Gye-Chun Cho

The size and shape of soil particles reflect the formation history of the grains. In turn, the macroscale behavior of the soil mass results from particle level interactions which are affected by particle shape. Sphericity, roundness, and smoothness characterize different scales associated with particle shape. New experimental data and results from published studies are gathered into two databases to explore the effects of particle shape on packing density and on the small-to-large strain mechani

Soil treatment and improvement is commonly performed in the field of geotechnical engineering. Methods and materials to achieve this such as soil stabilization and mixing with cementitious binders have been utilized in engineered soil applications since the beginning of human civilization. Demand for environment-friendly and sustainable alternatives is currently rising. Since cement, the most commonly applied and effective soil treatment material, is responsible for heavy greenhouse gas emission

Various applications of biopolymer-based soil treatment (BPST) in geotechnical engineering have been implemented in recent years, including dust control, soil strengthening and erosion control. Despite BPST methods can ensure the effectiveness of engineering while meeting environmental protection requirements, BPST technology requires further validation in terms of site applicability, durability, and economic feasibility. This study aims to provide a state-of-the-art review and future prospectiv

Microbial biopolymers have recently been introduced as a new material for soil treatment and improvement. Biopolymers provide significant strengthening to soil, even in small quantities (i.e., at 1/10th or less of the required amount of conventional binders, such as cement). In particular, thermo-gelating biopolymers, including agar gum, gellan gum, and xanthan gum, are known to strengthen soils noticeably, even under water-saturated conditions. However, an explicitly detailed examination of the

Road maintenance technology is required to maintain favorable driving conditions and prevent accidents. In particular, a sensor technology is required for detecting road damage. In this study, we developed a new sensor technology that can detect road damage using a deep learning-based image processing algorithm. The proposed technology includes a super-resolution and semi-supervised learning method based on a generative adversarial network. The former improves the quality of the road image to ma