Search results

Inclination angle has been reported to have an enhancing effect on the thermal-hydraulic characteristics and entropy of some thermal systems. Therefore, this paper aims to numerically investigate the effects of inclination angle, volume concentration and Reynolds number on the thermal and hydraulic characteristics and entropy generation rates of water-based Al₂O₃ nanofluids through a smooth circular aluminum pipe in a turbulent flow.

A constant heat flux of 2,000 Watts is applied to the circular surface of the tube. Reynolds number is varied between 4,000 and 20,000 for different volume concentrations of alumina nanoparticles of 0.5%, 1.0% and 2.0% for tube inclination angles of ±90o, ±60o, ±45o, ±30o and 0o, respectively. The simulation is performed in an ANSYS Fluent environment using the realizable kinetic energy–epsilon turbulent model.

Results show that +45o tube orientation possesses the largest thermal deviations of 0.006% for 0.5% and 1.0% vol. concentrations for Reynolds numbers 4,000 and 12,000. −45o gives a maximum pressure deviation of −0.06% for the same condition. The heat transfer coefficient and pressure drop give maximum deviations of −0.35% and −0.39%, respectively, for 2.0% vol. concentration for Reynolds number of 20,000 and angle ±90o. A 95%–99.8% and 95%–98% increase in the heat transfer and total entropy generation rates, respectively, is observed for 2.0% volume concentration as tube orientation changes from the horizontal position upward or downward.

Research investigating the effect of inclination angle on thermal-hydraulic performance and entropy generation rates in-tube turbulent flow of nanofluid is very scarce in the literature.

The purpose of this research is to study the dynamic behavior of hydrostatic squeeze film dampers made of four hydrostatic pads, fed through four capillary restrictors with micropolar lubricant.

The modified version of Reynolds equation is solved numerically by the finite differences and the Gauss–Seidel methods to determine the pressure field generated on the hydrostatic bearing flat pads. In the first step, the effects of the pad dimension ratios on the stiffness and damping coefficients are investigated. In the second step, the damping factor is evaluated with respect to the micropolar properties.

The analysis revealed that the hydrostatic squeeze film dampers lubricated with micropolar lubricants produces the maximum damping factor for characteristic length of micropolar lubricant less than 5, while the same bearing operating with Newtonian lubricants reaches its maximum damping factor at eccentricity ratios larger than 0.4.

The results obtained show that the effects of micropolar lubricants on the dynamic performances are predominantly affected by the pad geometry and eccentricity ratio.

Due to high speeds, heavy loads, large slide-to-roll ratios (SRR) and other variable operating conditions, some rolling bearings that have been working in harsh conditions may experience flash temperatures in the contact area, which may result in early damage like smearing and then affect service life. This study aims to investigate the flash temperature phenomenon of rolling bearings through theoretical and experimental analysis.

A technology for measuring temperature distribution in rolling ball on disk contact under lubrication was developed. The test-rig can simulate the ball bearing contact. The effects of working conditions such as entrainment speed, load, SRR and lubricating oil viscosity on the flash temperature were investigated.

The results of the theoretical calculation and experiments indicate that the parameters promoting the reduction of film thickness in elastohydrodynamic lubrication are always related with the number of flash points, even film thickness reduced to mixed lubrication. The flash temperature is easier to happen in conditions of high SRR, heavy load, slow entrainment speed and low viscosity oil.

This work conducts an experimental study on the flash temperature phenomenon, providing a test technology for bearing lubrication and failure investigation.

This author has opted into Transparent Peer Review available at: https://publons.com/publon/10.1108/ILT-04-2023-0104

Incumbent retail organisations need to develop new capabilities to adapt with the increasingly competitive retail landscape. Despite the growing relevance of innovation in retail practice, the strategic management of innovation in retailing is still vastly under-researched. This explorative study thus aims to investigate how incumbent retail firms can organise for innovation from an organisational ambidexterity perspective.

A single-case study of an established Swedish retail firm was conducted from December 2016 to July 2018 and followed up in June 2021. The authors followed the process of implementation of organisational changes aimed to increase innovation in the company, particularly the introduction of a digital marketing initiative and a corporate innovation hub. Data collection was based on nine semi-structured interviews and participant observations and unstructured interviews from 13 meetings and workshops. An abductive approach to data analysis was followed, iteratively comparing theoretical concepts and empirical data using open, axial and selective coding to distil findings into aggregated themes.

Given the inherently limited formalisation of innovation processes in most retail organisations, structural ambidexterity appears to be necessary when the aim is radical, strategic retail innovation. Structural mechanisms are able to safeguard the space and resources to focus on long-term research and projects with higher risk and uncertainty; however, integration of innovation activities to the mainstream organisation is critical. Pursuing contextual ambidexterity, wherein instead of structural solutions, employees are empowered to divide employees' time between innovation-related and efficiency-related tasks, is more likely related to retail innovations that are incremental and operational.

The paper contributes to the emerging topic of strategic management of innovation in retailing, by explicating how incumbent retailers can organise for innovation depending on the type of innovation that is aimed for, using organisational ambidexterity as a novel perspective.

The purpose of this study is to identify the possible relation between the vibration and the stall by using the vibration response of the airfoil. For this purpose, the root mean square values of the acceleration signals are evaluated to demonstrate the compatibility between the stall angles and the vibration levels.

