Lotfi, Marzieh, Shafiee, Mojtaba, Sharipova, Altynay, Babayev, Alpamys, Issakhov, Miras, and Aidarova, Saule
Enhancing heat transfer rates while concurrently reducing pressure drop will significantly enhance the energy efficiency of industrial heat exchangers, thereby contributing to a cleaner and more sustainable environment in the future. This study explores the fluid flow of a novel combination solution in a helical heat exchanger under a constant heat flux across various Reynolds numbers (5000–17000) aiming to uncover synergies that enhance heat transfer efficiency while reducing drag for the first time. Two key performance metrics, namely Drag Reduction (DR) and Heat Transfer Enhancement (HTE), along with the thermal effective index, are introduced to evaluate both hydrodynamic and thermal characteristics. Under turbulent conditions, an aqueous solution containing Anionic PAM (100–500 ppm) obtains a noteworthy 43% DR at 500 ppm. Simultaneously, a colloidal solution of nano-SiO2 (500–3000 ppm) in deionized water demonstrates an impressive 47% HTE at 2000 ppm. Furthermore, this study introduces two novel terms, “heat transfer enhancement synergy” and “drag reduction synergy,” marking their debut in the literature. The investigation extends to exploring four Nano-SiO2_PAM combinations which is the novelty of the study, revealing an outstanding 93.3% synergy in HTE. Precisely, at Reynolds 14,000, the synergy between 100 ppm PAM and 2000 ppm SiO2 (named comb.20 as the best combination) attains a remarkable 73.76% in DR, showcasing a noteworthy thermal effectiveness reaching approximately 200%. Even for comb.20, at Reynolds 5000, the synergy achieves a notable 133.33% in DR and 76.22% in HTE, which is quite significant. This result is attributed to a complex formation that elongates the polymer chain due to the presence of nanoparticles around the polymer chain, effectively damping eddies. Furthermore, a novel set of correlations is proposed for the prediction of the Nusselt number of the aforementioned solutions, demonstrating a remarkable agreement with experimental data with a maximum error of 24%.Graphical Abstract: Enhancing heat transfer rates while concurrently reducing pressure drop will significantly enhance the energy efficiency of industrial heat exchangers, thereby contributing to a cleaner and more sustainable environment in the future. This study explores the fluid flow of a novel combination solution in a helical heat exchanger under a constant heat flux across various Reynolds numbers (5000–17000) aiming to uncover synergies that enhance heat transfer efficiency while reducing drag for the first time. Two key performance metrics, namely Drag Reduction (DR) and Heat Transfer Enhancement (HTE), along with the thermal effective index, are introduced to evaluate both hydrodynamic and thermal characteristics. Under turbulent conditions, an aqueous solution containing Anionic PAM (100–500 ppm) obtains a noteworthy 43% DR at 500 ppm. Simultaneously, a colloidal solution of nano-SiO2 (500–3000 ppm) in deionized water demonstrates an impressive 47% HTE at 2000 ppm. Furthermore, this study introduces two novel terms, “heat transfer enhancement synergy” and “drag reduction synergy,” marking their debut in the literature. The investigation extends to exploring four Nano-SiO2_PAM combinations which is the novelty of the study, revealing an outstanding 93.3% synergy in HTE. Precisely, at Reynolds 14,000, the synergy between 100 ppm PAM and 2000 ppm SiO2 (named comb.20 as the best combination) attains a remarkable 73.76% in DR, showcasing a noteworthy thermal effectiveness reaching approximately 200%. Even for comb.20, at Reynolds 5000, the synergy achieves a notable 133.33% in DR and 76.22% in HTE, which is quite significant. This result is attributed to a complex formation that elongates the polymer chain due to the presence of nanoparticles around the polymer chain, effectively damping eddies. Furthermore, a novel set of correlations is proposed for the prediction of the Nusselt number of the aforementioned solutions, demonstrating a remarkable agreement with experimental data with a maximum error of 24%. [ABSTRACT FROM AUTHOR]