Ecological optimization and LCA of TiO₂-SiC/ water hybrid nanofluid in a shell and tube heat exchanger by ANN

The current study estimates the environmental impact and cost model for the early-stage design of a shell and tube heat exchanger (STHE). Additionally, the lifecycle analysis (LCA) compares the effects of use of nanofluid in the chemical processing industry to increase the effectiveness of the heat transfer to the typical STHE system. Nanofluids increase heat transfer, as evidenced by the results of the experiments. The Nusselt number and pressure drop were both increased by roughly 65% and 8%, respectively, using 0.5 vol% of TiO2-SiC/water hybrid nanofluid compared to water as coolant. The ecological impact of STHE was estimated as s attribute of Ecological (E-F) and total cost estimation function using artificial neural networks (ANN). Finally, the IdematLightLCA (2.8.6 version) software was used to calculate energy content, Carbon footprint, and cost over the lifespan of the baseline. The results show that nanofluid-based STHE has an average payback period considerably longer than typical coolant systems but saves superior economic value at the end of its lifetime. According to the findings, the suggested novel method is both cost-effective and environmentally feasible.