Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Muhammad Shoaib Arif"'
Autor:
Suhail Saleem, Muhammad Rafiq, Nauman Ahmed, Muhammad Shoaib Arif, Ali Raza, Zafar Iqbal, Shafiullah Niazai, Ilyas Khan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract Most of the countries in the world are affected by the coronavirus epidemic that put people in danger, with many infected cases and deaths. The crowding factor plays a significant role in the transmission of coronavirus disease. On the other
Externí odkaz:
https://doaj.org/article/d67b10a6829349c6a11af8224bf5ba14
Publikováno v:
International Journal of Thermofluids, Vol 23, Iss , Pp 100755- (2024)
It is imperative to investigate the proposed computational scheme for the resolution of two-dimensional partial differential equations that result from non-Newtonian nanofluid flow over flat and oscillatory sheets, taking into account the effects of
Externí odkaz:
https://doaj.org/article/bbd312c633b847b6b2ff9f73bf5e6cab
Publikováno v:
Emerging Science Journal, Vol 8, Iss 1, Pp 326-340 (2024)
This study focuses on the cutting-edge field of epidemic modeling, providing a comprehensive investigation of a third-order two-stage numerical approach combined with neural network simulations for the SEIR (Susceptible-Exposed-Infectious-Removed) ep
Externí odkaz:
https://doaj.org/article/5af2c96e7b55463dbde2249510ca6e55
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
This study presents the first comprehensive numerical simulation of heat and mass transfer in fractal-like mixed convective nanofluid flows. The flow of non-Newtonian nanofluids over flat and oscillating sheets is modelled mathematically, and a finit
Externí odkaz:
https://doaj.org/article/fea5e1f40556401d99530175a7d68c4e
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
A novel stochastic numerical scheme is introduced to solve stochastic differential equations. The development of the scheme is based on two different parts. One part finds the solution for the deterministic equation, and the second part is the numeri
Externí odkaz:
https://doaj.org/article/c2d2fd58fab0495f8906743d73a0a841
Publikováno v:
Partial Differential Equations in Applied Mathematics, Vol 9, Iss , Pp 100660- (2024)
The complex and ever-changing characteristics of epidemic modelling, particularly when considering random elements, provide a substantial obstacle in creating precise and practical numerical methods for solving differential equations. This study cont
Externí odkaz:
https://doaj.org/article/397adbf9b0ea4ca8a20402c035946bff
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
This paper introduces an exponential time integrator scheme for solving partial differential equations in time, specifically addressing the scalar time-dependent convection-diffusion equation. The proposed second-order accurate scheme is demonstrated
Externí odkaz:
https://doaj.org/article/6ab58e3404c246b69be3a9cf52055097
Publikováno v:
Fractal and Fractional, Vol 8, Iss 5, p 276 (2024)
An explicit computational scheme is proposed for solving fractal time-dependent partial differential equations (PDEs). The scheme is a three-stage scheme constructed using the fractal Taylor series. The fractal time order of the scheme is three. The
Externí odkaz:
https://doaj.org/article/9960306429e447139436d2697054cd05
Publikováno v:
Emerging Science Journal, Vol 7, Iss 3, Pp 808-820 (2023)
This study aims to propose numerical schemes for fractional time discretization of partial differential equations (PDEs). The scheme is comprised of two stages. Using von Neumann stability analysis, we ensure the robustness of the scheme. The energy
Externí odkaz:
https://doaj.org/article/b87976b4ab5f480dbbeda747ce9d2c54
Publikováno v:
Heliyon, Vol 9, Iss 10, Pp e20868- (2023)
This article suggests a fourth-order numerical approach for solving ordinary differential equations (ODEs) that are both linear and nonlinear. The suggested scheme is an explicit predictor-corrector scheme. For linear ODE, the proposed numerical sche
Externí odkaz:
https://doaj.org/article/49fb768c15b04c729106bf842cfc854f