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Maintaining the turbine blade’s temperature within the safety limit is challenging in high-pressure turbines. This paper aims to numerically present the conjugate heat transfer analysis of a novel approach to mini-channel embedded film-cooled flat plate.

Numerical simulations were performed at a steady state using SST k – ω turbulence model. Impingement and film cooling are classical approaches generally adopted for turbine blade analysis. The existing film cooling techniques were compared with the proposed design, where a mini-channel was constructed inside the solid plate. The impact of the blowing ratio (M), Biot number (Bi) and temperature ratio (TR) on overall cooling performance was also studied.

Overall cooling effectiveness was always shown to be higher for mini-channel embedded film-cooled plates. The effectiveness increases with increasing the blowing ratio from M = 0.3 to 0.7, then decreases with increasing blowing ratio (M = 1 and 1.4) due to lift-off conditions. The mini-channel embedded plate resulted in an approximately 21% increase in area-weighted average overall effectiveness at a blowing ratio of 0.7 and Bi = 1.605. The lower uniform temperature was also found for all blowing ratios at a low Biot number, where conduction heat transfer significantly impacts total cooling effectiveness.

To the best of the authors’ knowledge, this study presents a novel approach to improve the cooling performances of a film-cooled flat plate with better cooling uniformity by using embedded mini-channels. Despite the widespread application of microchannels and mini-channels in thermal and fluid flow analysis, the application of mini-channels for blade cooling is not explored in detail.

The purpose of this study is to explore the mist-air film cooling performance on a three-dimensional (3-D) flat plate. In mist-air film cooling technique, a small amount of water droplets is injected along with the coolant air. The objective is to study the influence of shape of the coolant hole and operating conditions on the cooling effectiveness.

In this study, 3-D numerical simulations are performed. To simulate the mist-air film cooling over a flat plate, air is considered as a continuous phase and mist is considered as a discrete phase. Turbulence in the flow is accounted using Reynolds averaged Navier–Stokes equation and is modeled using k–e model with enhanced wall treatment.

The results of this study show that, for cylindrical coolant hole, coolant with 5% mist concentration is not effective for mainstream temperatures above 600 K, whereas for fan-shaped hole, even 2% mist concentration has shown significant impact on cooling effectiveness for temperatures up to 1,000 K. For given mist-air coolant flow conditions, different trend in effectiveness is observed for cylindrical and fan-shaped coolant hole with respect to main stream temperature.

This study is limited to a flat plate geometry with single coolant hole.

The motivation of this study comes from the requirement of high efficiency cooling techniques for cooling of gas turbine blades. This study aims to study the performance of mist-air film cooling at different geometric and operating conditions.

The originality of this study lies in studying the effect of parameters such as mist concentration, droplet size and blowing ratio on cooling performance, particularly at high mainstream temperatures. In addition, a systematic performance comparison is presented between the cylindrical and fan-shaped cooling hole geometries.

This paper aims to understand the effect of extrusion conditions on the degree of foaming of polylactic acid (PLA) during three-dimensional (3D) printing. It was also targeted to optimize the slicing parameters for 3D printing and to study how the properties of printed parts are influenced by the extrusion conditions.

This study used a commercially available PLA filament that undergoes chemical foaming. An extrusion 3D printer was used to produce individual extrudates and print samples that were characterized using an optical microscope, scanning electron microscope and custom in-house apparatuses.

The degree of foaming of the extrudates was found to strongly depend on the extrusion temperature and the material feed speed. Higher temperatures significantly increased the number of nucleation sites for the blowing agent as well as the growth rate of micropores. Also, as the material feed speed increased, the micropores were allowed to grow bigger which resulted in higher degrees of foaming. It was also found that, as the degree of foaming increased, the porous parts printed with optimized slicing parameters were lightweight and thermally less conductive.

This study fills the gap in literature where it examines the foaming behavior of individual extrudates as they are extruded. By doing so, this work distinguishes the effect of extrusion conditions from the effect of slicing parameters on the foaming behavior which enhances the understanding of extrusion of chemically foamed PLA.

The purpose of this study is to reduce the cracks, pores and unfused defects in arc welding, improve the crystalline structure of the weld, refine its grains and improve the mechanical properties.

