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The present work is devoted to investigating the sensitivity analysis of the electroosmotic peristaltic motion of non-Newtonian Casson fluid with the effect of the chemical reaction and magnetohydrodynamics through the porous medium. The main focus is on flow efficiency quantities such as pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. This initiative is to bridge the existing gap in the available literature.

The governing equations of the problem are mathematically formulated and subsequently simplified for sensitivity analysis under the assumptions of a long wavelength and a small Reynolds number. The simplified equations take the form of coupled nonlinear differential equations, which are solved using the built-in Matlab routine bvp4c. The response surface methodology and artificial neural networks are used to develop the empirical model for pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall.

The empirical model demonstrates an excellent fit with a coefficient of determination reaching 100% for responses, frictional forces on the upper wall and frictional forces on the lower wall and 99.99% for response, for pressure rise per wavelength. It is revealed through the sensitivity analysis that pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall are most sensitive to the permeability parameter at all levels.

The objective of this study is to use artificial neural networks simulation and analyze the sensitivity of electroosmotic peristaltic motion of non-Newtonian fluid with the effect of chemical reaction.

The purpose of this study is to elaborate mixed convection impact in stratified nanofluid flow by convectively heated moving surface. Rheological relations of second-grade fluid are used for formulation. Magnetic field, heat absorption/generation and convective conditions are considered for modeling.

Convergent solutions are achieved using homotopy procedure.

The authors found opposing behavior for radiation and thermal stratification variables against thermal field.

No such analysis has yet been reported.

This study aims to model the important flow response quantities over a shrinking wedge with the help of response surface methodology (RSM) and an artificial neural network (ANN). An ANN simulation for optimal thermal transport of incompressible viscous fluid under the impact of the magnetic effect (MHD) over a shrinking wedge with sensitivity analysis and optimization with RSM has yet not been investigated. This effort is devoted to filling the gap in existing literature.

A statistical experimental design is a setup with RSM using a central composite design (CCD). This setup involves the combination of values of input parameters such as porosity, shrinking and magnetic effect. The responses of skin friction coefficient and Nusselt number are required against each parameter combination of the experimental design, which is computed by solving the simplified form of the governing equations using bvp4c (a built-in technique in MATLAB). An empirical model for Cf_x and Nu_x using RSM and ANN adopting the Levenberg–Marquardt algorithm based on trained neural networks (LMA-TNN) is attained. The empirical model for skin friction coefficient and Nusselt number using RSM has 99.96% and 99.99% coefficients of determination, respectively.

The values of these matrices show the goodness of fit for these quantities. The authors compared the results obtained from bvp4c, RSM and ANN and found them all to be in good agreement. A sensitivity analysis is performed, which shows that Cf_x as well as Nu_x are most affected by porosity. However, they are least affected by magnetic parameters.

This study aims to simulate ANN and sensitivity analysis for optimal thermal transport of magnetic viscous fluid over shrinking wedge.

This study aims to examine the cilia-driven flow of magnetohydrodynamics (MHD) non-Newtonian fluid through a porous medium. The Jeffrey fluid model is taken into account. The fluid motion in a two-dimensional symmetric channel emphasizes the dominance of viscous properties over inertial properties in the context of long wavelength and low Reynolds number approximations.

An integrated numerical and analytic results are obtained by hybrid approach. A statistical method analysis of variance along with response surface methodology is used. Sensitivity analysis is used to validate the accuracy of nondimensional numbers.

The impact of various flow parameters is presented graphically and in numerical tables. It is noted that the velocity slip parameter is the most sensitive flow parameter in velocity and relaxation to retardation time ratio in temperature.

A model on cilia-generated flow of MHD non-Newtonian Jeffrey fluid is proposed.

In the present article, sensitivity analysis was studied in the presence of the combined effects of thermal radiation, suction and magnetohydrodynamics (MHD) effects on a Nimonic 80A-Fe_3O4/water hybrid nanofluid across moving a wedge with variable surface temperature and buoyancy effects.

The governing equations were transformed using similarity transformations and solved using MATLAB bvp4c code and response surface methodology (RSM), with quadratic face-centred central composite design being implemented. All results and graphs were formulated after positive outcomes of our results with existing literature.

An increase in magnetic parameter (M) and velocity ratio parameter (R) resulted in an increase in velocity profiles and local Nusselt number, while a reverse trend was observed for temperature profiles. With radiation parameter Rd = 0.8, the local Nusselt number increased by 4.08% as the velocity ratio parameter increased from R = 0.0 to R = 0.5. The Nusselt number was found to be most sensitive to R, while the latter produced negative sensitivity on skin friction coefficient. The skin friction coefficient for the hybrid nanofluid model increased by 35.39% compared to the regular fluid model, with a very low standard deviation value of 10⁻⁴. The Model F-value for Nusselt number model was found to be 939278.49 with a noise ratio of 3618.711. Skin friction coefficient was found to be most sensitive with respect to changes in the parametric values of M.

Nimonic 80A being a super-alloy of nickel-iron-chromium and built in high frequency melting, it can work up to 1500°F and is extensively used in automobile exhaust valves.

The present study finds numerous applications in biotoxicity studies, medical industries, water heaters and the forging of hot exhaust valve heads.

In view of various applications of our present study, there remains a gap in examining the sensitivity analysis of a hybrid nanofluid flow model across a moving permeable wedge using the Tiwari–Das model, which required clinical investigations numerically and statistically.