An experimental study is conducted on NACA 4415 airfoil at Reynolds numbers 69e3, 77e3 and 85e3. Experiments are performed from 0° to 25° of the angles of attack (AoA) for each Reynolds number condition. To observe the change of the vibration values at the stall region clearly, experiments are performed with the AoA ranging from 10° to 25° in 1° increments. Three acceleration sensors are used to obtain the vibration data.

The results show that the increase in the amplitude of the vibration is directly related to the decrease in lift. These findings indicate that this approach could be beneficial in detecting stall on airfoil-type structures.

This study proposes a new approach for detecting stall over the airfoil using the vibration data.

Research has documented how white teachers often fall short of their anti-racist intentions. However, much of this research is done with preservice teachers or teachers across disciplines. The authors investigate stories in which white English teachers who teach substantial proportions of black students and who self-reported anti-racist goals nevertheless fell short of those goals. The purpose of the study is to understand the tensions between racial liberalism and racial literacy in their pedagogy.

The authors snowball sampled 12 veteran white high school English teachers (3–27 years’ experience) who taught in schools with substantial proportions of black students. The authors used a two-stage interview process to narrow the sample to 7 teachers who confirmed their anti-racist intentions and who wrote narratives of moments when they tried to be anti-racist, but the lesson failed in some way. The authors used a three-stage narrative analysis to analyze how racial liberalism and racial literacy were reflected in the narratives.

The veteran English teachers, despite their anti-racist intentions, told narratives that reflected racial liberalism, portraying racism as an individual and interpersonal phenomenon. Some narratives showed teachers who had taken steps toward racial literacy, but no narratives showed a fully developed sense of racial literacy, portraying the layers of institutional and structural racism in English education.

The sample suggests that veteran white English teachers are subject to similar limited racial literacies as novice teachers. While the authors found glimmers of racial literacy, they still note the work necessary to equip veteran English teachers with the racial literacies necessary for anti-racist instruction. The authors propose directions for teacher education, systemic support and professional development.

This study aims to understand how the texture shape, number of textures and addition of nanoparticle additives in lubricants impact the dynamic characteristics of journal bearing by comparing six different texture shapes like triangle, chevron, arc, circle, rectangle and elliptical applied in pressure-increasing region under various geometrical and operating conditions.

The finite element method approach has been employed to solve governing Reynold’s equation, assuming iso-viscous Newtonian fluid, for computation of performance parameters like stiffness and damping coefficient, threshold speed, etc. By using a regression model, the impact of adding nanoparticles Al₂O₃ and CuO to the base lubricant on viscosity variation is calculated for selected temperature ranges and weight fractions of nanoparticles.

The arc-shaped texture with an area density of 28.27%, eccentricity ratio of 0.2 and texture depth of 0.6 exhibited 35.22% higher direct stiffness and 41.4% higher damping coefficient compared to the lowest value in the circle-shaped texture. Increasing the number of arc-shaped textures on the bearing surface with low area density led to declining stiffness and damping parameters. However, with nanoparticle additives, the arc-shaped texture further showed 10.75% and 8.11% improvement in stiffness and 9.99% and 4.87% enhancement in damping coefficient for Al₂O₃ and CuO, respectively, at 90 °C temperature and 0.5% weight fraction.

By understanding the influence of texture shapes on the dynamic characteristics, engineers can design bearings that exhibit improved stability and enhance overall performance.

This paper aims to determine, which values guide consumers decision-making on natural health products for concentration and cognition (NHPCC) and how they link to choice-relevant product attributes. The purpose is to contribute to a better understanding of NHPCC consumption choices, which can encourage more consumer-centric product development and positioning.

Based on the means-end chain approach, in-depth laddering interviews with 26 consumers of NHP were conducted in Germany from October to December 2020. Qualitative content analysis was applied and a hierarchical value map over the dominant association was built and analyzed.

Five terminal values were found to be relevant for NHPCC decision-making. The personal focused values security, self-direction and stimulation are via health mainly associated with trust and a conscious decision-making, which is linked to the product attributes of effectiveness, tolerance and declaration. Social focused values of universalism or benevolence guide attention on the attributes of sustainability and regionality.

The study contributes to close the knowledge gap concerning the linkages between abstract values and concrete product attributes of NHP through associated consequences. To the best of the authors’ knowledge, this is the first study that analyzed these links for NHPCC, although such products are gaining more interest among companies and consumers. Companies can benefit from the outcomes by developing more consumer-centric product concepts and marketing communication strategies for NHPCC. Due to higher attention on relevant information, consumers’ decision-making could become safer and more conscious.

Fused Filament Fabrication (FFF) is an extrusion-based manufacturing process using fused thermoplastics. Despite its low cost, the FFF is not extensively used in high-value industrial sectors mainly due to parts' anisotropy (related to the deposition strategy) and residual stresses (caused by successive heating cycles). Thus, this study aims to investigate the process improvement and the optimization of the printed parts.

In this work, a meshless technique – the Radial Point Interpolation Method (RPIM) – is used to numerically simulate the viscoplastic extrusion process – the initial phase of the FFF. Unlike the FEM, in meshless methods, there is no pre-established relationship between the nodes so the nodal mesh will not face mesh distortions and the discretization can easily be modified by adding or removing nodes from the initial nodal mesh. The accuracy of the obtained results highlights the importance of using meshless techniques in this field.

Meshless methods show particular relevance in this topic since the nodes can be distributed to match the layer-by-layer growing condition of the printing process.

Using the flow formulation combined with the heat transfer formulation presented here for the first time within an in-house RPIM code, an algorithm is proposed, implemented and validated for benchmark examples.

Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.

A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.

Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.

In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.