Taking E690 marine steel as the research object, the experiment adopts a new process method of laser forging coupled arc welding. Welding for comparative experiments. Experiments show that the “V”-shaped groove arc welding process has a larger fusion area, but has pores, the arc current is 168 A, the arc voltage is 28 V and the welding speed is 600 mm/min.

It can be seen from tensile tests that the coupling welding process has the highest tensile strength and yield strength, 872 MPa and 692 MPa, respectively, and the fracture elongation is 29.29%. The single-beam laser forging coupled arc welding process has a distance of laser and wire of 6–8 mm, a laser wavelength of 1,064 nm and the highest weld fusion ratio. The microhardness test shows that the average hardness of single-beam laser forging in the weld zone is 487.54 HV, which is 10.30% higher than that of arc welding. The average hardness in the fusion zone is 788.08 HV, which is 14.52% higher than that of the arc welding process.

The originality of the experiment: proposed a new process method of coupling arc repair for offshore steel forging; adopted a new process method of simultaneous coupling of single-beam short-pulse laser, double-beam short-pulse laser and arc welding; and obtained effect of pulsed laser and arc composite repair on porosity and fusion of E690 marine steel welds.

Nonlinear mixed-convective entropy optimized the flow of hyperbolic-tangent nanofluid (HTN) with magnetohydrodynamics (MHD) process is considered over a vertical slendering surface. The impression of activation energy is incorporated in the modeling with the significance of nonlinear radiation, dissipative-function, heat generation/consumption connection and Joule heating. Research in this area has practical applications in the design of efficient heat exchangers, thermal management systems or nanomaterial-based devices.

Suitable set of variables is introduced to transform the PDEs (Partial differential equations) system into required ODEs (Ordinary differential equations) system. The transformed ODEs system is then solved numerically via finite difference method. Graphical artworks are made to predict the control of applicable transport parameters on surface entropy, Bejan number, Sherwood number, skin-friction, Nusselt number, temperature, velocity and concentration fields.

It is noticed from present numerical examination that Bejan number aggravates for improved estimations of concentration-difference parameter a_2, Eckert number E_c, thermal ratio parameter ?_w and radiation parameter R_d, whereas surface entropy condenses for flow performance index n, temperature-difference parameter a_1, thermodiffusion parameter N_t and mixed convection parameter ?. Sherwood number is enriched with the amplification of pedesis-motion parameter N_b, while opposite development is perceived for thermodiffusion parameter. Lastly, outcomes are matched with formerly published data to authenticate the present numerical investigation.

To the best of the authors' knowledge, no investigation has been reported yet that explains the entropic behavior with activation energy in the flowing of hyperbolic-tangent mixed-convective nanomaterial due to a vertical slendering surface.

The purpose of this study is to provide that porous media and viscous dissipation are crucial considerations when working with hybrid nanofluids in various applications.Recent years have witnessed significant progress in optimizing these fluids for enhanced heat transfer within porous (Darcy–Forchheimer) structures, offering promising solutions for various industries seeking improved thermalmanagement and energy efficiency.

The first step is to transform the original partial differential equations into a system of first-order ordinary differential equations (ODEs). The fourth-order Runge–Kutta method is chosen for its accuracy in solving ODEs. The present study investigates the free convective boundary layer flow of hybrid nanofluids over a moving thin inclined needle with the slip flow brought about by inclined Lorentz force and Darcy–Forchheimer porous matrix, viscous dissipation.

It is found that slip conditions (velocity and Thermal) exist for a range of the natural convection boundary layer flow. In the hybrid nanofluid flow, which consists of Al₂O₃ and Fe₃O₄ are nanoparticles, H₂O − C₂H₆O₂ (50:50) are considered as the base fluid. The consequence of the governing parameter on the momentum and temperature profile distribution is graphically depicted. The range of the variables is 1 ≤ M ≤ 4, 1 ≤ d ≤ 2.5, 1 ≤ δ ≤ 4, 1 ≤ Fr ≤ 7, 1 ≤ Kr ≤ 7 and 0.5≤λ ≤ 3.5. The Nusselt number and skin friction factors are used to calculate the numerical values of various parameters, which are displayed in Table 4. These analyses elucidate that upsurges in the value of the Fr noticeably diminish the momentum and temperature. It is investigated to see if the contemporary results are in outstanding promise with the outcomes reported in earlier works.

