lubricant and multilobe configuration on the rotor-dynamic performance and stability analysis of hydrodynamic journal bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0201/

The porous bearings are commonly used in slider thrust bearings owing to their self-lubricating properties and cost effectiveness as compared to conventional hydrodynamic bearings. The purpose of this paper is to numerically investigate usefulness of porous layer in hydrostatic thrust bearing operating with magnetic fluid. The effect of magnetic field and permeability has been analysed on steady-state (film pressure, film reaction and lubricant flow rate) and rotor-dynamic (stiffness and damping) parameters of bearing.

Finite element approach is used to obtain numerical solution of flow governing equations (Magneto-hydrodynamics Reynolds equation, Darcy law and capillary equation) for computing abovementioned performance indices. Finite element method formulation converts elliptical Reynolds equation into set of algebraic equation that are solved using Gauss–Seidel method.

It has been reported that porosity has limited but adverse effects on performance parameters of bearing. The adverse effects of porosity can be minimized by using a circular pocket for achieving better steady-state response and an annular/elliptical pocket, for having better rotor-dynamic response. The use of magnetic fluid is found to be substantially enhancing the fluid film reaction (53%) and damping parameters (55%).

The present work recommends use of circular pocket for achieving better steady-state performance indices. However, annular and elliptical pockets should be preferred, when design criteria for the bearing are better rotor-dynamic performance.

This study deals with influence of magnetic fluid, porosity and pocket shape on rotor-dynamic performance of externally pressurized thrust bearing.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0289/

Micro-surface texturing is emerging as a possible way to enhance the tribological performance of hydrodynamic fluid film bearings. In view of this, numerical simulations are carried out to examine the influence of surface texture on performance of hybrid thrust bearing system. This paper aims to determine optimum attributes of micro-grooves for thrust bearing operating in hybrid mode.

An iterative source code based on finite element formulation of Reynolds equation has been developed to numerically simulate flow of lubricant through the bearing. Mass-conserving algorithm based on Jakobsson–Floberg–Olsson (JFO) condition has been used to numerically capture cavitation phenomenon in the bearing. Gauss Siedel method has been used to obtain steady state performance parameters of the bearings.

A parametric study has been performed to improve the load supporting capacity of the bearing by optimizing micro-groove attributes and configuration. It is noticed that use of full-section micro-groove is beneficial in improving the efficiency of bearing by enhancing the fluid film reaction and reducing the film frictional power losses.

This study is helpful in examining the usefulness of micro-groove textured surfaces in hybrid thrust bearing applications.

This study aims to explore peer performance as the motivation behind gross profit manipulation through two different channels, namely, cost of goods sold (COGS) misclassification and revenue misclassification.

Gross profit expectation model (Poonawala and Nagar, 2019) and operating revenue expectation model (Malikov et al., 2018) are used to measure COGS and revenue misclassification, respectively. The panel data regression models are used to analyze the data for this study.

The study results show that firms engage in gross profit manipulation to meet the industry’s average gross margin, implying that peer performance is an important benchmark that firms strive to achieve through misclassification strategies. Further results exhibit that firms prefer COGS misclassification over revenue misclassification for manipulating gross profit, implying that firms choose the shifting strategy based on the relative advantage of each shifting tool.

The findings suggest that firms that just meet or slightly beat industry-average profitability levels are highly likely to engage in classification shifting (CS). Thus, investors and analysts should be careful when evaluating such firms by comparing them with other firms in the same industry.

First, this study is among earlier attempts to investigate CS motivated by peer performance. Second, this study investigates both tools of gross profit manipulation by taking a uniform sample of firms over the same period and provides compelling evidence that firms prefer one shifting tool over another depending on the relative advantage of each shifting tool.

This study aims to investigate the impact of mandatory corporate social responsibility (CSR) spending legislation on the earnings management strategies of firms.

The authors use panel data regression models to analyze the data for this study. This study covers the post-legislation period, which spans over five years from the financial year ending March 2015 to the financial year ending March 2019.

The results show that firms manipulate accounting measures to avoid breaching the cut-off criteria for mandatory CSR. In particular, the results show that firms operating around the operating revenue threshold misclassify operating revenue as non-operating revenue. In contrast, firms operating around the net worth and net profit thresholds do downward real and accrual earnings management. These results are consistent with several robustness measures.

To the best of the authors’ knowledge, this is the first study that examines the impact of mandatory CSR spending on earnings management.

The main purpose of this study is to explore and validate the question “whether altmetric mentions can predict citations to scholarly articles”. The paper attempts to explore the nature and degree of correlation between altmetrics (from ResearchGate and three social media platforms) and citations.

A large size data sample of scholarly articles published from India for the year 2016 is obtained from the Web of Science database and the corresponding altmetric data are obtained from ResearchGate and three social media platforms (Twitter, Facebook and blog through Altmetric.com aggregator). Correlations are computed between early altmetric mentions and later citation counts, for data grouped in different disciplinary groups.

Results show that the correlation between altmetric mentions and citation counts are positive, but weak. Correlations are relatively higher in the case of data from ResearchGate as compared to the data from the three social media platforms. Further, significant disciplinary differences are observed in the degree of correlations between altmetrics and citations.

The results support the idea that altmetrics do not necessarily reflect the same kind of impact as citations. However, articles that get higher altmetric attention early may actually have a slight citation advantage. Further, altmetrics from academic social networks like ResearchGate are more correlated with citations, as compared to social media platforms.

The paper has novelty in two respects. First, it takes altmetric data for a window of about 1–1.5 years after the article publication and citation counts for a longer citation window of about 3–4 years after the publication of article. Second, it is one of the first studies to analyze data from the ResearchGate platform, a popular academic social network, to understand the type and degree of correlations.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2019-0364

A computational fluid dynamics based parametric analysis for shell and helical tube heat exchanger (SHTHE) using CuO/water and Al₂O₃/water nanofluids is the main purpose of the present work. The parameters having impact on the performance of a heat exchanger have been studied in depth. As the solid nanoparticle shows higher thermal conductivity compared to liquid particles, inclusion of this nanoparticle into the base fluid significantly enhances the thermal conductivity of the liquid. Incorporation of nanofluid in the heat exchanger can increase its performance.

The simulation is performed in Solid-Works flow simulation, and the performance of SHTHE is observed by varying the pitch of helical tube from 0.013 to 0.018 m and coil diameter from 0.0813 to 0.116 m, keeping the other parameters constant. The tube side and shell side flow rate is kept as 2 LPM.

The results indicate that the effectiveness of the heat exchanger increases with the increase of pitch and coil diameter. The maximum effectiveness of 0.5022 for CuO/water and 0.4928 for Al₂O₃/water nanofluid is observed at a pitch of 0.018 m and the coil diameter of 0.116 m.

It is observed that CuO/water nanofluid shows better performance compared with Al₂O₃/water nanofluid. For a coil diameter of 0.116 m and pitch of 0.018 m, the SHTHE with CuO/water nanofluid shows 1.82% greater effectiveness compared to the effectiveness with Al₂O₃/water nanofluid.

This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures.

The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging.

The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution.

The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures.

The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only.

The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly.

Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings.