Analytical model for extremum analysis of moistened fins involving all nonlinear energy exchange processes. (January 2023)

• Record Type: Journal Article
• Authors: Kundu, Balaram; Yook, Se-Jin
• Is Part Of: Case studies in thermal engineering. Volume 41(2023)
• Publication Date: 2023-01
• Subjects: Analytic -- Decomposition method -- Nonlinear convection coefficients -- Variable thermal conductivity -- Heat load -- Moistened fin; Heat engineering -- Case studies -- Periodicals; 621.40205
• DOI: 10.1016/j.csite.2022.102691
• Languages: English
• ISSNs: 2214-157X

Abstract

Abstract: Dehumidification on a fin surface happens when the thermal interface state maintains an undervalue corresponding to saturation condition, and a temperature boundary layer develops during heat transmission. The local thickness of the temperature boundary layer changes, and consequently, sensible and latent heat transfer coefficients become highly non-uniform. In this study, a new mathematical procedure depending on the Adomian decomposition method (ADM) is established to predict the heat transfer duty from a moistened fin where all heat transfer modes involved are functions of temperature. A cubic algebraic equation for connecting the specific humidity of air and the thermal state level of a fin is closer to the actual relation determined based on the regression analysis, which converts the governing equation into a highly nonlinear character. The present model has no restriction using the fractional power factor of temperature-dependent convection coefficients. The current results highlight that the variable convection coefficients decrease both the fin performance index and heat load rate, and this influence becomes significant at the optimum design condition. Therefore, establishing the optimum state of a fin adopting all the variability events in the practical design system is essential for the correct analysis. As the equipment implementation analysis always requires an extremum study, the proposed research will help to predict the optimum information in the practical design with the highest accurate prediction of results. Graphical abstract: Image 1