MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641079379 A) filed by Dr. J. Prakash Arul Jose; and Nisha. N. P on June 27, 2026, for Prediction Of Leakage Through Geosynthetic Clay Liner Using Machine Learning.
Inventors include Dr. J. Prakash Arul Jose; and Nisha. N. P.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Prediction of Leakage Through Geosynthetic Clay Liner Using Machine Learning Abstract Microscopic examination was used to begin investigating the changes in geosynthetic clay liner (GCL) specimens that had been hydrated with two separate solutions: pure water and a 50 percent concentration NaCl solution. After already being hydrated with NaCl aqueous solution, the GCL samples were examined under an electron microscope. Even though the treated GCL samples’ surfaces mirrored those of the untreated GCL, a crystal deposit was found there. It was found that the bentonite particles in the GCL sample appeared more solid after being hydrated with distilled water as opposed to the NaCl solution using a scanning electron microscope (SEM). It seems that wetting the salt solution decreases the bentonite particles’ tendency to swell. Additionally, it was demonstrated by the energy-dispersive X-ray spectrometer (EDS) data that distilled water hydration had no impact on the distribution of the elements identified in the GCL samples. On the other hand, the presence of bound chlorine demonstrated that the bentonite particles had absorbed the NaCl solution. The hydrated GCL sample’s hydraulic conductivity showed some variation as well.
Disclaimer: Curated by HT Syndication.