Recent literature in environmental management suggests that fostering employees’ innovative behaviour in green service is vital for enhancing the environmental sustainability of hospitality organizations. Despite this, few efforts have been made to understand how green entrepreneurial leadership (GEL) relates to green service innovative behaviour (GSIB). This study aims to examine whether GEL can promote GSIB among hospitality employees through the serial mediation of green learning orientation (GLO) and green knowledge acquisition (GKA) using the conservation of resources theory. The authors expect environmental dynamism to strengthen the relationship between GEL and employees’ GSIB, leveraging the resource-based view theory.

This study collected data through a multi-wave survey (four waves, two weeks apart) from 341 employees working in three-to-five-star hotels in Pakistan’s major cities. The authors used partial least squares structural equation modelling to evaluate the hypotheses proposed in the theoretical model.

The study revealed a significant relationship between GEL and employee GSIB, mediated by GLO and GKA. In addition, environmental dynamism strengthened the relationship of GEL with employee GSIB.

The research advances the literature on GEL in the hospitality sector by providing insights into the mediating and moderating processes that translate GEL into GSIB among hospitality employees. Moreover, the research provides important implications for hotels investing in green initiatives and looking for ways to foster employees’ GSIB.

The purpose of this paper is to predict the effects of magnetic field, heat and mass transfer and rotation on the peristaltic flow of an incompressible Newtonian fluid in a channel with compliant walls. The whole system is in a rotating frame of reference.

The governing equations of two-dimensional fluid have been simplified under long wavelength and low Reynolds number approximation. The solutions are carried out for the stream function, temperature, concentration field, velocity and heat transfer coefficient.

The results indicate that the effects of permeability, magnetic field and rotation are very pronounced in the phenomena. Impacts of various involved parameters appearing in the solutions are carefully analyzed.

The effect of the concentration distribution, heat and mass transfer and rotation on the wave frame is analyzed theoretically and computed numerically. Numerical results are given and illustrated graphically in each case considered. A comparison was made with the results obtained in the presence and absence of rotation, magnetic field and heat and mass transfer.

This paper aims to examine the impact of various economic, social and environmental issues on the sustainable development of Pakistan, both directly and indirectly through the sustainability dimensions of China–Pakistan Economic Corridor (CPEC), a multi-billion-dollar megaproject.

Using a quantitative (deductive) methodological approach, data were collected using a strategy of an online questionnaire survey from diverse stakeholders of CPEC in Pakistan. Partial least squares-based structural equation modeling technique was used to test the relationship between observed and latent variables.

The results confirmed the positive impact of various economic, social and environmental issues on the sustainable development of Pakistan directly and indirectly through the partial mediation of sustainability dimensions of CPEC.

Sustainability perceptions of stakeholders about CPEC and its relationship with sustainable development are critical issues for governments and policymakers. This paper suggest how economic, social and environmental dimensions of CPEC can enhance the positive perception which is necessary for stakeholder involvement and support for megaprojects such as CPEC.

This study evaluated the megaprojects of CPEC from a sustainability perspective through stakeholders’ perceptions by proposing and testing a parsimonious research model that has never been examined in the existing literature.

This study aims to present a unique hybrid metaheuristic approach to solving the nonlinear analysis of hall currents and electric double layer (EDL) effects in multiphase wavy flow by merging the firefly algorithm (FA) and the water cycle algorithm (WCA).

Nonlinear Hall currents and EDL effects in multiphase wavy flow are originally described by partial differential equations, which are then translated into an ordinary differential equation model. The hybrid FA-WCA technique is used to take on the optimization challenge and find the best possible design weights for artificial neural networks. The fitness function is efficiently optimized by this hybrid approach, allowing the optimal design weights to be determined.

The proposed strategy is shown to be effective by taking into account multiple variables to arrive at a single answer. The numerical results obtained from the proposed method exhibit good agreement with the reference solution within finite intervals, showcasing the accuracy of the approach used in this study. Furthermore, a comparison is made between the presented results and the reference numerical solutions of the Hall Currents and electroosmotic effects in multiphase wavy flow problem.

This comparative analysis includes various performance indices, providing a statistical assessment of the precision, efficiency and reliability of the proposed approach. Moreover, to the best of the authors’ knowledge, this is a new work which has not been explored in existing literature and will add new directions to the field of fluid flows to predict most accurate results.

Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To track changes in mass deposition, the effect of particle thermophoresis is therefore seen in a mixed convective flow of Williamson hybrid nanofluids upon a stretching/shrinking sheet.

The PDEs are transformed into ordinary differential equations (ODEs) using the similarity technique and then the bvp4c solver is employed for the altered transformed equations. The main factors influencing the heat, mass and flow profiles are displayed graphically.

The findings imply that the larger effects of the thermophoretic parameter cause the mass transfer rate to drop for both solutions. In addition, the suggested hybrid nanoparticles significantly increase the heat transfer rate in both outcomes. Hybrid nanoparticles work well for producing the most energy possible. They are essential in causing the flow to accelerate at a high pace.

The consistent results of this analysis have the potential to boost the competence of thermal energy systems.

It has not yet been attempted to incorporate hybrid nanofluids and thermophoretic particle deposition impact across a vertical stretching/shrinking sheet subject to double-diffusive mixed convection flow in a Williamson model. The numerical method has been validated by comparing the generated numerical results with the published work.