Scholarlink

<p>The work aims to explore the intelligent techniques on unsteady squeezing flow of a hybrid nanofluid possessing electrical conductivity between two parallel plates, an interesting phenomenon of great importance in mechanical, aerospace and biomedical engineering, hydrology or heat management systems. The model incorporates advanced features such as ternary hybrid nanoparticles—zirconia (<i>ZrO</i><sub><i>2</i></sub>), molybdenum disulfide (<i>MoS</i><sub><i>2</i></sub>), and graphene oxide (<i>GO</i>) combined with a base fluid mixture of <i>H</i><sub>2</sub><i>O</i>-<i>C</i><sub><i>2</i></sub><i>H</i><sub><i>6</i></sub><i>O</i><sub><i>2</i></sub> (50 %–50 %), variable thermal conductivity, an inclined magnetic field, and heat source/sink. With these features, it becomes possible to explain appropriately the flow and heat transfer phenomena that take place in the system. This study therefore mostly aims at examining the combined effect which these parameters have on the velocity and temperature distributions, skin friction, and heat transfer rates. The governing partial differential equations (PDEs) are translated into ordinary differential equations (ODEs) through the use of similarity transformations. The problem is then treated using the intelligent techniques (artificial neural network technique (ANN)) and the results validated analytically through the use of the differential transform method (DTM). It was established in the study that with the increase of an inclined magnetic field strength, it is possible to note that the accompanying decrease in scale not occurring during a rise in the Hartmann number (Ha) having a value of zero to a value of 10 can result in the increase in the boundary layer thickness of about 18–22 percent in the range of the considered parameters, while heat sources and elevated nanoparticle volume fractions improve heat transfer rates, as indicated with the increase in Nusselt numbers by 15–20 %. These results have potential applications in such areas as energy systems, thermal insulation, and industrial fluid systems that operate with highly regulated temperatures.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

ANN-DTM analyse of the squeezing flow of ZrO2-MoS2-GO/H2O-C2H6O2 between two parallel plates under combined effects of inclined magnetic field and heat source

  • 期刊论文

  • 发表日期：

    2026年3月11日

查看全文
  • Zaki Mrzog Alaofi,
  • Shekar Saranya,
  • Pachiyappan Ragupathi,
  • Sohail Nadeem,
  • Mohamed Kezzar,
  • Mohamed Rafik Sari,
  • Farhan Lafta Rashid,
  • Ibrahim Mahariq

摘要

The work aims to explore the intelligent techniques on unsteady squeezing flow of a hybrid nanofluid possessing electrical conductivity between two parallel plates, an interesting phenomenon of great importance in mechanical, aerospace and biomedical engineering, hydrology or heat management systems. The model incorporates advanced features such as ternary hybrid nanoparticles—zirconia (ZrO2), molybdenum disulfide (MoS2), and graphene oxide (GO) combined with a base fluid mixture of H2O-C2H6O2 (50 %–50 %), variable thermal conductivity, an inclined magnetic field, and heat source/sink. With these features, it becomes possible to explain appropriately the flow and heat transfer phenomena that take place in the system. This study therefore mostly aims at examining the combined effect which these parameters have on the velocity and temperature distributions, skin friction, and heat transfer rates. The governing partial differential equations (PDEs) are translated into ordinary differential equations (ODEs) through the use of similarity transformations. The problem is then treated using the intelligent techniques (artificial neural network technique (ANN)) and the results validated analytically through the use of the differential transform method (DTM). It was established in the study that with the increase of an inclined magnetic field strength, it is possible to note that the accompanying decrease in scale not occurring during a rise in the Hartmann number (Ha) having a value of zero to a value of 10 can result in the increase in the boundary layer thickness of about 18–22 percent in the range of the considered parameters, while heat sources and elevated nanoparticle volume fractions improve heat transfer rates, as indicated with the increase in Nusselt numbers by 15–20 %. These results have potential applications in such areas as energy systems, thermal insulation, and industrial fluid systems that operate with highly regulated temperatures.