Lab

Jahid H.'s Research Team


About the lab

Our research team is a hub of innovation and scholarly pursuit in Mechanical Engineering, spanning Computational Fluid Dynamics, Heat Transfer, Combustion, Materials, Nanofluids, Aerodynamics, Machine Learning, and more. Led by Md. Jahid Hasan, our team thrives on collaboration, pushing boundaries, and advancing knowledge.

If you're passionate about expanding the horizons of science and engineering, you could be a part of us. We value collaboration, scholarly growth, and breaking conventional limits. Connect with us on ResearchGate to explore ongoing projects, research outcomes, and opportunities to contribute to transformative discoveries.

Featured research (7)

Helical tube heat exchangers (HTHE) are commonly used as thermal devices in various thermal engineering applications. A comparative investigation was undertaken to examine several helical tube designs in relation to their potential uses with water and nanofluids. Additionally, employing the ternary hybrid nanofluid (THNF) flow in helical-type heat exchangers to assess the heat transfer and frictional loss is a unique concept, as there is currently no research on this specific application. This study involves analyzing three different design configurations, each of which has three different inlet profiles: round, square, and oval shapes. Hence, a numerical analysis has been conducted on nine cases, each including the same pipe length, helix diameter, and pitch distance. The specified range for the Reynolds number under the water and THNF flow condition is 5000–25000. The results are acquired for both fluids, considering the Nusselt number (Nu), friction factor (f), outlet temperature (Tout), and entropy production (Sg). Multi-Criteria Decision Making (MCDM) is employed to provide a thorough assessment of the overall performance of the proposed designs. The results have been shown as graphical representations, streamlines and contours where Nusselt number, friction factor and entropy generation have been evaluated. The Nusselt number has a higher value for the oval cross-section, while it reaches its lowest value for the square cross-section. The highest heat transfer rate is got for Design 1 with the oval-shaped case. The friction factor for a circular cross-section HHTE is 48 % higher than the friction factor for a square cross-section profile. In addition, the square shape at a Reynolds number (Re) of 25000 exhibits 5 % less entropy formation compared to the oval shape geometry at a Reynolds number of 5000. The results of MCDM analysis indicate that Design 1, which features a square section, exhibits superior performance. Conversely, Design 2, which incorporates a circular cross-section, demonstrates poor performance. Among the six ternary hybrid nanofluids, the Al2O3+CNT+Graphene nanofluid with a water basis exhibits the greatest Nusselt number.
Phase change materials (PCMs) are widely used in various applications, however, their low conductivity and long phase transition time hinder thermal energy supply. Thus, numerous researchers have studied various fin designs to solve this problem. In this study, with the unique combinations of two, three and four rectangular fins and straight, curved and angled branching fins, nine novel cases have been proposed to examine the melting enhancement of PCM in shell and tube-type heat exchangers. A numerical two-dimensional analysis has been conducted in a transient state using N-eicosane PCM, considering the natural convection effect. The CFD of this numerical model has been validated with pertinent literature work. The evolution of the solid-liquid interface and natural convection has been visualized by liquid fraction, isotherm expansion and velocity streamlines. At first, three proposed branching designs are compared for different numbers (two, three and four) of rectangular fins. Following the methodology, evaluating the impact of branching fins for two and four rectangular fins, the best branching design was the angled fins with 8.25 % and 28.58 % melting time improvement, respectively, compared to the curved fins, which performed the worst. For three rectangular fins, straight branching fins were identified as the best with a 21.2 % melting time improvement compared to the angled branching fins as the worst performer. Lastly, among all the nine cases, two rectangular fins with angled branching perform the best, with 84.6 % melting time savings. The worst performer is four rectangular fins with curved branching, saving 40 % melting time compared to no fin case. In addition to that, the cases with two rectangular fins significantly outperform other cases in terms of energy storage rate.
Microchannel heat sinks provide the solution to the ever-increasing heat flux generated from micro-electric components. In this study, performance optimization of a microchannel heat sink with delta winglet vortex generators was carried out based on the data obtained from numerical CFD simulations. A total of 192 design points were generated by altering the fluid velocity in terms of Reynolds number (Re), winglet width (W d), length (L d), and the angle of attachment (β) of the winglet. The Artificial Neural Network (ANN) model coupled with Non-dominated Sorting Genetic Algorithm NSGA-II was used simultaneously to minimize the friction factor and increase the Nusselt number. The ANN model predicted the output values within the error limit of 10%. The Pareto optimal front generated by the algorithm contains the input parameters in the range 982 < Re < 988, 177 μm < L d < 233 μm, 10 μm < W d < 25 μm, 57 • < β < 64 •. Decision-making methods TOPSIS, LINMAP, and Shannon entropy were employed to calculate the optimal solution from the data set and the obtained points showcased 70%, 120% and 158% surge in Nusselt number while an increase of friction factor by 35%, 109%, and 140% respectively is reported. The Performance Evaluation Criteria (PEC) values obtained from the best solutions were 1.52, 1.72, and 1.92, respectively. Furthermore, the accuracy of the optimal solutions was verified numerically. The flow and thermal field of the microchannel are also analyzed, and results showed that the angle of attachment and width of the winglet played a crucial role in the overall performance.
The increasing fuel prices have led researchers to work on the efficiency and development of heat-transferring devices. One such device is the hot water radiator, which is familiar in the domestic arena. The study aims to increase the efficiency and cooling performance of hot water 3D radiators by modifying the design of their fins and adding perforations for better fluid mixing. CFD simulations were carried out on the radiators with modified fin geometries (Wavy, Spike-rib, Cut-sections, Straight) and with two different intensities of perforation (19 and 38 perforations) for each case at varying inlet flowrates of the radiator. The numerical model in this study was validated with experimental work. The hydrothermal performance of each radiator was measured in terms of fin surface temperature, entropy generation, heat transfer rate, and thermal enhancement factor. The temperature distributions and fluid flow streamlines have also been shown. The results show that modifying the fin geometries augments the overall heat transfer rate by up to 131 % while perforating the fins boosts the rate to 134 %. Moreover, the radiation heat transfer is seen to have surpassed the convection heat transfer by 60–160 % for the modified radiator cases. Finally, the most efficient radiator is found based on the thermal enhancement factor, which is the spike-fin arrangement.

Lab head

Md. Jahid Hasan
Department
  • Department of Biosystems Engineering
About Md. Jahid Hasan
  • I am a Doctoral Student. I have been actively conducting academic research for five years with true dedication and passion for excellence and dedicating all my efforts to hone my skills as an avid researcher in Computational Fluid Dynamics (CFD) and Modeling and Simulation (M&S). This has been reflected in my achievements, including 35+ publications in peer-reviewed journals, many certifications, professional memberships, research awards, contributions to the peer-review process, etc.

Members (15)

Nowroze Farhan Ifraj
  • Virginia Tech (Virginia Polytechnic Institute and State University)
Sharzil Huda Tahsin
  • Ahsanullah University of Science & Tech
Mostafa Kamal Fahad
  • Ahsanullah University of Science & Tech
Md. Araful Hoque
  • Ahsanullah University of Science & Tech
Dipta Dey
  • Ahsanullah University of Science & Tech
Fawaz Bukht Majmader
  • Islamic University of Technology
Rifat Ahamed
  • Islamic University of Technology
Salim Subah
  • Ahsanullah University of Science & Tech