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This study proposes a framework that demonstrates how the perceived value of augmented reality (AR) shopping influences the formation of psychological ownership of product and technology. The mediating role of flow experience and the moderating role of perceived control are identified.

An online survey study recruiting 480 participants who experienced AR shopping was conducted to test the hypotheses.

Functional value is negatively related to psychological ownership of product and technology whereas emotional value shows opposite effects. Flow experience mediates the relationships between functional/emotional value and psychological ownership of product and technology. Perceived control moderates the relationship between emotional value and flow experience, as well as the relationship between functional/emotional value and psychological ownership of product and technology.

The findings suggest the importance of AR’s functional and emotional values in developing psychological ownership of product and technology. To mitigate the negative effect of functional value, AR designers should focus on creating emotionally engaging apps that induce a flow experience, thereby enhancing psychological ownership. Furthermore, AR apps should be designed to empower users with a sense of control in the AR experience.

This research contributes to the AR and psychological ownership literature. It introduces a model that can explain both the formation of psychological ownership of product and psychological ownership of technology, thereby expanding the current understanding. By adding perceived values as antecedents of psychological ownership, it enriches the psychological ownership literature. Moreover, it enhances the flow experience literature by demonstrating the role of flow experience in the formation of psychological ownership of product and technology.

This study aims to explore entropy evaluation in the bi-directional flow of Casson hybrid nanofluids within a stagnated domain, a topic of significant importance for optimizing thermal systems. The aim is to investigate the behavior of unsteady, magnetized and laminar flow using a parametric model based on the thermo-physical properties of alumina and copper nanoparticles.

The research uses boundary layer approximations and the Keller-box method to solve the derived ordinary differential equations, ensuring numerical accuracy through convergence and stability analysis. A comparison benchmark has been used to authenticate the accuracy of the numerical outcomes.

Results indicate that increasing the Casson fluid parameter (ranging from 0.1 to 1.0) reduces velocity, the Bejan number decreases with higher bidirectional flow parameter (ranging from 0.1 to 0.9) and the Nusselt number increases with higher nanoparticle concentrations (ranging from 1% to 4%).

This study has limitations, including the assumption of laminar flow and the neglect of possible turbulent effects, which could be significant in practical applications.

The findings offer insights for optimizing thermal management systems, particularly in industries where precise control of heat transfer is crucial. The Keller-box simulation method proves to be effective in accurately predicting the behavior of such complex systems, and the entropy evaluation aids in assessing thermodynamic irreversibilities, which can enhance the efficiency of engineering designs.

These findings provide valuable insights into the thermal management of hybrid nanofluid systems, marking a novel contribution to the field.

This study aims to focuse on the flow behavior of a specific nanofluid composed of blood-based iron oxide nanoparticles, combined with motile gyrotactic microorganisms, in a ciliated channel with electroosmosis.

This study applies a powerful mathematical model to examine the combined impacts of bio convection and electrokinetic forces on nanofluid flow. The presence of cilia, which are described as wave-like motions on the channel walls, promotes fluid propulsion, which improves mixing and mass transport. The velocity and dispersion of nanoparticles and microbes are modified by the inclusion of electroosmosis, which is stimulated by an applied electric field. This adds a significant level of complexity.

To ascertain their impact on flow characteristics, important factors such as bio convection Rayleigh number, Grashoff number, Peclet number and Lewis number are varied. The results demonstrate that while the gyrotactic activity of microorganisms contributes to the stability and homogeneity of the nanofluid distribution, electroosmotic forces significantly enhance fluid mixing and nanoparticle dispersion. This thorough study clarifies how to take advantage of electroosmosis and bio convection in ciliated micro channels to optimize nanofluid-based biomedical applications, such as targeted drug administration and improved diagnostic processes.

First paper discussed “Numerical Computation of Cilia Transport of Prandtl Nanofluid (Blood-Fe₃O₄) Enhancing Convective Heat Transfer along Micro Organisms under Electroosmotic effects in Wavy Capillaries”.

The purpose of this study was to leverage agency theory to examine the impact of board attributes on cash flow management in Ghana’s financial institutions.

Data for the study was collected from the annual published financial statements of selected financial institutions, which were obtained from their respective websites. The sampling technique used was purposive, resulting in the selection of 15 financial institutions in Ghana, of which 10 were listed on the Ghana Stock Exchange and 5 were non-listed. The study covered a period of 10 years, ranging from 2011 to 2020. The two-step generalized method of moments estimation was used to determine the relationship between the board attributes and cash flow management.

