Title:
Predicting Sorptivity via Surface Wettability: A Computer Vision Approach
Author(s):
Hossein Kabir
Publication:
Web Session
Volume:
ws_S24_Kabir.pdf
Issue:
Appears on pages(s):
Keywords:
DOI:
Date:
3/24/2024
Abstract:
The inherent ability of cementitious systems to absorb and transmit liquids through tiny capillary pores is commonly assessed using initial sorptivity, which serves as a crucial indicator of their long-term durability. However, the conventional method for determining sorptivity involves labor-intensive measurements that can take up to 6 hours, as it relies on continuous monitoring of specimen mass changes when exposed to water. In our study, using computer vision, we leverage the inherent surface-wetting properties of cementitious systems to swiftly estimate sorptivity, accomplishing this task in just a matter of minutes. Through a comprehensive analysis of 63 different paste systems featuring varying water-to-cement ratios (ranging from 0.4 to 0.8) and subjected to various curing periods (ranging from 1 to 7 days), we establish robust correlations (with adjusted R-squared values exceeding 0.9) between the initial sorptivity (measured over approximately 6 hours) and the dynamics of liquid drop spreading. This includes a contact angle measurement of around 0.5 seconds and a drop residence time of less than 10 minutes. These findings facilitate rapid and automated assessment of initial sorptivity and long-term durability of cementitious materials.