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Neutrosophic multiple-attribute decision making (MADM) is one of the major study areas in ambiguous and inconsistent decision-making problems. The single-valued neutrosophic number (SVNN), which is an expansion of the fuzzy number, intuitionistic fuzzy number, can handle difficulties involving a huge quantity of erroneous, partial, and inconsistent information. To address the multi-criteria decision-making problems, novel aggregation operators (AGOs) are proposed in this article considering the benefits of the SVNN. The new AGOs consider the interrelationship involving any number of input data and can remove the effect of unreliable data. This article adds the Aczel-Alsina (AA) operations to increase the flexibility of the new AGOs. This study proposes the single-valued neutrosophic Aczel-Alsina power Muirhead mean (SVNAAPMM) operator, single-valued neutrosophic Aczel-Alsina power dual Muirhead mean (SVNAAPDMM) operator which combines the Aczel-Asina operational rules with the power average/geometric operator and the Muirhead/ dual Muirhead mean operators. Some core characteristics and special cases with respect to the parameters are explored and it is found that various existing AGOs are special cases of the newly initiated AGOs. Further, weighted form these AGOs are introduced. Then, we set up the MADM technique using the two AGOs that are suggested to solve MADM problems. We then give a numerical example about strategic supplier's selection and compare it to other related MADM techniques already in use in the SVNN information to demonstrate the effectiveness and appropriateness of the anticipated technique. [ABSTRACT FROM AUTHOR]

The term "thermal conductance" is used to describe a material's ability to transport or conduct heat. Materials with high thermal conductivity are employed as heating elements, while those with poor thermal conductivity are used for insulation purposes. It is known that the thermal conductivity of pure metals decreases as temperature increases. In this study, the primary focus is on the physical assessment of thermal conductivity, entropy, and the improvement rate of thermal density in a magnetic nanofluid. To achieve this, nonlinear partial differential equations are transformed into ordinary differential equations. These equations are further solved using a computational method known as the Keller box technique. Various flow parameters, such as the Eckert number, density parameter, magnetic-force parameter, thermophoretic number, buoyancy number, and Prandtl parameter, are examined for their impact on velocity, temperature distribution, and concentration distribution. For the asymptotic results, the appropriate range of parameters, such as 1.0 ≤ ξ ≤ 5.0, 0.0 ≤ n ≤ 0.9, 0.1 ≤ Ec ≤ 2.0, 0.7 ≤ Pr ≤ 7.0, 0.1 ≤ Nt ≤ 0.5, and 0.1 ≤ Nb ≤ 0.9, is utilized. The key findings of this study are related to the assessment of heat transfer in a magnetic nanofluid considering thermal conductivity, entropy generation, and temperature density. It is observed that the temperature distribution increases as entropy generation increases. From a physical perspective, thermal conductivity acts as a facilitating factor in enhancing heat transfer. The study concludes by emphasizing the consistency achieved through a comparison of the latest findings with previously reported analyses. [ABSTRACT FROM AUTHOR]

This study investigates the effects of activation energy and chemical reactions on the boundary layer flow around a wedge that is moving in a nanofluid. To represent the problem, nonlinear partial differential equations are utilized. These equations can be reduced to nonlinear coupled ordinary differential equations using similarity transformations. These equations are numerically solved using the Keller Box technique, and then their numerical and pictorial solutions are studied using MATLAB. The study looks at the relationship between the velocity, temperature, and concentration profiles and important factors such as the Prandtl number, constant moving parameter, activation energy, and reaction rate. The parametric range of factors such as 0.1 ≤ λ ≤ 1.0, 0.1 ≤ Le ≤ 3.0, 0.1 ≤ E ≤ 2.0, 0.1 ≤ Pr ≤ 7.0, 0.1 ≤ Nt ≤ 0.5, 0.1 ≤ Nb ≤ 1.0, 0.1 ≤ σ ≤ 3.4, 0.1 ≤ δ ≤ 2.5, and 0.1 ≤ β ≤ 2.0 is utilized. Furthermore, a comprehensive investigation is conducted into the remedies for skin friction and heat transmission rate. It is deduced that a growing magnitude in moving fluid velocity is noted for lower Prandtl, moving factor, reaction factor, and greater activation energy. It is depicted that the maximum enhancing magnitude in temperature and concentration with good distributions is examined for each pertinent factor. The growing magnitude of heat transport is noted for lower Lewis and temperature-difference factors but increases as pressure-gradient and Brownian factor rise. [ABSTRACT FROM AUTHOR]

The importance of this investigation is to examine the heat and mass transportation of magneto nanofluid movement along a heated sheet with exponential temperature-dependent density, entropy optimization, thermal buoyancy, activation energy, and chemical reaction aspects. The influence of these factors in cutting tools by means of machining and nanofluid lubrication is a significant process in cutting zone, chip cleaning, lubricating, and cooling productivity in milling. The corresponding energy activation and chemical process are essential to understand the thermal behavior of nanofluid. The appropriate transformations are used to solve nonlinear partial differential equations within the framework of ordinary differential equations using stream functions and similarity variables. The Keller box method is employed to efficiently solve these equations computationally under the Newton–Raphson approach. Through tables and figures, the fluid velocity, temperature distribution, and concentration consequences are sketched using various controlling parameters. It is seen that the fluid temperature function increases with noticeable amplitude as the Eckert factor, variable density, chemical-reaction, and activation energy increase. It is found that the noticeable enhancement in heat and mass transportation is deduced for maximum Brownian motion and thermophoresis. This work is important in various applications such as cutting fluids, drilling, brake oil, engine oil, minimum quantity lubrication, enhanced oil recovery, and controlled friction between the tool-chip and tool-work during machining operations. [ABSTRACT FROM AUTHOR]

The usage of nanoparticles is effectively enhanced in industries and technologies because of their intensified thermal performance. Nanomaterials innovatively play a significant role in technological applications such as biosensors, the petroleum related industry and biofuels. Due to such exceptional performance of nanomaterials, the magneto-hydrodynamics squeezed nanofluid flow is examined through the parallel walls. The transportation phenomenon of heat and mass with viscous dissipation and double stratification is also investigated under Cattaneo–Christov phenomenon. The constitutive equations (PDEs) are transmuted with precise similarity variable into dimensionless equations (ODEs). The acquired ODEs are evaluated through the assistance of Homotopic technique. The impacts of the emerging parameters are described graphically on the concerned profiles. The graphical discussion clarifies that both stratification parameters diminish both profiles (thermal & solutal). Concentration field is decreased by the thermophoresis parameter. The relaxation time parameters decrease the heat and mass transport. Moreover, both Brownian and thermophoresis parameters raise the temperature. [ABSTRACT FROM AUTHOR]