| Literature DB >> 35654805 |
Muhammad Sohail1, Essam R El-Zahar2,3, Abd Allah A Mousa4, Umar Nazir5, Saad Althobaiti6, Ali Althobaiti4, Nehad Ali Shah7, Jae Dong Chung8.
Abstract
Thermal performance can be enhanced due to the mixing of nanoparticles in base fluid. This research discusses the involvement of ternary hybrid nanoparticles in the mixture of pseudo-plastic fluid model past over a two dimensional porous stretching sheet. Modelling of energy equation is carried out in the presence of external heat source or sink and viscous dissipation. The flow presenting equations and derived in Cartesian coordinate system under usual boundary layer theory in the form of complex coupled partial differential equations (PDEs). The derived PDEs have been converted into corresponding ordinary differential equations (ODEs) with the engagement of suitable transformation. The engineers, scientists and mathematicians have great interest in the solution of differential equations because to understand the real physics of the problem. Here, finite element scheme has been used to approximate the solution of the converted problem. The contribution of several emerging parameters on solution have been displayed through graphs and discussed. It is recommended that the finite element method can be engaged to approximate the solution of nonlinear problems arising in modelling the problem in mathematical physics.Entities:
Year: 2022 PMID: 35654805 PMCID: PMC9163131 DOI: 10.1038/s41598-022-12857-3
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.996
Figure 1Prepared scheme of tri-hybrid nanoparticles.
Thermal properties for ethylene glycol, aluminium oxide, titanium dioxide and silicon dioxide in [33 and 34].
| Nanoparticles | |||
|---|---|---|---|
| 0.253 | 1113.5 | ||
| 32.9 | 6310 | ||
| 8.953 | 4250 | ||
| 1.4013 | 2270 |
Figure 2Geometrical view of flow model.
Illustration of numerical values of and within 330 elements.
| Elements | ||
|---|---|---|
| 30 | 0.059668223 | 0.067321344 |
| 60 | 0.052621388 | 0.053600561 |
| 90 | 0.050436000 | 0.049611093 |
| 120 | 0.049374316 | 0.047715502 |
| 150 | 0.048743940 | 0.046612898 |
| 180 | 0.048328516 | 0.045888606 |
| 210 | 0.048036051 | 0.045375348 |
| 240 | 0.047817660 | 0.044993943 |
| 270 | 0.047641974 | 0.044705003 |
| 300 | 0.047504933 | 0.044472856 |
| 330 | 0.057145238 | 0.055316303 |
Validation of skin friction coefficient with published work for .
| Maleki et al.[ | Present work |
|---|---|
| 0.44375 | 0.044705003 |
| 0.44375 | 0.047504933 |
| 0.4437 | 0.048328516 |
Figure 3Distribution in against
Figure 4Distribution in against
Figure 5Distribution in against
Figure 6Distribution in against
Figure 7Distribution in against
Figure 8Distribution in against
Figure 9Distribution in against
Figure 10Distribution in against
Variation in skin friction coefficient and temperature gradient versus distribution in , and including tri-hybrid nanoparticles.
| − 1.5 | 0.42797718 | 0.55852906 | |
| 0.1 | 0.41870728 | 0.76092060 | |
| 0.7 | 0.40781438 | 0.64303994 | |
| 0.0 | 0.20881888 | 1.5281956 | |
| 0.5 | 0.36868534 | 1.3571423 | |
| 0.7 | 1.3571423 | 1.3038192 | |
| 0.3 | 0.35320488 | 1.3720856 | |
| 0.6 | 0.15365893 | 1.3894693 | |
| 0.8 | 0.029884079 | 1.4646254 | |
Thermal aspects of Nusselt number and skin friction coefficient versus and
| Variation in parameters | |||
|---|---|---|---|
| 0.0 | 0.81715589 | 1.3564572 | |
| 0.3 | 0.82745549 | 1.2935174 | |
| 0.7 | 0.81653926 | 1.1204841 | |
| 0.0 | 0.84463158 | 1.6390042 | |
| 206 | 0.83190583 | 1.7503621 | |
| 208 | 0.81849360 | 1.8555670 | |
| 0.0 | 1.0182082 | 1.7389999 | |
| 0.6 | 1.8221094 | 1.8817948 | |
| 1.2 | 1.9434104 | 1.9379620 | |