ABSTRACT Current study deals with influence of rotating and thermal radiative fluxing on fluid’s thermal, hydrodynamic, and concentration behavior flowing between two nonparallel walls in existence of uniform magnetized force. The modeling is based on nonlinear partial differential equations (PDEs) such as continuity, momentum, temperature, and concentricity equations. These equations are converted into a system of nonlinear ordinary differential equations (ODEs) utilizing similarity transformations. Analytical solution has been constructed using the Differential Transform Method (DTM). The present results are compared to results obtained by the HAM package and by the numerical procedure (RKF-45) for validation. The impacts of active variables like the rotational factor, Hartmann, Schmidt numbers, and thermal radiation parameter, are investigated on the rapidity, temperature, and concentricity profiles. Moreover, frictional force factor, Nusselt, and Sherwood quantities. It is found that speed and concentricity of the fluid flow increase with the growth of Hartmann number, whereas a reverse behaviour is observed for thermal distribution. Results obtained also reveal an improvement in frictional force factor, Nusselt and Sherwood numbers with the enhancement of Reα parameter. It is found that an increase in the rotational parameter Ro and the radiation factor Rd leads to a decrease in the Nusselt number.

ABSTRACT The current effort is executed to interpret the heat transmission of combined stenosis and aneurysm in an artery, taking into account variable properties such as viscous dissipation and thermal radiation. We reduced the two directional energy and momentum equations to unidirectional flow by normalizing them under the mild stenotic assumption. After that, a mathematical framework for the physical problem is developed. An intricate nonlinear set of partial differential equations results from this formulation. A suitable numerical method of finite difference is employed on consequent equations to solve them. Afterward, graphical results predict the region of flow and the influence of involved parameters is shown in pictorial form. Furthermore, these solutions are employed to test how certain parameters, like streamlines, flow rate, and wall shear stress, affect blood flow. Using streamlines, we will also observe the general behavior of blood flow patterns.

ABSTRACT This study is important because it helps us understand how different factors affect the flow of a special liquid with nanoparticles, giving us useful insights for real-world applications in engineering and technology. This research endeavours to explore and contrast the distinctive characteristics of steady, 2-D magnetohydrodynamic (MHD) and stagnation point (Hiemenz) flow in Carreau hybrid nanofluid {Fe3O4-Cu/kerosene-engine Oil} over a nonlinear stretching-shrinking surface with its counterpart, Carreau nanofluid. Employing the laws of conservation encompassing mass, momentum, energy, and concentration, our methodology probes into the multifaceted effects induced by factors like the suction-injection, viscous dissipation, Newtonian heating, Hiemenz flow, thermophoresis, and Brownian motion. This exploration involves the transformation of governing partial differential equations (PDEs) into a system of ordinary differential equations (ODEs) through similarity transformations. Subsequently, the intricate non-linear ODEs are meticulously solved using the bvp4c technique, an adept MATLAB built-in function, facilitating a comprehensive understanding of the intricate dynamics within the system. In addition, the study considers the Newtonian heating effect and a numerical comparison is performed to verify the results. Using two different types of nanoparticles dispersed in kerosene-engine oil, it was demonstrated that increasing Weissenberg parameter values resulted in significant improvements in thermal conductivity and thermal velocity. A comparison of Carreau nanofluid thermal and concentration velocities with Carreau hybrid nanofluid showed that Carreau nanofluid values are lower (Weissenberg parameter). Higher Biot numbers are associated with reduced temperature velocity and elevated concentration velocity.

ABSTRACT This study investigates the application of artificial intelligence (AI) in fluid dynamics, mainly using a neural network trained by the Levenberg – Marquardt method (NN-BLMM), to model magnetohydrodynamic (MHD) stagnation point Ree – Eyring flow. We focus on this flow over a convectively heated stretched surface by integrating the Cattaneo – Christov heat model. The initial complex nonlinear partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs) using suitable similarity variables. A dataset was generated using the Lobatto IIIA numerical solver to analyze the effects of various fluid flow and thermal parameters. The NN-BLMM model was then rigorously evaluated through training, testing, and validation phases and compared with reference data. This ensures the model’s precision and effectiveness. We observe that an increase in the Powell – Eyring fluid parameter notably reduces the fluid’s shear resistance, implying a decrease in viscosity. Concurrently, the heat transfer rate within the fluid medium increases with an increase in the internal heat generation parameter. These findings highlight the robustness of NN-BLMM in simulating complex fluid dynamics, emphasizing AI’s potential to provide a deeper understanding of non-Newtonian fluid behaviors. This research has important implications for industrial applications in which precise control over fluid properties and heat transfer is crucial.

