Analyzing the dynamic patterns of COVID-19 through nonstandard finite difference scheme DOI Creative Commons
Abeer Aljohani, Ali Shokri, Herbert Mukalazi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 11, 2024

Abstract This paper presents a novel approach to analyzing the dynamics of COVID-19 using nonstandard finite difference (NSFD) schemes. Our model incorporates both asymptomatic and symptomatic infected individuals, allowing for more comprehensive understanding epidemic's spread. We introduce an unconditionally stable NSFD system that eliminates need traditional Runge–Kutta methods, ensuring dynamical consistency numerical accuracy. Through rigorous analysis, we evaluate performance different strategies validate our analytical findings. work demonstrates benefits schemes modeling infectious diseases, offering advantages in terms stability efficiency. further illustrate dynamic behavior under various conditions simulations. The results from these simulations demonstrate effectiveness proposed capturing complex dynamics.

Language: Английский

Bödewadt flow of thermally radiative hybrid nanofluid under the implication of horizontal magnetic field DOI
Abdur Rauf, S. A. Shehzad, Asma Khalid

et al.

Numerical Heat Transfer Part A Applications, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 19

Published: May 8, 2024

It is a known fact that the implication of uniform magnetic field in transversal direction to fluid flow concerns stabilization velocity and deterioration heat transfer rate. now recognized applied horizontal useful for stabilizing/destabilizing rate, which principally rely upon angle such as cooling/heating disk surface. Considering this, present study investigates an incompressible three-dimensional Bödewadt above stretchable with field. The defines stable angular movement at sufficient large distance from stationary Such balanced by Centrifugal forces featured through radial pressure gradient. radiative attributes are characterized hybrid nanofluid, composition Copper (Cu) Titanium Dioxide (TiO2) water (H2O) base fluid. A well-known approach similarity variables adopted first normalize model then resultant system coupled non-linear ordinary differential equations solved Runge-Kutta-Fehlberg (RKF) MATLAB built-in package. graphical results on thermal fields sketched different values dimensionless quantities. observed terms horizontally has stabilizing impact along axis close 0° or 90°, whereas destabilizing influence noticed between 30°−60°. temperature enhanced enlarged parametric Biot number solid volume fractions. Local Nusselt-number increased surface radiation parameter.

Language: Английский

Citations

4
Numerical treatment for double diffusion phenomenon with generalized heat flux effects in 3d nanomaterial flow over bi-directional stretched wall DOI

Saeed Ehsan Awan,

Muhammad Awais, Muhammad Asif Zahoor Raja

et al.

Numerical Heat Transfer Part A Applications, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 27

Published: March 7, 2024

Current study aims to numerically investigate the bi-directional flow of nanofluids in presence Cattaneo–Christov double diffusion for two heat sources, namely, prescribed surface temperature (PST) along with flux (PHF). The conventional mathematical model partial differential equations (PDEs) system have been reduced into an equivalent set ordinary (ODEs). dynamics form approximate solutions ODEs is presented by Adams and Explicit Runge Kutta numerical solvers. For better understanding influence physical parameter interest including Brownian movement parameter, thermophoresis concentration relaxation Schmidt number, Prandtl thermal ratio stretching Deborah number on temperature, as well profiles are exhaustively. Appropriateness scheme ascertained through close resemblance results different state art counterparts negligible error around 10–05 10–09.

Language: Английский

Citations

3
Entropy and energy transfer analysis of a Maxwell thin‐film fluid over an inclined surface with viscous dissipation effect DOI

Revathi Devi Murugan,

Narsu Sivakumar, Nainaru Tarakaramu

et al.

ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, Journal Year: 2024, Volume and Issue: 104(6)

Published: March 26, 2024

Abstract Non‐Newtonian fluid plays a vital role in the field of manufacturing and engineering sector, because its immense heat transfer rate. The two‐dimensional incompressible unsteady Maxwell nanofluid thin‐film flow with MHD viscous dissipation over an inclined surface is investigated. One mechanisms second law thermodynamics, that irreversibility which also analyzed. thin film energy motion equations additional information have been turned into coupled differential system third order. transformed ODE are further evaluated by using Homotopy Analysis Method (HAM). variations entropy rate, velocity, Bejan number temperature various emerging parameters This could potentially lead to development solar systems both affordable highly efficient, so enabling more efficient use renewable sources reducing our dependence on fossil fuels.