The results can be very helpful to improve the energy efficiency of thermal systems.

The hybrid nanofluids in heat transfer have the potential to improve the energy efficiency and performance of a wide range of systems.

This study proposes that in the combined effects of hybrid nanofluid properties, the inclined Lorentz force, the Darcy–Forchheimer model for porous media and viscous dissipation on the boundary layer flow of a conducting fluid over a moving thin inclined needle. Assessing the potential practical applications of the hybrid nanofluids in inclined needles, this could involve areas such as biomedical engineering, drug delivery systems or microfluidic devices. In future should explore the benefits and limitations of using hybrid nanofluids in these applications.

Social psychology has focused on an individual’s reaction to emergencies and witnessing a crime, which has developed theories of bystander intervention and bystander apathy. The purpose of this study is to explore why people choose to intervene when they are a bystander to intimate partner violence (IPV) and the psychological processes that underpin this. Decision-making was explored drawing on literature from the whistleblowing field.

Through a mixed methods epistemology, this study explored factors that explained intervening behaviour concerning IPV. In total, 212 participants who had known someone who was a victim of IPV were recruited from the general population.

A logistic regression model indicated that conscientiousness and fairness were found to predict intervening behaviour. Being a child witness was found to predict non-intervening behaviour. Qualitative analysis revealed three types of bystander apathy: those who lacked capability as they were children; those who were indifferent and did not see it as their place to intervene; and those who wanted to intervene but did not as they were frightened of exacerbating the situation.

IPV has significant physical and psychological effects on victims. However, the choice to intervene is complex, and bystander intervention in this study was also associated in some cases with not only a continuation of the IPV behaviour towards the victim but also aggression and physical violence towards the bystander (whistleblower retaliation). Based on the findings of this study, recommendations are made for how to support bystanders and victims of IPV.

This study involved participants with real-life experience of being a bystander to IPV. The mixed methodology provided an insight into the psychological processes, which underpin bystander experiences of IPV and maps onto the literature in relation to whistleblowing.

Based on the stimulus-organism-response (SOR) model and Transactional Model of Stress and Coping, the current study aims to investigate the direct effects of workplace bullying (WPB) on internal whistleblowing (IW) and workplace withdrawal (WW), as well as the indirect effects, including the mediating role of moral injury (MI) and moderating role of inclusive leadership (IL) in the hospitality sector.

Three-waves approach was used to collect data from 266 hotel employees in India. AMOS 21 and Macro-PROCESS were used to analyse the hypothesised relationships.

WPB has a direct effect on IW and workplace withdrawal. MI mediated the relationship between WPB and IW and WPB and WW. Further, IL moderated the relationship between WPB and MI.

The results of the current study have significant policy-related, academic and practical implications. Executives must be aware of WPB incidents and take prompt action to completely stop them.

The study contributes to the literature by analysing the role of MI as a mediator for the relationship between WPB and WPB's coping strategies like IW and workplace withdrawal. This study also answers repeated calls for more research on MI and MI's consequences.

The authors seek to analyze the impact of weak corporate governance by top executives of a firm on the firm's earnings reports. This research is meant to further emphasize the impact of co-opted executives on a firm, primarily through their impact on earnings management.

Using financial data from 11,473 firm-year observations, the authors utilize ordinary least squares (OLS), 2-stage IV regressions, propensity score matching (PSM) and entropy balancing to analyze the impact of a co-opted top management team on discretionary accruals and restatements.

The authors find empirical evidence that firms with weak corporate governance from top executives are more likely to manipulate reported earnings and have lower financial reporting quality. The authors also find that the effect of co-opted executives on earnings management is weaker when a chief executive officer's (CEO’s) incentives are not aligned with those of top executives, suggesting that executives prevent earnings management due to reputational concerns. Co-opted chief financial officers (CFOs) increase the magnitude of earnings management in a firm but are not solely responsible for the authors' results.

The authors' results suggest that the top executive team provides an important first defense in the prevention of earnings management and corporate wrongdoing. Co-option of the top executive team may be an important consideration when doing research into corporate governance.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.