ABSTRACT This study describes the design and implementation of an algebraic approach for a dynamic optimal decoupling controller in a multi-variable liquid-level system. This method aligns with model-matching criteria and the frequency-matching technique. The prime objective of the proposed approach is to create a closed-loop feedback system using a PID controller that aligns with a user-defined linear system model in terms of both system dynamics and static behavioral response. To illustrate robust stability, the study incorporates multiplicative input and output uncertainty. Simulation results verify the efficacy of the proposed decentralized controller, presenting its effectiveness in achieving both set-point accuracy and disturbance attenuation. Furthermore, the study employs disk margin analysis to ascertain safe ranges for gain and phase margin.

ABSTRACT Cancer is the world’s second-biggest cause of death, accounting for roughly 10 million deaths in 2020 and estimated to reach 16 million by 2040. In this study, we propose a novel technique for the treatment of tumor models with a power-law kernel with the Sumudu transform. The analysis was made for a generalized form of analytical solution that is unique and Picard K-stable by using Hilbert and Banach space results. The model investigates the Ulam-Hyers-Rassias stability, uniqueness of solutions, and impact of fractional derivatives with the power-law kernel. Reproductive number analysis with an equilibrium point shows the bounded solution in the feasible region. In the end, numerical simulations are drawn through figures at different fractional and fractal dimensions for the dynamics of treatment and the growth of normal cells. The analysis shows crucial criteria for system stability, ensuring the efficacy of therapeutic interventions through novel mathematical and biological insights.

ABSTRACT Electric vehicles (EVs) can be employed intelligently in Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) modes for Load Frequency Control (LFC) in the power grid. Due to the rapid variation of charging or discharging power, EVs can perform frequency regulation tasks and serve as distributed energy storage devices. In this paper, a linearized model of an interconnected multi-area power system is formulated in the restructured environment to include Electric Vehicle Aggregators (EVA). The DISCO Participation Matrix (DPM) is used to model Poolco and bilateral contracts in restructured multi-area power systems along with the participation of EVs. The faster dynamic response of EVs can effectively control the deviations in area frequencies imposed by the DISCOs load demand. The gains of the integral controller employed in each area are tuned by Real Coded Genetic Algorithm (RGA) by minimizing the integral square error function for area frequency deviations. The efficacy of power support from the EVs for load frequency control is validated by simulating different Poolco and bilateral transactions. It is shown that the EVs have a significant impact on obtaining optimal transient response for area frequencies, tie-line powers and power generation of conventional thermal generating units for any type of transaction in a restructured environment.

ABSTRACT In the contemporary power system, congestion is a big hazard to system security. Congestion reduces the capability of the power system to work under secure limits of thermal and voltage profiles. Implementing FACTS devices or rescheduling the generator’s active power output are the most prevalent ways to mitigate congestion in the current scenario and hence this paper presents generator rescheduling for congestion management under the N-1 contingency condition. The generator sensitivity factor (GSF) is used to select the generators’ participation in the rescheduling process. The minimization of active power rescheduled by the selected generators is the key to success. JAYA algorithm is used first time in this work to reduce the congestion cost of the system. Furthermore, the JAYA algorithm is applied to a modified IEEE 30 bus system and the results obtained are validated by comparing them with other popular heuristic algorithms as available in the literature for diverse case studies.

ABSTRACT This Riga plate, which extends the configuration with permanent magnets and electrodes, may induce a wall-parallel Lorentz force over the magnetic field and exterior electrics, enabling efficient control of the fluid flow. In this paper, the focus is on considering the three-dimensional flow characteristics of Williamson fluid past the Riga plate in the absence of variable thermal properties. Many influential factors, such as convective boundary conditions of temperature, viscous dissipation, binary chemical reactions, and thermal radiation, are studied in their analysis. To address the study problem, dimensionless parameters are used to clarify the conductive partial differential equations. This dimensionless form was consequently determined mathematically by applying the shooting technique. The affected engineering parameters were interpreted graphically to appeal to physical interest. It was observed that the velocity distribution slows down into the viscosity parameter and stretching ratio constant. The enhanced temperature distribution was noticed in the increase in the thermal conductivity parameter. The rate of heat transport (130.56%) rises in the presence of Biot numbers. This causes significant increases in convective heat transport and heat energy.

ABSTRACT This paper presents a fuzzy logic and optimization-based controller design for load frequency control of a single area system with a non-reheated turbine. The controller’s unknown parameters are determined using Big Bang-Big Crunch (BB-BC) optimization algorithm by minimizing the integral square error. In addition, extensive simulation experiments on an existing single-area power system were conducted to test the efficacy of the proposed design technique. The findings show that the proposed controller outperforms the recently developed controllers regarding transient response and error parameters. The suggested controller’s capability is also demonstrated by improved external disturbance rejections despite plant parameter variations. The reduced model of a single area load frequency control system is also obtained in this paper. It found that the dynamic response of the obtained reduced system is close to the original single area LFC system.