The study found that board size had a positive and significant influence on net cash flow from operating, investing and financing activities. The study also discovered that the proportion of nonexecutive directors had a positive and significant influence on net cash flow from operating, investing and financing activities. In addition, it was revealed that the proportion of female directors on the board exhibited a positive and significant influence on net cash flow from operating activities but a negative and significant influence on net cash flow from investing and financing activities.

The study recommends increasing female representation on corporate boards to 25%, as women bring valuable skills, knowledge and experience that positively impact the financial institutions’ cash flows.

This study focused on the impact of board attributes on cash flow management within Ghana. It explored how corporate governance affects strategic decisions related to cash flow management, contributing original insights to this field of research.

The purpose of this study is to optimize and improve conventional welding using EMF assisted technology. Current industrial production has put forward higher requirements for welding technology, so the optimization and improvement of traditional welding methods become urgent needs.

External magnetic field assisted welding is an emerging technology in recent years, acting in a non-contact manner on the welding. The action of electromagnetic forces on the arc plasma leads to significant changes in the arc behavior, which affects the droplet transfer and molten pool formation and ultimately improve the weld seam formation and joint quality.

In this paper, different types of external magnetic fields are analyzed and summarized, which mainly include external transverse magnetic field, external longitudinal magnetic field and external cusp magnetic field. The research progress of welding behavior under the effect of external magnetic field is described, including the effect of external magnetic field on arc morphology, droplet transfer and weld seam formation law.

However, due to the extremely complex physical processes under the action of the external magnetic field, the mechanism of physical fields such as heat, force and electromagnetism in the welding has not been thoroughly analyzed, in-depth theoretical and numerical studies become urgent.

This study aims to introduce a novel machine learning feature vector (MLFV) method to bring machine learning to overcome the time-consuming computational fluid dynamics (CFD) simulations for rapidly predicting turbulent flow characteristics with acceptable accuracy.

In this method, CFD snapshots are encoded in a tensor as the input training data. Then, the MLFV learns the relationship between data with a rod filter, which is named feature vector, to learn features by defining functions on it. To demonstrate the accuracy of the MLFV, this method is used to predict the velocity, temperature and turbulent kinetic energy fields of turbulent flow passing over an innovative nature-inspired Dolphin turbulator based on only ten CFD data.

The results indicate that MLFV and CFD contours alongside scatter plots have a good agreement between predicted and solved data with R² ≃ 1. Also, the error percentage contours and histograms reveal the high precisions of predictions with MAPE = 7.90E-02, 1.45E-02, 7.32E-02 and NRMSE = 1.30E-04, 1.61E-03, 4.54E-05 for prediction velocity, temperature, turbulent kinetic energy fields at Re = 20,000, respectively.

The method can have state-of-the-art applications in a wide range of CFD simulations with the ability to train based on small data, which is practical and logical regarding the number of required tests.

The paper introduces a novel, innovative and super-fast method named MLFV to address the time-consuming challenges associated with the traditional CFD approach to predict the physics of turbulent heat and fluid flow in real time with the superiority of training based on small data with acceptable accuracy.

This paper aims to investigate the effect of different wing height layouts on the aerodynamic performance and flow structure of high-speed train, in a train-wing coupling method with multiple tandem wings installed on the train roof.

The improved delayed detached eddy simulation method based on shear stress transport k- ω turbulence model has been used to conduct computational fluid dynamics simulation on the train with three different wing height layouts, at a Reynolds number of 2.8 × 10⁶. The accuracy of the numerical method has been validated by wind tunnel experiments.

The wing height layout has a significant effect on the lift, while its influence on the drag is weak. There are three distinctive vortex structures in the flow field: wingtip vortex, train body vortex and pillar vortex, which are influenced by the variation in wing height layout. The incremental wing layout reduces the mixing and merging between vortexes in the flow field, weakening the vorticity and turbulence intensity. This enhances the pressure difference between the upper and lower surfaces of both the train and wings, thereby increasing the overall lift. Simultaneously, it reduces the slipstream velocity at platform and trackside heights.

This paper contributes to understanding the aerodynamic characteristics and flow structure of a high-speed train coupled with wings. It provides a reference for the design aiming to achieve equivalent weight reduction through aerodynamic lift synergy in trains.

