Application of sorptivity–diffusivity relationship for the refinement of hydraulic diffusivity function parameters obtained through inverse analysis

• Published in: Journal of building pathology and rehabilitation Vol. 5; no. 1
• Main Authors: Korakuti, Hanumanthu, Sarkar, Kaustav
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2020
• Subjects: Building Materials; Building Repair and Maintenance; Energy Efficiency; Engineering; Engineering Thermodynamics; Heat and Mass Transfer; Research Article; Structural Materials; Porous building materials; Water absorption; Sorptivity; Hydraulic diffusivity; FDM
• ISSN: 2365-3159; 2365-3167
• DOI: 10.1007/s41024-019-0068-2

The modelling of water absorption in porous building materials is critical to the rational assessment of their performance during service. The non-linear diffusion equation has been extensively used to describe the phenomena with a two-parameter, moisture–dependent hydraulic diffusivity function, D ( θ n ) , as the transport parameter. For a given material, the parameters of D ( θ n ) are often fitted through inverse modelling, which requires the non-destructive measurement of moisture profiles with expensive equipment. An alternative to this approach, is to use a sorptivity–diffusivity model which quantifies the parameters of D ( θ n ) on the basis of sorptivity determined through simple gravimetric measurements made in the course of a water-absorption test. However, the latter approach requires assuming the value of one of the two parameters to quantify the other. The objective of this paper is to demonstrate a novel combination of the two methods for obtaining refined estimates of parameters in D ( θ n ) . The idea has been demonstrated by considering the instances of OPC–lime–sand mortar, fired clay brick, Lepine stone and sand specimen for which the moisture intrusion profiles and D ( θ n ) modelled through inverse analysis have been reported previously by independent researchers. Analysis reveals that, the sorptivity–diffusivity model when used as a refinement tool for the parameters of D ( θ n ) fitted through inverse analysis leads to improvements of up to about 12% and 5% in the estimation of moisture content and penetration depth respectively.