Search

This study investigates the thermal performance and exergy destruction of parabolic trough collector by Response Surface Methodology. This collector is simulated by the Monte Carol Ray Tracing method and the results are coupled to the Computational Fluid Dynamics. Thermo-hydraulic performance and the characteristics of the thermodynamics second law are studied with the turbulence-inducing elements and hybrid nanofluid. The absorber tube features elements with a helical profile along its wall. New correlations are presented to describe thermal performance and exergy destruction, and the modeling output shows that these correlations have high prediction accuracy. Response Surface Methodology results also show that turbulators have a nonlinear effect on thermal performance while the Reynolds number has a nonlinear effect on exergy destruction. Fe3O4 nanoparticles and carbon nanotube lead to an increase of 13 % and 10 % of Nusselt number, respectively, at Re=12000. Also, it leads to a decrease of 7 % and 6.7 % of exergy destruction, respectively. Increasing the working fluid flow rate from 12000 to 22000 improves thermal performance up to 73 %, and decreases exergy destruction up to 48 %. The maximum value of thermal performance is equal to 2.1, and this value is related to the highest Reynolds number and the absorber tube including turbulence-inducing elements.

This research zeroes in on improving the freezing process by synergistically employing a wavy wall and fins. To enhance cold penetration, the phase change material (PCM) is enriched with nanoparticles, and a single-phase model is adopted due to the low nanoparticle concentration. The numerical simulations leverage the Galerkin method and the validation procedure affirms the precision of the code, extensively evaluating the impacts of φ (concentration of additives) and dp (particle diameter). With an increase in particle diameter (dp), there is an initial 19.76% decrease in the required time, succeeded by a subsequent 50.56% increase when φ = 0.04. Furthermore, an escalation in φ results in an 11.04%, 40.91%, and 26.36% reduction in completion time for dp values of 50, 40, and 30 nm, respectively. Without the inclusion of powders, the solidification process lasts for 84.8 s. However, with the introduction of the optimal powder size, this duration significantly reduces to 50.1 s. This emphasizes the efficiency improvements attained through the strategic integration of a wavy wall, fins, and PCM infused with nanoparticles.

This article explores the acceleration of discharge speed through the introduction of nanoparticles. Utilizing simulations based on the Galerkin method, the study has developed and examined the effects of various variables. The utilized tank has been equipped with fin and additives with various shape factor (m) and volume fraction (φ) have been dispersed into water. The denser mesh near the ice front was considered in each time stage involving adaptive grid approach. Also, a validation test was presented to illustrate the precision of modeling. Contours and curves for different ranges of parameters were exemplified in results. The quickest process takes 641.19s while the longest process takes 877.17s. Increasing m causes conductivity to increase and speed of process enhances about 6.96 %. Moreover, augmenting the value of φ makes period of process reduce about 26.9 %.

The solidifying phenomena have been scrutinized in current work and techniques for expedition of process have been incorporated. The shape of geometry and shape of nanoparticles can alter the productivity of the unit. Utilizing higher concentration and bigger value of shape factor can accelerate the process. The present unsteady phenomena were simulated via Galerkin approach and to augment the accuracy, the shape of the mesh was adapted with location of the ice front. The existence of nanoparticles within water can enhance the freezing rate by about 26.73 %. The required time alters from 232.63s to 216.4s, when powders with bigger shape factor utilizes. Augment of concentration of powders from 0.02 to 0.04 can drop the solidification time around 13.78 %.

Increment in speed of solidification has been scrutinized in this work by means of dispersing nanomaterial. Altering the shape of container and loading additives can be assumed as effective ways for increasing performance of storage unit. The fraction (φ) and diameter (dp) of additives were assumed as variables. The main assumptions for mathematical models are ignoring convective terms and considering uniform concentration. The solutions of such unsteady form of equations have been derived based on finite element method combined with an adaptive grid. The longest freezing happens for pure water case and it takes 446. 45s. The middle magnitude of dp has the best performance and with dispersing such particles with a fraction of 0.04, the freezing time drops about 41.2 %. As dp increases, the period of freezing, firstly decreases about 19.96 % then it augments around 49.19 %. The needed time for the best case is 262.49s.