Reconciliation Procedure for Gas−Liquid Interfacial Area and Mass-Transfer Coefficient in Randomly Packed Towers

Abstract

Interfacial areas (aw) and volumetric mass-transfer coefficients (kLaw, KLaw, kGaw, and KGaw) required for randomly packed tower design were gathered from the literature to generate a working database including over 3780 measurements. A set of artificial neural network correlations for the gas−liquid interfacial area and the pure local mass-transfer coefficients was proposed. Thus, the gas−liquid interfacial area and the pure local mass-transfer coefficients (kγ, where γ = G or L) were extracted using a reconciliation procedure which combined actually measured interfacial areas with pseudo interfacial areas inferred from the actually measured volumetric mass-transfer coefficients. The neural network weights of the two aw and kγ correlations were adjusted using a least-squares composite criterion simultaneously over the five mass-transfer parameters. The first correlation representing the gas−liquid interfacial area [aw/aT = f(ReL,FrL,EoL,χ,K)] yielded an average absolute relative error (AARE) of 22.5% for the 325 measurements available. The second one, representing either kG or kL, was also implemented using the following structure: Shγ = f(Reγ,Frγ,Scγ,χ). The combination of both correlation predictions (i.e., kγaw) yielded an AARE of 24.4% for the local and global volumetric mass-transfer coefficients (3455 data).