Simulation of Prandtl Nanofluid in the Mixed Convective Flow of Activation Energy with Gyrotactic Microorganisms: Numerical Outlook Features of Micro-Machines.

The physiological systems and biological applications that have arisen during the past 15 years depend heavily on the microscale and nanoscale fluxes. Microchannels have been utilized to develop new diagnostic assays, examine cell adhesion and molecular transport, and replicate the fluid flow microenvironment of the circulatory system. The various uses of MHD boundary flow in engineering and technology are extensive, ranging from MHD power generators and the polymer industry to MHD flow meters and pumps and the spinning of filaments. In this investigation, the (Magnetohydrodynamic) MHD flow of Prandtl nanofluid is investigated along with mixed convection, energy activation, microorganism, and chemical reaction. The flow model is considered through partial differential equations in dimensionless form which is then integrated numerically via considering the Bvp4c technique. The outcome is numerous emerging physical parameters over velocity profile, temperature, mass concentration, and microorganism with the separate pertinent quantities such as the Prandtl fluid parameter, elastic fluid parameter, magnetic field, mixed convection parameter, activation energy, chemical reaction, Brownian motion, thermophoretic force, Prandtl number, and Schmidt number. The friction factor, rate of heat transfer and Sherwood number, and density of microbes are revealed numerically and graphically. The outcomes indicate that the Prandtl fluid parameter and elastic fluid parameter tend to enhance the velocity profile. It is also noted that the Prandtl fluid parameter depreciates the thermal rate with the addition of the concentration profile while the opposite trend is recorded for activation energy. Obtained numerical outcomes are correspondingly compared with the current statistics in limiting cases and a close match is obtained.

Proactive visual prediction auditing the green eco-safety through backcasting approach booster by grey recruitment priority conceptual framework.

Climate change is a challenge that endangers societal TBL elements' stability. The countries' economies focus on planning for reducing carbon emissions 'CE' and replacing them with low CE energy. This objective needs accurate prediction for CE till 2030 via recording the most significant variables related to CE causes. The variables ( L i q ) are divided into two types tacking in phase I through two steps. The first step classifying the government policies that tackling by the backcasting approach to ranking them. The second step classifies the nature of the energy source which produces CE in Mega ton by SVM. The second phase is fed by phase I outputs to generate a series of prediction values by the LSTM, which is supported by the grey recruitment technique GRPT ( 1 , 1 ) to reduce the forecasting errors. The proposed conceptual framework named (Green Eco-Safety Monitoring; GESM), which considered a methodology gathering the backcasting, SVM, and LSTM provided by GRPT ( 1 , 1 ) in phase II. The paper tracks 21 governorates' CE. Proactive monitoring helps take corrective actions, enhancing the reduction in errors gap to less than 2.4%. The paper reveals that the industrial sector extracting CE at (38.67%) to 2020 with hopeful reduction of 1.72% annually if the government's interested in supporting carbon sinks, which drastically decreased to 1% by 2020 and to 0.72% annually by 2030.

Significance of Free Convection Flow over an Oscillating Inclined Plate Induced by Nanofluid with Porous Medium: The Case of the Prabhakar Fractional Approach.

Given the importance and use of electrically conducted nanofluids, this work aims to examine an engine-oil-based nanofluid including various nanoparticles. In the current study, a fractional model for inspecting the thermal aspect of a Brinkman-type nanofluid, composed of (molybdenum disulfide (MOS2) and graphene oxide (GO) nanoparticles flows on an oscillating infinite inclined plate, which characterizes an asymmetrical fluid flow, heat, and mass transfer. Furthermore, the Newtonian heating effect, magnetic field, and slip boundary conditions were taken into account. The objectives for implementing the Prabhakar-like fractional model are justified because this fractional algorithm has contemporary definitions with no singularity restrictions. Furthermore, the guided fractional model was solved using the Laplace transform and several inverse methods. The obtained symmetrical solutions have been visually analyzed to investigate the physics of several relevant flow parameters on the governed equations. Some exceptional cases for the momentum field are compiled to see the physical analysis of the flowing fluid symmetry. The results show that the thermal enhancement can be progressively improved with the interaction of the molybdenum disulfide-engine oil-based nanofluid suspension, rather than with the graphene oxide mixed nanoparticle fluid. Furthermore, the temperature and momentum profiles enhance due to the factional parameters for molybdenum disulfide and the graphene oxide-engine oil-based nanofluid suspension. This study's graphical and numerical comparison with the existing literature has shown a very close resemblance with the present work, which provides confidence that the unavailable results are accurate. The results show that an increase improved the heat transmission in the solid nanoparticle volume fractions. In addition, the increment in the mass and heat transfer was analyzed in the numerical evaluation, while the shear stress was enhanced with the enhancement in the Prabhakar fractional parameter α.