POD-TANN 방법론을 활용하여 단일 말뚝 기초의 수평 하중에 대한 점토층의 거동을 효율적으로 모사할 수 있는 거시요소를 개발하였다.
POD-TANNアプローチを用いて、飽和粘土層中のモノパイルの水平方向の非線形応答を効率的にモデル化することができる。
The author employs computer vision to predict land surface displacement for Carbon Capture and Sequestration (CCS) projects, aiming to inform decision-making processes. By training models directly from subsurface geometry images, the study addresses challenges in CCS projects.
The author presents an integrated model combining EOS, pore-crush, strength, and damage to simulate near-field ground-shock responses efficiently.