A Study on the Relationship of Heat Exchanger Design Parameters with Water Lily Stem Profile by Robust Statistical Method

Abstract

The study has successfully modeled and simulated a polymorphic tube based on the water lily stem using the robust statistical method and software. Taguchi analysis shows that the size factor E (Cross-section length of inner hole) with the effects values 39.89% has the most significant influence on the response temperature difference ((Δt) 0C). The size factor A (Peduncle diameter) has the most critical influence on the response pressure difference (ΔP (Pa)), with an effect value of 42.88%. The size factor C (Large inner hole diameter) with the significant effect value of 34.78% affects the response velocity difference (Δv (m/s)) the most. By ANOVA analysis, the results of response temperature difference analysis show that both the T-value and P-value of the size factor E (Cross-section length of inner hole) reach values that satisfy the setup requirements, with T-value reaching the most significant T-value 3.85 and the P-value 0.043 being smaller than the benchmark value 0.05, the final result indicated the size factor E (Cross-section length of inner hole) is the factor that has the most significant influence on the temperature difference of the model. For pressure difference, the results show that both the T-value and P-value of the size factor A (Peduncle diameter) reach values that satisfy the setup requirements, with the T-value reaching the largest T-value 12.19 and P-value 0.001 being smaller than the benchmark value of 0.05, the size factor A (Peduncle diameter) is the factor that has the most significant influence on the pressure difference of the model. For velocity difference, the results show that both the T-value and P-value of the size factor C (Large inner hole diameter) reach values that satisfy the set requirements, with the T-value reaching the largest T-value of 3.72 and the P-value 0.047 being smaller than the benchmark value 0.05, the size factor C (Large inner hole diameter) is the factor that has the most significant influence on the velocity difference of the model. Minitab software verification based on the Means graph drawn by Minitap17 software, the results show the best combination for response temperature difference is A3-B2-C1-D2-E2. Similarly, the best combination for response pressure and velocity differences is A2-B2-C3-D1-E1 and A2-B3-C2-D1-E3, respectively.