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The present study scrutinizes the relative performance of various near-wall treatments coupled with two-equation RANS models to explore the turbulence transport mechanism in terms of the kinetic energy budget in a plane wall jet and the significance of the near-wall molecular and turbulent shear, to select the best combination among the models which reveals wall jet characteristics most efficiently.

A two-dimensional steady incompressible plane wall jet in a quiescent surrounding is simulated using ANSYS-Fluent solver. Three near-wall treatments, namely the Standard Wall Function (SWF), Enhanced Wall Treatment (EWT) and Menter-Lechner (ML) treatment coupled with Realisable, RNG and Standard k-e models and also the Standard and Shear-Stress Transport (SST) k-ω models are employed for this investigation.

The ML treatment slightly overestimated the budget components on an outer scale, whereas the k-ω models strikingly underestimated them. In the buffer layer at the inner scale, the SWF highly over-predicts turbulent production and dissipation and k-ω models over-predict dissipation. Appreciably accurate inner and outer scale k-budgets are observed with the EWT schemes. With a sufficiently resolved near-wall mesh, the Realisable model with EWT exhibits the mean flow, turbulence characteristics and turbulence energy transport even better than the SST k-ω model.

Three distinct near-wall strategies are chosen for comparative performance analysis, focusing not only on the mean flow and turbulence characteristics but the turbulence energy budget as well, for finding the best combination, having potential as a viable and low-cost alternative to LES and DNS for wall jet simulation in industrial application.

The purpose of this paper is to investigate the thermoelastic interactions in a homogeneous, transversely isotropic infinite medium with a spherical cavity in the context of two temperature Lord-Shulman (2TLS) generalized theory of thermoelasticity considering Eringen’s nonlocal theory and memory dependent derivative (MDD). Memory-dependent derivative is found to be better than fractional calculus for reflecting the memory effect which leads us to the current investigation.

The governing field equations of the problem are solved analytically using the eigenvalue approach in the transformed domain of Laplace when the cavity’s boundary is being loaded thermomechanically. Using MATLAB software the numerical solution in real space-time domain is obtained by Stehfest method.

Numerical results for the different thermophysical quantities are presented in graphs and the effects of delay time parameter, non-local parameter and two temperature parameters are studied thereafter. The outcomes of this study convince that the displacement u, conductive temperature ϕ, thermodynamic temperature θ are concave upward whereas radial stress τ_rr is concave downward for every choice of delay time parameter ω, two temperature parameter η and non-local parameter “ζ”. As a specific instance of our findings, the conclusions of an equivalent problem involving integer order thermoelasticity theory can be obtained, and the corresponding results of this article can be readily inferred for isotropic materials.

The novelty of this research lies in the adoption of generalized thermoelastic theory with memory dependent derivative and Eringen’s nonlocality for analyzing the thermoelastic interactions in an infinite body with spherical cavity by employing eigenvalue approach. It has applications to many thermo-dynamical systems.

This study aims to examine the implementation of agile practices in Industry 4.0 to assess the financial performance measurements of manufacturing firms. It also investigates the relationship between supply chain performance and financial performance.

The study is based on an experimental research design by collecting data from 329 responses from key officials of manufacturing firms. The analyses are carried out to explore this modern concept with the help of the SPSS program, which is used to conduct a confirmatory factor and reliability analysis and Smart-partial least square (PLS) version 4.0 with structural equation modeling.

This research demonstrates the positive effect agile supply chain strategies in Industry 4.0 may have on manufacturing companies' financial performance as a whole. Everything throughout the supply chain in Industry 4.0, from the manufacturers to the end users, is taken into account as a potential performance booster. The values obtained from the model's study show that it is both dependable and effective, surpassing the threshold for such claims. The research is supported by factors like customer involvement (CUS), continuous improvement (CI), integration (INT), modularity (MOD), management style (MS) and supplier involvement (SI) but is undermined by factors including postponement (PPT).

According to the findings of the study, Industry 4.0 firms' financial performance and overall competitiveness are significantly improved when their supply chains are more agile. A more agile supply chain helps businesses to more rapidly adapt to shifts in consumer demand, shorten the amount of time it takes to produce a product, enhance product quality and boost customer happiness. As a consequence of this, there will be an increase in revenue, an improvement in profitability and continued sustainable growth.

There are literary works available on agile practices in various fields, but the current study outlines the need to understand how supply chains perform financially under the mediating effect of agile supply chains in Industry 4.0 which contribute most to the organization's success. The study will aid companies in understanding how agile practices will further the overall performance of the organization financially.