Language: Английский

Citations

3
Application of deep learning to study aggregative and non-aggregative nanofluid flow within the nozzle of a liquid rocket engine DOI
Noor Muhammad, Naveed Ahmed,

Mehwish Rani

et al.

International Communications in Heat and Mass Transfer, Journal Year: 2024, Volume and Issue: 155, P. 107449 - 107449

Published: April 24, 2024

Language: Английский

Citations

2
Artificial Neural Network and Response Surface Methodology-Driven Optimization of Cu–Al2O3/Water Hybrid Nanofluid Flow in a Wavy Enclosure with Inclined Periodic Magnetohydrodynamic Effects DOI Creative Commons
Tarikul Islam, Sílvio Gama, Marco Martins Afonso

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 13(1), P. 78 - 78

Published: Dec. 28, 2024

This study explores the optimization of a Cu–Al2O3/water hybrid nanofluid within an irregular wavy enclosure under inclined periodic MHD effects. Hybrid nanofluids, with different mixture ratios copper (Cu) and alumina (Al2O3) nanoparticles in water, are used this study. Numerical simulations using Galerkin residual-based finite-element method (FEM) conducted to solve governing PDEs. At same time, artificial neural networks (ANNs) response surface methodology (RSM) employed optimize thermal performance by maximizing average Nusselt number (Nuav), key indicator transport efficiency. Thermophysical properties such as viscosity conductivity evaluated for validation against experimental data. The results include visual representations heatlines, streamlines, isotherms various physical parameters. Additionally, Nuav, friction factors, efficiency index analyzed nanoparticle ratios. findings show that buoyancy parameters significantly influence heat transfer, friction, addition Cu improves compared Al2O3 nanofluid, demonstrating superior nanofluid. also indicate adding Cu/water diminishes rate. waviness geometry shows significant impact on management well. Moreover, statistical RSM analysis indicates high R2 value 98.88% function, which suggests model is well suited predicting Nuav. Furthermore, ANN demonstrates accuracy mean squared error (MSE) 0.00018, making it strong alternative analysis. Finally, focuses interaction between geometry, effects, can transfer contribute energy-efficient cooling or heating technologies.

Language: Английский

Citations

2
A stochastic scale conjugate neural network procedure for the SIRC epidemic delay differential system DOI
Zulqurnain Sabir, Atef F. Hashem,

Zill E Shams

et al.

Computer Methods in Biomechanics & Biomedical Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: May 6, 2024

In this study, a stochastic computing structure is provided for the numerical solutions of SIRC epidemic delay differential model, i.e. SIRC-EDDM using dynamics COVID-19. The design scale conjugate gradient (CG) neural networks (SCGNNs) presented treatment SIRC-EDDM. mathematical model divided into susceptible S(ρ), recovered R(ρ), infected I(ρ), and cross-immune C(ρ), while performances have been three different cases. exactitude SCGNNs perceived through comparison accomplished reference outcomes (Runge-Kutta scheme) negligible absolute error (AE) that are performed around 10−06 to 10−08 each case obtained results reduce mean square (MSE) train, validation, test data. neuron analysis also shows AE by taking 14 neurons provide more accurateness as compared 4 numbers neurons. To check proficiency SCGNNs, comprehensive studies accessible histograms (EHs) investigations, state transitions (STs) values, MSE performances, regression measures, correlation.

Language: Английский

Citations

1
Analyzing the dynamic patterns of COVID-19 through nonstandard finite difference scheme DOI Creative Commons
Abeer Aljohani, Ali Shokri, Herbert Mukalazi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 11, 2024

Abstract This paper presents a novel approach to analyzing the dynamics of COVID-19 using nonstandard finite difference (NSFD) schemes. Our model incorporates both asymptomatic and symptomatic infected individuals, allowing for more comprehensive understanding epidemic's spread. We introduce an unconditionally stable NSFD system that eliminates need traditional Runge–Kutta methods, ensuring dynamical consistency numerical accuracy. Through rigorous analysis, we evaluate performance different strategies validate our analytical findings. work demonstrates benefits schemes modeling infectious diseases, offering advantages in terms stability efficiency. further illustrate dynamic behavior under various conditions simulations. The results from these simulations demonstrate effectiveness proposed capturing complex dynamics.

Language: Английский

Citations

0