This study aims to validate the linear flow theory with computational fluid dynamics (CFD) simulations and to propose a novel shape for the airfoil that will improve supersonic aerodynamic performance compared to the National Advisory Committee for Aeronautics (NACA) 64a210 airfoil.

To design the new airfoil shape, this study uses a convex optimization approach to obtain a global optimal shape for an airfoil. First, modeling is conducted using linear flow theory, and then numerical verification is done by CFD simulations using ANSYS Fluent. The optimization process ensures that the new airfoil maintains the same cross-sectional area and thickness as the NACA 64a210 airfoil. This study found that an efficient way to obtain the ideal airfoil shape is by using linear flow theory, and the numerical simulations supported the assumptions inherent in the linear flow theory.

This study’s findings show notable improvements (from 4% to 200%) in the aerodynamic performance of the airfoil, especially in the supersonic range, which points to the suggested airfoil as a potential option for several fighter aircraft. Under various supersonic conditions, the optimized airfoil exhibits improved lift-over-drag ratios, leading to improved flight performance and lower fuel consumption.

This study was conducted mainly for supersonic flow, whereas the subsonic flow is tested for a Mach number of 0.7. This study would be extended for both subsonic and supersonic flights.

Convex optimization and linear flow theory are combined in this work to create an airfoil that performs better in supersonic conditions than the NACA 64a210. By closely matching the CFD results, the linear flow theory's robustness is confirmed. This means that the initial design phase no longer requires extensive CFD simulations, and the linear flow theory can be used quickly and efficiently to obtain optimal airfoil shapes.

The proposed airfoil can be used in different fighter aircraft to enhance performance and reduce fuel consumption. Thus, lower carbon emission is expected.

The unique aspect of this work is how convex optimization and linear flow theory were combined to create an airfoil that performs better in supersonic conditions than the NACA 64a210. Comprehensive CFD simulations were used for validation, highlighting the optimization approach's strength and usefulness in aerospace engineering.

The performance of a bladeless Tesla turbine is closely tied to momentum diffusion, kinetic energy transfer and wall shear stress generation on its rotating disks. The surface roughness adds complexity of flow analysis in such a domain. This paper aims to assess the effect of roughness on flow structures and the application of roughness models in flow cross sections with submillimeter height, including both stationary and rotating walls.

This research starts with the examination of flow over a rough flat plate, and then proceeds to study flow within minichannels, evaluating the effect of roughness on flow characteristics. An in-house test stand validates the numerical solutions of minichannel. Finally, flow through the minichannel with corotating walls was analyzed. The k-ω SST turbulent model and Aupoix's roughness method are used for numerical simulations.

The findings emphasize the necessity of considering the constricted dimensions of the flow cross section, thereby improving the alignment of derived results with theoretical estimations. Moreover, this study explores the effects of roughness on flow characteristics within the minichannel with stationary and rotating walls, offering valuable insights into this intricate phenomenon, and depicts the appropriate performance of chosen roughness model in studied cases.

The originality of this investigation is the assessment and validation of flow characteristics inside minichannel with stationary and corotating walls when the roughness is implemented. This phenomenon, along with the effect of roughness on the transportation of kinetic energy to the rough surface of a minichannel in an in-house test setup, is assessed.

The purpose of this study is to compare the thermal performance of two flow configurations in corrugated plate heat exchanger (CPHE): vertical flow configuration (CPHE_vert.) and diagonal flow configuration (CPHE_diag.). The study aims to determine the differences between these configurations and evaluate their respective thermal performance based on metrics such as heat transfer rates, pressure drop values and flow distribution.

The study compares the thermal performance of two flow arrangements of CPHE using identical geometrical dimensions and test conditions. Computational fluid dynamics (CFD) is employed, and a validated numerical model is used for the investigation. The comparison is based on analyzing the rate of heat transfer and pressure drop data between the two flow arrangements.

The findings indicate that the diagonal flow configuration in CPHEs offers improved flow distribution, enhanced heat transfer performance and lower pressure drop compared to the vertical flow configuration. However, the differences in general in the thermal performance of CPHE_vert. and CPHE_diag. are found to be minimal.

To the best of the author’s knowledge, this study represents the first attempt to investigate the impact of vertical and diagonal flow configurations on the thermal performance of the CPHE.