Fluid circulation and thermal exchange properties via integrated natural and artificial convection within a container have attracted considerable interest due to its many industrial uses. This present work concentrates on determining the effect of the Richardson number on flow and heat transfer in a cylinder filled with Cu-Water nanofluid at different nanoparticle concentrations. The governing equations: continuity and Navier Stoke fields were discretized using the finite difference approach and simulated in C++ programming language. In this work, the Richardson parameter ranged from 2.6*104 to 2.8*104, while the concentration of Cu nanoparticles ranged from 1% to 10%, and the results are presented as Nusselt number, vorticity, and stream function profiles. The results reveal that the maximum Richardson value is 2.76 x 104 at the nanoparticle volume of 0.04, resulting in a considerable increase in the convective heat transfer rate. Furthermore, as the Richardson parameters increase, the Nusselt number in the nanofluid increases exponentially while the local drag coefficient decreases. The stream function, longitudinal velocity and circulation increase as the Richardson parameters grow. The technical design for air turbulence prediction involves an understanding of the Richardson-driven connection as a mix of wind speed and convective stability variables.

The flow of fluids and heat characteristics through free convection within an enclosed space has gained substantial study due to the various applications in manufacturing industries. This work examined the influence of buoyancy factors on normal convection in a heated tube filled with Copper (Cu) nanofluid. The method of finite difference was employed to characterize the regulating fluid formulae, and C++ programming language was employed to evaluate the Navier Stoke and continuity fields. This study examined Cu nanoparticles with particle sizes ranging from 1% to 10% and buoyancy values between 2.6 x 103 and 2.8 x 103 N. Cu nanofluid was used as the working fluid and the findings are presented as temperature gradient, Nusselt number, stream function, and vorticity curves. The findings revealed that an increase in the weight proportions of nanoparticles to 0.04 amplifies the buoyancy parameters to the highest value of 2.75 x 103 N; it yields a substantial enhancement in the heat transport rate by convection. Also, as the buoyancy factor increases, the temperature gradient, vorticity, and stream function of the nanofluid improve, while the local drag coefficient decreases. This study advances the understanding of buoyancy-driven convective flow and heat behavior in the technical design of floating vessels for safety and effectiveness.